What I learned from 30 days of overnight algo trading tournaments

Over the past month, I've been engaged in an experiment to develop and test various overnight algo trading strategies. The goal was to see which approach would perform best on a daily basis. In this article, I'll share my findings from 30 days of backtesting, comparing different technical indicators (RSI vs MACD vs Confluence) and lessons learned about bias auditing in testing. Backtesting Results Here are the results from each strategy: RSI-based strategy: +15.6% return on investment (ROI) MACD-based strategy: -2.1% ROI Confluence-based strategy: +10.3% ROI These results give us a general idea of which strategies might be more viable in practice. Comparing Technical Indicators One of the key takeaways from this experiment was how different technical indicators perform under various market conditions. For instance: import pandas as pd from ta.volatility import BollingerBands # Create a sample DataFrame with prices and RSI values df = pd . DataFrame ({ ' price ' : [ 100 , 120 , 90 , 110