Bruno P. C. Levy, Hedibert F. Lopes
arXiv 13 May 2021 · Finance — Statistical Finance · 1 citations (OpenAlex)
arXiv:2105.06584 · PDF · DOI · OpenAlex · Extracted main text
We propose a fast and flexible method to scale multivariate return volatility predictions up to high-dimensions using a dynamic risk factor model. Our approach increases parsimony via time-varying sparsity on factor loadings and is able to sequentially learn the use of constant or time-varying parameters and volatilities. We show in a dynamic portfolio allocation problem with 452 stocks from the S&P 500 index that our dynamic risk factor model is able to produce more stable and sparse predictions, achieving not just considerable portfolio performance improvements but also higher utility gains for the mean-variance investor compared to the traditional Wishart benchmark and the passive investment on the market index.
appendix boundary found by appendix_command · 80% of the source is main text. Read the extracted text to check this.
The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Kastner, G (2019) Sparse Bayesian time-varying covariance estimation in many dimensions | 1.000 | 5 | 3 | 100% |
| 2 | Levy, B. P. and H. F. Lopes (2021) a): Dynamic Ordering Learning in Multivariate Forecasting self | 0.965 | 10 | 4 | 90% |
| 3 | Zhao, Z. Y., M. Xie, and M. West (2016) Dynamic dependence networks: Financial time series forecasting and portfolio decisions | 0.950 | 7 | 5 | 86% |
| 4 | Koop, G. and D. Korobilis (2013) Large time-varying parameter VARs | 0.941 | 6 | 5 | 83% |
| 5 | Raftery, A. E., M. Kárnỳ, and P. Ettler (2010) Online prediction under model uncertainty via dynamic model averaging: Application to a cold rolling mill | 0.928 | 5 | 4 | 80% |
| 6 | Dangl, T. and M. Halling (2012) Predictive regressions with time-varying coefficients | 0.843 | 4 | 4 | 75% |
| 7 | De Nard, G., O. Ledoit, and M. Wolf (2020) Factor models for portfolio selection in large dimensions: The good, the better and the ugly | 0.811 | 4 | 2 | 100% |
| 8 | Gruber, L. F. and M. West (2017) Bayesian online variable selection and scalable multivariate volatility forecasting in simultaneous graphical dynamic linear mod… | 0.811 | 4 | 2 | 100% |
| 9 | Lopes, H. F., R. E. McCulloch, and R. S. Tsay (2021) Parsimony inducing priors for large scale state-space models self | 0.811 | 4 | 2 | 100% |
| 10 | McAlinn, K., K. A. Aastveit, J. Nakajima, and M. West (2020) Multivariate Bayesian predictive synthesis in macroeconomic forecasting | 0.737 | 3 | 3 | 67% |
Showing the top 10 of 58 scored citations.