case study on arbitrage pricing theory
An Empirical Investigation of Arbitrage Pricing Theory: A case
Zimbabwe
Petros Jecheche
University of Zimbabwe
ABSTRACT
This study investigates the Arbitrage Pricing Theory for the case of Zimbabwe using time series data from 1980 to 2005 within a vector autoregressive (VAR) framework. The Granger causality tests are conducted to establish the existence of causality among the variables like inflation, exchange rate and Gross Domestic Product. The VAR estimates as shown by the impulse response and variance decomposition together with the Granger causality test show that there is unidirectional causality from Consumer Price Index to Stock Prices. Although the Granger causality test has indicated that there is no causality between RGDP and Stock Prices, the variance decomposition has shown that the real GDP explains deviations in the Stock Prices in the long run. Granger causality tests found no meaningful relationships between Stock Prices and Exchange Rate but considering impulse response functions the effect is significant as early as the first period.
Keywords: Arbitrage, Capital Asset Pricing Model (CAPM), Efficient Market Hypothesis, Vector Auto Regression Model (VAR), Impulse Response, Variance Decomposition.
INTRODUCTION
The Capital Asset Pricing Model (CAPM) and the Arbitrage Pricing Theory (APT) have emerged as two models that have tried to scientifically measure the potential for assets to generate a return or a loss. Both of them are based on the efficient market hypothesis, and are part of the modern portfolio theory. The Efficient Market Hypothesis (EMH) (Fama, 1965), states that at any given time, security prices fully reflect all available information. If the asset is overpriced, then arbitrageurs will short the asset, until reduced demand for purchasing it caused the price to fall. The opposite is true for underpriced securities.
The CAPM is based on several simplifying assumptions and because most of these assumptions
Zimbabwe
Petros Jecheche
University of Zimbabwe
ABSTRACT
This study investigates the Arbitrage Pricing Theory for the case of Zimbabwe using time series data from 1980 to 2005 within a vector autoregressive (VAR) framework. The Granger causality tests are conducted to establish the existence of causality among the variables like inflation, exchange rate and Gross Domestic Product. The VAR estimates as shown by the impulse response and variance decomposition together with the Granger causality test show that there is unidirectional causality from Consumer Price Index to Stock Prices. Although the Granger causality test has indicated that there is no causality between RGDP and Stock Prices, the variance decomposition has shown that the real GDP explains deviations in the Stock Prices in the long run. Granger causality tests found no meaningful relationships between Stock Prices and Exchange Rate but considering impulse response functions the effect is significant as early as the first period.
Keywords: Arbitrage, Capital Asset Pricing Model (CAPM), Efficient Market Hypothesis, Vector Auto Regression Model (VAR), Impulse Response, Variance Decomposition.
INTRODUCTION
The Capital Asset Pricing Model (CAPM) and the Arbitrage Pricing Theory (APT) have emerged as two models that have tried to scientifically measure the potential for assets to generate a return or a loss. Both of them are based on the efficient market hypothesis, and are part of the modern portfolio theory. The Efficient Market Hypothesis (EMH) (Fama, 1965), states that at any given time, security prices fully reflect all available information. If the asset is overpriced, then arbitrageurs will short the asset, until reduced demand for purchasing it caused the price to fall. The opposite is true for underpriced securities.
The CAPM is based on several simplifying assumptions and because most of these assumptions
References: Akmal, R. (1997). ‘Stock markets, banks, and growth: correlation or causality?’, Policy Research Working Paper 2670, Washington DC: World Bank. Attaullah, D. (2001), Macroeconomic influence on the stock market: evidence from an emerging market in South Asia. Journal of Emerging Market Finance 3(3): 85- 304. Azeez K. P. and V. Yonoezawa, (2003), “Firm characteristics, unanticipated inflation and stock returns”, The Journal of finance, Vol. 43 No.4, pp. 965-981. Basu, S., 1977, Investment performance of common stock in relation to their price-earning ratios: a test of the efficient market hypothesis, Journal of Finance, vol 32, pp.663-682 Binswanger, R Black N. (1972), “The effects of macroeconomic factors on stock returns: Istanbul Stock Market”, Studies in Economics and Finance, Vol Bouvatier, V., (2006), Hot Money inflows in China: how the People’s Bank of China took up the challenge, Centre National de la Recherche Scientifique Campbell, J Chakaza R. (2008), “The fiscal and monetary linkage between stock returns and inflation in Zimbabwe”, The Journal of fnance, Vol Chen, J. S., 2005, Reviews on housing finance in China, International housing financial conference, July 7. 