Mathematical Finance

Carry Strategies Across Asset Classes: Mathematical Foundations

Imagine borrowing money at 1% and lending it at 5%. The 4% difference seems like an obvious profit, yet financial theory suggests this opportunity shouldn’t exist. Markets should quickly eliminate such discrepancies through arbitrage. But across currencies, bonds, and stocks, these “carry” opportunities persist with remarkable consistency.

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The Minimum Correlation Algorithm: Rethinking Portfolio Diversification Through Mathematical Elegance

“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.

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How Fractional Differencing Revolutionized My Feature Engineering for Investment Strategies

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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