||What Drives Stock Market Returns?
An Empirical Evidence from Panel Smooth Transition Regression Model
||Department of Banking and Finance
||由於近年來，全球經濟一直受到油價波動、全球金融風暴與美國量化寬鬆政策的影響，因此股票市場在遭受不同風險情況下，對於報酬的影響應該也會不同。故本文擬加入不同的風險因子(油價、全球市場與匯率風險)，並運用縱橫平滑移轉迴歸模型(Panel Smooth Transition Regression)分別來探討股票市場報酬如何受到總體經濟、財務理論與國際金融相關因素的影響。
本文第一個研究議題為「在油價波動的衝擊下，探討總體經濟與股票市場報酬的非線性關係」，實證結果發現：當油價風險較小時(約小於5%)，貨幣供給(Money Supply)對於股票市場報酬影響較大，反之，當油價風險較大時(約大於5%)，則是實質經濟活動(Real Activity)對於股票市場報酬影響較大。
第二個研究議題為「探討資本資產定價模型的非線性關係」，本篇利用全球市場風險做為門檻變數，探討 與股票市場報酬的非線性關係，實證結果發現： 與股票市場報酬存在正向關係；但是當全球市場風險較小時，反而對於股票市場報酬的影響較為顯著。
本文最後的研究議題為「探討在匯率風險下，外人投資與股票市場報酬的非線性關係」，實證結果發現：在匯率風險較小時，不論外人投資的型態為何，對於股票市場報酬都為正向的關係；然而當匯率風險較大時，外人直接投資(Foreign Direct Investment)與外人證券投資(Foreign Portfolio Investment) 對於股票市場報酬則為負向的關係。
||In recent years, oil price volatility, global financial crises and America's Quantitative Easing Monetary Policy have been affecting the global economy. Hence, stock market returns should be affected based on different investment risks. For this reason, the purpose of this dissertation utilize the Panel Smooth Transition Regression (PSTR) model to investigate the influence of the stock market returns on macroeconomics, financial theory and international finance from three different risk factors (oil, global market and exchange rate risks).
The topic of the first part is: Nonlinear investigation for the impact of oil price volatility on the fundamental analysis. Empirical evidence shows that when real oil price volatility is in a low regime (approximately less than 5%), money supply tends to have a greater effect on real stock returns. Conversely, when real oil price volatility is in a high regime (approximately greater than 5%), real activity have a greater effect on real stock returns.
The topic of the second part is: Threshold effects in the capital asset pricing model. We set the volatility of world market excess return as the threshold variable, and to examine the nonlinear relationship between beta (systematic risk) and returns (world market excess returns). The results show that all beta values are positive and higher in the low regime (i.e., volatility of world market excess return is low) and lower in the high regime (i.e., volatility of world market excess return is high).
Finally, The topic of the third part is: Nonlinear relationship between foreign investments and stock market returns with exchange rate volatility. The results show that all foreign investments are positive in the low regime for exchange rate volatility, , no matter what kind of investment. But in the high regime, the relationship between the stock market returns both foreign direct and portfolio investments have negative relations.
