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Stock portfolio of GLD over the past 30 years.
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Backtesting with the Dual momentum strategy.
Inspiration
We were inspired by the fact that many strategies look strong in aggregate but perform very differently depending on market regime, volatility, and macro conditions. We wanted to expose that nuance instead of hiding it behind a single backtest result.
What it does
This app runs strategy backtests and identifies the periods where a strategy performs best and worst. It then analyzes the market conditions during those periods and explains the regime behind the results in plain language.
How we built it
We built the project around historical market data, market-state indicators, and strategy backtesting. The app loads price and macro data, compares strategy performance to broader market history, and summarizes the conditions driving that performance.
Challenges we ran into
The hardest part was balancing statistical rigor with clear explanations. Backtests can be misleading without context, so we had to make the market-state summaries meaningful and understandable.
Accomplishments that we're proud of
We created a tool that moves beyond “Did this strategy work?” to “Under what market conditions does it work, and why?” That makes the project useful for learning and for practical strategy analysis.
What we learned
We learned that strategy performance depends as much on the market regime as on the signal itself. Strong signals often work only under specific macro, volatility, trend, and sector conditions.
What's next for Strategy Tester
We want to expand the app with more strategies, include even more accurate data, and more educational insight for quantitative learners. The goal is to make it a clearer, more interactive way to understand market dynamics and even serve as a potential tool for market dynamics.
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