JMF  Vol.1 No.2 , August 2011
A Comparison of Minimum Risk Portfolios under the Credit Crunch Crisis
ABSTRACT
In this paper the behaviour of various popular risk portfolios measures used for portfolio construction are compared using data from the recent financial crisis. Results are revealing the way optimal portfolios should be constructed. Despite the conventional wisdom, short selling gives only a marginal improvement to portfolio performance during the crisis period. Optimal semivariance portfolio produces better results than the portfolio constructed with the more advanced expected short fall method. Additional historical information has added to performance up to a point and long dated history seems not to be commensurate with additional benefits. Rebalancing frequency seems to have an optimal point that favours neither overtrading nor the conventional buy and hold strategy.

Cite this paper
nullT. Mavralexakis, K. Kiriakopoulos, G. Kaimakamis and A. Koulis, "A Comparison of Minimum Risk Portfolios under the Credit Crunch Crisis," Journal of Mathematical Finance, Vol. 1 No. 2, 2011, pp. 34-39. doi: 10.4236/jmf.2011.12005.
References
[1]   R. M. Stulz, “Risk Management and Derivatives,” 1st Edition, Thomson South Western, Florence, 2006.

[2]   H. M. Marko-witz, “Portfolio Selection,” Journal of Finance, Vol. 14, No. 1, 1952, pp. 77-91. doi:10.2307/2975974

[3]   A. A. Gaivoronski and G. Pflung, “Finding Optimal Portfolios with Constraints on Value at Risk,” Proceedings of the 3rd Stockholm Seminar in Risk Behaviour and Risk Management, Stockholm, 14-16 June 1999.

[4]   R. Gandy, “Portfolio Optimization with Risk Constraints,” PhD Thesis, Universitat Ulm, Ulm, 2005.

[5]   R. T. Rockafellar and S. Uryasev, “Optimization of Conditional Value at-Risk,” The Journal of Risk, Vol. 2, No. 3, 2000, pp. 21-41.

[6]   R. T. Rockafellar and S. Uryasev, “Conditional Value-at- Risk for General Loss Distributions,” Journal of Banking and Finance, Vol. 26, No. 7, 2002, pp. 1443-1471. doi:10.1016/S0378-4266(02)00271-6

[7]   P. Krokhmal, J. Palmquist and S. Uryasev, “Portfolio Optimization with Conditional Value-at-Risk Objective and Constraints,” Journal of Risk, Vol. 4, No. 2, 2002, pp. 43-68.

[8]   D. Huang, S. Zhu and F. Fabozzi, “Portfolio Selection with Uncertain Exit Times: A Robust CVAR Approach,” Journal of Economics Dynamics and Control, Vol. 32, No. 2, 2008, pp. 594-623. doi:10.1016/j.jedc.2007.03.003

[9]   P. Artzner, F. Delbaen, J.-M. Eber and D. Heath, “Coherent Measures of Risk,” Mathematical Finance, Vol. 9, No. 3, 1999, pp. 203-228. doi:10.1111/1467-9965.00068

[10]   S. Cheng, Y. Liu and S. Wang, “Progress in Risk Measurement,” Advanced Modelling and Optimization, Vol. 6, No. 1, 2004, pp. 1-20.

[11]   H. Follmer and A. Schied, “Convex and Coherent Risk Measures,” In: R. Cont, Ed., Encyclopedia of Quantitative Finance, John Wiley & Sons, Hoboken, 2010, pp. 355-363.

[12]   S. Alexander, T. F. Coleman and Y. Li, “Derivatives Portfolio Hedging Based on CVAR,” In: D. Szeg?, Ed., Risk Measures for the 21 Century, Wiley, Hoboken, 2003, pp. 339-363.

[13]   S. Alexander, T. F. Coleman and Y. Li, “Minimizing CVAR and VAR for a Portfolio of Derivatives,” Journal of Banking and Finance, Vol. 30, No. 2, 2006, pp. 583-605. doi:10.1016/j.jbankfin.2005.04.012

[14]   M. Gilli and E. Schumann, “An Empirical Analysis of Alternative Portfolio Selection Criteria,” Swiss Finance Institute Research Paper No. 09-06, March 2009.

[15]   V. DeMiguel, L. Garlappi and R. Uppal, “Optimal versus Naive Diversification: How Inefficient Is the 1/N Portfolio Strategy,” Review of Financial Studies, Vol. 22, No. 5, 2007, pp. 1915-1953.

[16]   C. Mamoghli and S. Daboussi, “Optimisation de Portefeuille Dans le Cadre du Downside Risk,” Portfolio Optimization in a Downside Risk Framework, Working Paper, 19 August 2008.

[17]   S. R. Pliska and K. Suzuk, “Optimal Tracking for Asset Allocation with Fixed and Proportional Transaction Costs,” Journal of Quantitative Finance, Vol. 4, No. 2, 2004, pp. 233-243. doi:10.1080/14697680400000027

 
 
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