Fads Models with Markov Switching Hetroskedasticity: decomposing Tehran Stock Exchange return into Permanent and Transitory Components

Document Type : Original Article

Authors

1 Associate Professor, Faculty of Economics, Allameh Tabataba'i University, Tehran, Iran

2 Associate Professor, Faculty of Economics, Allameh Tabataba'i University, Tehran, Iran (Corresponding author)

3 Ph.D. Candidate in Financial Economics, Faculty of Economics, Allameh Tabataba'i University, Iran

Abstract

Stochastic behavior of stock returns is very important for investors and policy makers in the stock market. In this paper, the stochastic behavior of the return index of Tehran Stock Exchange (TEDPIX) is examined using unobserved component Markov switching model (UC-MS) for the 3/27/2010 until 8/3/2015 period. In this model, stock returns are decomposed into two components; a permanent component and a transitory component. This approach allows analyzing the impact of shocks of permanent and transitory components. The transitory component has a three-state Markov switching heteroscedasticity (low, medium, and high variances). Results show that the unobserved component Markov switching model is appropriate for this data. Low value of RCM criteria implies that the model can successfully distinguish among regimes. The aggregate autoregressive coefficients in the temporary component are about 0.4. The duration of high-variance regime for the transitory component is short-lived and reverts to normal levels quickly. The implied result of the research is that the presidential election may have a significant effect on being in the third regime.