||Table of Content
Chapter 1 Introduction 1
Chapter 2 Literature Review 4
2.1 Relationship between macroeconomic variables and stock market returns 4
2.2 Issues about Capital Asset Pricing Model (CAPM) 6
2.3 Relationship between foreign investments and stock market returns 8
Chapter 3 Methodology 11
3.1 Panel Unit Root Test 11
3.2 Panel Smooth Transition Regression (PSTR) 13
Chapter 4 Empirical Investigation 21
4.1 Nonlinear Investigation for the Impact of Oil Price Volatility on the Fundamental Analysis 21
4.1.1 Data and Summary Statistics 21
4.1.2 Empirical results 23
4.2 Threshold effects in the capital asset pricing model using panel smooth transition regression (PSTR) Evidence from net oil export and import groups 29
4.2.1 Data and Summary Statistics 29
4.2.2 Empirical results 32
4.3 Nonlinear relationship between foreign investments and stock market returns with exchange rate volatility 37
4.3.1 Data and Summary Statistics 37
4.3.2 Empirical results 39
Chapter 5 Conclusions 43
List of Tables
Table 4.1.1 Countries and stock price indices employed in the study. 22
Table 4.1.2 Descriptive statistics 22
Table 4.1 3 Panel unit root tests 23
Table 4.1 4 LM test for remaining nonlinearity 24
Table 4.1 5 Determination of the number of location parameters 25
Table 4.1 6 Parameter estimates for the final PSTR models 26
Table 4.1 7 Estimation of coefficients of control variables in PSTR models 26
Table 4.2.1 Stock price indices and risk-free rate employed in the study. 30
Table 4.2.2 Summary statistics 31
Table 4.2.3 Panel unit root tests 32
Table 4.2.4 LM test for remaining nonlinearity 33
Table 4.2.5 Determination of the number of location parameters 33
Table 4.2.6 Parameter estimates for the final PSTR models 35
Table 4.2.7 Estimation of coefficients of control variables in PSTR models 35
Table4.3.1 Summary statistics 38
Table4.3.2 Panel unit root tests 39
Table4.3.3 LM test for remaining nonlinearity 40
Table4.3.4 Determination of the number of location parameters 40
Table4.3.5 Parameter estimates for the final PSTR models 41
Table4.3.6 Estimation of coefficients of control variables in PSTR models 42
List of Figures
Figure 4.1.1 Transition function with respect to transition variable for model A. 28
Figure 4.1.2 Transition function with respect to transition variable for model B. 28
Abugri, B. A., (2008), Empirical relationship between macroeconomic volatility and stock returns: Evidence from Latin American markets. International Review of Financial Analysis, 17(2), 396-410.
Aloui, C., Jammazi, R. and Dhakhlaoui, I., (2008), Crude oil volatility shocks and stock market returns. Journal of Energy Markets, 1, 68-96.
Aloui, C. and Jammazi, R., (2009), The effects of crude oil shocks on stock market shifts behaviour: A regime switching approach. Energy Economics, 31, 789-799.
Andrews, D. W. K., and Ploberger, W., (1994), Optimal tests when a nuisance parameter is present only under the alternative. Econometrica, 62, 1383–1414.
Arouri, M., Lahiani, A. and Bellalah, M., (2010), More on the impact of oil price stocks on stock market returns: the case of GCC countries. International Journal of Economics and Finance, 2, 132-139.
Asprem, M., (1989), Stock prices, asset portfolios and macroeconomic variables in ten European countries. Joutnal of Banking and Finance, 13, 589-612.
Balduzzi, P., (1995), Stock returns, inflation, and the ‘proxy hypothesis’: A new look at the data. Economics Letters, 48(1), 47-53.
Balvers, R. J., Cosimano, T. F. and McDonald, B., (1990), Predicting stock returns in an efficient marke. Journal of Finance, 45, 1109-28.
Basher, S. A. and Sadorsky, P., (2006), Oil price risk and emerging stock markets. Global Finance Journal, 17, 224-251.
Bilson, C. M., Brailsford, T. J. and Hooper, V. J., (2001), Selecting macroeconomic variables as explanatory factors of emerging stock market returns. Pacific-Basin Finance Journal, 9(4), 401-426.
Black, F., Jensen, M. C. and Scholes, M., (1972), The capital asset pricing model: Some empirical tests. Studies in the Theory of Capital Markets.
Bohn, H. and Tesar, L. L., (1996), U.S. equity investment in foreign markets: portfolio rebalancing or return chasing? The American Economic Review, 86(2), 77-81.
Bredin, D. and Hyde, S., (2007), Regime changes in the relationship between stock returns and the macroeconomy. UCD Working Paper.
Brennan, M. J. and Cao, H. H., (1997), International portfolio investment flows. The Journal of Finance, 52(5), 1851-1880.
Canova, F. and De Nicolo, G., (2000), Stock returns, term structure, inflation and real activity: An international perspective. Macroeconomic Dynamics, 4, 343-372.
Chang, K. L., (2009), Do macroeconomic variables have regime-dependent effects on stock return dynamics? Evidence from the Markov regime switching model. Economic Modelling, 26, 1283-99.
Chen, S. S., (2010), Do higher oil prices push the stock market into bear territory. Energy Economics, 32, 490-95.
Chen, S. and Huang, N., (2007), Estimates of the ICAPM with regime switching betas: Evidence for four Pacific Rim economies. Applied Financial Economics, 17, 313-327.
