Analysis on Asymmetric Tail Dependence of Portfolio Returns
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We use the generalized Pareto distribution and the copula to analyze the impact of asymmetric tail dependence on the risk measures. Simulation results show that the risk measures with symmetric tail dependence underestimate those with asymmetric tail dependence. We also quantify the superiority in the portfolio returns from characterizing the asymmetric tail dependence. The returns of the optimal portfolios from the asymmetric marginals are higher than the returns of the optimal portfolios from the symmetric marginals in the majority of the cases. A caution needs to be exercised in concluding that characterizing the asymmetric dependence in the process of modeling the marginal distributions seems to have an impact on the performance of the optimal portfolio due to the statistical significance of the rate differentials.
Abstract
We use the generalized Pareto distribution and the copula to analyze the impact of asymmetric tail dependence on the risk measures. Simulation results show that the risk measures with symmetric tail dependence underestimate those with asymmetric tail dependence. We also quantify the superiority in the portfolio returns from characterizing the asymmetric tail dependence. The returns of the optimal portfolios from the asymmetric marginals are higher than the returns of the optimal portfolios from the symmetric marginals in the majority of the cases. A caution needs to be exercised in concluding that characterizing the asymmetric dependence in the process of modeling the marginal distributions seems to have an impact on the performance of the optimal portfolio due to the statistical significance of the rate differentials.
참고문헌 (16)
- Amaya, D., "Does Realized Skewness Predict the Cross‐Section of Equity Returns?", Journal of Financial Economics, 118(1), pp.135~167 (2015)
- Beyond the Sample: Extreme Quantile and Probability Estimation with Applications to Financial Data, "Danielsson, J.", Tinbergen Institute, ~, pp.Discussion paper, TI98-016 (1998), 2
- Danielsson, J., "Using a Bootstrap Method to Choose the Sample Fraction in Tail Index Estimation", Journal of Multivariate Analysis, 76, pp.226~248 (2001)
- de Roon, F., "A Simple Skewed Distribution with Asset Pricing Applications", Review of Finance, 21(6), pp.2169~2197 (2017)
- Embrechts, P., "Modelling Extreme Events" (1997), Springer-Verlag
- Goldie, C., "Slow Variation with Reminder: Theory and Applications", Quarterly Journal of Mathematics, Oxford 2nd Series, 38, pp.45~71 (1987)
- Hall, P., "Using the Bootstrap to Estimate Mean Square Error and Select Smoothing Parameter in Nonparametric Problem", Journal of Multivariate Analysis, 32, pp.177~203 (1990)
- Hansen, B., "Autoregressive Conditional Density Estimation", International Economic Review, 35, pp.705~730 (1994)
- Harvey, C., "Autoregressive Conditional Skewness", Journal of Financial and Quantitative Analysis, 34, pp.465~487 (1999)
- Harvey, C., "Conditional Skewness in Asset Pricing Tests", Journal of Finance, 55(3), pp.1263~1295 (2000)
- McNeil, A., "Estimation of Tail-Related Risk Measures for Heteroskedastic Financial Time Series: An Extreme Value Approach", Journal of Empirical Finance, 7, pp.271~300 (2000)
- McNeil A., "The Peaks over Thresholds Method for Estimating High Quantiles of Loss Distributions" (1997), Department of Mathematics, ETH Zentrum
- Patton, A., "On the Out‐Of‐Sample Importance of Skewness and Asymmetric Dependence for Asset Allocation", Journal of Financial Econometrics, 2(1), pp.130~168 (2004)
- Thiele, S., "Modeling the Conditional Distribution of Financial Returns with Asymmetric Tails", Journal of Applied Econometrics, 35(1), pp.46~60 (2020)
- Zhu, D., "A Generalized Asymmetric Student‐t Distribution with Application to Financial Econometrics", Journal of Econometrics, 157, pp.297~305 (2010)
- Zivot, E., "Modeling financial time series with S-PLUS" (2006), Springer