first comit

.direnv/bin/nix-direnv-reload

@@ -0,0 +1,19 @@
+#!/usr/bin/env bash
+set -e
+if [[ ! -d "/home/work/Documents/rust/invest-bot" ]]; then
+  echo "Cannot find source directory; Did you move it?"
+  echo "(Looking for "/home/work/Documents/rust/invest-bot")"
+  echo 'Cannot force reload with this script - use "direnv reload" manually and then try again'
+  exit 1
+fi
+
+# rebuild the cache forcefully
+_nix_direnv_force_reload=1 direnv exec "/home/work/Documents/rust/invest-bot" true
+
+# Update the mtime for .envrc.
+# This will cause direnv to reload again - but without re-building.
+touch "/home/work/Documents/rust/invest-bot/.envrc"
+
+# Also update the timestamp of whatever profile_rc we have.
+# This makes sure that we know we are up to date.
+touch -r "/home/work/Documents/rust/invest-bot/.envrc" "/home/work/Documents/rust/invest-bot/.direnv"/*.rc

.direnv/flake-inputs/anbs72p9zzvyk3a227k0zmas73l56gxl-source

@@ -0,0 +1 @@
+/nix/store/anbs72p9zzvyk3a227k0zmas73l56gxl-source

.direnv/flake-inputs/gnf2ayqhb31qvgh1s9mg3aqaj9378cg7-source

@@ -0,0 +1 @@
+/nix/store/gnf2ayqhb31qvgh1s9mg3aqaj9378cg7-source

.direnv/flake-inputs/vanbyn1mbsqmff9in675grd5lqpr69zl-source

@@ -0,0 +1 @@
+/nix/store/vanbyn1mbsqmff9in675grd5lqpr69zl-source

.direnv/flake-inputs/w0x3nihmdb6cwdqh0i0h4fs95alvv770-source

@@ -0,0 +1 @@
+/nix/store/w0x3nihmdb6cwdqh0i0h4fs95alvv770-source

.direnv/flake-profile-a5d5b61aa8a61b7d9d765e1daf971a9a578f1cfa

@@ -0,0 +1 @@
+/nix/store/zbn6060daq4hb2na0y451xrpp7wnz5b2-nix-shell-env

.envrc

@@ -0,0 +1 @@
+use flake

.gitignore

@@ -0,0 +1,3 @@
+target/
+.env
+*.log

Cargo.toml

@@ -0,0 +1,52 @@
+[package]
+name = "vibe-invest"
+version = "0.1.0"
+edition = "2021"
+description = "Vibe Invest - Algorithmic Trading System using Alpaca API"
+authors = ["Vibe Invest Team"]
+
+[dependencies]
+# Async runtime
+tokio = { version = "1", features = ["full"] }
+
+# HTTP client for Alpaca API
+reqwest = { version = "0.12", features = ["json"] }
+
+# Serialization
+serde = { version = "1", features = ["derive"] }
+serde_json = "1"
+
+# Date/time handling
+chrono = { version = "0.4", features = ["serde"] }
+
+# CLI argument parsing
+clap = { version = "4", features = ["derive"] }
+
+# Environment variables
+dotenvy = "0.15"
+
+# Logging
+tracing = "0.1"
+tracing-subscriber = { version = "0.3", features = ["env-filter"] }
+tracing-appender = "0.2"
+
+# Error handling
+anyhow = "1"
+thiserror = "2"
+
+# CSV output for backtest results
+csv = "1"
+
+# Rate limiting
+governor = "0.8"
+
+# Number formatting
+num-format = "0.4"
+
+# Web server for dashboard
+axum = "0.8"
+tower-http = { version = "0.6", features = ["cors"] }
+
+# XDG directories
+dirs = "5"
+lazy_static = "1.5"

LICENCE

@@ -0,0 +1,232 @@
+GNU GENERAL PUBLIC LICENSE
+Version 3, 29 June 2007
+
+Copyright © 2007 Free Software Foundation, Inc. <https://fsf.org/>
+
+Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed.
+
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+7. Additional Terms.
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+
+Nothing in this License shall be construed as excluding or limiting any implied license or other defenses to infringement that may otherwise be available to you under applicable patent law.
+
+12. No Surrender of Others' Freedom.
+If conditions are imposed on you (whether by court order, agreement or otherwise) that contradict the conditions of this License, they do not excuse you from the conditions of this License. If you cannot convey a covered work so as to satisfy simultaneously your obligations under this License and any other pertinent obligations, then as a consequence you may not convey it at all. For example, if you agree to terms that obligate you to collect a royalty for further conveying from those to whom you convey the Program, the only way you could satisfy both those terms and this License would be to refrain entirely from conveying the Program.
+
+13. Use with the GNU Affero General Public License.
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+
+14. Revised Versions of this License.
+The Free Software Foundation may publish revised and/or new versions of the GNU General Public License from time to time. Such new versions will be similar in spirit to the present version, but may differ in detail to address new problems or concerns.
+
+Each version is given a distinguishing version number. If the Program specifies that a certain numbered version of the GNU General Public License “or any later version” applies to it, you have the option of following the terms and conditions either of that numbered version or of any later version published by the Free Software Foundation. If the Program does not specify a version number of the GNU General Public License, you may choose any version ever published by the Free Software Foundation.
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+
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+
+15. Disclaimer of Warranty.
+THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM “AS IS” WITHOUT WARRANTY OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
+
+16. Limitation of Liability.
+IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.
+
+17. Interpretation of Sections 15 and 16.
+If the disclaimer of warranty and limitation of liability provided above cannot be given local legal effect according to their terms, reviewing courts shall apply local law that most closely approximates an absolute waiver of all civil liability in connection with the Program, unless a warranty or assumption of liability accompanies a copy of the Program in return for a fee.
+
+END OF TERMS AND CONDITIONS
+
+How to Apply These Terms to Your New Programs
+
+If you develop a new program, and you want it to be of the greatest possible use to the public, the best way to achieve this is to make it free software which everyone can redistribute and change under these terms.
+
+To do so, attach the following notices to the program. It is safest to attach them to the start of each source file to most effectively state the exclusion of warranty; and each file should have at least the “copyright” line and a pointer to where the full notice is found.
+
+     vibe-invest
+     Copyright (C) 2026  mrfluffy
+
+     This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
+
+     This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more details.
+
+     You should have received a copy of the GNU General Public License along with this program.  If not, see <https://www.gnu.org/licenses/>.
+
+Also add information on how to contact you by electronic and paper mail.
+
+If the program does terminal interaction, make it output a short notice like this when it starts in an interactive mode:
+
+     vibe-invest  Copyright (C) 2026  mrfluffy
+     This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
+     This is free software, and you are welcome to redistribute it under certain conditions; type `show c' for details.
+
+The hypothetical commands `show w' and `show c' should show the appropriate parts of the General Public License. Of course, your program's commands might be different; for a GUI interface, you would use an “about box”.
+
+You should also get your employer (if you work as a programmer) or school, if any, to sign a “copyright disclaimer” for the program, if necessary. For more information on this, and how to apply and follow the GNU GPL, see <https://www.gnu.org/licenses/>.
+
+The GNU General Public License does not permit incorporating your program into proprietary programs. If your program is a subroutine library, you may consider it more useful to permit linking proprietary applications with the library. If this is what you want to do, use the GNU Lesser General Public License instead of this License. But first, please read <https://www.gnu.org/philosophy/why-not-lgpl.html>.

README.md

@@ -0,0 +1,178 @@
+# invest-bot: Tech Giants Trading Bot
+
+## Algorithmic trading system using Alpaca API
+
+`invest-bot` is a sophisticated algorithmic trading bot designed to trade a diversified portfolio of 50 "Tech Giants" stocks. It employs a hybrid strategy combining momentum and mean-reversion principles, leveraging various technical indicators to generate precise trade signals. The bot supports both live paper trading and extensive backtesting with historical data, complete with a real-time web dashboard for monitoring performance.
+
+## Table of Contents
+
+- [Features](#features)
+- [Getting Started](#getting-started)
+  - [Prerequisites](#prerequisites)
+  - [Installation](#installation)
+  - [Configuration](#configuration)
+- [Usage](#usage)
+  - [Live Trading](#live-trading)
+  - [Backtesting](#backtesting)
+  - [Web Dashboard](#web-dashboard)
+- [Strategy Overview](#strategy-overview)
+- [Technology Stack](#technology-stack)
+- [Contributing](#contributing)
+- [License](#license)
+- [Acknowledgements](#acknowledgements)
+
+## Features
+
+-   **Hybrid Trading Strategy**: Combines momentum and mean-reversion logic for robust signal generation.
+-   **Multi-Indicator Analysis**: Utilizes a suite of technical indicators including:
+    -   Relative Strength Index (RSI)
+    -   Moving Average Convergence Divergence (MACD)
+    -   Exponential Moving Averages (EMA)
+    -   Average Directional Index (ADX)
+    -   Bollinger Bands
+    -   Custom Momentum Indicators
+-   **Live Paper Trading**: Execute trades in a simulated environment using the Alpaca API, without risking real capital.
+-   **Comprehensive Backtesting**: Test the strategy against historical data over custom periods (years, months) and initial capital.
+-   **Real-time Web Dashboard**: Monitor portfolio performance, account statistics, and open positions through a responsive web interface.
+-   **Configurable Timeframes**: Run the bot on `Daily` or `Hourly` data bars.
+-   **Robust Logging**: Detailed logging for both console and file, aiding in monitoring and debugging.
+-   **Error Handling & Rate Limiting**: Graceful error management and adherence to API rate limits for stable operation.
+
+## Getting Started
+
+Follow these instructions to set up and run the `invest-bot`.
+
+### Prerequisites
+
+-   [Rust](https://www.rust-lang.org/tools/install) (latest stable version recommended)
+-   [Alpaca API Key and Secret Key](https://alpaca.markets/) (for paper trading)
+
+### Installation
+
+1.  **Clone the repository:**
+
+    ```bash
+    git clone https://github.com/your-username/invest-bot.git
+    cd invest-bot
+    ```
+
+2.  **Build the project:**
+
+    ```bash
+    cargo build --release
+    ```
+    This will compile the optimized release binary in `target/release/invest-bot`.
+
+### Configuration
+
+The bot requires API credentials and can be configured via environment variables. Create a `.env` file in the project root directory:
+
+```
+ALPACA_API_KEY=YOUR_ALPACA_API_KEY
+ALPACA_SECRET_KEY=YOUR_ALPACA_SECRET_KEY
+DASHBOARD_PORT=5000 # Optional: Customize the dashboard port
+```
+
+**Note:** Replace `YOUR_ALPACA_API_KEY` and `YOUR_ALPACA_SECRET_KEY` with your actual Alpaca paper trading API keys.
+
+## Usage
+
+### Live Trading
+
+To run the bot in live paper trading mode:
+
+```bash
+cargo run --release
+# Or, if you have built the release binary:
+# ./target/release/invest-bot
+```
+
+By default, the bot runs with `Daily` timeframe bars. To specify `Hourly` bars:
+
+```bash
+cargo run --release -- --timeframe hourly
+```
+
+The bot will continuously analyze the market during trading hours, execute trades, and update the dashboard.
+
+### Backtesting
+
+To backtest the strategy with historical data, use the `--backtest` flag. You can specify the duration (years/months) and initial capital.
+
+-   **Backtest for 3 years (default capital):**
+
+    ```bash
+    cargo run --release -- --backtest --years 3
+    ```
+
+-   **Backtest for 5 years with custom capital:**
+
+    ```bash
+    cargo run --release -- --backtest --years 5 --capital 50000
+    ```
+
+-   **Combine years and months:**
+
+    ```bash
+    cargo run --release -- --backtest --years 1 --months 6
+    ```
+
+-   **Hourly timeframe backtest:**
+
+    ```bash
+    cargo run --release -- --backtest --years 1 --timeframe hourly
+    ```
+
+Backtest results, including equity curve and trades, will be saved to `backtest_equity_curve.csv` and `backtest_trades.csv` respectively.
+
+### Web Dashboard
+
+When running in live trading mode, a real-time web dashboard is automatically started. Access it in your browser at:
+
+```
+http://localhost:5000
+```
+(or your custom `DASHBOARD_PORT`). The dashboard displays:
+
+-   Account summary (portfolio value, cash, buying power)
+-   Real-time portfolio performance graph
+-   Current open positions
+
+## Strategy Overview
+
+The `invest-bot` utilizes a dynamic hybrid strategy. It identifies potential trades using a combination of:
+
+-   **RSI (Relative Strength Index):** To gauge overbought/oversold conditions and mean-reversion opportunities.
+-   **MACD (Moving Average Convergence Divergence):** For trend identification and reversals.
+-   **EMA (Exponential Moving Averages):** To determine short-term and long-term trends.
+-   **ADX (Average Directional Index):** To measure trend strength.
+-   **Bollinger Bands:** To identify volatility and potential price breakouts/reversals.
+-   **Momentum:** Custom indicators to capture price acceleration.
+
+Risk management includes position sizing based on portfolio value and buying power, with integrated stop-loss and take-profit mechanisms.
+
+## Technology Stack
+
+-   **Rust**: Primary programming language for performance and safety.
+-   **Tokio**: Asynchronous runtime for concurrent operations (e.g., API calls, dashboard).
+-   **Alpaca API**: For market data, account information, and trade execution (paper trading).
+-   **Axum**: Web framework for building the real-time dashboard.
+-   **Chart.js**: JavaScript library for interactive chart visualization on the dashboard.
+-   **Serde**: Rust serialization/deserialization framework for JSON and CSV.
+-   **Clap**: Command-line argument parser for a user-friendly CLI.
+-   **Dotenvy**: For managing environment variables.
+-   **Tracing**: Structured logging framework.
+
+## Contributing
+
+Contributions are welcome! Please feel free to open an issue or submit a pull request.
+
+## License
+
+This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details (if applicable).
+
+## Acknowledgements
+
+-   [Alpaca.markets](https://alpaca.markets/) for their accessible trading API.
+-   [Rust Community](https://www.rust-lang.org/) for an amazing language and ecosystem.
+-   [Chart.js](https://www.chartjs.org/) for the powerful charting library.

flake.lock

@@ -0,0 +1,63 @@
+{
+  "nodes": {
+    "fenix": {
+      "inputs": {
+        "nixpkgs": [
+          "nixpkgs"
+        ],
+        "rust-analyzer-src": "rust-analyzer-src"
+      },
+      "locked": {
+        "lastModified": 1769929675,
+        "narHash": "sha256-EBpe7sXCPLs+qVePXbA7kc+Kmpmp0pWysEpjjEWTK+E=",
+        "rev": "78d518f5ca32a86dc767de481160dbae640c70cf",
+        "revCount": 2542,
+        "type": "tarball",
+        "url": "https://api.flakehub.com/f/pinned/nix-community/fenix/0.1.2542%2Brev-78d518f5ca32a86dc767de481160dbae640c70cf/019c1851-0ed1-7f81-b175-8e8bbad651e6/source.tar.gz"
+      },
+      "original": {
+        "type": "tarball",
+        "url": "https://flakehub.com/f/nix-community/fenix/0.1"
+      }
+    },
+    "nixpkgs": {
+      "locked": {
+        "lastModified": 1770562336,
+        "narHash": "sha256-ub1gpAONMFsT/GU2hV6ZWJjur8rJ6kKxdm9IlCT0j84=",
+        "rev": "d6c71932130818840fc8fe9509cf50be8c64634f",
+        "revCount": 942779,
+        "type": "tarball",
+        "url": "https://api.flakehub.com/f/pinned/NixOS/nixpkgs/0.1.942779%2Brev-d6c71932130818840fc8fe9509cf50be8c64634f/019c3fb4-003d-710c-9b72-1d2bb1b28de3/source.tar.gz"
+      },
+      "original": {
+        "type": "tarball",
+        "url": "https://flakehub.com/f/NixOS/nixpkgs/0.1"
+      }
+    },
+    "root": {
+      "inputs": {
+        "fenix": "fenix",
+        "nixpkgs": "nixpkgs"
+      }
+    },
+    "rust-analyzer-src": {
+      "flake": false,
+      "locked": {
+        "lastModified": 1769857242,
+        "narHash": "sha256-3eKpRRzKz0KzY7CJzRXFm4POwEqbuTohyQ2ajI/zKvg=",
+        "owner": "rust-lang",
+        "repo": "rust-analyzer",
+        "rev": "17304e9c7e11d26139672d3d77aa498b1cae0d69",
+        "type": "github"
+      },
+      "original": {
+        "owner": "rust-lang",
+        "ref": "nightly",
+        "repo": "rust-analyzer",
+        "type": "github"
+      }
+    }
+  },
+  "root": "root",
+  "version": 7
+}