Keywords

References

1)     Albert, J. H. and Chib, S. (1993). Bayes Inference via Gibbs Sampling of Autoregressive Time Series Subject to Markov Mean and Variance Shifts.  Journal of Business and Economic Statistics, 11, 1-15.
2)     Ang, A. and Bekaert, G. (2002). Regime Switches in Interest Rate. Journal of Business and Economic Statistics, 20, 163-182
3)     Bhar, R. and Shigeyuki, H. (2004). Empirical Characteristic of Permanent and Transitory Components of Stock Returns: Analysis in a Markov-Switching Heteroscedasticity Framework. Economic Letters, 82, 157-165.
4)     Camerer, C. (1989). Bubbles and Fads in Asset Prices.  Journal of Economic Surveys, 3(1), 1-41.
5)     Campbell, J. and Mankiw, G. (1987). Are Output Fluctuation Transitory? Quarterly Journal of Economics, 102, 857-880.
6)     Carter, C. K. and Kohn, R. (1994). On Gibbs Sampling for State Space Models. Biometrika, 81, 541-553.
7)     Chan, K., Treepongkaruna, S., Brooks, R., and Gray, S. (2011). Asset Market Linkages: Evidence from Financial, Commodity and Real Estate Assets. Journal of Banking and Finance, 35 (6),1415-1426.
8)     Chen, Sh. and Shen, Ch. (2012). Examining the Stochastic Behavior of REIT Returns: Evidence from the Regime Switching Approach. Journal Economic Modeling, Vol. 29, 291-298
9)     Clark, P. (1987). The Cyclical Component of U.S. Economic Activity. Quarterly Journal of Economics, 102, 797-814.
10)  Diebold, F. X., (1986). Modeling the Persistence of Conditional Variances: A Comment. Economietric Reviews, 5 (1), 51-56.
11)  Engle, R. and Lee, G. (1992). A Permanent and Transitory Component of Stock Returns Volatility. University of California, San Diego Discussion paper. 92-44.
12)  Engle, R. and Chowdhury, M. (1992). Implied ARCH Models from Option Prices. Journal of Econometrics, 52, 289-311.
13)  Fama, E., French, K. (1988). Permanent and Transitory Component of Stock Prices. Journal of Political Economy, 96(2), 246-273.
14)  Fama, E., Fischer, L., Jensen, M., and Roll, R. (1969). The Adjustment of Risk Prices to New Information. International Economic Review, 10.
15)  Friedman, B. and Laibson, D. (1989). The Economic Implications of Extraordinary Movement in Stock Prices. Brooking papers of Economic Activity, 2, 137-189.
16)  Gelfand, A. and Smith, A. (1990). Sampling-based Approaches to Calculating Marginal Densities. Journal of the American Statistical Association, 85, 398-409.
17)  Hamilton, J. (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycles. Econometrica, 57, 357-384.
18)  Hamilton, J. and Susmel, R. (1994). Autoregressive Conditional Heteroscedasticity and Changes in Regime. Journal of Econometrics, 64, 307-333.
19)  Hammoudeh, Sh. and Choi, K. (2007). Characteristic of Permanent and Transitory Returns in Oil-Sensitive Emerging Stock Market: The Case of GCC Countries. Journal of International Financial Market, Institutions and Money, 17, 231-245.
20)  Kim, Ch. and Kim, M. (1996). Transient Fads and the Crash of ’87. Journal of Applied Econometrics, 11(1), 41-58.
21)  Kim, Ch. and Nelson, Ch., Startz, R. (1991). Mean Reversion in Stock Prices? A Reappraisal of the Empirical Evidence. Review of Economic Studies, 58, 515-528.
22)  Kim, Ch. and Nelson, Ch. (1998). Testing for Mean Reversion in Heteroskedastic Data II: Autoregression Tests Based on Gibbs Sampling-Augmented Randomization. Journal of Empirical Finance, 8(4), 385-396.
23)  Kim, Ch., Nelson, Ch. and Startz, R. (1998). Testing for Mean Reversion in Heteroskedastic Data Based on Gibbs Sampling-Augmented Randomization.  Journal of Empirical Finance, 5, 131-154.
24)  Kim, Ch., Nelson, Ch. (1999). State Space Models with Regime Switching; Classical and Gibbs Sampling Approaches with Applications. The MIT Press, Cambridge, Massachusetts, London, England.
25)  Le Roy, S. and Porter, R. (1981). The Present-Value Relation: Test Based on Implied Variance Bounds.  Econometrica, 49(3), 555-574.
26)  Najarzadeh, R., Sahabi, B., and Soleimani, S. (2013). The Relationship Between Inflation and Inflation Uncertainty in the Short and Long Run: State Space Model with Markov Switching Heteroscedasticity. Journal of Economic Research, 18 (54), 1-25.
27)  Nazifi Naeini, M. and Fatahi, Sh. (2012). Compering Regime Switching GARCH Models and GARCH Models in Developing Countries (case study of IRAN). Journal of Analisis Financiero, 60-68.
28)  Poterba, J. and Summers, L. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22, 27-59.
29)  Schaller, H. and Van Norden, S. (2002). Fads or Bubbles? A Journal of The Institute Advanced Studies, Vienna, Austria, 27.
30)  Schwert, W. (1990). Stock Volatility and the Crash of ’87. The Review of Financial Studies, 3, 77-102.
31)  Shiller, R. (1981). Do Stock Prices Move too Much to Be Justified by Subsequent Changes in Dividends? The American Economic Review, 71(3), 421-436.
32)  Shiller, R. (1984). Stock Prices and Social Dynamics. Brookings papers on Economic Activity, 457-498.
33)  Soleimani, S., Falahati, A., and Rostami, A. R. (2016). Permanent and Transitory Components of Stock Returns: An Application of State Space with Markov Switching Heteroscedasticity. Journal of Economic Modeling Research, 7(25), 69-90.
34)  Summers, L. (1986). Does the Stock Market Rationally Reflect Fundamental Values? Journal of Finance XLI, 591-601.
35)  Watson, M. (1986). Univariate Detrending Models with Stochastic Trends. Journal of Monetary Economics,18, 49-75.
36)  West, K. (1988). Bubbles, Fads and Stock Prices Volatility Test: A Partial Evaluation. National Bureau of Economic Research, Working paper. 2574.
International Journal of Finance & Managerial Accounting
Volume 2, Issue 8
January 2018
Pages 19-28

Files

Share

How to cite

Statistics