Asymptotic behavior of Mean-CVaR portfolio selection model under nonparametric framework
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Portfolio selection is an important issue in finance and it involves the balance between risk and return. This paper investigates portfolio selection under Mean-CVaR model in a nonparametric framework with α-mixing data as financial data tends to be dependent. Many works have provided some insight into the performance of portfolio selection from the aspects of data and simulation while in this paper we concentrate on the asymptotic behaviors of the optimal solutions and risk estimation in theory.
Keywordsnonparametric estimation portfolio selection convex program asymptotic property
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- S X Chen. Nonparametric estimation of expected shortfall, J Financ Econ, 2008, 6: 87–107.Google Scholar
- P Jorion. Value at Risk: A new benchmark for measuring derivatives risk, Irwin Professional Pub, 1996.Google Scholar
- K Kato. Weighted Nadaraya-Watson estimation of conditional expected shortfall, J Financ Econ, 2012, 10: 265–291.Google Scholar
- A Lucas, P Klaassen. Extreme returns, downside risk, and optimal asset allocation, J Portfolio Manage, 1998, 25: 71–79.Google Scholar
- H M Markowitz. Portfolio selection, J Financ, 1952, 7(1): 77–91.Google Scholar
- H Mausser, D Rosen. Beyond VaR, from measuring risk to managing risk, ALGO Res Quart, 1999, 1: 5–20.Google Scholar
- J P Morgan, R M Reuters. Technical Document, Morgan Guaranty Trust Company of New York, 1996, 91.Google Scholar
- G Pflug. Some remarks on the value-at-risk and the conditional value-at-risk, In: Probabilistic Constrained Optimization: Methodology and Applications, Kluwer Acad Publ.Google Scholar
- C Stein. Inadmissibility of the usual estimator for the mean of a multivariate normal distribution, In: Proceedings of the Third Berkeley Symposium on Mathematical Statistics and Probability, Vol 1, 197-206, 1956.Google Scholar
- L Wassermann. All of Nonparametric Statistics, Springer, New York, 2006.Google Scholar