flake.nix

@@ -0,0 +1,104 @@
+{
+  description = "A Nix-flake-based Rust development environment";
+
+  inputs = {
+    nixpkgs.url = "https://flakehub.com/f/NixOS/nixpkgs/0.1"; # unstable Nixpkgs
+    fenix = {
+      url = "https://flakehub.com/f/nix-community/fenix/0.1";
+      inputs.nixpkgs.follows = "nixpkgs";
+    };
+  };
+
+  outputs =
+    { self, ... }@inputs:
+
+    let
+      supportedSystems = [
+        "x86_64-linux"
+        "aarch64-linux"
+        "x86_64-darwin"
+        "aarch64-darwin"
+      ];
+      forEachSupportedSystem =
+        f:
+        inputs.nixpkgs.lib.genAttrs supportedSystems (
+          system:
+          f {
+            pkgs = import inputs.nixpkgs {
+              inherit system;
+              overlays = [
+                inputs.self.overlays.default
+              ];
+            };
+          }
+        );
+    in
+    {
+      overlays.default = final: prev: {
+        rustToolchain =
+          with inputs.fenix.packages.${prev.stdenv.hostPlatform.system};
+          combine (
+            with stable;
+            [
+              clippy
+              rustc
+              cargo
+              rustfmt
+              rust-src
+            ]
+          );
+      };
+
+      packages = forEachSupportedSystem (
+        { pkgs }:
+        {
+          default = pkgs.rustPlatform.buildRustPackage {
+            pname = "vibe-invest";
+            version = "0.1.0";
+            src = ./.;
+            cargoLock.lockFile = ./Cargo.lock;
+
+            nativeBuildInputs = with pkgs; [
+              pkg-config
+            ];
+
+            buildInputs = with pkgs; [
+              openssl
+            ];
+          };
+        }
+      );
+
+      apps = forEachSupportedSystem (
+        { pkgs }:
+        {
+          default = {
+            type = "app";
+            program = "${self.packages.${pkgs.stdenv.hostPlatform.system}.default}/bin/vibe-invest";
+          };
+        }
+      );
+
+      devShells = forEachSupportedSystem (
+        { pkgs }:
+        {
+          default = pkgs.mkShell {
+            packages = with pkgs; [
+              rustToolchain
+              openssl
+              pkg-config
+              cargo-deny
+              cargo-edit
+              cargo-watch
+              rust-analyzer
+            ];
+
+            env = {
+              # Required by rust-analyzer
+              RUST_SRC_PATH = "${pkgs.rustToolchain}/lib/rustlib/src/rust/library";
+            };
+          };
+        }
+      );
+    };
+}

src/alpaca.rs

@@ -0,0 +1,476 @@
+//! Alpaca API client for market data and trading.
+
+use anyhow::{Context, Result};
+use chrono::{DateTime, Duration, Utc};
+use reqwest::header::{HeaderMap, HeaderValue, CONTENT_TYPE};
+use serde::{Deserialize, Serialize};
+use std::collections::HashMap;
+use std::sync::Arc;
+use tokio::sync::Mutex;
+use tokio::time::{sleep, Duration as TokioDuration};
+
+use crate::config::Timeframe;
+use crate::types::Bar;
+
+const DATA_BASE_URL: &str = "https://data.alpaca.markets/v2";
+const TRADING_BASE_URL: &str = "https://paper-api.alpaca.markets/v2";
+const RATE_LIMIT_REQUESTS_PER_MINUTE: u32 = 200;
+
+/// Alpaca API client.
+pub struct AlpacaClient {
+    http_client: reqwest::Client,
+    api_key: String,
+    api_secret: String,
+    last_request_time: Arc<Mutex<std::time::Instant>>,
+}
+
+// API Response types
+#[derive(Debug, Deserialize)]
+struct BarsResponse {
+    bars: HashMap<String, Vec<AlpacaBar>>,
+    next_page_token: Option<String>,
+}
+
+// Single-symbol bars response (different format from multi-symbol)
+#[derive(Debug, Deserialize)]
+struct SingleBarsResponse {
+    bars: Vec<AlpacaBar>,
+    symbol: String,
+    next_page_token: Option<String>,
+}
+
+#[derive(Debug, Deserialize)]
+struct AlpacaBar {
+    t: DateTime<Utc>,
+    o: f64,
+    h: f64,
+    l: f64,
+    c: f64,
+    v: f64,
+    vw: Option<f64>,
+}
+
+#[derive(Debug, Deserialize)]
+pub struct Account {
+    pub id: String,
+    pub status: String,
+    pub buying_power: String,
+    pub portfolio_value: String,
+    pub cash: String,
+}
+
+#[derive(Debug, Deserialize)]
+pub struct Position {
+    pub symbol: String,
+    pub qty: String,
+    pub market_value: String,
+    pub avg_entry_price: String,
+    pub current_price: String,
+    pub unrealized_pl: String,
+    pub unrealized_plpc: String,
+    pub change_today: Option<String>,
+}
+
+#[derive(Debug, Deserialize)]
+pub struct Clock {
+    pub is_open: bool,
+    pub next_open: DateTime<Utc>,
+    pub next_close: DateTime<Utc>,
+}
+
+#[derive(Debug, Serialize)]
+struct OrderRequest {
+    symbol: String,
+    qty: String,
+    side: String,
+    #[serde(rename = "type")]
+    order_type: String,
+    time_in_force: String,
+}
+
+#[derive(Debug, Deserialize)]
+pub struct Order {
+    pub id: String,
+    pub symbol: String,
+    pub qty: String,
+    pub side: String,
+    pub status: String,
+}
+
+impl AlpacaClient {
+    /// Create a new Alpaca client.
+    pub fn new(api_key: String, api_secret: String) -> Result<Self> {
+        let mut headers = HeaderMap::new();
+        headers.insert(CONTENT_TYPE, HeaderValue::from_static("application/json"));
+
+        let http_client = reqwest::Client::builder()
+            .default_headers(headers)
+            .build()
+            .context("Failed to create HTTP client")?;
+
+        Ok(Self {
+            http_client,
+            api_key,
+            api_secret,
+            last_request_time: Arc::new(Mutex::new(std::time::Instant::now())),
+        })
+    }
+
+    /// Enforce rate limiting.
+    async fn enforce_rate_limit(&self) {
+        let min_interval =
+            TokioDuration::from_secs_f64(60.0 / RATE_LIMIT_REQUESTS_PER_MINUTE as f64);
+
+        let mut last_time = self.last_request_time.lock().await;
+        let elapsed = last_time.elapsed();
+
+        if elapsed < min_interval {
+            sleep(min_interval - elapsed).await;
+        }
+
+        *last_time = std::time::Instant::now();
+    }
+
+    /// Add authentication headers to a request.
+    fn auth_headers(&self) -> HeaderMap {
+        let mut headers = HeaderMap::new();
+        headers.insert(
+            "APCA-API-KEY-ID",
+            HeaderValue::from_str(&self.api_key).unwrap(),
+        );
+        headers.insert(
+            "APCA-API-SECRET-KEY",
+            HeaderValue::from_str(&self.api_secret).unwrap(),
+        );
+        headers
+    }
+
+    /// Fetch historical bar data for a symbol with pagination support.
+    pub async fn get_historical_bars(
+        &self,
+        symbol: &str,
+        timeframe: Timeframe,
+        start: DateTime<Utc>,
+        end: DateTime<Utc>,
+    ) -> Result<Vec<Bar>> {
+        let tf_str = match timeframe {
+            Timeframe::Daily => "1Day",
+            Timeframe::Hourly => "1Hour",
+        };
+
+        let mut all_bars = Vec::new();
+        let mut page_token: Option<String> = None;
+
+        loop {
+            self.enforce_rate_limit().await;
+
+            let mut url = format!(
+                "{}/stocks/{}/bars?timeframe={}&start={}&end={}&feed=iex&limit=10000",
+                DATA_BASE_URL,
+                symbol,
+                tf_str,
+                start.format("%Y-%m-%dT%H:%M:%SZ"),
+                end.format("%Y-%m-%dT%H:%M:%SZ"),
+            );
+
+            if let Some(ref token) = page_token {
+                url.push_str(&format!("&page_token={}", token));
+            }
+
+            let response = self
+                .http_client
+                .get(&url)
+                .headers(self.auth_headers())
+                .send()
+                .await
+                .context("Failed to fetch bars")?;
+
+            if !response.status().is_success() {
+                let status = response.status();
+                let text = response.text().await.unwrap_or_default();
+                anyhow::bail!("API error {}: {}", status, text);
+            }
+
+            // Single-symbol endpoint returns a different format
+            let data: SingleBarsResponse = response.json().await.context("Failed to parse bars response")?;
+
+            for b in &data.bars {
+                all_bars.push(Bar {
+                    timestamp: b.t,
+                    open: b.o,
+                    high: b.h,
+                    low: b.l,
+                    close: b.c,
+                    volume: b.v,
+                    vwap: b.vw,
+                });
+            }
+
+            // Check for more pages
+            if let Some(token) = data.next_page_token {
+                if !token.is_empty() {
+                    page_token = Some(token);
+                    continue;
+                }
+            }
+            break;
+        }
+
+        Ok(all_bars)
+    }
+
+    /// Fetch historical bars for multiple symbols.
+    pub async fn get_multi_historical_bars(
+        &self,
+        symbols: &[&str],
+        timeframe: Timeframe,
+        start: DateTime<Utc>,
+        end: DateTime<Utc>,
+    ) -> Result<HashMap<String, Vec<Bar>>> {
+        self.enforce_rate_limit().await;
+
+        let tf_str = match timeframe {
+            Timeframe::Daily => "1Day",
+            Timeframe::Hourly => "1Hour",
+        };
+
+        let symbols_str = symbols.join(",");
+        let url = format!(
+            "{}/stocks/bars?symbols={}&timeframe={}&start={}&end={}&feed=iex&limit=10000",
+            DATA_BASE_URL,
+            symbols_str,
+            tf_str,
+            start.format("%Y-%m-%dT%H:%M:%SZ"),
+            end.format("%Y-%m-%dT%H:%M:%SZ"),
+        );
+
+        let response = self
+            .http_client
+            .get(&url)
+            .headers(self.auth_headers())
+            .send()
+            .await
+            .context("Failed to fetch bars")?;
+
+        if !response.status().is_success() {
+            let status = response.status();
+            let text = response.text().await.unwrap_or_default();
+            anyhow::bail!("API error {}: {}", status, text);
+        }
+
+        let data: BarsResponse = response.json().await.context("Failed to parse bars response")?;
+
+        let mut result = HashMap::new();
+        for (symbol, bars) in data.bars {
+            let converted: Vec<Bar> = bars
+                .iter()
+                .map(|b| Bar {
+                    timestamp: b.t,
+                    open: b.o,
+                    high: b.h,
+                    low: b.l,
+                    close: b.c,
+                    volume: b.v,
+                    vwap: b.vw,
+                })
+                .collect();
+            result.insert(symbol, converted);
+        }
+
+        Ok(result)
+    }
+
+    /// Get account information.
+    pub async fn get_account(&self) -> Result<Account> {
+        self.enforce_rate_limit().await;
+
+        let url = format!("{}/account", TRADING_BASE_URL);
+
+        let response = self
+            .http_client
+            .get(&url)
+            .headers(self.auth_headers())
+            .send()
+            .await
+            .context("Failed to get account")?;
+
+        if !response.status().is_success() {
+            let status = response.status();
+            let text = response.text().await.unwrap_or_default();
+            anyhow::bail!("API error {}: {}", status, text);
+        }
+
+        response.json().await.context("Failed to parse account")
+    }
+
+    /// Get all positions.
+    pub async fn get_positions(&self) -> Result<Vec<Position>> {
+        self.enforce_rate_limit().await;
+
+        let url = format!("{}/positions", TRADING_BASE_URL);
+
+        let response = self
+            .http_client
+            .get(&url)
+            .headers(self.auth_headers())
+            .send()
+            .await
+            .context("Failed to get positions")?;
+
+        if !response.status().is_success() {
+            let status = response.status();
+            let text = response.text().await.unwrap_or_default();
+            anyhow::bail!("API error {}: {}", status, text);
+        }
+
+        response.json().await.context("Failed to parse positions")
+    }
+
+    /// Get position for a specific symbol.
+    pub async fn get_position(&self, symbol: &str) -> Result<Option<Position>> {
+        self.enforce_rate_limit().await;
+
+        let url = format!("{}/positions/{}", TRADING_BASE_URL, symbol);
+
+        let response = self
+            .http_client
+            .get(&url)
+            .headers(self.auth_headers())
+            .send()
+            .await
+            .context("Failed to get position")?;
+
+        if response.status().as_u16() == 404 {
+            return Ok(None);
+        }
+
+        if !response.status().is_success() {
+            let status = response.status();
+            let text = response.text().await.unwrap_or_default();
+            anyhow::bail!("API error {}: {}", status, text);
+        }
+
+        let position: Position = response.json().await.context("Failed to parse position")?;
+        Ok(Some(position))
+    }
+
+    /// Get market clock.
+    pub async fn get_clock(&self) -> Result<Clock> {
+        self.enforce_rate_limit().await;
+
+        let url = format!("{}/clock", TRADING_BASE_URL);
+
+        let response = self
+            .http_client
+            .get(&url)
+            .headers(self.auth_headers())
+            .send()
+            .await
+            .context("Failed to get clock")?;
+
+        if !response.status().is_success() {
+            let status = response.status();
+            let text = response.text().await.unwrap_or_default();
+            anyhow::bail!("API error {}: {}", status, text);
+        }
+
+        response.json().await.context("Failed to parse clock")
+    }
+
+    /// Submit a market order.
+    pub async fn submit_market_order(
+        &self,
+        symbol: &str,
+        qty: f64,
+        side: &str,
+    ) -> Result<Order> {
+        self.enforce_rate_limit().await;
+
+        let url = format!("{}/orders", TRADING_BASE_URL);
+
+        let order_request = OrderRequest {
+            symbol: symbol.to_string(),
+            qty: qty.to_string(),
+            side: side.to_string(),
+            order_type: "market".to_string(),
+            time_in_force: "day".to_string(),
+        };
+
+        let response = self
+            .http_client
+            .post(&url)
+            .headers(self.auth_headers())
+            .json(&order_request)
+            .send()
+            .await
+            .context("Failed to submit order")?;
+
+        if !response.status().is_success() {
+            let status = response.status();
+            let text = response.text().await.unwrap_or_default();
+            anyhow::bail!("API error {}: {}", status, text);
+        }
+
+        response.json().await.context("Failed to parse order")
+    }
+
+    /// Check if market is open.
+    pub async fn is_market_open(&self) -> Result<bool> {
+        let clock = self.get_clock().await?;
+        Ok(clock.is_open)
+    }
+
+    /// Get next market open time.
+    pub async fn get_next_market_open(&self) -> Result<DateTime<Utc>> {
+        let clock = self.get_clock().await?;
+        Ok(clock.next_open)
+    }
+}
+
+/// Helper to fetch bars for backtesting with proper date handling.
+/// Fetches each symbol individually to avoid API limits on multi-symbol requests.
+pub async fn fetch_backtest_data(
+    client: &AlpacaClient,
+    symbols: &[&str],
+    years: f64,
+    timeframe: Timeframe,
+    warmup_days: i64,
+) -> Result<HashMap<String, Vec<Bar>>> {
+    let end = Utc::now();
+    let days = (years * 365.0) as i64 + warmup_days + 30;
+    let start = end - Duration::days(days);
+
+    tracing::info!(
+        "Fetching {:.2} years of data ({} to {})...",
+        years,
+        start.format("%Y-%m-%d"),
+        end.format("%Y-%m-%d")
+    );
+
+    let mut all_data = HashMap::new();
+
+    // Fetch each symbol individually like Python does
+    // The multi-symbol endpoint has a 10000 bar limit across ALL symbols
+    for symbol in symbols {
+        tracing::info!("  Fetching {}...", symbol);
+
+        match client
+            .get_historical_bars(symbol, timeframe, start, end)
+            .await
+        {
+            Ok(bars) => {
+                if !bars.is_empty() {
+                    tracing::info!("  {}: {} bars loaded", symbol, bars.len());
+                    all_data.insert(symbol.to_string(), bars);
+                } else {
+                    tracing::warn!("  {}: No data", symbol);
+                }
+            }
+            Err(e) => {
+                tracing::error!("  Failed to fetch {}: {}", symbol, e);
+            }
+        }
+    }
+
+    Ok(all_data)
+}

