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Difficulty: Hard
Category: portfolio_optimization
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Topics: covariance-estimation, shrinkage, numpy, portfolio-optimization, ledoit-wolf
Sample covariance matrices are often noisy and ill-conditioned, leading to unstable portfolio optimizations. Ledoit-Wolf shrinkage addresses this by combining the sample covariance with a structured, well-behaved target matrix, like the constant-correlation matrix. This technique is a standard tool in quantitative finance for risk management and portfolio construction. Task Implement the function solution(returns: list) -> list that applies Ledoit-Wolf constant-correlation shrinkage to a T x N
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