TY - JOUR
T1 - Copula-based Black–Litterman portfolio optimization
AU - Sahamkhadam, Maziar
AU - Stephan, Andreas
AU - Östermark, Ralf
N1 - Funding Information:
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.
Publisher Copyright:
© 2021 The Authors
PY - 2022/3/16
Y1 - 2022/3/16
N2 - 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.
AB - 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.
KW - Black–Litterman framework
KW - Conditional value-at-risk
KW - Finance
KW - Portfolio optimization
KW - Tail constraints
KW - Truncated regular vine copula
UR - http://www.scopus.com/inward/record.url?scp=85119565907&partnerID=8YFLogxK
U2 - 10.1016/j.ejor.2021.06.015
DO - 10.1016/j.ejor.2021.06.015
M3 - Article
AN - SCOPUS:85119565907
SN - 0377-2217
VL - 297
SP - 1055
EP - 1070
JO - European Journal of Operational Research
JF - European Journal of Operational Research
IS - 3
ER -