src/backtester.rs

@@ -0,0 +1,699 @@
+//! Backtesting engine for the trading strategy.
+
+use anyhow::{Context, Result};
+use chrono::{DateTime, Duration, Utc};
+use std::collections::{BTreeMap, HashMap, HashSet};
+
+use crate::alpaca::{fetch_backtest_data, AlpacaClient};
+use crate::config::{
+    get_all_symbols, IndicatorParams, Timeframe, HOURS_PER_DAY, MAX_POSITION_SIZE,
+    MIN_CASH_RESERVE, STOP_LOSS_PCT, TAKE_PROFIT_PCT, TOP_MOMENTUM_COUNT,
+    TRADING_DAYS_PER_YEAR, TRAILING_STOP_ACTIVATION, TRAILING_STOP_DISTANCE,
+};
+use crate::indicators::{calculate_all_indicators, generate_signal};
+use crate::types::{
+    BacktestPosition, BacktestResult, EquityPoint, IndicatorRow, Signal, Trade,
+};
+
+/// Backtesting engine for the trading strategy.
+pub struct Backtester {
+    initial_capital: f64,
+    cash: f64,
+    positions: HashMap<String, BacktestPosition>,
+    trades: Vec<Trade>,
+    equity_history: Vec<EquityPoint>,
+    entry_prices: HashMap<String, f64>,
+    high_water_marks: HashMap<String, f64>,
+    params: IndicatorParams,
+    timeframe: Timeframe,
+}
+
+impl Backtester {
+    /// Create a new backtester.
+    pub fn new(initial_capital: f64, timeframe: Timeframe) -> Self {
+        Self {
+            initial_capital,
+            cash: initial_capital,
+            positions: HashMap::new(),
+            trades: Vec::new(),
+            equity_history: Vec::new(),
+            entry_prices: HashMap::new(),
+            high_water_marks: HashMap::new(),
+            params: timeframe.params(),
+            timeframe,
+        }
+    }
+
+    /// Calculate current portfolio value.
+    fn get_portfolio_value(&self, prices: &HashMap<String, f64>) -> f64 {
+        let positions_value: f64 = self
+            .positions
+            .iter()
+            .map(|(symbol, pos)| pos.shares * prices.get(symbol).unwrap_or(&pos.entry_price))
+            .sum();
+        self.cash + positions_value
+    }
+
+    /// Calculate position size based on risk management.
+    fn calculate_position_size(&self, price: f64, portfolio_value: f64) -> u64 {
+        let max_allocation = portfolio_value * MAX_POSITION_SIZE;
+        let available_cash = self.cash - (portfolio_value * MIN_CASH_RESERVE);
+
+        if available_cash <= 0.0 {
+            return 0;
+        }
+
+        let position_value = max_allocation.min(available_cash);
+        (position_value / price).floor() as u64
+    }
+
+    /// Execute a simulated buy order.
+    fn execute_buy(
+        &mut self,
+        symbol: &str,
+        price: f64,
+        timestamp: DateTime<Utc>,
+        portfolio_value: f64,
+    ) -> bool {
+        if self.positions.contains_key(symbol) {
+            return false;
+        }
+
+        let shares = self.calculate_position_size(price, portfolio_value);
+        if shares == 0 {
+            return false;
+        }
+
+        let cost = shares as f64 * price;
+        if cost > self.cash {
+            return false;
+        }
+
+        self.cash -= cost;
+        self.positions.insert(
+            symbol.to_string(),
+            BacktestPosition {
+                symbol: symbol.to_string(),
+                shares: shares as f64,
+                entry_price: price,
+                entry_time: timestamp,
+            },
+        );
+        self.entry_prices.insert(symbol.to_string(), price);
+        self.high_water_marks.insert(symbol.to_string(), price);
+
+        self.trades.push(Trade {
+            symbol: symbol.to_string(),
+            side: "BUY".to_string(),
+            shares: shares as f64,
+            price,
+            timestamp,
+            pnl: 0.0,
+            pnl_pct: 0.0,
+        });
+
+        true
+    }
+
+    /// Execute a simulated sell order.
+    fn execute_sell(&mut self, symbol: &str, price: f64, timestamp: DateTime<Utc>) -> bool {
+        let position = match self.positions.remove(symbol) {
+            Some(p) => p,
+            None => return false,
+        };
+
+        let proceeds = position.shares * price;
+        self.cash += proceeds;
+
+        let pnl = proceeds - (position.shares * position.entry_price);
+        let pnl_pct = (price - position.entry_price) / position.entry_price;
+
+        self.trades.push(Trade {
+            symbol: symbol.to_string(),
+            side: "SELL".to_string(),
+            shares: position.shares,
+            price,
+            timestamp,
+            pnl,
+            pnl_pct,
+        });
+
+        self.entry_prices.remove(symbol);
+        self.high_water_marks.remove(symbol);
+
+        true
+    }
+
+    /// Check if stop-loss, take-profit, or trailing stop should trigger.
+    fn check_stop_loss_take_profit(&mut self, symbol: &str, current_price: f64) -> Option<Signal> {
+        let entry_price = match self.entry_prices.get(symbol) {
+            Some(&p) => p,
+            None => return None,
+        };
+
+        let pnl_pct = (current_price - entry_price) / entry_price;
+
+        // Update high water mark
+        if let Some(hwm) = self.high_water_marks.get_mut(symbol) {
+            if current_price > *hwm {
+                *hwm = current_price;
+            }
+        }
+
+        // Fixed stop loss
+        if pnl_pct <= -STOP_LOSS_PCT {
+            return Some(Signal::StrongSell);
+        }
+
+        // Take profit
+        if pnl_pct >= TAKE_PROFIT_PCT {
+            return Some(Signal::Sell);
+        }
+
+        // Trailing stop (only after activation threshold)
+        if pnl_pct >= TRAILING_STOP_ACTIVATION {
+            if let Some(&high_water) = self.high_water_marks.get(symbol) {
+                let trailing_stop_price = high_water * (1.0 - TRAILING_STOP_DISTANCE);
+                if current_price <= trailing_stop_price {
+                    return Some(Signal::Sell);
+                }
+            }
+        }
+
+        None
+    }
+
+    /// Run the backtest simulation.
+    pub async fn run(&mut self, client: &AlpacaClient, years: f64) -> Result<BacktestResult> {
+        let symbols = get_all_symbols();
+
+        // Calculate warmup period
+        let warmup_period = self.params.min_bars() + 10;
+        let warmup_calendar_days = if self.timeframe == Timeframe::Hourly {
+            (warmup_period as f64 / HOURS_PER_DAY as f64 * 1.5) as i64
+        } else {
+            (warmup_period as f64 * 1.5) as i64
+        };
+
+        tracing::info!("{}", "=".repeat(70));
+        tracing::info!("STARTING BACKTEST");
+        tracing::info!("Initial Capital: ${:.2}", self.initial_capital);
+        tracing::info!("Period: {:.2} years ({:.1} months)", years, years * 12.0);
+        tracing::info!("Timeframe: {:?} bars", self.timeframe);
+        if self.timeframe == Timeframe::Hourly {
+            tracing::info!(
+                "Parameters scaled {}x (e.g., RSI: {}, EMA_TREND: {})",
+                HOURS_PER_DAY,
+                self.params.rsi_period,
+                self.params.ema_trend
+            );
+        }
+        tracing::info!("{}", "=".repeat(70));
+
+        // Fetch historical data
+        let raw_data = fetch_backtest_data(
+            client,
+            &symbols.iter().map(|s| *s).collect::<Vec<_>>(),
+            years,
+            self.timeframe,
+            warmup_calendar_days,
+        )
+        .await?;
+
+        if raw_data.is_empty() {
+            anyhow::bail!("No historical data available for backtesting");
+        }
+
+        // Calculate indicators for all symbols
+        let mut data: HashMap<String, Vec<IndicatorRow>> = HashMap::new();
+        for (symbol, bars) in &raw_data {
+            let min_bars = self.params.min_bars();
+            if bars.len() < min_bars {
+                tracing::warn!(
+                    "{}: Only {} bars, need {}. Skipping.",
+                    symbol,
+                    bars.len(),
+                    min_bars
+                );
+                continue;
+            }
+            let indicators = calculate_all_indicators(bars, &self.params);
+            data.insert(symbol.clone(), indicators);
+        }
+
+        // Get common date range
+        let mut all_dates: BTreeMap<DateTime<Utc>, HashSet<String>> = BTreeMap::new();
+        for (symbol, rows) in &data {
+            for row in rows {
+                all_dates
+                    .entry(row.timestamp)
+                    .or_insert_with(HashSet::new)
+                    .insert(symbol.clone());
+            }
+        }
+
+        let all_dates: Vec<DateTime<Utc>> = all_dates.keys().copied().collect();
+
+        // Calculate trading start date
+        let end_date = Utc::now();
+        let trading_start_date = end_date - Duration::days((years * 365.0) as i64);
+
+        // Filter to only trade on requested period
+        let trading_dates: Vec<DateTime<Utc>> = all_dates
+            .iter()
+            .filter(|&&d| d >= trading_start_date)
+            .copied()
+            .collect();
+
+        // Ensure we have enough warmup
+        let trading_dates = if !trading_dates.is_empty() {
+            let first_trading_idx = all_dates
+                .iter()
+                .position(|&d| d == trading_dates[0])
+                .unwrap_or(0);
+            if first_trading_idx < warmup_period {
+                trading_dates
+                    .into_iter()
+                    .skip(warmup_period - first_trading_idx)
+                    .collect()
+            } else {
+                trading_dates
+            }
+        } else {
+            trading_dates
+        };
+
+        if trading_dates.is_empty() {
+            anyhow::bail!(
+                "No trading days available after warmup. \
+                 Try a longer backtest period (at least 4 months recommended)."
+            );
+        }
+
+        tracing::info!(
+            "\nSimulating {} trading days (after {}-day warmup)...",
+            trading_dates.len(),
+            warmup_period
+        );
+
+        // Build index lookup for each symbol's data
+        let mut symbol_date_index: HashMap<String, HashMap<DateTime<Utc>, usize>> = HashMap::new();
+        for (symbol, rows) in &data {
+            let mut idx_map = HashMap::new();
+            for (i, row) in rows.iter().enumerate() {
+                idx_map.insert(row.timestamp, i);
+            }
+            symbol_date_index.insert(symbol.clone(), idx_map);
+        }
+
+        // Main simulation loop
+        for (day_num, current_date) in trading_dates.iter().enumerate() {
+            // Get current prices and momentum for all symbols
+            let mut current_prices: HashMap<String, f64> = HashMap::new();
+            let mut momentum_scores: HashMap<String, f64> = HashMap::new();
+
+            for (symbol, rows) in &data {
+                if let Some(&idx) = symbol_date_index.get(symbol).and_then(|m| m.get(current_date)) {
+                    let row = &rows[idx];
+                    current_prices.insert(symbol.clone(), row.close);
+                    if !row.momentum.is_nan() {
+                        momentum_scores.insert(symbol.clone(), row.momentum);
+                    }
+                }
+            }
+
+            let portfolio_value = self.get_portfolio_value(&current_prices);
+
+            // Momentum ranking: sort symbols by momentum
+            let mut ranked_symbols: Vec<String> = momentum_scores.keys().cloned().collect();
+            ranked_symbols.sort_by(|a, b| {
+                let ma = momentum_scores.get(a).unwrap_or(&0.0);
+                let mb = momentum_scores.get(b).unwrap_or(&0.0);
+                mb.partial_cmp(ma).unwrap_or(std::cmp::Ordering::Equal)
+            });
+            let top_momentum_symbols: HashSet<String> =
+                ranked_symbols.iter().take(TOP_MOMENTUM_COUNT).cloned().collect();
+
+            // Process sells first (for all symbols with positions)
+            let position_symbols: Vec<String> = self.positions.keys().cloned().collect();
+            for symbol in position_symbols {
+                let rows = match data.get(&symbol) {
+                    Some(r) => r,
+                    None => continue,
+                };
+
+                let idx = match symbol_date_index.get(&symbol).and_then(|m| m.get(current_date)) {
+                    Some(&i) => i,
+                    None => continue,
+                };
+
+                if idx < 1 {
+                    continue;
+                }
+
+                let current_row = &rows[idx];
+                let previous_row = &rows[idx - 1];
+
+                if current_row.rsi.is_nan() || current_row.macd.is_nan() {
+                    continue;
+                }
+
+                let mut signal = generate_signal(&symbol, current_row, previous_row);
+
+                // Check stop-loss/take-profit/trailing stop
+                if let Some(sl_tp) = self.check_stop_loss_take_profit(&symbol, signal.current_price)
+                {
+                    signal.signal = sl_tp;
+                }
+
+                // Execute sells
+                if signal.signal.is_sell() {
+                    self.execute_sell(&symbol, signal.current_price, *current_date);
+                }
+            }
+
+            // Process buys (only for top momentum stocks)
+            for symbol in &ranked_symbols {
+                let rows = match data.get(symbol) {
+                    Some(r) => r,
+                    None => continue,
+                };
+
+                // Only buy top momentum stocks
+                if !top_momentum_symbols.contains(symbol) {
+                    continue;
+                }
+
+                let idx = match symbol_date_index.get(symbol).and_then(|m| m.get(current_date)) {
+                    Some(&i) => i,
+                    None => continue,
+                };
+
+                if idx < 1 {
+                    continue;
+                }
+
+                let current_row = &rows[idx];
+                let previous_row = &rows[idx - 1];
+
+                if current_row.rsi.is_nan() || current_row.macd.is_nan() {
+                    continue;
+                }
+
+                let signal = generate_signal(symbol, current_row, previous_row);
+
+                // Execute buys
+                if signal.signal.is_buy() {
+                    self.execute_buy(symbol, signal.current_price, *current_date, portfolio_value);
+                }
+            }
+
+            // Record equity
+            self.equity_history.push(EquityPoint {
+                date: *current_date,
+                portfolio_value: self.get_portfolio_value(&current_prices),
+                cash: self.cash,
+                positions_count: self.positions.len(),
+            });
+
+            // Progress update
+            if (day_num + 1) % 100 == 0 {
+                tracing::info!(
+                    "  Processed {}/{} days... Portfolio: ${:.2}",
+                    day_num + 1,
+                    trading_dates.len(),
+                    self.equity_history.last().map(|e| e.portfolio_value).unwrap_or(0.0)
+                );
+            }
+        }
+
+        // Close all remaining positions at final prices
+        let final_date = trading_dates.last().copied().unwrap_or_else(Utc::now);
+        let position_symbols: Vec<String> = self.positions.keys().cloned().collect();
+
+        for symbol in position_symbols {
+            if let Some(rows) = data.get(&symbol) {
+                if let Some(last_row) = rows.last() {
+                    self.execute_sell(&symbol, last_row.close, final_date);
+                }
+            }
+        }
+
+        // Calculate results
+        let result = self.calculate_results(years)?;
+
+        // Print summary
+        self.print_summary(&result);
+
+        Ok(result)
+    }
+
+    /// Calculate performance metrics from backtest.
+    fn calculate_results(&self, years: f64) -> Result<BacktestResult> {
+        if self.equity_history.is_empty() {
+            anyhow::bail!(
+                "No trading days after indicator warmup period. \
+                 Try a longer backtest period (at least 4 months recommended)."
+            );
+        }
+
+        let final_value = self.cash;
+        let total_return = final_value - self.initial_capital;
+        let total_return_pct = total_return / self.initial_capital;
+
+        // CAGR
+        let cagr = if years > 0.0 {
+            (final_value / self.initial_capital).powf(1.0 / years) - 1.0
+        } else {
+            0.0
+        };
+
+        // Calculate daily returns
+        let mut daily_returns: Vec<f64> = Vec::new();
+        for i in 1..self.equity_history.len() {
+            let prev = self.equity_history[i - 1].portfolio_value;
+            let curr = self.equity_history[i].portfolio_value;
+            if prev > 0.0 {
+                daily_returns.push((curr - prev) / prev);
+            }
+        }
+
+        // Sharpe Ratio (assuming 252 trading days, risk-free rate ~5%)
+        let risk_free_daily = 0.05 / TRADING_DAYS_PER_YEAR as f64;
+        let excess_returns: Vec<f64> = daily_returns.iter().map(|r| r - risk_free_daily).collect();
+
+        let sharpe = if !excess_returns.is_empty() {
+            let mean = excess_returns.iter().sum::<f64>() / excess_returns.len() as f64;
+            let variance: f64 = excess_returns.iter().map(|r| (r - mean).powi(2)).sum::<f64>()
+                / excess_returns.len() as f64;
+            let std = variance.sqrt();
+            if std > 0.0 {
+                (mean / std) * (TRADING_DAYS_PER_YEAR as f64).sqrt()
+            } else {
+                0.0
+            }
+        } else {
+            0.0
+        };
+
+        // Sortino Ratio (downside deviation)
+        let negative_returns: Vec<f64> = daily_returns.iter().filter(|&&r| r < 0.0).copied().collect();
+        let sortino = if !negative_returns.is_empty() && !daily_returns.is_empty() {
+            let mean = daily_returns.iter().sum::<f64>() / daily_returns.len() as f64;
+            let neg_variance: f64 =
+                negative_returns.iter().map(|r| r.powi(2)).sum::<f64>() / negative_returns.len() as f64;
+            let neg_std = neg_variance.sqrt();
+            if neg_std > 0.0 {
+                (mean / neg_std) * (TRADING_DAYS_PER_YEAR as f64).sqrt()
+            } else {
+                0.0
+            }
+        } else {
+            0.0
+        };
+
+        // Maximum Drawdown
+        let mut max_drawdown = 0.0;
+        let mut max_drawdown_pct = 0.0;
+        let mut peak = self.initial_capital;
+
+        for point in &self.equity_history {
+            if point.portfolio_value > peak {
+                peak = point.portfolio_value;
+            }
+            let drawdown = point.portfolio_value - peak;
+            let drawdown_pct = drawdown / peak;
+            if drawdown < max_drawdown {
+                max_drawdown = drawdown;
+                max_drawdown_pct = drawdown_pct;
+            }
+        }
+
+        // Trade statistics
+        let sell_trades: Vec<&Trade> = self.trades.iter().filter(|t| t.side == "SELL").collect();
+        let winning_trades: Vec<&Trade> = sell_trades.iter().filter(|t| t.pnl > 0.0).copied().collect();
+        let losing_trades: Vec<&Trade> = sell_trades.iter().filter(|t| t.pnl <= 0.0).copied().collect();
+
+        let total_trades = sell_trades.len();
+        let win_count = winning_trades.len();
+        let lose_count = losing_trades.len();
+        let win_rate = if total_trades > 0 {
+            win_count as f64 / total_trades as f64
+        } else {
+            0.0
+        };
+
+        let avg_win = if !winning_trades.is_empty() {
+            winning_trades.iter().map(|t| t.pnl).sum::<f64>() / winning_trades.len() as f64
+        } else {
+            0.0
+        };
+
+        let avg_loss = if !losing_trades.is_empty() {
+            losing_trades.iter().map(|t| t.pnl).sum::<f64>() / losing_trades.len() as f64
+        } else {
+            0.0
+        };
+
+        let total_wins: f64 = winning_trades.iter().map(|t| t.pnl).sum();
+        let total_losses: f64 = losing_trades.iter().map(|t| t.pnl.abs()).sum();
+        let profit_factor = if total_losses > 0.0 {
+            total_wins / total_losses
+        } else {
+            f64::INFINITY
+        };
+
+        Ok(BacktestResult {
+            initial_capital: self.initial_capital,
+            final_value,
+            total_return,
+            total_return_pct,
+            cagr,
+            sharpe_ratio: sharpe,
+            sortino_ratio: sortino,
+            max_drawdown,
+            max_drawdown_pct,
+            total_trades,
+            winning_trades: win_count,
+            losing_trades: lose_count,
+            win_rate,
+            avg_win,
+            avg_loss,
+            profit_factor,
+            trades: self.trades.clone(),
+            equity_curve: self.equity_history.clone(),
+        })
+    }
+
+    /// Print backtest summary.
+    fn print_summary(&self, result: &BacktestResult) {
+        println!("\n");
+        println!("{}", "=".repeat(70));
+        println!("{:^70}", "BACKTEST RESULTS");
+        println!("{}", "=".repeat(70));
+        println!("\n{:^70}", "PORTFOLIO PERFORMANCE");
+        println!("{}", "-".repeat(70));
+        println!("  Initial Capital:      ${:>15.2}", result.initial_capital);
+        println!("  Final Value:          ${:>15.2}", result.final_value);
+        println!(
+            "  Total Return:         ${:>15.2} ({:>+.2}%)",
+            result.total_return,
+            result.total_return_pct * 100.0
+        );
+        println!("  CAGR:                  {:>15.2}%", result.cagr * 100.0);
+        println!();
+        println!("{:^70}", "RISK METRICS");
+        println!("{}", "-".repeat(70));
+        println!("  Sharpe Ratio:          {:>15.2}", result.sharpe_ratio);
+        println!("  Sortino Ratio:         {:>15.2}", result.sortino_ratio);
+        println!(
+            "  Max Drawdown:         ${:>15.2} ({:.2}%)",
+            result.max_drawdown,
+            result.max_drawdown_pct * 100.0
+        );
+        println!();
+        println!("{:^70}", "TRADE STATISTICS");
+        println!("{}", "-".repeat(70));
+        println!("  Total Trades:          {:>15}", result.total_trades);
+        println!("  Winning Trades:        {:>15}", result.winning_trades);
+        println!("  Losing Trades:         {:>15}", result.losing_trades);
+        println!("  Win Rate:              {:>15.2}%", result.win_rate * 100.0);
+        println!("  Avg Win:              ${:>15.2}", result.avg_win);
+        println!("  Avg Loss:             ${:>15.2}", result.avg_loss);
+        println!("  Profit Factor:         {:>15.2}", result.profit_factor);
+        println!("{}", "=".repeat(70));
+
+        // Show recent trades
+        if !result.trades.is_empty() {
+            println!("\n{:^70}", "RECENT TRADES (Last 10)");
+            println!("{}", "-".repeat(70));
+            println!(
+                "  {:12} {:8} {:6} {:8} {:12} {:12}",
+                "Date", "Symbol", "Side", "Shares", "Price", "P&L"
+            );
+            println!("{}", "-".repeat(70));
+
+            for trade in result.trades.iter().rev().take(10).rev() {
+                let date_str = trade.timestamp.format("%Y-%m-%d").to_string();
+                let pnl_str = if trade.side == "SELL" {
+                    format!("${:.2}", trade.pnl)
+                } else {
+                    "-".to_string()
+                };
+                println!(
+                    "  {:12} {:8} {:6} {:8.0} ${:11.2} {:12}",
+                    date_str, trade.symbol, trade.side, trade.shares, trade.price, pnl_str
+                );
+            }
+            println!("{}", "=".repeat(70));
+        }
+    }
+}
+
+/// Save backtest results to CSV files.
+pub fn save_backtest_results(result: &BacktestResult) -> Result<()> {
+    // Save equity curve
+    if !result.equity_curve.is_empty() {
+        let mut wtr = csv::Writer::from_path("backtest_equity_curve.csv")
+            .context("Failed to create equity curve CSV")?;
+
+        wtr.write_record(["date", "portfolio_value", "cash", "positions_count"])?;
+
+        for point in &result.equity_curve {
+            wtr.write_record(&[
+                point.date.to_rfc3339(),
+                point.portfolio_value.to_string(),
+                point.cash.to_string(),
+                point.positions_count.to_string(),
+            ])?;
+        }
+
+        wtr.flush()?;
+        tracing::info!("Equity curve saved to: backtest_equity_curve.csv");
+    }
+
+    // Save trades
+    if !result.trades.is_empty() {
+        let mut wtr =
+            csv::Writer::from_path("backtest_trades.csv").context("Failed to create trades CSV")?;
+
+        wtr.write_record(["timestamp", "symbol", "side", "shares", "price", "pnl", "pnl_pct"])?;
+
+        for trade in &result.trades {
+            wtr.write_record(&[
+                trade.timestamp.to_rfc3339(),
+                trade.symbol.clone(),
+                trade.side.clone(),
+                trade.shares.to_string(),
+                trade.price.to_string(),
+                trade.pnl.to_string(),
+                trade.pnl_pct.to_string(),
+            ])?;
+        }
+
+        wtr.flush()?;
+        tracing::info!("Trades saved to: backtest_trades.csv");
+    }
+
+    Ok(())
+}

