Gurgul, Henryk and Lach, Łukasz (2010): The causal link between Polish stock market and key macroeconomic aggregates. Published in: Betriebswirtschaftliche Forschung und Praxis , Vol. 4, (2010): pp. 367383.

PDF
MPRA_paper_52250.pdf Download (260kB)  Preview 
Abstract
This paper with the application of linear, nonlinear and long–run Granger causality tests, examines the causal links between the main Polish market price index (WIG) of the Warsaw Stock Exchange and four macroeconomic aggregates, namely the value of sold industrial production, the unemployment rate, the interest rate and the rate of inflation using monthly data for the period from January 1998 to June 2008. We found a bidirectional linear causal relationship between the stock market index and sold industrial production and strong evidence of linear and nonlinear Granger causality from changes in the interest rate to fluctuations in the stock market index. Furthermore, all examined macroeconomic variables were found to have a longrun causal influence on the performance of the stock market.
Item Type:  MPRA Paper 

Original Title:  The causal link between Polish stock market and key macroeconomic aggregates 
Language:  English 
Keywords:  stock market, macroeconomic aggregates, cointegration, linear and nonlinear causality, market efficienc 
Subjects:  C  Mathematical and Quantitative Methods > C3  Multiple or Simultaneous Equation Models ; Multiple Variables > C32  TimeSeries Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models G  Financial Economics > G1  General Financial Markets > G14  Information and Market Efficiency ; Event Studies ; Insider Trading 
Item ID:  52250 
Depositing User:  Dr Łukasz Lach 
Date Deposited:  17 Dec 2013 06:37 
Last Modified:  11 Oct 2019 11:30 
References:  1. Abhyankar, A. (1998), Linear and nonlinear Granger causality: Evidence from the U.K. stock index futures market, Journal of Futures Markets, 18, pp. 519–540. 2. Asimakopoulos, I., Ayling, D., Mahmood W.M. (2000), Nonlinear Granger causality in the currency futures returns, Economics Letters, 68, pp. 25–30. 3. Baek, E., Brock, W. (1992), A general test for Granger causality: Bivariate model, Technical Report, Iowa State University and University of Wisconsin, Madison. 4. Balduzzi, P. (1995), Stock Returns, Inflation and the Proxy Hypothesis: A New Look at the Data, Economics Letters, 48, pp. 47–53. 5. Blanchard, O.J., Changyong, R., Summers L. (1993), The Stock Market, Profit and Investment, Quarterly Journal of Economics, 108, pp. 115–136. 6. Brock, W. (1991), Causality, Chaos, Explanation and Prediction in Economics and Finance, in: J. Casti, A. Karlqvist (Eds.), Beyond Belief: Randomness, Prediction and Explanation in Science, CRC Press, Boca Raton, FL, pp. 230–279 (Chapter 10). 7. Charemza, W., Deadman, D. (1997), New directions in econometric practice (2nd edn), Edward Elgar, Cheltenham. 8. Chen, N.F., Roll, R., Ross, S.A. (1986), Economic Forces and the Stock Market, Journal of Business, 59, pp. 383–403. 9. Cheng, J.C., Taylor, L.W., Weng, W. (2006), Exchange rates and prices: revisiting Granger causality tests, Journal of Post Keynesian Economics, 29, No. 2, pp. 259–283. 10. Chirinko, R.S., Schaller, H. (1996), Bubbles, Fundamentals and Investment: A Multiple Equation Testing Strategy, Journal of Monetary Economics, 38, pp. 47–76. 11. Diks, C., Panchenko, V. (2006), A new statistic and practical guidelines for nonparametric Granger causality testing, Journal of Economic Dynamics & Control, 30, pp. 1647–1669. 12. Dik, C., Panchenko, V. (2005), A note on the HiemstraJones test for Granger noncausality, Studies in Nonlinear Dynamics and Econometrics, 9, No. 2, Article 4. 13. Fama, E.F. (1981), Stock Returns, Real Activity, Inflation and Money, American Economic Review, 71, pp. 545–565. 14. Fama, E.F., Schwert, G.W. (1997), Asset Returns and Inflation, Journal of Financial Economics 5, pp. 115–146. 15. Graham, F.C. (1996), Inflation, Real Stock Returns and Monetary Policy, Applied Financial Economics, 6, pp. 29–35. 16. Granger, C.W.J. (1981), Some properties of time series data and their use in econometric model specification, Journal of Econometrics, 16, pp. 121–130. 17. Granger, C.W.J. (1986), Developments in the Study of Cointegrated Economic Variables, Oxford Bulletin of Economics and Statistics, 48, pp. 213–228. 18. Granger, C.W.J. (1969), Investigating causal relations by econometric models and cross–spectral methods, Econometrica, 37, pp. 424–438. 19. Granger, C.W.J., Newbold, P. (1974), Spurious regression in econometrics, Journal of Econometrics, 2, pp. 111–120. 20. Granger, C.W.J. (1988), Some recent developments in the concept of causality, Journal of Econometrics, 39, pp. 199211. 21. Hiemstra, C., Jones, J.D. (1994), Testing for linear and nonlinear Granger causality in the stock pricevolume relation, Journal of Finance, 49, No. 5, pp. 1639–1664. 22. Lütkepohl, H. (1991), Introduction to Multiple Time Series Analysis, SpringerVerlag, New York. 23. Morck, R., Schleifer, A., Vishny, R.W. (1990), The Stock Market and Investment: Is the Market a Sideshow? Brookings Papers on Economic Activity, 2, pp. 157–215. 24. Phillips, P.C.B. (1986), Understanding the spurious regression in econometrics, Journal of Econometrics, 33, pp. 311–340. 25. Sims, C.A., Stock, J.H., Watson, M.W. (1990), Inference in linear time series models with some unit roots, Econometrica, 58, pp. 133–144. 26. Tobin, J. (1969), A General Equilibrium Approach to Monetary Theory, Journal of Money, Credit and Banking, 1, pp. 15–29. 27. Toda, H.Y., Yamamoto, T. (1995), Statistical inference in vector autoregressions with possibly integrated processes, Journal of Econometrics, 66, pp. 225–250. 
URI:  https://mpra.ub.unimuenchen.de/id/eprint/52250 