Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2006 | nr 2 Financial markets : principles of modeling forecasting and decision-making | 209--220
Tytuł artykułu

Modeling and Predicting Japanese Stock Returns Based on the ARFIMA-FIGARCH

Treść / Zawartość
Warianty tytułu
Języki publikacji
Chapter 12 presents Japanese stock returns by modeling persistence in both their mean and volatility. Firstly, evidence is obtained of persistence in the Japanese stock mean and volatility. Secondly, it has been found that the models incorporating persistence and appropriate economic fundamentals produce more accurate forecasts than those from a linear model. For example, the long-term interest rate is found to be significant in the Japanese stock return equation. The positive relationship between the stock return and the long-term rate reported in this chapter is consistent with the Japanese experience when a rise in the nominal interest rate has been regarded as a sign of economic recovery, rather than a harbinger of higher inflation rates and a slowdown of its economic growth in the future. Thirdly, the forecasting accuracy of the mean of the stock return appears reliable, particularly in the long-term context, once the persistent characteristics and an appropriate determinant are properly considered in estimation models. The results may be encouraging for investors who make investment decisions based on statistical methods, and have some implications for portfolio formulation. (fragment of text)
  • University of Tsukuba, Japan
  • Baillie R. T., Bollerslev T., Mikkelsen H. O. (1996), Fractionally Integrated Generalized Autoregressive Conditional Heteroskedasticity, Journal of Econometrics, 74, 3-30.
  • Bollerslev T., Mikkelsen H. O. (1996), Modeling and Pricing Long Memory in Stock Market Volatility, Journal of Econometrics, 73, 151-184.
  • Busse J. A. (1999), Volatility Timing in Mutual Funds: Evidence from Daily Returns, Review of Financial Studies, 12, 1009-1041.
  • Campbell J. Y., Lo A. W., MacKinlay A. C. (1997), The Econometrics of Financial Markets, Princeton: University Press.
  • Cheung Y-W., Lai K. S. (1995), A Search lor Long Memory in International Stock Market Returns, Journal of International Money and Finance, 14(4), 597-615.
  • Crato N., de Lima P. J. F. (1994), Long-Range Dependence in the Conditional Variance of Stock Returns, Economics Letters, 281-285.
  • Diebold F. X., Mariano R. S. (1995), Comparing Predictive Accuracy, Journal of Business and Economic Statistics, 13(3), 253-263.
  • Engle R. F. (1992), Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation, Econometrica, 50(4), 987-1006.
  • Engle R. F., Ng V. K. (1993), Measuring and Testing the Impact of News on Volatility, Journal of Finance, 48, 1749-1778.
  • Fama E. F. (1970), Efficient Capital Markets: A Review of Theory and Empirical Work, Journal of Finance, 25, 383-417.
  • Glosten L. R., Jagannathan R., and Runkle D. E. (1993), On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks, Journal of Finance, 48, 1779-1801.
  • Granger C. W. J., Joyeux R. (1980), An Introduction to Long-Memory Time Series Models and Fractional Differencing, Journal of Time Series Analysis, 1(1), 15-29.
  • Harcey A. C. (1998), Long Memory in Stochastic Volatility, in: Knight J., Satchell S. (eds.), Forecasting Volatility in the Financial Markets, London: Butterworth-Heinemann, 307-320.
  • Hosking J. R. M. (1981), Fractional Differencing, Biometrika, 68(1), 165-176.
  • Johannes M., Poison N., Stroud J. (2002), Sequential Optimal Portfolio Performance: Market and Volatility Timing, Wharton School, University of Pennsylvania, Working Paper.
  • Kaul G. (1996), Predictable Components in Stock Returns, in: Maddala G. S., Rao C. R. (eds.), Statistical Methods in Finance, Handbook of Statistics, Vol. 14, Elsevier: Amsterdam, 269-296.
  • LeRoy S. F. (1996), Stock Price Volatility, in: Maddala G. S., Rao C. R. (eds.), Statistical Methods in Finance, Handbook of Statistics, Vol. 14. Amsterdam: Elsevier, 193-208.
  • Lo A. W. (1991), Long-Term Memory in Stock Market Prices, Econometrica, 59(5), 1279-1313.
  • McKenzie M. D. (2001), Non-Periodic Australian Stock Market Cycles: Evidence from Rescaled Range Analysis, Economic Record, 77, 393-406.
  • Mills T. C. (1993), Is There Long-Term Memory in U.K. Stock Returns?, Applied Financial Economics, 3, 303-306.
  • Nagayasu J. (2005), Determinants of the Tokyo Stock Price Index: Searching for Explanations of the Depression, Department of Social Systems and Management, Graduate School of Systems and Information Engineering, University of Tsukuba, Discussion Paper Series, 1117.
  • Poon S-H., Granger C. W. J. (2003), Forecasting Volatility in Financial Markets: A Review, Journal of Economic Literature, 41, 478-539.
  • Shiller R. J. (1984), Stock Prices and Social Dynamics, Brookings Papers on Economic Activity, 2, 457-497.
  • Summers L. H. (1986), Does the Stock Market Rationally Reflect Fundamental Values?, Journal of Finance, 41, 591-601.
Typ dokumentu
Identyfikator YADDA

Zgłoszenie zostało wysłane

Zgłoszenie zostało wysłane

Musisz być zalogowany aby pisać komentarze.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.