Chen, N. F., Roll, R. and Ross, S. A., (1986), Economic forces and the stock market. Journal of Business, 59, 383-403.
Colletaz, G. and Hurlin, C., (2006), Threshold effects in the public capital productivity: an international panel smooth transition approach. Document de Recherche du Laboratoire d’Economie d’Orleans, 2006-1.
Davies, R.B., (1977), Hypothesis Testing when a Nuisance Parameter is Present Only Under the Alternative. Biometrika, 64, 247-254.
Domian, D. L., Gilster, J. E. and Louton, D. A., (1996), Expected Inflation, Interest Rates, and Stock Returns. Financial Review, 31(4), 809-830.
Eitrheim, Ø. and Teräsvirta, T., (1996), Testing the. Adequacy of Smooth Transition Autoregressive Models. Journal of Econometrics, 74, 59-75.
Enders, W., (2004), Applied econometric time series. WILEY Press.
Fama, E. F., (1981), Stock returns, real activity, inflation and money. American Economic Review, 71, 545-565.
Fama, E. F., (1990), Stock returns, expected returns and real activity. Journal of Finance, 45, 1089-1108.
Fama, E. F. and French, K., (1992), The cross-section of expected stock returns. Journal of Finance, 47, 427-465.
Fama, E. F. and MacBeth, J., (1973), Risk, return and equilibrium: Empirical tests. Journal of Political Economy, 81, 607-636.
Fletcher, J., (2000), On the conditional relationship between beta and return in international stock markets. International Review of Financial Analysis, 9, 235-245.
Froot, K. A., O'Connell, P. and Seasholes, M. S., (2001), The portfolio flows of international investors. Journal of Financial Economics, 59, 151-193.
Geske, R. and Roll, R., (1983), The Fiscal and Monetary Linkage between Stock Returns and Inflation. The Journal of Finance, 38(1), 1-33.
Gonzalez, A., Teräsvirta, T. and van Dijk, D., (2004), Panel Smooth Transition Regression Model and an Application to Investment under Credit Constraint. Working Paper Stockholm School of Economics.
Gonzalez, A., Teräsvirta, T. and van Dijk, D., (2005), Panel Smooth Transition Regression Models. Working Paper Stockholm School of Economics.
Granger, G. W. J. and Teräsvirta, T., (1993), Modelling Nonlinear Economic Relationships. Oxford University Press.
Guidolin, M. and Ono, S., (2006), Are the dynamic linkages between the macroeconomy and asset prices time-varying? Journal of Economics and Business, 58, 480-518.
Hansen, B. E., (1996), Inference when a nuisance parameter is not identified under the null hypothesis. Econometrica, 64, 413–430.
Hansen, B. E., (1999), Threshold effects in non-dynamic panels: Estimation, testing and inference. Journal of Econometrics, 93, 345−368.
Hsiao, C., (2003), Analysis of Panel Data, 2nd edn. Cambridge, UK: Cambridge University Press.
Im, K. S., Pesaran, M. H. and Shin, Y., (2003), Testing for Unit Roots in Heterogeneous Panels. Journal of Econometrics, 115, 53–74.
James, C., Koreisha, S. and Partch, M., (1985), A VARMA analysis of the causal relations among stock returns real output and nominal interest rates. Journal of Finance, 40, 1375-1384.
Jansen, E. S. and T. Teräsvirta., (1996), Testing Parameter Constancy and Super Exogeneity in Econometric Equations. Oxford Bulletin of Economics and Statistics, 58, 735-763.
Jawadi, F., Arouri, M. and Bellalah, M., (2010), Nonlinear linkages between oil and stock markets in developed and emerging countries. International Journal of Business, 15, 19-31.
Kwon, C. S. and Shin, T. S., (1999), Cointegration and causality between macroeconomic variables and stock market returns. Global Finance Journal, 10(1), 71-81.
Lee, B., (1992), Causal relations among stock returns, interest rates, real activity and inflation. Journal of Finance, 47, 1591-1603.
Levin, A. and Lin, C. J., (1992), Unit Root Tests in Panel Data: Asymptotic and Finite Sample Properties. Discussion Paper, University of California, San Diego.
Levin, A. and Lin, C. J., (1993) Unit Root Tests in Panel Data: New Results. Discussion Paper, University of California, San Diego.
