In this video, we perform a full quantitative backtest of the RSI + Bollinger Bands strategy – one of the most popular combinations in technical analysis that merges volatility and momentum trading concepts.
I’m a quant trader and software engineer, and in this research-driven breakdown, we test how this hybrid setup performs across cryptocurrency, US stocks, futures, and forex markets using Python and a fully algorithmic backtesting framework.
This system buys when RSI is oversold and the price drops below the lower Bollinger Band, then exits once the price returns to the midline as RSI recovers. The short setup follows the same logic in reverse.
We evaluate the profitability, Sharpe ratio, win rate, drawdowns, and trade distribution across multiple timeframes and assets, to see whether this well-known strategy truly holds up in different market regimes.
0: 00 Bollinger Band + RSI Strategy
1: 12 What is Historical Testing?
1: 37 Coding and Config Strategy
2: 52 Candlestick Chart Plotting
3: 32 Crypto Binance Futures
4: 50 USA Equities Market
5: 37 USA Futures CME, NYNEX, COMEX, CBOE
5: 58 Forex Market
6: 42 Hyperparameter Optimization, Tuning
7: 07 Summary Results, Total PnL, Insights
Markets & Timeframes Tested
• Crypto (Binance Futures, BTC, ETH, SOL)
• US Stocks (NASDAQ, NYSE equities)
• Futures (CME, COMEX, NYMEX indices and commodities)
• Forex (EUR/USD, GBP/USD, USD/JPY, and more)
• Timeframes: from 1-minute scalping to daily swing trading
What You’ll Learn
• How RSI and Bollinger Bands interact to define market extremes
• Complete Python backtesting workflow (data, logic, execution)
• Strategy optimization and performance metrics
• Multi-market robustness testing and risk analysis
• How volatility and momentum signals combine to time reversals
If you’re into algorithmic trading, quant research, or want to validate trading strategies with real data instead of hype, this video gives a clear, data-driven perspective on a classic setup.
Includes:
• RSI–Bollinger Bands entry/exit logic
• Risk/reward and Sharpe analysis
• Multi-market comparisons
• Real trade simulation and portfolio allocation results
⚠️ Disclaimer: This content is for educational purposes only and not financial advice.
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