src/bot.rs

@@ -0,0 +1,490 @@
+//! Live trading bot using Alpaca API.
+
+use anyhow::Result;
+use chrono::{Duration, Utc};
+use std::collections::HashMap;
+use tokio::time::{sleep, Duration as TokioDuration};
+
+use crate::alpaca::AlpacaClient;
+use crate::config::{
+    get_all_symbols, IndicatorParams, Timeframe, BOT_CHECK_INTERVAL_SECONDS, HOURS_PER_DAY,
+    MAX_POSITION_SIZE, MIN_CASH_RESERVE, STOP_LOSS_PCT, TAKE_PROFIT_PCT,
+};
+use crate::indicators::{calculate_all_indicators, generate_signal};
+use crate::paths::{LIVE_EQUITY_FILE, LIVE_POSITIONS_FILE};
+use crate::types::{EquitySnapshot, PositionInfo, Signal, TradeSignal};
+
+/// Live trading bot for paper trading.
+pub struct TradingBot {
+    client: AlpacaClient,
+    params: IndicatorParams,
+    timeframe: Timeframe,
+    entry_prices: HashMap<String, f64>,
+    equity_history: Vec<EquitySnapshot>,
+}
+
+impl TradingBot {
+    /// Create a new trading bot.
+    pub async fn new(
+        api_key: String,
+        api_secret: String,
+        timeframe: Timeframe,
+    ) -> Result<Self> {
+        let client = AlpacaClient::new(api_key, api_secret)?;
+
+        let mut bot = Self {
+            client,
+            params: timeframe.params(),
+            timeframe,
+            entry_prices: HashMap::new(),
+            equity_history: Vec::new(),
+        };
+
+        // Load persisted state
+        bot.load_entry_prices();
+        bot.load_equity_history();
+
+        // Log account info
+        bot.log_account_info().await;
+
+        tracing::info!("Trading bot initialized successfully (Paper Trading Mode)");
+
+        Ok(bot)
+    }
+
+    /// Load entry prices from file.
+    fn load_entry_prices(&mut self) {
+        if LIVE_POSITIONS_FILE.exists() {
+            match std::fs::read_to_string(&*LIVE_POSITIONS_FILE) {
+                Ok(content) => {
+                    if !content.is_empty() {
+                        match serde_json::from_str::<HashMap<String, f64>>(&content) {
+                            Ok(prices) => {
+                                tracing::info!("Loaded entry prices for {} positions.", prices.len());
+                                self.entry_prices = prices;
+                            }
+                            Err(e) => tracing::error!("Error parsing positions file: {}", e),
+                        }
+                    }
+                }
+                Err(e) => tracing::error!("Error loading positions file: {}", e),
+            }
+        }
+    }
+
+    /// Save entry prices to file.
+    fn save_entry_prices(&self) {
+        match serde_json::to_string_pretty(&self.entry_prices) {
+            Ok(json) => {
+                if let Err(e) = std::fs::write(&*LIVE_POSITIONS_FILE, json) {
+                    tracing::error!("Error saving positions file: {}", e);
+                }
+            }
+            Err(e) => tracing::error!("Error serializing positions: {}", e),
+        }
+    }
+
+    /// Load equity history from file.
+    fn load_equity_history(&mut self) {
+        if LIVE_EQUITY_FILE.exists() {
+            match std::fs::read_to_string(&*LIVE_EQUITY_FILE) {
+                Ok(content) => {
+                    if !content.is_empty() {
+                        match serde_json::from_str::<Vec<EquitySnapshot>>(&content) {
+                            Ok(history) => {
+                                tracing::info!("Loaded {} equity data points.", history.len());
+                                self.equity_history = history;
+                            }
+                            Err(e) => tracing::error!("Error parsing equity history: {}", e),
+                        }
+                    }
+                }
+                Err(e) => tracing::error!("Error loading equity history: {}", e),
+            }
+        }
+    }
+
+    /// Save equity snapshot.
+    async fn save_equity_snapshot(&mut self) -> Result<()> {
+        let account = self.client.get_account().await?;
+        let positions = self.client.get_positions().await?;
+
+        let mut positions_map = HashMap::new();
+        for pos in &positions {
+            positions_map.insert(
+                pos.symbol.clone(),
+                PositionInfo {
+                    qty: pos.qty.parse().unwrap_or(0.0),
+                    market_value: pos.market_value.parse().unwrap_or(0.0),
+                    avg_entry_price: pos.avg_entry_price.parse().unwrap_or(0.0),
+                    current_price: pos.current_price.parse().unwrap_or(0.0),
+                    unrealized_pnl: pos.unrealized_pl.parse().unwrap_or(0.0),
+                    pnl_pct: pos.unrealized_plpc.parse::<f64>().unwrap_or(0.0) * 100.0,
+                    change_today: pos.change_today.as_ref().and_then(|s| s.parse::<f64>().ok()).unwrap_or(0.0) * 100.0,
+                },
+            );
+        }
+
+        let snapshot = EquitySnapshot {
+            timestamp: Utc::now().to_rfc3339(),
+            portfolio_value: account.portfolio_value.parse().unwrap_or(0.0),
+            cash: account.cash.parse().unwrap_or(0.0),
+            buying_power: account.buying_power.parse().unwrap_or(0.0),
+            positions_count: positions.len(),
+            positions: positions_map,
+        };
+
+        self.equity_history.push(snapshot.clone());
+
+        // Keep last 7 trading days of equity data (1 snapshot per minute).
+        const MINUTES_PER_HOUR: usize = 60;
+        const DAYS_TO_KEEP: usize = 7;
+        const MAX_SNAPSHOTS: usize = DAYS_TO_KEEP * HOURS_PER_DAY * MINUTES_PER_HOUR;
+
+        if self.equity_history.len() > MAX_SNAPSHOTS {
+            let start = self.equity_history.len() - MAX_SNAPSHOTS;
+            self.equity_history = self.equity_history[start..].to_vec();
+        }
+
+        // Save to file
+        match serde_json::to_string_pretty(&self.equity_history) {
+            Ok(json) => {
+                if let Err(e) = std::fs::write(&*LIVE_EQUITY_FILE, json) {
+                    tracing::error!("Error saving equity history: {}", e);
+                }
+            }
+            Err(e) => tracing::error!("Error serializing equity history: {}", e),
+        }
+
+        tracing::info!("Saved equity snapshot: ${:.2}", snapshot.portfolio_value);
+
+        Ok(())
+    }
+
+    /// Log current account information.
+    async fn log_account_info(&self) {
+        match self.client.get_account().await {
+            Ok(account) => {
+                let portfolio_value: f64 = account.portfolio_value.parse().unwrap_or(0.0);
+                let buying_power: f64 = account.buying_power.parse().unwrap_or(0.0);
+                let cash: f64 = account.cash.parse().unwrap_or(0.0);
+
+                tracing::info!("Account Status: {}", account.status);
+                tracing::info!("Buying Power: ${:.2}", buying_power);
+                tracing::info!("Portfolio Value: ${:.2}", portfolio_value);
+                tracing::info!("Cash: ${:.2}", cash);
+            }
+            Err(e) => tracing::error!("Failed to get account info: {}", e),
+        }
+    }
+
+    /// Get position quantity for a symbol.
+    async fn get_position(&self, symbol: &str) -> Option<f64> {
+        match self.client.get_position(symbol).await {
+            Ok(Some(pos)) => pos.qty.parse().ok(),
+            Ok(None) => None,
+            Err(e) => {
+                tracing::error!("Failed to get position for {}: {}", symbol, e);
+                None
+            }
+        }
+    }
+
+    /// Calculate position size based on risk management.
+    async fn calculate_position_size(&self, price: f64) -> u64 {
+        let account = match self.client.get_account().await {
+            Ok(a) => a,
+            Err(e) => {
+                tracing::error!("Failed to get account: {}", e);
+                return 0;
+            }
+        };
+
+        let portfolio_value: f64 = account.portfolio_value.parse().unwrap_or(0.0);
+        let buying_power: f64 = account.buying_power.parse().unwrap_or(0.0);
+
+        let max_allocation = portfolio_value * MAX_POSITION_SIZE;
+        let available_funds = buying_power - (portfolio_value * MIN_CASH_RESERVE);
+
+        if available_funds <= 0.0 {
+            return 0;
+        }
+
+        let position_value = max_allocation.min(available_funds);
+        (position_value / price).floor() as u64
+    }
+
+    /// Check if stop-loss or take-profit should trigger.
+    fn check_stop_loss_take_profit(&self, symbol: &str, current_price: f64) -> Option<Signal> {
+        let entry_price = match self.entry_prices.get(symbol) {
+            Some(&p) => p,
+            None => return None,
+        };
+
+        let pnl_pct = (current_price - entry_price) / entry_price;
+
+        if pnl_pct <= -STOP_LOSS_PCT {
+            tracing::warn!("{}: Stop-loss triggered at {:.2}% loss", symbol, pnl_pct * 100.0);
+            return Some(Signal::StrongSell);
+        }
+
+        if pnl_pct >= TAKE_PROFIT_PCT {
+            tracing::info!("{}: Take-profit triggered at {:.2}% gain", symbol, pnl_pct * 100.0);
+            return Some(Signal::Sell);
+        }
+
+        None
+    }
+
+    /// Execute a buy order.
+    async fn execute_buy(&mut self, symbol: &str, signal: &TradeSignal) -> bool {
+        // Check if already holding
+        if let Some(qty) = self.get_position(symbol).await {
+            if qty > 0.0 {
+                tracing::info!("{}: Already holding {} shares, skipping buy", symbol, qty);
+                return false;
+            }
+        }
+
+        let shares = self.calculate_position_size(signal.current_price).await;
+        if shares == 0 {
+            tracing::info!("{}: Insufficient funds for purchase", symbol);
+            return false;
+        }
+
+        match self
+            .client
+            .submit_market_order(symbol, shares as f64, "buy")
+            .await
+        {
+            Ok(_order) => {
+                self.entry_prices.insert(symbol.to_string(), signal.current_price);
+                self.save_entry_prices();
+
+                tracing::info!(
+                    "BUY ORDER EXECUTED: {} - {} shares @ ~${:.2} \
+                     (RSI: {:.1}, MACD: {:.3}, Confidence: {:.2})",
+                    symbol,
+                    shares,
+                    signal.current_price,
+                    signal.rsi,
+                    signal.macd_histogram,
+                    signal.confidence
+                );
+
+                true
+            }
+            Err(e) => {
+                tracing::error!("Failed to execute buy for {}: {}", symbol, e);
+                false
+            }
+        }
+    }
+
+    /// Execute a sell order.
+    async fn execute_sell(&mut self, symbol: &str, signal: &TradeSignal) -> bool {
+        let current_position = match self.get_position(symbol).await {
+            Some(qty) if qty > 0.0 => qty,
+            _ => {
+                tracing::info!("{}: No position to sell", symbol);
+                return false;
+            }
+        };
+
+        match self
+            .client
+            .submit_market_order(symbol, current_position, "sell")
+            .await
+        {
+            Ok(_order) => {
+                if let Some(entry) = self.entry_prices.remove(symbol) {
+                    let pnl_pct = (signal.current_price - entry) / entry;
+                    tracing::info!("{}: Realized P&L: {:.2}%", symbol, pnl_pct * 100.0);
+                    self.save_entry_prices();
+                }
+
+                tracing::info!(
+                    "SELL ORDER EXECUTED: {} - {} shares @ ~${:.2} \
+                     (RSI: {:.1}, MACD: {:.3})",
+                    symbol,
+                    current_position,
+                    signal.current_price,
+                    signal.rsi,
+                    signal.macd_histogram
+                );
+
+                true
+            }
+            Err(e) => {
+                tracing::error!("Failed to execute sell for {}: {}", symbol, e);
+                false
+            }
+        }
+    }
+
+    /// Analyze a symbol and generate trading signal.
+    async fn analyze_symbol(&self, symbol: &str) -> Option<TradeSignal> {
+        let min_bars = self.params.min_bars();
+
+        // Calculate days needed for data
+        let days = if self.timeframe == Timeframe::Hourly {
+            (min_bars as f64 / HOURS_PER_DAY as f64 * 1.5) as i64 + 10
+        } else {
+            (min_bars as f64 * 1.5) as i64 + 30
+        };
+
+        let end = Utc::now();
+        let start = end - Duration::days(days);
+
+        let bars = match self.client.get_historical_bars(symbol, self.timeframe, start, end).await {
+            Ok(b) => b,
+            Err(e) => {
+                tracing::warn!("{}: Failed to get historical data: {}", symbol, e);
+                return None;
+            }
+        };
+
+        if bars.len() < min_bars {
+            tracing::warn!(
+                "{}: Only {} bars, need {} for indicators",
+                symbol,
+                bars.len(),
+                min_bars
+            );
+            return None;
+        }
+
+        let indicators = calculate_all_indicators(&bars, &self.params);
+
+        if indicators.len() < 2 {
+            return None;
+        }
+
+        let current = &indicators[indicators.len() - 1];
+        let previous = &indicators[indicators.len() - 2];
+
+        let mut signal = generate_signal(symbol, current, previous);
+
+        // Check stop-loss/take-profit
+        if let Some(sl_tp) = self.check_stop_loss_take_profit(symbol, signal.current_price) {
+            signal.signal = sl_tp;
+        }
+
+        Some(signal)
+    }
+
+    /// Execute one complete trading cycle.
+    async fn run_trading_cycle(&mut self) {
+        tracing::info!("{}", "=".repeat(60));
+        tracing::info!("Starting trading cycle...");
+        self.log_account_info().await;
+
+        let symbols = get_all_symbols();
+
+        for symbol in symbols {
+            tracing::info!("\nAnalyzing {}...", symbol);
+
+            let signal = match self.analyze_symbol(symbol).await {
+                Some(s) => s,
+                None => {
+                    tracing::warn!("{}: Analysis failed, skipping", symbol);
+                    continue;
+                }
+            };
+
+            tracing::info!(
+                "{}: Signal={}, RSI={:.1}, MACD Hist={:.3}, Momentum={:.2}%, \
+                 Price=${:.2}, Confidence={:.2}",
+                symbol,
+                signal.signal.as_str(),
+                signal.rsi,
+                signal.macd_histogram,
+                signal.momentum,
+                signal.current_price,
+                signal.confidence
+            );
+
+            if signal.signal.is_buy() {
+                self.execute_buy(symbol, &signal).await;
+            } else if signal.signal.is_sell() {
+                self.execute_sell(symbol, &signal).await;
+            } else {
+                tracing::info!("{}: Holding position (no action)", symbol);
+            }
+
+            // Small delay between symbols
+            sleep(TokioDuration::from_millis(500)).await;
+        }
+
+        // Save equity snapshot for dashboard
+        if let Err(e) = self.save_equity_snapshot().await {
+            tracing::error!("Failed to save equity snapshot: {}", e);
+        }
+
+        tracing::info!("Trading cycle complete");
+        tracing::info!("{}", "=".repeat(60));
+    }
+
+    /// Main bot loop - runs continuously during market hours.
+    pub async fn run(&mut self) -> Result<()> {
+        let symbols = get_all_symbols();
+
+        tracing::info!("{}", "=".repeat(60));
+        tracing::info!("TECH GIANTS TRADING BOT STARTED");
+        tracing::info!("Timeframe: {:?} bars", self.timeframe);
+        if self.timeframe == Timeframe::Hourly {
+            tracing::info!(
+                "Parameters scaled {}x (RSI: {}, EMA_TREND: {})",
+                HOURS_PER_DAY,
+                self.params.rsi_period,
+                self.params.ema_trend
+            );
+        }
+        tracing::info!("Symbols: {}", symbols.join(", "));
+        tracing::info!(
+            "Strategy: RSI({}) + MACD({},{},{}) + Momentum",
+            self.params.rsi_period,
+            self.params.macd_fast,
+            self.params.macd_slow,
+            self.params.macd_signal
+        );
+        tracing::info!("Bot Check Interval: {} seconds", BOT_CHECK_INTERVAL_SECONDS);
+        tracing::info!("{}", "=".repeat(60));
+
+        loop {
+            match self.client.is_market_open().await {
+                Ok(true) => {
+                    self.run_trading_cycle().await;
+
+                    tracing::info!(
+                        "Next signal check in {} seconds...",
+                        BOT_CHECK_INTERVAL_SECONDS
+                    );
+                    sleep(TokioDuration::from_secs(BOT_CHECK_INTERVAL_SECONDS)).await;
+                }
+                Ok(false) => {
+                    match self.client.get_next_market_open().await {
+                        Ok(next_open) => {
+                            let wait_seconds = (next_open - Utc::now()).num_seconds().max(0);
+                            tracing::info!("Market closed. Next open: {}", next_open);
+                            tracing::info!("Waiting {:.1} hours...", wait_seconds as f64 / 3600.0);
+
+                            let sleep_time = (wait_seconds as u64).min(300).max(60);
+                            sleep(TokioDuration::from_secs(sleep_time)).await;
+                        }
+                        Err(e) => {
+                            tracing::error!("Failed to get next market open: {}", e);
+                            tracing::info!("Market closed. Checking again in 5 minutes...");
+                            sleep(TokioDuration::from_secs(300)).await;
+                        }
+                    }
+                }
+                Err(e) => {
+                    tracing::error!("Failed to check market status: {}", e);
+                    tracing::info!("Retrying in 60 seconds...");
+                    sleep(TokioDuration::from_secs(60)).await;
+                }
+            }
+        }
+    }
+}