Levin, A., Lin, C. and Chu, C. J., (2002), Unit Root Tests in Panel Data: Asymptotic and Finite-Sample Properties. Journal of Econometrics, 108, 1–24.
Lintner, J., (1965), The valuation of risk assets and the selection of risky investments in stock portfolios and capital budgets. Review of Economics and Statistics, 47, 13-37.
Lundbergh, S., Teräsvirta, T. and van Dijk, D., (2003), Time-varying smooth transition autoregressive models. Journal of Business and Economic Statistics, 21, 104–121.
Luukkonen, R., Saikkonen P. and Teräsvirta, T., (1988), Testing Linearity Against Smooth Transition Autoregressive Models. Biometrika, 75, 491-499.
Mandelker, G. and Tandon, K., (1985), Common stock returns, real activity, money, and inflation: Some international evidence. Journal of International Money and Finance. 4(2), 267-286.
Markowitz, H., (1952), Portfolio selection. Journal of Finance, 7, 77-91.
McMillan, D. G., (2001), Nonlinear predictability of stock market returns: evidence from nonparametric and threshold models. International Review of Economics and Finance, 10, 353-68.
Miller, M. H. and Scholes, M., (1972), Rate of return in relation to risk: A reexamination of some recent findings. Studies in the Theory of Capital Markets, 47-78.
Mossin, J., (1966), Equilibrium in a capital asset market. Econometrica, 34, 768-783.
Narayan, K. P. and Narayan, S., (2010), Modeling the impact of oil prices on Vietnam’s stock prices. Applied Energy, 87, 356-361.
Nandha, M. and Hammoudeh, S., (2007), Systematic risk, and oil price and exchange rate sensitivities in Asia-Pacific stock markets. Research in International Business and Finance, 21, 326-341.
Nieh, C. C., (2002), The effect of the Asian financial crisis on the relationships among open macroeconomic factors for Asian countries. Applied Economics, 34, 491-502.
Park, K. and Ratti, R. A., (2000), Real Activity, Inflation, Stock Returns, and Monetary Policy. Financial Review, 35(2), 59-78.
Park, J. and Ratti, R. A., (2008), Oil price shocks and stock markets in the U.S. and 13 European countries. Energy Economics, 30, 2587-2608.
Pettengill, G. N., Sundaram, S. and Mathur, I., (1995), The conditional relation between beta and returns. Journal of Financial and Quantitative Analysis, 30, 101-116.
Pesaran, M. H. and Timmermann, A., (1994), Forecasting stock returns: An examination of stock market trading in the presence of transaction costs. Journal of Forecasting, 13, 335-67.
Pesaran, M. H. and Timmermann, A., (1995), Predictability of stock returns: Robustness and economic significance. Journal of Finance, 50, 1201-28.
Ramos, S. B. and Veiga, H., (2011), Risk factors in oil and gas industry returns: International evidence. Energy Economics, 33, 525-542.
Schwert, G.W., (1990), Stock returns and real activity: A century of evidence. Journal of Finance, 45, 1237-1257.
Sharpe, W., (1964), Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk. Journal of Finance, 19, 425-442.
Tang, G. Y. N. and Shum, W. C., (2003), The conditional relationship between beta and returns: Recent evidence from international stock markets. International Business Review, 12, 109-126.
Teräsvirta, T., (1994), Specification, Estimation and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425),208-18.
Tesar, L. L. and Werner, I. M., (1994), International equity transactions and U.S. portfolio choice. The Internationalization of Equity Markets, 185-215
Tesar, L. L. and Werner, I. M., (1995a), Home bias and high turnover. Journal of International Money and Finance, 14, 467-492.
Tesar, L. L. and Werner, I. M., (1995b), U.S. equity investment in emerging stock markets. The World Bank Economic Review, 9(1), 109-130.
Warther, V. A., (1995), Aggregate mutual fund and security returns. Journal of Financial Economics, 39, 209-235.
Woodward, G. and Brooks, R., (2009), Do realized betas exhibit up/down market tendencies. International Review of Economics and Finance, 18, 511-519.
Woodward, G. and Marisetty, V., (2005), Introducing non-linear dynamics to the two-regime market model: Evidence. The Quarterly Review of Economics and Finance, 45, 559-581.