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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,657 papers · 148 categories

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0111 · Mar 202319922001200920172026
1 result for “VHAR”
Forecasting Large Realized Covariance Matrices: The Benefits of Factor Models and Shrinkageq-fin.ST

Improved covariance matrix forecasting for S&P 500 using factor models and shrinkage.

problem Forecasting large covariance matrices of returns in finance.
method Decompose covariance matrix into firm-level factors and sectoral restrictions. Estimate using VHAR models with LASSO.
result Significantly improved forecasting precision compared to benchmarks.
covariance matrixfactor modelsshrinkageVHARLASSO
2023-03-22abs ↗pdf ↗