src/config.rs

@@ -0,0 +1,171 @@
+//! Configuration constants for the trading bot.
+
+// Stock Universe
+pub const MAG7: &[&str] = &["AAPL", "MSFT", "GOOGL", "AMZN", "META", "NVDA", "TSLA"];
+pub const SEMIS: &[&str] = &["AVGO", "AMD", "ASML", "QCOM", "MU"];
+pub const GROWTH_TECH: &[&str] = &["NFLX", "CRM", "NOW", "UBER", "SNOW"];
+pub const HEALTHCARE: &[&str] = &["LLY", "UNH", "ISRG", "VRTX", "ABBV", "MRK", "PFE"];
+pub const FINTECH_VOLATILE: &[&str] = &["V", "MA", "COIN", "PLTR", "MSTR"];
+pub const SP500_FINANCIALS: &[&str] = &["JPM", "GS", "MS", "BLK", "AXP", "C"];
+pub const SP500_INDUSTRIALS: &[&str] = &["CAT", "GE", "HON", "BA", "RTX", "LMT", "DE"];
+pub const SP500_CONSUMER: &[&str] = &["COST", "WMT", "HD", "NKE", "SBUX", "MCD", "DIS"];
+pub const SP500_ENERGY: &[&str] = &["XOM", "CVX", "COP", "SLB", "OXY"];
+
+/// Get all symbols in the trading universe (50 stocks).
+pub fn get_all_symbols() -> Vec<&'static str> {
+    let mut symbols = Vec::new();
+    symbols.extend_from_slice(MAG7);
+    symbols.extend_from_slice(SEMIS);
+    symbols.extend_from_slice(GROWTH_TECH);
+    symbols.extend_from_slice(HEALTHCARE);
+    symbols.extend_from_slice(FINTECH_VOLATILE);
+    symbols.extend_from_slice(SP500_FINANCIALS);
+    symbols.extend_from_slice(SP500_INDUSTRIALS);
+    symbols.extend_from_slice(SP500_CONSUMER);
+    symbols.extend_from_slice(SP500_ENERGY);
+    symbols
+}
+
+// Strategy Parameters
+pub const RSI_PERIOD: usize = 14;
+pub const RSI_OVERSOLD: f64 = 30.0;
+pub const RSI_OVERBOUGHT: f64 = 70.0;
+pub const RSI_PULLBACK_LOW: f64 = 35.0;
+pub const RSI_PULLBACK_HIGH: f64 = 60.0;
+
+pub const MACD_FAST: usize = 12;
+pub const MACD_SLOW: usize = 26;
+pub const MACD_SIGNAL: usize = 9;
+
+pub const MOMENTUM_PERIOD: usize = 5;
+
+pub const EMA_SHORT: usize = 9;
+pub const EMA_LONG: usize = 21;
+pub const EMA_TREND: usize = 50;
+
+// ADX - Trend Strength
+pub const ADX_PERIOD: usize = 14;
+pub const ADX_THRESHOLD: f64 = 25.0;
+pub const ADX_STRONG: f64 = 35.0;
+
+// Bollinger Bands
+pub const BB_PERIOD: usize = 20;
+pub const BB_STD: f64 = 2.0;
+
+// ATR for volatility-based stops
+pub const ATR_PERIOD: usize = 14;
+pub const ATR_MULTIPLIER_STOP: f64 = 1.5;
+pub const ATR_MULTIPLIER_TRAIL: f64 = 2.5;
+
+// Volume filter
+pub const VOLUME_MA_PERIOD: usize = 20;
+pub const VOLUME_THRESHOLD: f64 = 0.8;
+
+// Momentum Ranking
+pub const TOP_MOMENTUM_COUNT: usize = 4;
+
+// Risk Management
+pub const MAX_POSITION_SIZE: f64 = 0.22;
+pub const MIN_CASH_RESERVE: f64 = 0.01;
+pub const STOP_LOSS_PCT: f64 = 0.025;
+pub const TAKE_PROFIT_PCT: f64 = 0.40;
+pub const TRAILING_STOP_ACTIVATION: f64 = 0.12;
+pub const TRAILING_STOP_DISTANCE: f64 = 0.07;
+
+// Trading intervals
+pub const BOT_CHECK_INTERVAL_SECONDS: u64 = 60;
+pub const BARS_LOOKBACK: usize = 100;
+
+// Backtest defaults
+pub const DEFAULT_INITIAL_CAPITAL: f64 = 100_000.0;
+pub const TRADING_DAYS_PER_YEAR: usize = 252;
+
+// Hours per trading day (for scaling parameters)
+pub const HOURS_PER_DAY: usize = 7;
+
+/// Indicator parameters that can be scaled for different timeframes.
+#[derive(Debug, Clone)]
+pub struct IndicatorParams {
+    pub rsi_period: usize,
+    pub macd_fast: usize,
+    pub macd_slow: usize,
+    pub macd_signal: usize,
+    pub momentum_period: usize,
+    pub ema_short: usize,
+    pub ema_long: usize,
+    pub ema_trend: usize,
+    pub adx_period: usize,
+    pub bb_period: usize,
+    pub atr_period: usize,
+    pub volume_ma_period: usize,
+}
+
+impl IndicatorParams {
+    /// Create parameters for daily timeframe.
+    pub fn daily() -> Self {
+        Self {
+            rsi_period: RSI_PERIOD,
+            macd_fast: MACD_FAST,
+            macd_slow: MACD_SLOW,
+            macd_signal: MACD_SIGNAL,
+            momentum_period: MOMENTUM_PERIOD,
+            ema_short: EMA_SHORT,
+            ema_long: EMA_LONG,
+            ema_trend: EMA_TREND,
+            adx_period: ADX_PERIOD,
+            bb_period: BB_PERIOD,
+            atr_period: ATR_PERIOD,
+            volume_ma_period: VOLUME_MA_PERIOD,
+        }
+    }
+
+    /// Create parameters for hourly timeframe (scaled by HOURS_PER_DAY).
+    pub fn hourly() -> Self {
+        let scale = HOURS_PER_DAY;
+        Self {
+            rsi_period: RSI_PERIOD * scale,
+            macd_fast: MACD_FAST * scale,
+            macd_slow: MACD_SLOW * scale,
+            macd_signal: MACD_SIGNAL * scale,
+            momentum_period: MOMENTUM_PERIOD * scale,
+            ema_short: EMA_SHORT * scale,
+            ema_long: EMA_LONG * scale,
+            ema_trend: EMA_TREND * scale,
+            adx_period: ADX_PERIOD * scale,
+            bb_period: BB_PERIOD * scale,
+            atr_period: ATR_PERIOD * scale,
+            volume_ma_period: VOLUME_MA_PERIOD * scale,
+        }
+    }
+
+    /// Get the minimum number of bars required for indicator calculation.
+    pub fn min_bars(&self) -> usize {
+        *[
+            self.macd_slow,
+            self.rsi_period,
+            self.ema_trend,
+            self.adx_period,
+            self.bb_period,
+        ]
+        .iter()
+        .max()
+        .unwrap()
+            + 5
+    }
+}
+
+/// Timeframe for trading data.
+#[derive(Debug, Clone, Copy, PartialEq, Eq, clap::ValueEnum)]
+pub enum Timeframe {
+    Daily,
+    Hourly,
+}
+
+impl Timeframe {
+    pub fn params(&self) -> IndicatorParams {
+        match self {
+            Timeframe::Daily => IndicatorParams::daily(),
+            Timeframe::Hourly => IndicatorParams::hourly(),
+        }
+    }
+}

