investing-backtesting

name	investing-backtesting
description	Use when running historical validation for this investing workspace. Covers both short-term and long-term backtests, reads the watchlist from input_config.json, executes the correct backtest command, and summarizes return, win rate, max drawdown, Sharpe ratio, and trade history before any recommendation workflow is trusted.

Investing Backtesting

Use this skill when the task is to validate strategy performance rather than generate new trade ideas.

Working directory

Assume the skill runs from this directory:

/Users/anuragmohan/Documents/POC/investing

If the runtime starts elsewhere, change into that directory first or use absolute paths.

What this skill does

• Runs the short-term or long-term backtest workflow
• Uses the configured watchlist from input_config.json
• Writes backtest snapshots into the state/ directory
• Summarizes performance metrics and recent simulated trades
• Helps decide whether the strategy should be treated as healthy, conservative, or blocked

Commands

Run from the working directory above.

Short-term backtest:

python3 /Users/anuragmohan/Documents/POC/investing/main.py backtest --format text

Long-term backtest:

python3 /Users/anuragmohan/Documents/POC/investing/main.py longterm-backtest --format text

If JSON output is needed:

python3 /Users/anuragmohan/Documents/POC/investing/main.py backtest --format json --output /Users/anuragmohan/Documents/POC/investing/shortterm_backtest.json
python3 /Users/anuragmohan/Documents/POC/investing/main.py longterm-backtest --format json --output /Users/anuragmohan/Documents/POC/investing/longterm_backtest.json

Input files

• Watchlist, starting capital, risk preference: /Users/anuragmohan/Documents/POC/investing/input_config.json

Backtest outputs are written to:

• /Users/anuragmohan/Documents/POC/investing/state/backtest_results.json
• /Users/anuragmohan/Documents/POC/investing/state/long_term_backtest_results.json

Expected summary

For each run, report:

• workflow name
• mode
• confidence
• total return
• win rate
• max drawdown
• Sharpe ratio
• total trades

If trade details are present, include a short sample of:

• ticker
• entry date
• exit date
• pnl
• pnl percent

Guardrails

• Do not claim a meaningful result if market data failed to download
• If the backtest returns empty metrics, explain that the run was not data-valid
• Treat win rate in context with return and drawdown, especially for longer-term trend-following systems
• Use short-term backtests for swing workflow validation and long-term backtests for position-trading workflow validation

Scheduling guidance

Recommended cadence:

• short-term backtest: once daily after market close
• long-term backtest: once daily after market close

It is fine to run both in the same scheduled job if the environment has stable market data access.