Politická ekonomie
Politická ekonomie
Politická ekonomie
TEORETICKÝ ČASOPIS • ISSN 0032-3233 (Print) • ISSN 2336-8225 (Online)

Politická ekonomie Vol. 66 No. 3

Asymetrie během finančních krizí: asymetrická volatilita převyšuje důležitost asymetrické korelace

DOI: https://doi.org/10.18267/j.polek.1190

[plný text (PDF)]

Lukáš Frýd

We have tested the stability of parameters loading the asymmetric behaviour of the correlation and the importance of this behavior on the portfolio selection. In this paper, we have analyzed the following time series S&P index, gold and CME 5-Year Treasury Note Futures during the most important crisis from 1992 to 2009. The methodology is based on the dynamic conditional correlation model and its asymmetric volatility and asymmetric correlation extensions. The stability of parameters was tested by t-test applied on the rol ling windows data. The information importance of asymmetric volatility and correlation was tested by global minimum variance portfolio. The results suggest that the parameters loading the asymmetric behavior of the correlation are not stable for the analyzed time series during the financial crisis. With one exception we have found out that global minimum variance portfolio based on the dynamic conditional correlation model with asymmetric volatility is significantly less volatile than the global minimum variance portfolio based on the asymmetric dynamic conditional correlation model.

JEL klasifikace: C58, G01, G11

Reference:
Baur, D., Lucey, B. (2010). Is Gold a Hedge or a Safe Haven? An Analysis of Stocks, Bonds and Gold. Financial Review, 45(2), 217229, https://doi.org/10.1111/j.1540-6288.2010.00244.x

Baur, D., McDermott, T. (2010). Is Gold a Safe Haven? International Evidence. Journal of Banking & Finance, 34(8), 18861898, https://doi.org/10.1016/j.jbankfin.2009.12.008

Billio, M., Caporin, M., Gobbo, M. (2006). Flexible Dynamic Conditional Correlation Multivariate GARCH Models for Asset Allocation. Applied Financial Economics Letters, 2(2), 123130, https://doi.org/10.1080/17446540500428843

Black, F. (1976). Studies of Stock Prices Volatility Changes. Proceeding from the American

Statistical Association. Business and Economics Statistics, 177–181.

Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal

of Econometrics, 31(3), 307–327, https://doi.org/10.1016/0304-4076(86)90063- 1

Bollerslev, T. (1990). Modelling the Coherence in Shortrun Nominal Exchange Rates:

A Multivariate Generalized Arch Model. The Review of Economics and Statistics, 72(3), 498,

https://doi.org/10.2307/2109358

Bollerslev, T., Engle, R. F., Wooldridge, J. M. (1988). A Capital Asset Pricing Model with

Timevarying Covariances. Journal of Political Economy, 96(1), 116–131, https://doi.org/10.1086/261527

Bollerslev, T., Wooldridge, J. M. (1992). Quasi-maximum Likelihood Estimation and Inference in Dynamic Models with Timevarying Covariances. Econometric Reviews, 11(2), 143–172, https://doi.org/10.1080/07474939208800229

Campbell, J. Y., Ammer, J. (1993). What Moves the Stock and Bond Markets? A Variance

Decomposition for Longterm Asset Returns’. The Journal of Finance, 48(1), 3,

https://doi.org/10.2307/2328880

Campbell, J. Y., Hentschel, L. (1992). No News is Good News. Journal of Financial Economics, 31(3), 281–318, https://doi.org/10.1016/0304-405x(92)90037-x

Cappiello, L., Engle, R. F., Sheppard, K. (2006). Asymmetric Dynamics in the Correlations

of Global Equity and Bond Returns. Journal of Financial Econometrics, 4(4), 537–572,

https://doi.org/10.1093/jjfinec/nbl005

Chiang, T. C., Li, J. (2009). The Dynamic Correlation between Stock and Bond Returns: Evidence from the U.S. Market. SSRN Electronic Journal, https://doi.org/10.2139/ssrn.1362225