src/dashboard.rs

@@ -0,0 +1,479 @@
+//! Web dashboard for monitoring portfolio performance.
+
+use axum::{
+    extract::State,
+    http::StatusCode,
+    response::{Html, IntoResponse, Json},
+    routing::get,
+    Router,
+};
+use serde::Serialize;
+use std::path::Path;
+use std::sync::Arc;
+use tower_http::cors::CorsLayer;
+
+use crate::alpaca::AlpacaClient;
+use crate::paths::LIVE_EQUITY_FILE;
+use crate::types::EquitySnapshot;
+
+/// Shared state for the dashboard.
+pub struct DashboardState {
+    pub client: AlpacaClient,
+}
+
+#[derive(Serialize)]
+struct AccountResponse {
+    portfolio_value: f64,
+    cash: f64,
+    buying_power: f64,
+    total_pnl: f64,
+    position_count: usize,
+}
+
+#[derive(Serialize)]
+struct EquityResponse {
+    dates: Vec<String>,
+    values: Vec<f64>,
+    source: String,
+}
+
+#[derive(Serialize)]
+struct PositionResponse {
+    symbol: String,
+    qty: f64,
+    market_value: f64,
+    avg_entry_price: f64,
+    current_price: f64,
+    unrealized_pnl: f64,
+    pnl_pct: f64,
+    change_today: f64,
+}
+
+const HTML_TEMPLATE: &str = r#"<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Trading Bot Dashboard</title>
+    <script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
+    <style>
+        * { margin: 0; padding: 0; box-sizing: border-box; }
+        body {
+            font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
+            background: linear-gradient(135deg, #1a1a2e 0%, #16213e 100%);
+            color: #eee;
+            min-height: 100vh;
+            padding: 20px;
+        }
+        .container { max-width: 1400px; margin: 0 auto; }
+        h1 {
+            text-align: center;
+            margin-bottom: 30px;
+            font-size: 2.5rem;
+            background: linear-gradient(90deg, #00d4ff, #7b2cbf);
+            -webkit-background-clip: text;
+            -webkit-text-fill-color: transparent;
+        }
+        .stats-grid {
+            display: grid;
+            grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
+            gap: 20px;
+            margin-bottom: 30px;
+        }
+        .stat-card {
+            background: rgba(255, 255, 255, 0.05);
+            border-radius: 16px;
+            padding: 24px;
+            text-align: center;
+            backdrop-filter: blur(10px);
+            border: 1px solid rgba(255, 255, 255, 0.1);
+        }
+        .stat-label { font-size: 0.85rem; color: #888; text-transform: uppercase; margin-bottom: 8px; }
+        .stat-value { font-size: 1.8rem; font-weight: 700; }
+        .stat-value.positive { color: #00ff88; }
+        .stat-value.negative { color: #ff4757; }
+        .chart-container {
+            background: rgba(255, 255, 255, 0.05);
+            border-radius: 16px;
+            padding: 24px;
+            margin-bottom: 30px;
+            border: 1px solid rgba(255, 255, 255, 0.1);
+        }
+        .chart-title { font-size: 1.3rem; margin-bottom: 20px; color: #fff; }
+        .positions-grid {
+            display: grid;
+            grid-template-columns: repeat(auto-fit, minmax(280px, 1fr));
+            gap: 20px;
+        }
+        .position-card {
+            background: rgba(255, 255, 255, 0.05);
+            border-radius: 16px;
+            padding: 20px;
+            border: 1px solid rgba(255, 255, 255, 0.1);
+        }
+        .position-header { display: flex; justify-content: space-between; align-items: center; margin-bottom: 15px; }
+        .position-symbol { font-size: 1.4rem; font-weight: 700; }
+        .position-pnl { font-size: 1.1rem; font-weight: 600; padding: 4px 12px; border-radius: 20px; }
+        .position-pnl.positive { background: rgba(0, 255, 136, 0.2); color: #00ff88; }
+        .position-pnl.negative { background: rgba(255, 71, 87, 0.2); color: #ff4757; }
+        .position-details { display: grid; grid-template-columns: 1fr 1fr; gap: 10px; }
+        .position-detail { padding: 8px 0; }
+        .position-detail-label { font-size: 0.75rem; color: #888; text-transform: uppercase; }
+        .position-detail-value { font-size: 1rem; font-weight: 500; margin-top: 2px; }
+        .loading { text-align: center; padding: 40px; color: #888; }
+        .refresh-btn {
+            position: fixed;
+            bottom: 30px;
+            right: 30px;
+            background: linear-gradient(135deg, #00d4ff, #7b2cbf);
+            border: none;
+            color: white;
+            padding: 15px 25px;
+            border-radius: 50px;
+            font-size: 1rem;
+            cursor: pointer;
+            box-shadow: 0 4px 15px rgba(0, 212, 255, 0.4);
+            transition: transform 0.2s ease;
+        }
+        .refresh-btn:hover { transform: scale(1.05); }
+        .last-updated { text-align: center; color: #666; font-size: 0.85rem; margin-top: 20px; }
+        .data-source { text-align: center; color: #888; font-size: 0.8rem; margin-top: 5px; }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <h1>Trading Bot Dashboard (Rust)</h1>
+        <div class="stats-grid" id="stats-grid">
+            <div class="stat-card">
+                <div class="stat-label">Portfolio Value</div>
+                <div class="stat-value" id="stat-portfolio-value">$0.00</div>
+            </div>
+            <div class="stat-card">
+                <div class="stat-label">Cash</div>
+                <div class="stat-value" id="stat-cash">$0.00</div>
+            </div>
+            <div class="stat-card">
+                <div class="stat-label">Buying Power</div>
+                <div class="stat-value" id="stat-buying-power">$0.00</div>
+            </div>
+            <div class="stat-card">
+                <div class="stat-label">Today's P&L</div>
+                <div class="stat-value" id="stat-pnl">$0.00</div>
+            </div>
+            <div class="stat-card">
+                <div class="stat-label">Open Positions</div>
+                <div class="stat-value" id="stat-positions">0</div>
+            </div>
+        </div>
+        <div class="chart-container">
+            <h2 class="chart-title">Portfolio Performance</h2>
+            <canvas id="portfolioChart"></canvas>
+        </div>
+        <div class="chart-container">
+            <h2 class="chart-title">Current Positions</h2>
+            <div class="positions-grid" id="positions-grid"><div class="loading">Loading...</div></div>
+        </div>
+        <p class="last-updated" id="last-updated"></p>
+        <p class="data-source" id="data-source"></p>
+    </div>
+    <button class="refresh-btn" onclick="loadAllData()">Refresh</button>
+    <script>
+        let portfolioChart = null;
+
+        function formatCurrency(value, sign = false) {
+            const signChar = value >= 0 ? (sign ? '+' : '') : '-';
+            return `${signChar}$${Math.abs(value).toLocaleString('en-US', {minimumFractionDigits: 2, maximumFractionDigits: 2})}`;
+        }
+
+        function updateText(elementId, value, isCurrency = false, sign = false) {
+            const el = document.getElementById(elementId);
+            if (el) el.textContent = isCurrency ? formatCurrency(value, sign) : value;
+        }
+
+        function updateClass(elementId, value) {
+            const el = document.getElementById(elementId);
+            if (el) {
+                el.classList.toggle('positive', value >= 0);
+                el.classList.toggle('negative', value < 0);
+            }
+        }
+
+        async function loadAccountStats() {
+            try {
+                const response = await fetch('/api/account');
+                const data = await response.json();
+
+                updateText('stat-portfolio-value', data.portfolio_value, true);
+                updateText('stat-cash', data.cash, true);
+                updateText('stat-buying-power', data.buying_power, true);
+                updateText('stat-pnl', data.total_pnl, true, true);
+                updateText('stat-positions', data.position_count);
+                updateClass('stat-pnl', data.total_pnl);
+
+            } catch (error) { console.error('Error loading account stats:', error); }
+        }
+
+        async function loadEquityCurve() {
+            try {
+                const response = await fetch('/api/equity');
+                const data = await response.json();
+                const sourceEl = document.getElementById('data-source');
+
+                if (data.source === 'live') {
+                    sourceEl.innerHTML = '<span style="color: #00ff88;">Live Data</span>';
+                } else if (data.source === 'backtest') {
+                    sourceEl.innerHTML = '<span style="color: #ffaa00;">Backtest Data</span>';
+                } else {
+                    sourceEl.innerHTML = '<span style="color: #888;">No data</span>';
+                }
+
+                if (!portfolioChart) {
+                    const ctx = document.getElementById('portfolioChart').getContext('2d');
+                    const gradient = ctx.createLinearGradient(0, 0, 0, 400);
+                    gradient.addColorStop(0, 'rgba(0, 212, 255, 0.3)');
+                    gradient.addColorStop(1, 'rgba(0, 212, 255, 0)');
+                    portfolioChart = new Chart(ctx, {
+                        type: 'line',
+                        data: { labels: [], datasets: [{
+                            label: 'Portfolio Value', data: [], borderColor: '#00d4ff',
+                            backgroundColor: gradient, fill: true, tension: 0.4,
+                            pointRadius: 0, borderWidth: 2
+                        }]},
+                        options: {
+                            responsive: true,
+                            plugins: { legend: { display: false } },
+                            scales: {
+                                x: { grid: { color: 'rgba(255,255,255,0.05)' }, ticks: { color: '#888', maxTicksLimit: 10 } },
+                                y: { grid: { color: 'rgba(255,255,255,0.05)' }, ticks: { color: '#888', callback: v => '$' + v.toLocaleString() } }
+                            }
+                        }
+                    });
+                }
+
+                portfolioChart.data.labels = data.dates;
+                portfolioChart.data.datasets[0].data = data.values;
+                portfolioChart.update('none'); // 'none' for no animation
+
+            } catch (error) { console.error('Error loading equity curve:', error); }
+        }
+
+        async function loadPositions() {
+            try {
+                const response = await fetch('/api/positions');
+                const positions = await response.json();
+                const grid = document.getElementById('positions-grid');
+                if (positions.length === 0) {
+                    grid.innerHTML = '<div class="loading">No open positions</div>';
+                    return;
+                }
+                grid.innerHTML = positions.map(pos => {
+                    const pnlClass = pos.pnl_pct >= 0 ? 'positive' : 'negative';
+                    const pnlSign = pos.pnl_pct >= 0 ? '+' : '';
+                    const changeClass = pos.change_today >= 0 ? 'positive' : 'negative';
+                    const changeSign = pos.change_today >= 0 ? '+' : '';
+
+                    return `<div class="position-card">
+                        <div class="position-header">
+                            <span class="position-symbol">${pos.symbol}</span>
+                            <span class="position-pnl ${pnlClass}">${pnlSign}${pos.pnl_pct.toFixed(2)}%</span>
+                        </div>
+                        <div class="position-details">
+                            <div class="position-detail"><div class="position-detail-label">Shares</div><div class="position-detail-value">${pos.qty}</div></div>
+                            <div class="position-detail"><div class="position-detail-label">Market Value</div><div class="position-detail-value">${formatCurrency(pos.market_value)}</div></div>
+                            <div class="position-detail"><div class="position-detail-label">Avg Cost</div><div class="position-detail-value">${formatCurrency(pos.avg_entry_price)}</div></div>
+                            <div class="position-detail"><div class="position-detail-label">Current</div><div class="position-detail-value">${formatCurrency(pos.current_price)}</div></div>
+                            <div class="position-detail"><div class="position-detail-label">P&L</div><div class="position-detail-value ${pnlClass}">${formatCurrency(pos.unrealized_pnl, true)}</div></div>
+                            <div class="position-detail"><div class="position-detail-label">Today</div><div class="position-detail-value ${changeClass}">${changeSign}${pos.change_today.toFixed(2)}%</div></div>
+                        </div>
+                    </div>`;
+                }).join('');
+            } catch (error) { console.error('Error loading positions:', error); }
+        }
+
+        function updateTimestamp() {
+            document.getElementById('last-updated').textContent = 'Last updated: ' + new Date().toLocaleString();
+        }
+
+        async function loadAllData() {
+            await Promise.all([loadAccountStats(), loadEquityCurve(), loadPositions()]);
+            updateTimestamp();
+        }
+
+        // Initial load
+        document.addEventListener('DOMContentLoaded', () => {
+            loadAllData();
+            setInterval(loadAllData, 10000); // Refresh every 10 seconds
+        });
+    </script>
+</body>
+</html>"#;
+
+async fn index() -> Html<&'static str> {
+    Html(HTML_TEMPLATE)
+}
+
+async fn api_account(State(state): State<Arc<DashboardState>>) -> impl IntoResponse {
+    match get_account_data(&state.client).await {
+        Ok(data) => Json(data).into_response(),
+        Err(e) => {
+            tracing::error!("Failed to get account: {}", e);
+            (
+                StatusCode::INTERNAL_SERVER_ERROR,
+                Json(AccountResponse {
+                    portfolio_value: 0.0,
+                    cash: 0.0,
+                    buying_power: 0.0,
+                    total_pnl: 0.0,
+                    position_count: 0,
+                }),
+            )
+                .into_response()
+        }
+    }
+}
+
+async fn get_account_data(client: &AlpacaClient) -> anyhow::Result<AccountResponse> {
+    let account = client.get_account().await?;
+    let positions = client.get_positions().await?;
+
+    let total_pnl: f64 = positions
+        .iter()
+        .filter_map(|p| p.unrealized_pl.parse::<f64>().ok())
+        .sum();
+
+    Ok(AccountResponse {
+        portfolio_value: account.portfolio_value.parse().unwrap_or(0.0),
+        cash: account.cash.parse().unwrap_or(0.0),
+        buying_power: account.buying_power.parse().unwrap_or(0.0),
+        total_pnl,
+        position_count: positions.len(),
+    })
+}
+
+async fn api_equity() -> Json<EquityResponse> {
+    // Try live equity data first
+    if LIVE_EQUITY_FILE.exists() {
+        if let Ok(content) = std::fs::read_to_string(&*LIVE_EQUITY_FILE) {
+            if let Ok(data) = serde_json::from_str::<Vec<EquitySnapshot>>(&content) {
+                if !data.is_empty() {
+                    const MAX_DATAPOINTS_TO_SHOW: usize = 240; // 4 hours of data (1 per minute)
+                    let start_index = if data.len() > MAX_DATAPOINTS_TO_SHOW {
+                        data.len() - MAX_DATAPOINTS_TO_SHOW
+                    } else {
+                        0
+                    };
+                    let data_slice = &data[start_index..];
+
+                    let dates: Vec<String> = data_slice
+                        .iter()
+                        .map(|s| {
+                            if s.timestamp.len() >= 16 {
+                                s.timestamp[5..16].replace("T", " ")
+                            } else {
+                                s.timestamp.clone()
+                            }
+                        })
+                        .collect();
+                    let values: Vec<f64> = data_slice.iter().map(|s| s.portfolio_value).collect();
+
+                    return Json(EquityResponse {
+                        dates,
+                        values,
+                        source: "live".to_string(),
+                    });
+                }
+            }
+        }
+    }
+
+    // Fall back to backtest data
+    if Path::new("backtest_equity_curve.csv").exists() {
+        if let Ok(mut rdr) = csv::Reader::from_path("backtest_equity_curve.csv") {
+            let mut dates = Vec::new();
+            let mut values = Vec::new();
+
+            for result in rdr.records() {
+                if let Ok(record) = result {
+                    if let Some(date) = record.get(0) {
+                        let formatted = if date.len() >= 16 {
+                            date[5..16].replace("T", " ")
+                        } else {
+                            date.to_string()
+                        };
+                        dates.push(formatted);
+                    }
+                    if let Some(value) = record.get(1) {
+                        if let Ok(v) = value.parse::<f64>() {
+                            values.push(v);
+                        }
+                    }
+                }
+            }
+
+            if !dates.is_empty() {
+                return Json(EquityResponse {
+                    dates,
+                    values,
+                    source: "backtest".to_string(),
+                });
+            }
+        }
+    }
+
+    Json(EquityResponse {
+        dates: vec![],
+        values: vec![],
+        source: "none".to_string(),
+    })
+}
+
+async fn api_positions(State(state): State<Arc<DashboardState>>) -> impl IntoResponse {
+    match state.client.get_positions().await {
+        Ok(positions) => {
+            let mut result: Vec<PositionResponse> = positions
+                .iter()
+                .map(|p| PositionResponse {
+                    symbol: p.symbol.clone(),
+                    qty: p.qty.parse().unwrap_or(0.0),
+                    market_value: p.market_value.parse().unwrap_or(0.0),
+                    avg_entry_price: p.avg_entry_price.parse().unwrap_or(0.0),
+                    current_price: p.current_price.parse().unwrap_or(0.0),
+                    unrealized_pnl: p.unrealized_pl.parse().unwrap_or(0.0),
+                    pnl_pct: p.unrealized_plpc.parse::<f64>().unwrap_or(0.0) * 100.0,
+                    change_today: p
+                        .change_today
+                        .as_ref()
+                        .and_then(|s| s.parse::<f64>().ok())
+                        .unwrap_or(0.0)
+                        * 100.0,
+                })
+                .collect();
+
+            result.sort_by(|a, b| b.market_value.partial_cmp(&a.market_value).unwrap());
+            Json(result).into_response()
+        }
+        Err(e) => {
+            tracing::error!("Failed to get positions: {}", e);
+            Json(Vec::<PositionResponse>::new()).into_response()
+        }
+    }
+}
+
+/// Start the dashboard web server.
+pub async fn start_dashboard(client: AlpacaClient, port: u16) -> anyhow::Result<()> {
+    let state = Arc::new(DashboardState { client });
+
+    let app = Router::new()
+        .route("/", get(index))
+        .route("/api/account", get(api_account))
+        .route("/api/equity", get(api_equity))
+        .route("/api/positions", get(api_positions))
+        .layer(CorsLayer::permissive())
+        .with_state(state);
+
+    let listener = tokio::net::TcpListener::bind(format!("0.0.0.0:{}", port)).await?;
+    tracing::info!("Dashboard running on http://localhost:{}", port);
+
+    axum::serve(listener, app).await?;
+    Ok(())
+}

