2021/05/13 by Bruno P. C. Levy, Levy, Bruno P. C., Hedibert F. Lopes +1 · 1 citation
Decision Sciences · Economics, Econometrics and Finance · Engineering · #Econometrics (econ.EM) #FOS: Economics and business #Financial Markets and Investment Strategies #Financial Risk and Volatility Modeling #Reservoir Engineering and Simulation Methods #Statistical Finance (q-fin.ST) #Stock Market Forecasting Methods
paper · pdf · doi:10.48550/arxiv.2105.06584
openalex publication_date 2021/05/13 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
We propose a fast and flexible method to scale multivariate return volatility\npredictions up to high-dimensions using a dynamic risk factor model. Our\napproach increases parsimony via time-varying sparsity on factor loadings and\nis able to sequentially learn the use of constant or time-varying parameters\nand volatilities. We show in a dynamic portfolio allocation problem with 452\nstocks from the S&P 500 index that our dynamic risk factor model is able to\nproduce more stable and sparse predictions, achieving not just considerable\nportfolio performance improvements but also higher utility gains for the\nmean-variance investor compared to the traditional Wishart benchmark and the\npassive investment on the market index.\n