Trend + Engulfing S&P 500 Backtester

This project implements a long-only systematic trading strategy that combines a daily trend filter (EMA-based) with an hourly bullish engulfing candlestick pattern, and then backtests it on individual tickers or on a universe of S&P 500 stocks.[file:7][file:3]

Strategy Overview

The strategy operates on two timeframes and is designed to enter only in the direction of the prevailing daily uptrend.[file:7][file:3]

• Daily trend filter

  • Uses two EMAs on daily closing prices: a fast EMA and a slow EMA (default 9 and 21 periods).[file:7][file:3]
  • Long entries are allowed only when the fast EMA is above the slow EMA, indicating an uptrend.[file:7][file:3]

• Hourly entry signal

  • Uses a bullish engulfing pattern on hourly candles.[file:7][file:3]
  • A valid signal requires:
    • Previous candle is bearish (close < open).
    • Current candle is bullish (close > open).
    • Current candle body fully engulfs previous candle body (current open ≤ previous close and current close ≥ previous open).[file:7][file:3]

• Risk management and exits

  • Long-only: the strategy never opens short positions.[file:7][file:3]
  • Fixed take profit at a percentage above entry (default 3%).[file:7][file:3]
  • 1% trailing stop based on price, implemented via a trailing stop order.[file:7][file:3]
  • Position sizing targets a fixed percentage of account equity at risk per trade (default 2%).[file:7][file:3]

Repository Contents

• FINAL.py
  Interactive single-ticker backtest script:

  • Prompts for a ticker symbol.
  • Downloads ~2 years of hourly data and 5 years of daily data for that ticker.
  • Runs the TrendEngulfingStrategy with analyzers (Sharpe, drawdown, trade stats).
  • Prints a performance report and plots a candlestick chart of the backtest.[file:7]

• FINAL-FOR-DATA-TESTING.PY
  Batch backtest engine:

  • Reads a list of tickers from SNP500.CSV (expects a Symbol column).
  • Normalizes tickers (e.g., BRK.B → BRK-B) for the data provider.
  • Runs the same long-only strategy for each ticker.
  • Collects metrics (final value, Sharpe ratio, drawdown, win rate, profit factor, returns, etc.).
  • Saves results to a CSV file (e.g. ema921.csv or sp500_backtest_results.csv).[file:3]

• results.py
  Helper/analysis script intended for loading and inspecting the generated result CSVs.[file:2]

• SNP500.CSV
  Universe definition:

  • Contains S&P 500 tickers in a Symbol column.
  • Used as input for batch testing.[file:3][file:6]

• ema921.csv, ema2150.csv, sp500_backtest_results.csv
  Example backtest output files:

  • Each row corresponds to one ticker.
  • Contains per-ticker performance metrics from batch runs.[file:1][file:5][file:4]

Installation

1. Clone the repository

   git clone <your-repo-url>
   cd <your-repo-folder>