src/indicators.rs

@@ -0,0 +1,621 @@
+//! Technical indicator calculations.
+
+use crate::config::{
+    IndicatorParams, ADX_STRONG, ADX_THRESHOLD, BB_STD, RSI_OVERBOUGHT, RSI_OVERSOLD,
+    RSI_PULLBACK_HIGH, RSI_PULLBACK_LOW, VOLUME_THRESHOLD,
+};
+use crate::types::{Bar, IndicatorRow, Signal, TradeSignal};
+
+/// Calculate Exponential Moving Average (EMA).
+pub fn calculate_ema(data: &[f64], period: usize) -> Vec<f64> {
+    if data.is_empty() || period == 0 {
+        return vec![];
+    }
+
+    let mut ema = vec![f64::NAN; data.len()];
+    let multiplier = 2.0 / (period as f64 + 1.0);
+
+    // Start with SMA for the first period values
+    if data.len() >= period {
+        let sma: f64 = data[..period].iter().sum::<f64>() / period as f64;
+        ema[period - 1] = sma;
+
+        for i in period..data.len() {
+            ema[i] = (data[i] - ema[i - 1]) * multiplier + ema[i - 1];
+        }
+    }
+
+    ema
+}
+
+/// Calculate Simple Moving Average (SMA).
+pub fn calculate_sma(data: &[f64], period: usize) -> Vec<f64> {
+    if data.is_empty() || period == 0 {
+        return vec![];
+    }
+
+    let mut sma = vec![f64::NAN; data.len()];
+
+    for i in (period - 1)..data.len() {
+        let sum: f64 = data[(i + 1 - period)..=i].iter().sum();
+        sma[i] = sum / period as f64;
+    }
+
+    sma
+}
+
+/// Calculate standard deviation over a rolling window.
+pub fn calculate_rolling_std(data: &[f64], period: usize) -> Vec<f64> {
+    if data.is_empty() || period == 0 {
+        return vec![];
+    }
+
+    let mut std = vec![f64::NAN; data.len()];
+
+    for i in (period - 1)..data.len() {
+        let window = &data[(i + 1 - period)..=i];
+        let mean: f64 = window.iter().sum::<f64>() / period as f64;
+        let variance: f64 = window.iter().map(|x| (x - mean).powi(2)).sum::<f64>() / period as f64;
+        std[i] = variance.sqrt();
+    }
+
+    std
+}
+
+/// Calculate Relative Strength Index (RSI).
+pub fn calculate_rsi(closes: &[f64], period: usize) -> Vec<f64> {
+    if closes.len() < 2 || period == 0 {
+        return vec![f64::NAN; closes.len()];
+    }
+
+    let mut rsi = vec![f64::NAN; closes.len()];
+
+    // Calculate price changes
+    let mut gains = vec![0.0; closes.len()];
+    let mut losses = vec![0.0; closes.len()];
+
+    for i in 1..closes.len() {
+        let change = closes[i] - closes[i - 1];
+        if change > 0.0 {
+            gains[i] = change;
+        } else {
+            losses[i] = -change;
+        }
+    }
+
+    // Calculate initial average gain/loss
+    if closes.len() > period {
+        let mut avg_gain: f64 = gains[1..=period].iter().sum::<f64>() / period as f64;
+        let mut avg_loss: f64 = losses[1..=period].iter().sum::<f64>() / period as f64;
+
+        if avg_loss == 0.0 {
+            rsi[period] = 100.0;
+        } else {
+            let rs = avg_gain / avg_loss;
+            rsi[period] = 100.0 - (100.0 / (1.0 + rs));
+        }
+
+        // Smoothed RSI calculation
+        for i in (period + 1)..closes.len() {
+            avg_gain = (avg_gain * (period - 1) as f64 + gains[i]) / period as f64;
+            avg_loss = (avg_loss * (period - 1) as f64 + losses[i]) / period as f64;
+
+            if avg_loss == 0.0 {
+                rsi[i] = 100.0;
+            } else {
+                let rs = avg_gain / avg_loss;
+                rsi[i] = 100.0 - (100.0 / (1.0 + rs));
+            }
+        }
+    }
+
+    rsi
+}
+
+/// Calculate MACD (Moving Average Convergence Divergence).
+pub fn calculate_macd(
+    closes: &[f64],
+    fast_period: usize,
+    slow_period: usize,
+    signal_period: usize,
+) -> (Vec<f64>, Vec<f64>, Vec<f64>) {
+    let fast_ema = calculate_ema(closes, fast_period);
+    let slow_ema = calculate_ema(closes, slow_period);
+
+    let mut macd_line = vec![f64::NAN; closes.len()];
+    for i in 0..closes.len() {
+        if !fast_ema[i].is_nan() && !slow_ema[i].is_nan() {
+            macd_line[i] = fast_ema[i] - slow_ema[i];
+        }
+    }
+
+    // Calculate signal line from MACD line (excluding NaN values)
+    let valid_macd: Vec<f64> = macd_line.iter().copied().filter(|x| !x.is_nan()).collect();
+    let signal_ema = calculate_ema(&valid_macd, signal_period);
+
+    // Map signal EMA back to original indices
+    let mut signal_line = vec![f64::NAN; closes.len()];
+    let mut valid_idx = 0;
+    for i in 0..closes.len() {
+        if !macd_line[i].is_nan() {
+            if valid_idx < signal_ema.len() {
+                signal_line[i] = signal_ema[valid_idx];
+            }
+            valid_idx += 1;
+        }
+    }
+
+    // Calculate histogram
+    let mut histogram = vec![f64::NAN; closes.len()];
+    for i in 0..closes.len() {
+        if !macd_line[i].is_nan() && !signal_line[i].is_nan() {
+            histogram[i] = macd_line[i] - signal_line[i];
+        }
+    }
+
+    (macd_line, signal_line, histogram)
+}
+
+/// Calculate Rate of Change (Momentum).
+pub fn calculate_roc(closes: &[f64], period: usize) -> Vec<f64> {
+    if closes.is_empty() || period == 0 {
+        return vec![];
+    }
+
+    let mut roc = vec![f64::NAN; closes.len()];
+
+    for i in period..closes.len() {
+        if closes[i - period] != 0.0 {
+            roc[i] = ((closes[i] - closes[i - period]) / closes[i - period]) * 100.0;
+        }
+    }
+
+    roc
+}
+
+/// Calculate True Range.
+fn calculate_true_range(highs: &[f64], lows: &[f64], closes: &[f64]) -> Vec<f64> {
+    let mut tr = vec![f64::NAN; highs.len()];
+
+    if !highs.is_empty() {
+        tr[0] = highs[0] - lows[0];
+    }
+
+    for i in 1..highs.len() {
+        let hl = highs[i] - lows[i];
+        let hc = (highs[i] - closes[i - 1]).abs();
+        let lc = (lows[i] - closes[i - 1]).abs();
+        tr[i] = hl.max(hc).max(lc);
+    }
+
+    tr
+}
+
+/// Calculate Average True Range (ATR).
+pub fn calculate_atr(highs: &[f64], lows: &[f64], closes: &[f64], period: usize) -> Vec<f64> {
+    let tr = calculate_true_range(highs, lows, closes);
+
+    // Use Wilder's smoothing (similar to EMA but with different multiplier)
+    let mut atr = vec![f64::NAN; tr.len()];
+
+    if tr.len() >= period {
+        // First ATR is simple average
+        let first_atr: f64 = tr[..period].iter().filter(|x| !x.is_nan()).sum::<f64>() / period as f64;
+        atr[period - 1] = first_atr;
+
+        // Subsequent ATR values use smoothing
+        for i in period..tr.len() {
+            atr[i] = (atr[i - 1] * (period - 1) as f64 + tr[i]) / period as f64;
+        }
+    }
+
+    atr
+}
+
+/// Calculate ADX (Average Directional Index) along with DI+ and DI-.
+pub fn calculate_adx(
+    highs: &[f64],
+    lows: &[f64],
+    closes: &[f64],
+    period: usize,
+) -> (Vec<f64>, Vec<f64>, Vec<f64>) {
+    let len = highs.len();
+    if len < 2 {
+        return (vec![f64::NAN; len], vec![f64::NAN; len], vec![f64::NAN; len]);
+    }
+
+    let mut plus_dm = vec![0.0; len];
+    let mut minus_dm = vec![0.0; len];
+
+    // Calculate +DM and -DM
+    for i in 1..len {
+        let up_move = highs[i] - highs[i - 1];
+        let down_move = lows[i - 1] - lows[i];
+
+        if up_move > down_move && up_move > 0.0 {
+            plus_dm[i] = up_move;
+        }
+        if down_move > up_move && down_move > 0.0 {
+            minus_dm[i] = down_move;
+        }
+    }
+
+    let tr = calculate_true_range(highs, lows, closes);
+
+    // Smooth the values using Wilder's smoothing
+    let mut smoothed_plus_dm = vec![f64::NAN; len];
+    let mut smoothed_minus_dm = vec![f64::NAN; len];
+    let mut smoothed_tr = vec![f64::NAN; len];
+
+    if len >= period {
+        smoothed_plus_dm[period - 1] = plus_dm[..period].iter().sum();
+        smoothed_minus_dm[period - 1] = minus_dm[..period].iter().sum();
+        smoothed_tr[period - 1] = tr[..period].iter().filter(|x| !x.is_nan()).sum();
+
+        for i in period..len {
+            smoothed_plus_dm[i] =
+                smoothed_plus_dm[i - 1] - (smoothed_plus_dm[i - 1] / period as f64) + plus_dm[i];
+            smoothed_minus_dm[i] =
+                smoothed_minus_dm[i - 1] - (smoothed_minus_dm[i - 1] / period as f64) + minus_dm[i];
+            smoothed_tr[i] =
+                smoothed_tr[i - 1] - (smoothed_tr[i - 1] / period as f64) + tr[i];
+        }
+    }
+
+    // Calculate DI+ and DI-
+    let mut di_plus = vec![f64::NAN; len];
+    let mut di_minus = vec![f64::NAN; len];
+
+    for i in 0..len {
+        if !smoothed_tr[i].is_nan() && smoothed_tr[i] != 0.0 {
+            di_plus[i] = (smoothed_plus_dm[i] / smoothed_tr[i]) * 100.0;
+            di_minus[i] = (smoothed_minus_dm[i] / smoothed_tr[i]) * 100.0;
+        }
+    }
+
+    // Calculate DX
+    let mut dx = vec![f64::NAN; len];
+    for i in 0..len {
+        if !di_plus[i].is_nan() && !di_minus[i].is_nan() {
+            let di_sum = di_plus[i] + di_minus[i];
+            if di_sum != 0.0 {
+                dx[i] = ((di_plus[i] - di_minus[i]).abs() / di_sum) * 100.0;
+            }
+        }
+    }
+
+    // Calculate ADX (smoothed DX)
+    let mut adx = vec![f64::NAN; len];
+    let adx_start = period * 2 - 1;
+
+    if len > adx_start {
+        // First ADX is simple average of DX
+        let first_adx: f64 = dx[(period - 1)..adx_start]
+            .iter()
+            .filter(|x| !x.is_nan())
+            .sum::<f64>()
+            / period as f64;
+        adx[adx_start - 1] = first_adx;
+
+        for i in adx_start..len {
+            if !dx[i].is_nan() {
+                adx[i] = (adx[i - 1] * (period - 1) as f64 + dx[i]) / period as f64;
+            }
+        }
+    }
+
+    (adx, di_plus, di_minus)
+}
+
+/// Calculate Bollinger Bands.
+pub fn calculate_bollinger_bands(
+    closes: &[f64],
+    period: usize,
+    std_dev: f64,
+) -> (Vec<f64>, Vec<f64>, Vec<f64>, Vec<f64>) {
+    let middle = calculate_sma(closes, period);
+    let std = calculate_rolling_std(closes, period);
+
+    let mut upper = vec![f64::NAN; closes.len()];
+    let mut lower = vec![f64::NAN; closes.len()];
+    let mut pct_b = vec![f64::NAN; closes.len()];
+
+    for i in 0..closes.len() {
+        if !middle[i].is_nan() && !std[i].is_nan() {
+            upper[i] = middle[i] + std_dev * std[i];
+            lower[i] = middle[i] - std_dev * std[i];
+
+            let band_width = upper[i] - lower[i];
+            if band_width != 0.0 {
+                pct_b[i] = (closes[i] - lower[i]) / band_width;
+            }
+        }
+    }
+
+    (upper, middle, lower, pct_b)
+}
+
+/// Calculate all technical indicators for a series of bars.
+pub fn calculate_all_indicators(bars: &[Bar], params: &IndicatorParams) -> Vec<IndicatorRow> {
+    if bars.is_empty() {
+        return vec![];
+    }
+
+    let closes: Vec<f64> = bars.iter().map(|b| b.close).collect();
+    let highs: Vec<f64> = bars.iter().map(|b| b.high).collect();
+    let lows: Vec<f64> = bars.iter().map(|b| b.low).collect();
+    let volumes: Vec<f64> = bars.iter().map(|b| b.volume).collect();
+
+    // Calculate all indicators
+    let rsi = calculate_rsi(&closes, params.rsi_period);
+    let (macd, macd_signal, macd_histogram) =
+        calculate_macd(&closes, params.macd_fast, params.macd_slow, params.macd_signal);
+    let momentum = calculate_roc(&closes, params.momentum_period);
+    let ema_short = calculate_ema(&closes, params.ema_short);
+    let ema_long = calculate_ema(&closes, params.ema_long);
+    let ema_trend = calculate_ema(&closes, params.ema_trend);
+    let atr = calculate_atr(&highs, &lows, &closes, params.atr_period);
+    let (adx, di_plus, di_minus) = calculate_adx(&highs, &lows, &closes, params.adx_period);
+    let (bb_upper, bb_middle, bb_lower, bb_pct) =
+        calculate_bollinger_bands(&closes, params.bb_period, BB_STD);
+    let volume_ma = calculate_sma(&volumes, params.volume_ma_period);
+
+    // Build indicator rows
+    let mut rows = Vec::with_capacity(bars.len());
+
+    for i in 0..bars.len() {
+        let bar = &bars[i];
+
+        let vol_ratio = if !volume_ma[i].is_nan() && volume_ma[i] != 0.0 {
+            bar.volume / volume_ma[i]
+        } else {
+            f64::NAN
+        };
+
+        let ema_dist = if !ema_trend[i].is_nan() && ema_trend[i] != 0.0 {
+            (bar.close - ema_trend[i]) / ema_trend[i]
+        } else {
+            f64::NAN
+        };
+
+        let atr_pct_val = if !atr[i].is_nan() && bar.close != 0.0 {
+            atr[i] / bar.close
+        } else {
+            f64::NAN
+        };
+
+        rows.push(IndicatorRow {
+            timestamp: bar.timestamp,
+            open: bar.open,
+            high: bar.high,
+            low: bar.low,
+            close: bar.close,
+            volume: bar.volume,
+            rsi: rsi[i],
+            macd: macd[i],
+            macd_signal: macd_signal[i],
+            macd_histogram: macd_histogram[i],
+            momentum: momentum[i],
+            ema_short: ema_short[i],
+            ema_long: ema_long[i],
+            ema_trend: ema_trend[i],
+            ema_bullish: !ema_short[i].is_nan()
+                && !ema_long[i].is_nan()
+                && ema_short[i] > ema_long[i],
+            trend_bullish: !ema_trend[i].is_nan() && bar.close > ema_trend[i],
+            atr: atr[i],
+            atr_pct: atr_pct_val,
+            adx: adx[i],
+            di_plus: di_plus[i],
+            di_minus: di_minus[i],
+            bb_upper: bb_upper[i],
+            bb_middle: bb_middle[i],
+            bb_lower: bb_lower[i],
+            bb_pct: bb_pct[i],
+            volume_ma: volume_ma[i],
+            volume_ratio: vol_ratio,
+            ema_distance: ema_dist,
+        });
+    }
+
+    rows
+}
+
+/// Generate trading signal from current and previous indicator rows.
+pub fn generate_signal(symbol: &str, current: &IndicatorRow, previous: &IndicatorRow) -> TradeSignal {
+    let rsi = current.rsi;
+    let macd = current.macd;
+    let macd_signal_val = current.macd_signal;
+    let macd_hist = current.macd_histogram;
+    let momentum = current.momentum;
+    let ema_short = current.ema_short;
+    let ema_long = current.ema_long;
+    let current_price = current.close;
+
+    // Advanced indicators
+    let trend_bullish = current.trend_bullish;
+    let volume_ratio = if current.volume_ratio.is_nan() {
+        1.0
+    } else {
+        current.volume_ratio
+    };
+    let adx = if current.adx.is_nan() { 25.0 } else { current.adx };
+    let di_plus = if current.di_plus.is_nan() {
+        25.0
+    } else {
+        current.di_plus
+    };
+    let di_minus = if current.di_minus.is_nan() {
+        25.0
+    } else {
+        current.di_minus
+    };
+    let bb_pct = if current.bb_pct.is_nan() {
+        0.5
+    } else {
+        current.bb_pct
+    };
+    let ema_distance = if current.ema_distance.is_nan() {
+        0.0
+    } else {
+        current.ema_distance
+    };
+
+    // MACD crossover detection
+    let macd_crossed_up = !previous.macd.is_nan()
+        && !previous.macd_signal.is_nan()
+        && !macd.is_nan()
+        && !macd_signal_val.is_nan()
+        && previous.macd < previous.macd_signal
+        && macd > macd_signal_val;
+
+    let macd_crossed_down = !previous.macd.is_nan()
+        && !previous.macd_signal.is_nan()
+        && !macd.is_nan()
+        && !macd_signal_val.is_nan()
+        && previous.macd > previous.macd_signal
+        && macd < macd_signal_val;
+
+    // EMA trend
+    let ema_bullish = !ema_short.is_nan() && !ema_long.is_nan() && ema_short > ema_long;
+
+    // ADX trend strength
+    let is_trending = adx > ADX_THRESHOLD;
+    let strong_trend = adx > ADX_STRONG;
+    let trend_up = di_plus > di_minus;
+
+    // Calculate scores
+    let mut buy_score: f64 = 0.0;
+    let mut sell_score: f64 = 0.0;
+
+    // TREND STRENGTH FILTER
+    if is_trending {
+        if trend_up && trend_bullish {
+            buy_score += 3.0;
+        } else if !trend_up && !trend_bullish {
+            sell_score += 3.0;
+        }
+    } else {
+        // Ranging market - use mean reversion
+        if bb_pct < 0.1 {
+            buy_score += 2.0;
+        } else if bb_pct > 0.9 {
+            sell_score += 2.0;
+        }
+    }
+
+    // PULLBACK ENTRY
+    if trend_bullish && ema_bullish {
+        if !rsi.is_nan() && rsi > RSI_PULLBACK_LOW && rsi < RSI_PULLBACK_HIGH {
+            buy_score += 3.0;
+        }
+        if ema_distance > 0.0 && ema_distance < 0.03 {
+            buy_score += 1.5;
+        }
+        if bb_pct < 0.3 {
+            buy_score += 2.0;
+        }
+    }
+
+    // OVERSOLD/OVERBOUGHT
+    if !rsi.is_nan() {
+        if rsi < RSI_OVERSOLD {
+            if trend_bullish {
+                buy_score += 4.0;
+            } else {
+                buy_score += 2.0;
+            }
+        } else if rsi > RSI_OVERBOUGHT {
+            sell_score += 3.0;
+        }
+    }
+
+    // MACD MOMENTUM
+    if macd_crossed_up {
+        buy_score += 2.5;
+        if strong_trend && trend_up {
+            buy_score += 1.0;
+        }
+    } else if macd_crossed_down {
+        sell_score += 2.5;
+    } else if !macd_hist.is_nan() {
+        if macd_hist > 0.0 {
+            buy_score += 0.5;
+        } else if macd_hist < 0.0 {
+            sell_score += 0.5;
+        }
+    }
+
+    // MOMENTUM
+    if !momentum.is_nan() {
+        if momentum > 5.0 {
+            buy_score += 2.0;
+        } else if momentum > 2.0 {
+            buy_score += 1.0;
+        } else if momentum < -5.0 {
+            sell_score += 2.0;
+        } else if momentum < -2.0 {
+            sell_score += 1.0;
+        }
+    }
+
+    // EMA CROSSOVER
+    let prev_ema_bullish = !previous.ema_short.is_nan()
+        && !previous.ema_long.is_nan()
+        && previous.ema_short > previous.ema_long;
+
+    if ema_bullish && !prev_ema_bullish {
+        buy_score += 2.0;
+    } else if !ema_bullish && prev_ema_bullish {
+        sell_score += 2.0;
+    } else if ema_bullish {
+        buy_score += 0.5;
+    } else {
+        sell_score += 0.5;
+    }
+
+    // VOLUME CONFIRMATION
+    let has_volume = volume_ratio >= VOLUME_THRESHOLD;
+    if has_volume && volume_ratio > 1.5 {
+        if buy_score > sell_score {
+            buy_score += 1.0;
+        } else if sell_score > buy_score {
+            sell_score += 1.0;
+        }
+    }
+
+    // DETERMINE SIGNAL
+    let total_score = buy_score - sell_score;
+
+    let signal = if total_score >= 6.0 {
+        Signal::StrongBuy
+    } else if total_score >= 3.5 {
+        Signal::Buy
+    } else if total_score <= -6.0 {
+        Signal::StrongSell
+    } else if total_score <= -3.5 {
+        Signal::Sell
+    } else {
+        Signal::Hold
+    };
+
+    let confidence = (total_score.abs() / 10.0).min(1.0);
+
+    TradeSignal {
+        symbol: symbol.to_string(),
+        signal,
+        rsi: if rsi.is_nan() { 0.0 } else { rsi },
+        macd: if macd.is_nan() { 0.0 } else { macd },
+        macd_signal: if macd_signal_val.is_nan() {
+            0.0
+        } else {
+            macd_signal_val
+        },
+        macd_histogram: if macd_hist.is_nan() { 0.0 } else { macd_hist },
+        momentum: if momentum.is_nan() { 0.0 } else { momentum },
+        ema_short: if ema_short.is_nan() { 0.0 } else { ema_short },
+        ema_long: if ema_long.is_nan() { 0.0 } else { ema_long },
+        current_price,
+        confidence,
+    }
+}

