Algorithmic Trading
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The Strategy That Lost Money for 2 Years (Then Made 19% Annually)
- Fabio Capela
- Systematic trading , Trading psychology , Portfolio management , Risk management , Personal journey , Algorithmic trading , Market regimes , Strategy development
Most trading success stories skip the embarrassing part. Here’s what actually happened.
Read MoreThe 7 Backtesting Sins That Kill Trading Strategies Before They Start
- Fabio Capela
- Algorithmic trading , Quantitative finance , Risk management , Systematic trading , Portfolio management , Backtesting , Trading systems , Investment strategy
Bottom Line Up Front: Even the most sophisticated trading algorithms fail in production because of fundamental backtesting errors. After analyzing thousands of strategy failures, we’ve identified seven critical mistakes that account for over 90% of the gap between backtest and live performance. Master these, and you’ll avoid the graveyard of “perfect” strategies that blew up on day one.
Read MoreThe Minimum Correlation Algorithm: Rethinking Portfolio Diversification Through Mathematical Elegance
- Fabio Capela
- Portfolio optimization , Quantitative finance , Diversification strategies , Risk management , Algorithmic trading , Modern portfolio theory , Asset allocation , Investment mathematics
“Don’t put all your eggs in one basket” – this timeless wisdom has evolved into one of finance’s most fundamental principles. Yet despite diversification’s universal acceptance, its mathematical underpinnings remain poorly understood by most practitioners. The conventional approach treats diversification as simply holding many assets, but this perspective misses the profound mathematical reality that drives risk reduction in portfolios.
Read MoreHow Fractional Differencing Revolutionized My Feature Engineering for Investment Strategies
- Fabio Capela
- Quantitative finance , Feature engineering , Machine learning , Systematic investing , Financial mathematics , Time series analysis , Advanced analytics , Algorithmic trading
As a theoretical physicist turned systematic investor, I’ve always been fascinated by the mathematical structures underlying financial markets. While most investors focus on price movements and traditional technical indicators, I discovered that the real edge comes from understanding the deeper statistical properties of market data—particularly how to extract meaningful features that preserve both trend information and stationarity.
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