Supertrend Optimizer & Zerodha Backtester
A Streamlit app for parallel Supertrend backtesting and parameter optimization on Indian equities.
Large-scale ATR-by-multiplier grid optimization on Zerodha Kite history, with equity curves, heatmaps, and 3D surfaces.
- Parallel ATR-by-multiplier grid optimization via multiprocessing
- Zerodha Kite historical data on 5m/15m timeframes
- Trade lists, equity curves, and parameter heatmaps
- 3D surface analytics to judge robustness
A local Streamlit application for backtesting and optimizing the Supertrend indicator on Indian-market data. It pulls Zerodha Kite historical candles, then runs large-scale parallel parameter optimization across an ATR-length by multiplier grid on 5-minute and 15-minute timeframes, using multiprocessing to make the sweep tractable. Results come back as trade lists, equity curves, a parameter heatmap, and a 3D surface so you can see how robust a setting is rather than cherry-picking one lucky combination.
It is quant tooling for the practical trader: fast, visual, and honest about how sensitive a strategy is to its parameters. Seeing an entire parameter surface at once discourages the common mistake of trusting a single lucky ATR-and-multiplier combination, and the multiprocessing sweep makes exploring that surface fast enough to actually do.
Backtesting tool for research only; past performance does not guarantee future results and nothing here is financial advice.
How it works
- Pull Zerodha Kite historical candles
- Define ATR length by multiplier grid
- Multiprocessing sweeps all combinations
- Results shown as trade lists and equity curves
- Heatmap and 3D surface show robustness
Software and automation are infrastructure, not financial advice. No performance guarantees. Every live system needs staged testing, risk limits, and owner approval.