src/main.rs

@@ -0,0 +1,207 @@
+//! Tech Giants Trading Bot - Algorithmic trading system using Alpaca API.
+//!
+//! A momentum + mean-reversion hybrid strategy for 50 stocks across multiple sectors.
+//! Uses RSI, MACD, EMA, ADX, Bollinger Bands, and momentum indicators for trade signals.
+//!
+//! # Usage
+//!
+//! ```bash
+//! # Live paper trading
+//! invest-bot
+//!
+//! # Backtest with historical data
+//! invest-bot --backtest --years 3
+//! invest-bot --backtest --years 5 --capital 50000
+//! ```
+
+mod alpaca;
+mod backtester;
+mod bot;
+mod config;
+mod dashboard;
+mod indicators;
+mod paths;
+mod types;
+
+use anyhow::{Context, Result};
+use clap::Parser;
+use std::env;
+use tracing_subscriber::{fmt, layer::SubscriberExt, util::SubscriberInitExt, EnvFilter};
+
+use crate::alpaca::AlpacaClient;
+use crate::backtester::{save_backtest_results, Backtester};
+use crate::bot::TradingBot;
+use crate::config::{Timeframe, DEFAULT_INITIAL_CAPITAL};
+
+/// Vibe Invest - Trade with Alpaca
+#[derive(Parser, Debug)]
+#[command(name = "vibe-invest")]
+#[command(author = "Vibe Invest Team")]
+#[command(version = "0.1.0")]
+#[command(about = "Tech Giants Trading Bot - Algorithmic trading system using Alpaca API")]
+#[command(
+    long_about = "A momentum + mean-reversion hybrid strategy for 50 stocks across multiple sectors.\n\
+                  Uses RSI, MACD, EMA, ADX, Bollinger Bands, and momentum indicators for trade signals.\n\n\
+                  Examples:\n  \
+                  Live trading:        invest-bot\n  \
+                  Live daily bars:     invest-bot --timeframe daily\n  \
+                  Backtest 3 years:    invest-bot --backtest --years 3\n  \
+                  Backtest 6 months:   invest-bot --backtest --months 6\n  \
+                  Backtest 1y 6m:      invest-bot --backtest --years 1 --months 6\n  \
+                  Custom capital:      invest-bot --backtest --years 5 --capital 50000\n  \
+                  Hourly backtest:     invest-bot --backtest --years 1 --timeframe hourly"
+)]
+struct Args {
+    /// Run in backtest mode instead of live trading
+    #[arg(short, long)]
+    backtest: bool,
+
+    /// Number of years to backtest (default: 1 if --months not specified)
+    #[arg(short, long, default_value_t = 0.0)]
+    years: f64,
+
+    /// Number of months to backtest (can combine with --years)
+    #[arg(short, long, default_value_t = 0.0)]
+    months: f64,
+
+    /// Initial capital for backtesting
+    #[arg(short, long, default_value_t = DEFAULT_INITIAL_CAPITAL)]
+    capital: f64,
+
+    /// Timeframe for bars
+    #[arg(short, long, value_enum, default_value_t = Timeframe::Daily)]
+    timeframe: Timeframe,
+}
+
+fn setup_logging(backtest_mode: bool) {
+    let filter = EnvFilter::try_from_default_env()
+        .unwrap_or_else(|_| EnvFilter::new("info"));
+
+    if backtest_mode {
+        // Console only for backtest
+        tracing_subscriber::registry()
+            .with(filter)
+            .with(fmt::layer())
+            .init();
+    } else {
+        // Console + file for live trading
+        let log_path = &paths::LOG_FILE;
+        let log_dir = log_path.parent().unwrap();
+        let log_file_name = log_path.file_name().unwrap();
+
+        let file_appender = tracing_appender::rolling::never(log_dir, log_file_name);
+        let (non_blocking, _guard) = tracing_appender::non_blocking(file_appender);
+
+        tracing_subscriber::registry()
+            .with(filter)
+            .with(fmt::layer())
+            .with(fmt::layer().with_writer(non_blocking).with_ansi(false))
+            .init();
+    }
+}
+
+fn print_banner(backtest: bool) {
+    if backtest {
+        println!(
+            r#"
+    +---------------------------------------------------------+
+    |         TECH GIANTS TRADING BOT - BACKTEST MODE         |
+    +---------------------------------------------------------+
+    |  Symbols: AAPL, MSFT, GOOGL, AMZN, META, NVDA, TSLA    |
+    |  Strategy: Momentum + RSI Mean Reversion + MACD        |
+    +---------------------------------------------------------+
+        "#
+        );
+    } else {
+        let dashboard_port = env::var("DASHBOARD_PORT").unwrap_or_else(|_| "5000".to_string());
+        println!(
+            r#"
+    +---------------------------------------------------------+
+    |         TECH GIANTS TRADING BOT - PAPER TRADING         |
+    +---------------------------------------------------------+
+    |  Symbols: AAPL, MSFT, GOOGL, AMZN, META, NVDA, TSLA    |
+    |  Strategy: Momentum + RSI Mean Reversion + MACD        |
+    |  Mode: Alpaca Paper Trading                             |
+    |  Dashboard: http://localhost:{:<29}|
+    +---------------------------------------------------------+
+        "#,
+            dashboard_port
+        );
+    }
+}
+
+fn get_credentials() -> Result<(String, String)> {
+    let api_key = env::var("ALPACA_API_KEY").context(
+        "Missing ALPACA_API_KEY. Please set it in your .env file or environment.",
+    )?;
+    let api_secret = env::var("ALPACA_SECRET_KEY").context(
+        "Missing ALPACA_SECRET_KEY. Please set it in your .env file or environment.",
+    )?;
+    Ok((api_key, api_secret))
+}
+
+#[tokio::main]
+async fn main() -> Result<()> {
+    // Load .env file if present
+    dotenvy::dotenv().ok();
+
+    let args = Args::parse();
+
+    setup_logging(args.backtest);
+    print_banner(args.backtest);
+
+    let (api_key, api_secret) = match get_credentials() {
+        Ok(creds) => creds,
+        Err(e) => {
+            eprintln!("\nConfiguration Error: {}", e);
+            eprintln!("\nPlease create a .env file with your Alpaca credentials:");
+            eprintln!("ALPACA_API_KEY=your_api_key");
+            eprintln!("ALPACA_SECRET_KEY=your_secret_key");
+            eprintln!("\nGet your free paper trading API keys at: https://alpaca.markets/");
+            std::process::exit(1);
+        }
+    };
+
+    if args.backtest {
+        run_backtest(api_key, api_secret, args).await
+    } else {
+        run_live_trading(api_key, api_secret, args).await
+    }
+}
+
+async fn run_backtest(api_key: String, api_secret: String, args: Args) -> Result<()> {
+    // Combine years and months (default to 1 year if neither specified)
+    let total_years = args.years + (args.months / 12.0);
+    let total_years = if total_years <= 0.0 { 1.0 } else { total_years };
+
+    let client = AlpacaClient::new(api_key, api_secret)?;
+    let mut backtester = Backtester::new(args.capital, args.timeframe);
+
+    let result = backtester.run(&client, total_years).await?;
+
+    // Save results to CSV
+    save_backtest_results(&result)?;
+
+    Ok(())
+}
+
+async fn run_live_trading(api_key: String, api_secret: String, args: Args) -> Result<()> {
+    let dashboard_port: u16 = env::var("DASHBOARD_PORT")
+        .unwrap_or_else(|_| "5000".to_string())
+        .parse()
+        .unwrap_or(5000);
+
+    // Create a separate client for the dashboard
+    let dashboard_client = AlpacaClient::new(api_key.clone(), api_secret.clone())?;
+
+    // Spawn dashboard in background
+    tokio::spawn(async move {
+        if let Err(e) = dashboard::start_dashboard(dashboard_client, dashboard_port).await {
+            tracing::error!("Dashboard error: {}", e);
+        }
+    });
+
+    // Run the trading bot
+    let mut bot = TradingBot::new(api_key, api_secret, args.timeframe).await?;
+    bot.run().await
+}

src/paths.rs

@@ -0,0 +1,35 @@
+//! App paths and file locations.
+
+use lazy_static::lazy_static;
+use std::path::PathBuf;
+
+lazy_static! {
+    /// Base data directory for the application, using XDG standards.
+    pub static ref DATA_DIR: PathBuf = {
+        let mut path = dirs::data_dir().unwrap_or_else(|| PathBuf::from("."));
+        path.push("invest-bot");
+        std::fs::create_dir_all(&path).expect("Failed to create data directory");
+        path
+    };
+
+    /// Path to the live positions JSON file.
+    pub static ref LIVE_POSITIONS_FILE: PathBuf = {
+        let mut path = DATA_DIR.clone();
+        path.push("live_positions.json");
+        path
+    };
+
+    /// Path to the live equity history JSON file.
+    pub static ref LIVE_EQUITY_FILE: PathBuf = {
+        let mut path = DATA_DIR.clone();
+        path.push("live_equity.json");
+        path
+    };
+
+    /// Path to the trading log file.
+    pub static ref LOG_FILE: PathBuf = {
+        let mut path = DATA_DIR.clone();
+        path.push("trading_bot.log");
+        path
+    };
+}

src/types.rs

@@ -0,0 +1,227 @@
+//! Data types and structures for the trading bot.
+
+use chrono::{DateTime, Utc};
+use serde::{Deserialize, Serialize};
+
+/// Trading signal types.
+#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
+#[serde(rename_all = "snake_case")]
+pub enum Signal {
+    StrongBuy,
+    Buy,
+    Hold,
+    Sell,
+    StrongSell,
+}
+
+impl Signal {
+    pub fn as_str(&self) -> &'static str {
+        match self {
+            Signal::StrongBuy => "strong_buy",
+            Signal::Buy => "buy",
+            Signal::Hold => "hold",
+            Signal::Sell => "sell",
+            Signal::StrongSell => "strong_sell",
+        }
+    }
+
+    pub fn is_buy(&self) -> bool {
+        matches!(self, Signal::Buy | Signal::StrongBuy)
+    }
+
+    pub fn is_sell(&self) -> bool {
+        matches!(self, Signal::Sell | Signal::StrongSell)
+    }
+}
+
+/// Represents a trading signal with all relevant data.
+#[derive(Debug, Clone)]
+pub struct TradeSignal {
+    pub symbol: String,
+    pub signal: Signal,
+    pub rsi: f64,
+    pub macd: f64,
+    pub macd_signal: f64,
+    pub macd_histogram: f64,
+    pub momentum: f64,
+    pub ema_short: f64,
+    pub ema_long: f64,
+    pub current_price: f64,
+    pub confidence: f64,
+}
+
+/// Represents a completed trade for tracking.
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct Trade {
+    pub symbol: String,
+    pub side: String,
+    pub shares: f64,
+    pub price: f64,
+    pub timestamp: DateTime<Utc>,
+    #[serde(default)]
+    pub pnl: f64,
+    #[serde(default)]
+    pub pnl_pct: f64,
+}
+
+/// Tracks a position during backtesting.
+#[derive(Debug, Clone)]
+pub struct BacktestPosition {
+    pub symbol: String,
+    pub shares: f64,
+    pub entry_price: f64,
+    pub entry_time: DateTime<Utc>,
+}
+
+/// Results from a backtest run.
+#[derive(Debug, Clone)]
+pub struct BacktestResult {
+    pub initial_capital: f64,
+    pub final_value: f64,
+    pub total_return: f64,
+    pub total_return_pct: f64,
+    pub cagr: f64,
+    pub sharpe_ratio: f64,
+    pub sortino_ratio: f64,
+    pub max_drawdown: f64,
+    pub max_drawdown_pct: f64,
+    pub total_trades: usize,
+    pub winning_trades: usize,
+    pub losing_trades: usize,
+    pub win_rate: f64,
+    pub avg_win: f64,
+    pub avg_loss: f64,
+    pub profit_factor: f64,
+    pub trades: Vec<Trade>,
+    pub equity_curve: Vec<EquityPoint>,
+}
+
+/// A point on the equity curve.
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct EquityPoint {
+    pub date: DateTime<Utc>,
+    pub portfolio_value: f64,
+    pub cash: f64,
+    pub positions_count: usize,
+}
+
+/// OHLCV bar data.
+#[derive(Debug, Clone)]
+pub struct Bar {
+    pub timestamp: DateTime<Utc>,
+    pub open: f64,
+    pub high: f64,
+    pub low: f64,
+    pub close: f64,
+    pub volume: f64,
+    pub vwap: Option<f64>,
+}
+
+/// A row of data with all calculated indicators.
+#[derive(Debug, Clone)]
+pub struct IndicatorRow {
+    pub timestamp: DateTime<Utc>,
+    pub open: f64,
+    pub high: f64,
+    pub low: f64,
+    pub close: f64,
+    pub volume: f64,
+
+    // RSI
+    pub rsi: f64,
+
+    // MACD
+    pub macd: f64,
+    pub macd_signal: f64,
+    pub macd_histogram: f64,
+
+    // Momentum
+    pub momentum: f64,
+
+    // EMAs
+    pub ema_short: f64,
+    pub ema_long: f64,
+    pub ema_trend: f64,
+    pub ema_bullish: bool,
+    pub trend_bullish: bool,
+
+    // ATR
+    pub atr: f64,
+    pub atr_pct: f64,
+
+    // ADX
+    pub adx: f64,
+    pub di_plus: f64,
+    pub di_minus: f64,
+
+    // Bollinger Bands
+    pub bb_upper: f64,
+    pub bb_middle: f64,
+    pub bb_lower: f64,
+    pub bb_pct: f64,
+
+    // Volume
+    pub volume_ma: f64,
+    pub volume_ratio: f64,
+
+    // EMA distance
+    pub ema_distance: f64,
+}
+
+impl Default for IndicatorRow {
+    fn default() -> Self {
+        Self {
+            timestamp: Utc::now(),
+            open: 0.0,
+            high: 0.0,
+            low: 0.0,
+            close: 0.0,
+            volume: 0.0,
+            rsi: 0.0,
+            macd: 0.0,
+            macd_signal: 0.0,
+            macd_histogram: 0.0,
+            momentum: 0.0,
+            ema_short: 0.0,
+            ema_long: 0.0,
+            ema_trend: 0.0,
+            ema_bullish: false,
+            trend_bullish: false,
+            atr: 0.0,
+            atr_pct: 0.0,
+            adx: 0.0,
+            di_plus: 0.0,
+            di_minus: 0.0,
+            bb_upper: 0.0,
+            bb_middle: 0.0,
+            bb_lower: 0.0,
+            bb_pct: 0.0,
+            volume_ma: 0.0,
+            volume_ratio: 0.0,
+            ema_distance: 0.0,
+        }
+    }
+}
+
+/// Live equity snapshot for dashboard.
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct EquitySnapshot {
+    pub timestamp: String,
+    pub portfolio_value: f64,
+    pub cash: f64,
+    pub buying_power: f64,
+    pub positions_count: usize,
+    pub positions: std::collections::HashMap<String, PositionInfo>,
+}
+
+/// Position information for dashboard.
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct PositionInfo {
+    pub qty: f64,
+    pub market_value: f64,
+    pub avg_entry_price: f64,
+    pub current_price: f64,
+    pub unrealized_pnl: f64,
+    pub pnl_pct: f64,
+    pub change_today: f64,
+}