Abstract
We extend the Black-Litterman (BL) approach to incorporate tail dependency in portfolio optimization and estimate the posterior joint distribution of returns using vine copulas. Our novel copula-based BL (CBL) model leads to flexibility in modeling returns symmetric and asymmetric multivariate distribution from a range of copula families. Based on a sample of the Eurostoxx 50 constituents (also for S&P 100 as robustness check), we evaluate the performance of the suggested CBL approach and portfolio optimization technique using out-of-sample back-testing. Our empirical analysis and robustness check indicate better performance for the CBL portfolios in terms of lower tail risk and higher risk-adjusted returns, compared to the benchmark strategies.
| Original language | English |
|---|---|
| Pages (from-to) | 1055-1070 |
| Number of pages | 16 |
| Journal | European Journal of Operational Research |
| Volume | 297 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 16 Mar 2022 |
| MoE publication type | A1 Journal article-refereed |
Funding
We want to thank Claudia Czado for her helpful comments. We are thankful to the developers of R packages “rmgarch” and “rvinecopulib”. In addition, we are grateful for the suggestions of seminar participants at the 13th International Conference on Computational and Financial Econometrics (CFE 2019) in London, 3rd Annual Workshop on Financial Econometrics organized by Örebro University School of Business, 2nd Annual Workshop on Emerging Topics in Financial Economics organized by Linkping University, 5th Econometric Research in Finance (ERFIN 2020) organized by SGH Warsaw School of Economics. The usual disclaimer applies.
Keywords
- Black–Litterman framework
- Conditional value-at-risk
- Finance
- Portfolio optimization
- Tail constraints
- Truncated regular vine copula