Chiang, T., Jeon, B., Li, H. (2007). Dynamic Correlation Analysis of Financial Contagion: Evidence from Asian Markets. Journal of International Money and Finance, 26(7), 12061228, https://doi.org/10.1016/j.jimonfin.2007.06.005

Christie, A. (1982). The Stochastic Behavior of Common Stock Variances Value, Leverage

and Interest Rate Effects’. Journal of Financial Economics, 10(4), 407–432, https://doi.org/10.1016/0304-405x(82)90018-6

Ciner, C., Gurdgiev, C., Lucey, B. (2013). Hedges and Safe Havens: An Examination of Stocks, Bonds, Gold, Oil and Exchange Rates. International Review of Financial Analysis, 29, 202-211, https://doi.org/10.1016/j.irfa.2012.12.001

Diebold, F. X., Mariano, R. S. (1995). Comparing Predictive Accuracy. Journal of Business

& Economic Statistics, 13(3), 253, https://doi.org/10.2307/1392185

Engle, R. (2002). Dynamic Conditional Correlation. Journal of Business & Economic Statistics, 20(3), 339–350, https://doi.org/10.1198/073500102288618487

Engle, R. F., Kroner, K. F. (1995). Multivariate Simultaneous Generalized ARCH. Econometric Theory, 11(1), 122, https://doi.org/10.1017/s0266466600009063

Engle, R. F., Lilien, D. M., Robins, R. P. (1987). Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model. Econometrica, 55(2), 391407, https://doi.org/10.2307/1913242

Gjika, D., Horváth, R. (2013). Stock Market Comovements in Central Europe: Evidence from

the Asymmetric DCC Model. Economic Modelling, 33, 55–64, https://doi.org/10.1016/j.econmod.2013.03.015

Glosten, L. R., Jagannathan, R., Runkle, D. E. (1993). On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks. The Journal of Finance, 48(5), 1779, https://doi.org/10.2307/2329067

Greene, W. H. (2011). Econometric Analysis. 7th edn. Harlow: Pearson Education.

Hull, J. (2017). Options, Futures, and other Derivatives. New York, NY: Pearson. ISBN 978-0134472089.

Jones, C. P., Wilson, J. W. (2004). The Changing Nature of Stock and Bond Volatility. Financial Analysts Journal, 60(1), 100–113, https://doi.org/10.2469/faj.v60.n1.2595

Kroner, K. F., Ng, V. K. (1998). Modeling Asymmetric Comovements of Asset Returns. Review

of Financial Studies, 11(4), 817–844, https://doi.org/10.1093/rfs/11.4.817

Longin, F., Solnik, B. (1995). Is the Correlation in International Equity Returns Constant: 1960–1990? Journal of International Money and Finance, 14(1), 3–26, https://doi.

org/10.1016/0261-5606(94)00001-h

Markowitz, H. (1952). Portfolio Selection. The Journal of Finance, 7(1), 77, https://doi.org/10.2307/2975974

Newey, W. K., West, K. D. (1987). A Simple, Positive Semi-Definite, Heteroskedasticity and

Autocorrelation Consistent Covariance Matrix. Econometrica, 55(3), 703, https://doi.

org/10.2307/1913610

Patton, A. J. (2011). Volatility Forecast Comparison Using Imperfect Volatility Proxies. Journal of Econometrics, 160(1), 246–256, https://doi.org/10.1016/j.jeconom.2010.03.034

Saleem, K. (2011). Time Varying Correlations between Stock and Bond returns: Empirical

evidence from Russia. Asian Journal of Finance & Accounting, 3(1), https://doi.org/10.5296/ajfa.v3i1.989

Sharpe, W. F. (1964). Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk. The Journal of Finance, 19(3), 425, https://doi.org/10.2307/2977928

Shiller, R. J., Beltratti, A. E. (1992). Stock Prices and Bond Yields. Journal of Monetary Economics, 30(1), 25–46, https://doi.org/10.1016/0304-3932(92)90042-z

Zakoian, J. M. (1994). Threshold Heteroskedastic Models. Journal of Economic Dynamics and

Control, 18(5), 931–955, https://doi.org/10.1016/0165-1889(94)90039-6