79816b9e2e
- Added HOURLY_ATR_STOP_MULTIPLIER (1.8x) vs daily (3.5x) - Added hourly-specific trail multipliers - Strategy now uses timeframe field to select appropriate stops - Tested multiple configurations on hourly: * 3.5x stops: -0.5% return, 45% max DD * 1.8x stops: -45% return, 53% max DD (worse) * Conservative regime (0.25x): -65% return, 67% max DD (terrible) - Conclusion: Hourly doesn't work with this strategy - Daily with relaxed regime remains best: +17.4% over 5yr, 24% max DD Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
67 lines
3.0 KiB
Markdown
67 lines
3.0 KiB
Markdown
# CLAUDE.md
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This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
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## Project Overview
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Vibe Invest is a Rust algorithmic trading bot using the Alpaca paper trading API. It executes a hybrid momentum + mean-reversion strategy across 50 tech/financial stocks. It has two execution modes: live paper trading and historical backtesting, plus a web dashboard.
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## Build & Run Commands
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```bash
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# Build
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cargo build --release
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# Run live paper trading (requires .env with ALPACA_API_KEY and ALPACA_SECRET_KEY)
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cargo run --release
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cargo run --release -- --timeframe hourly
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# Run backtesting
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cargo run --release -- --backtest --years 3
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cargo run --release -- --backtest --years 5 --capital 50000
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cargo run --release -- --backtest --years 1 --months 6 --timeframe hourly
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# Run backtesting with custom date range
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cargo run --release -- --backtest --start-date 2007-01-01 --end-date 2008-12-31
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cargo run --release -- --backtest --start-date 2020-03-01 --end-date 2020-12-31 --timeframe hourly
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# Lint and format (available via nix flake)
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cargo clippy
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cargo fmt
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```
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There are no tests currently in the project.
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## Architecture
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```
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main.rs CLI parsing (clap), logging setup, mode routing
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├── bot.rs Live trading loop: market hours detection, per-symbol analysis,
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│ order execution, position tracking (JSON persistence)
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├── backtester.rs Historical simulation: processes bars sequentially, tracks
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│ positions, calculates metrics (CAGR, Sharpe, Sortino, drawdown)
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├── alpaca.rs Alpaca REST API client with rate limiting (200 req/min via governor)
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├── indicators.rs Technical indicators: EMA, SMA, RSI, MACD, ADX, ATR,
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│ Bollinger Bands, ROC. Signal scoring algorithm in generate_signal()
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├── dashboard.rs Axum web server (default port 5000) with Chart.js frontend
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├── config.rs Strategy parameters, stock universe (50 symbols), risk limits
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├── types.rs Domain types: Signal, TradeSignal, Trade, BacktestResult, Bar, etc.
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└── paths.rs XDG-compliant file paths (~/.local/share/invest-bot/)
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```
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**Key data flow:** Both bot.rs and backtester.rs call `indicators::generate_signal()` which scores multiple indicators into a composite buy/sell signal. The bot executes via alpaca.rs; the backtester simulates internally.
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## Strategy Parameters (config.rs)
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- Hourly mode scales all indicator periods by 7x
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- Risk: max 22% position size, 2.5% stop-loss, 40% take-profit, trailing stop at 7% after 12% gain
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- Signal thresholds: StrongBuy ≥ 6.0, Buy ≥ 3.5, Sell ≤ -3.5, StrongSell ≤ -6.0
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- Backtester restricts to top 4 momentum stocks; live mode does not
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## Environment
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- Nix flake provides dev tools: rustc, cargo, clippy, rustfmt, rust-analyzer, cargo-watch
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- `.env` file required: `ALPACA_API_KEY`, `ALPACA_SECRET_KEY`, optional `DASHBOARD_PORT`
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- Persistent state stored in `~/.local/share/invest-bot/` (positions, equity history, logs)
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- Backtest outputs: `backtest_equity_curve.csv`, `backtest_trades.csv` in working directory
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