2005, Xi’an Chen, N Cuthbertson, 2004), “Do structural oil market shocks affect stock prices?”, Energy Economics, Vol. 31, pp. 569-575. DeFina, D. (1991). ‘A sensitivity analysis of cross-country growth regressions’, American Economic Review, 82: 942-63. Dickey D. and Fuller W. (1981), “Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root”, Econometrica, Vol. 49 No. 4, pp. 1057-1072. Erb C., Shin T. and Bacon F. (1996), “The effect of macroeconomic variables on stock market returns in developing markets”, Multinational Business Review, Vol. 5 No 2, pp. 63. Fama, E. F., 1965, Random Walks in Stock Market Prices, Financial Analysts Journal, vol 5,135-150 Fazal, M. J. and Mahmood, L. A. (2006), Money and stock prices: the channels of influence. Financial Times. (2007b, November 17) China warns on illegal capital flow, Retrieve Jan. 20, 2011, from http://www.ft.com/cms/s/0/1d0f8752-96ee-11dc-b2da-0000779fd2ac.html Gao, S., (2002), China stock market in a global perspective, Research Report of DJI, September 2002, Dow Jones Indexes. Gilles C. and Leroy, (1990), “Cointegration for market forecast in the Spanish stock market”, Applied Economics, Vol Granger, C. W. J. (1969), Developments in the study of cointegrated economic variables. Oxford Bulletin of Economics and Statistics 48: 213-228. Gultekin, G. H. (1983), Internationally diversified portfolios: Welfare gains and capital flows. Halicioglue, D. F. (2007), Econometric modeling with cointegrated variables: An overview. Hamao, Y., (1988), An empirical examination of the arbitrage pricing theory: using Japanese data, Japan and the World Economy, vol 1, pp.45-61 Johansen S Vector Autoregressive Models”, Econometrica, Vol. 59 No 6, pp. 1551-1580. Keim, D. B., 1985, Dividend yields and stock returns: implications abnormal January returns, Journal of Financial Economics, vol 14, pp.473-489 Keogh, A. J., 1994, Financial Management: principles and applications, 10th Edition, Pearson: Prentice Hall, New Jersey. Kurihara V. and K. Nezu (2006), “Macroeconomic determinants of European stock market volatility”, European Financial Management, Vol. 4 No. 3, pp. 361-377. Levy G. and Solomon E. (2000), “Macroeconomic influences on the stock market”, Journal of Economics and Finance, Vol Linter S. (1965), “Predicting the bear stock market: Macroeconomic variables as leading indicators”, Journal of Banking & Finance, Vol. 33, pp. 211-223. Liu, T. and Green, S., (2003), China’s informal stock market: how it developed, how it works and how it might grow, October 2003, Asia Programme Working Paper, No.8. Lang, X. P., 2005, Manipulation, publisher: Dongfang Publisher, Taipei. Lanzeni, L. M. and Hansakul, S., (2004). Enterprise reform & stock market development in mainland China: China special. Deutsche Bank Research, March 25, 2004. Markowitz, H. M., 1952, Portfolio Selection, Journal of Finance, March, pp.77-91 Martikainen, M Martikainen, N, Sjoo, B. and Zhang, J. (1999), Market segmentation and information diffusion in China’’ stock markets: panel data unit root and cointegration tests on A and B share prices. EFMA 2003 Helsinki Maysami, R Maysami, D., Phillips, B., Schmidt, P. and Shin, Y. (2004) “Testing the Null of Stationarity Against the Alternative of a Unit Root: How Sure Are We That Economic Time Series Have a Unit Root?”, Journal of Econometrics, 54, pp. 159–78 Merton A Mishra, M (1994). ‘Risk-Taking, Global Diversification, and Growth’, American Economic Review, 84(5), pp Mlambo M. and Biekpe K. (2005), “Analysis of the long-term relationship between macro-economic variables and the Chinese stock market using heteroscedastic cointegration”, Morel M. (1973), “Money and the stock market”, The Journal of Political Economy, Vol. 96 No. Mossin S. (1966), “Economic Forces and the Stock Market”, The Journal of Business, Vol. 59 No Mpohamba, B. (1955). ‘Financial markets in development, and the development of financial markets’, Journal of Economic Dynamics and Control, 21: 141-81. Mukherjee Y. and Naka E. (1995), “Recent stock price relationships between Japanese and US stock markets”, Studies in Economics and Finance, Vol New York Times. (2005, July 11) Another China bank is courted by the west, Retrieve Jan. 20, 2011, from http://www.nytimes.com/2005/07/11/business/worldbusiness/11bank.html Park, A. and Wang, S. G., (2002), China’s poverty statistics, China Economic Review. Vol.12 (4), pp.384-398. People’s Bank of China, (2005), 2004 report on China’s real estate market, August 5, 2005 Perkins, D Prasad, E. and Wei, S. J., (2005), The Chinese approach to capital inflows: patterns and possible explanations, IMF Working Paper, April 2005, WP/05/79, International Monetary Fund. Roll, R. and Ross, S. A., (1993), An empirical investigation of the arbitrage pricing theory, Journal of Finance Roll R. and Ross S.A. (1994), “An Empirical Investigation of the Arbitrage Pricing Theory”, The Journal of Finance, Vol Ross, S. A., 1976, The arbitrage theory of capital asset pricing, Journal of Economic Theory. Ross, S.A, (1993), “Economic variables and stock market returns: evidence from the Athens stock exchange”, Applied financial economics, Vol.16, pp. 993-1005. Sadorsky, A. (2010), Stock returns and economic activity: The UK case.European Journal of Finance 6(3): 280-297. Shanken, J. (1982). ‘Financial development, financing choice and economic growth’, Review of Development Economics, 9 (2): 135-49.