Explanation:
Quadratic programming explicitly accounts for variances and covariances (correlations) of asset returns, capturing more risk parameters than screening, stratification, or linear programming. However, estimating the full covariance matrix requires many inputs, which can introduce noise and estimation error. Option B is incorrect because screens can apply simple capitalization weights. Option C is incorrect because stratification controls risk by matching benchmark weights for categories, not by systematically overweighting lower risks. Option D is incorrect because linear programming characterizes stocks across multiple dimensions of risk (size, industry, etc.) and ignores explicit pair-wise correlations, unlike quadratic programming.
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A
The quadratic programming technique takes into account additional risk parameters compared to other major portfolio construction techniques but also requires more inputs, which leads to more noise.
B
The screening technique ranks stocks by risk-adjusted alpha but it does not apply any additional risk control measures such as weighting the selected stocks by their relative capitalization.
C
The stratification technique splits the list of stocks into categories and maintains risk control by overweighing the categories with lower risks and underweighting the categories with higher risks.
D
The linear programming technique focuses on the pair-wise correlations of stocks rather than characterizing each stock along multiple dimensions of risk such as size, industry, volatility, or beta.
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