Hostname: page-component-84b7d79bbc-4hvwz Total loading time: 0 Render date: 2024-07-27T22:18:29.527Z Has data issue: false hasContentIssue false
  • English
  • Français

Fluctuating Confidence in Stock Markets: Implications for Returns and Volatility

Published online by Cambridge University Press:  06 April 2009

Alexander David
Alexander David
Affiliation:
Division of Research and Statistics, Board of Governors of the Federal Reserve System, Washington, D.C. 20551.
Get access Rights & Permissions [Opens in a new window]

Abstract

The average relative profitability of different firms in the economy jumps erratically. Although investors are unable to observe these productivity switches, they continuously update their beliefs regarding high and low productivity firms by observing the total return on each firm, which consists of the average productivity plus noise. The portfolio choices, interest rate, and stock return processes are derived in a Cox-Ingersoll-Ross (1985a) style general equilibrium model. Three stylized facts of stock market returns are addressed: negative skewness, excess kurtosis, and predictive asymmetry (excess returns and future changes in volatility are negatively correlated). To measure the last stylized fact, an EGARCH model is fitted to sample paths simulated from the model. Parameter values that permit faster learning fit the three facts better.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 32 , Issue 4 , December 1997 , pp. 427 - 462
Copyright
Copyright © School of Business Administration, University of Washington 1997

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Baumol, W. J.Economic Theory and Operations Analysis. Englewood Cliffs, NJ: Prentice-Hall International Series in Management (1977).Google Scholar
Berndt, E.; Hall, B.; Hall, R.; and Hausman, J.. “Estimation and Inference in Nonlinear Structural Models.” Annals of Economic and Social Measurement, 3 (1974), 653–655.Google Scholar
Bickel, P. J., and Doksum, K. A.. Mathematical Statistics. Basic Ideas and Selected Topics. Oakland, CA: Holden-Day, Inc. (1976).Google Scholar
Black, F. “Studies of Stock Price Volatility Changes.” Proceeding of the Business and Economics Statistics Section, American Statistical Association, (1976), 177–181.Google Scholar
Bollerslev, T.; Engle, R. F.; and Woolridge, J. M.. “A Capital Asset Pricing Model with Time Varying Covariances.” Journal of Political Economy, 96 (02 1988), 116–131.Google Scholar
Bollerslev, T.; Chou, R. Y.; and Kroner, K. F.. “ARCH Modelling in Finance. A Review of the Theory and Empirical Practice.” Journal of Econometrics, 52 (04–05 1992), 5–59.CrossRefGoogle Scholar
Campbell, J. Y., and Hentschel, L.. “No News is Good News: An Asymmetric Model of Changing Volatility in Stock Returns.” Journal of Financial Economics, 31 (06 1992), 281–318.CrossRefGoogle Scholar
Cecchetti, S.; Lam, P.; and Mark, N.. “The Equity Premium and the Risk-Free Rate: Matching the Moments.” Journal of Monetary Economics, 31 (02 1993), 21–45.Google Scholar
Christie, A. “The Stochastic Behavior of Common Stock Variances: Value, Leverage, and Interest Rate Effects.” Journal of Financial Economics, 10 (12 1982), 407–432.Google Scholar
Clark, P. “A Subordinated Stochastic Process Model With Finite Variance for Speculative Prices.” Econometrica, 41 (01 1973), 131–155.CrossRefGoogle Scholar
Cox, J.; Ingersoll, J.; and Ross, S.. “An Intertemporal General Equilibrium Model of Asset Prices.” Econometrica, 53 (03 1985a), 363–384.CrossRefGoogle Scholar
Cox, J.; Ingersoll, J.; and Ross, S.. “A Theory of the Term Structure of Interest Rates.” Econometrica, 53 (03 1985b), 385–407.CrossRefGoogle Scholar
David, A. Business Cycle Risk and the Equity Premium. Ph.D. Diss., Dept. of Economics, Univ. of California at Los Angeles (1993).Google Scholar
David, A.; Oh, S.; Ostroy, J.; and Shin, K.. “Cyclical Fluctuations in Uncertainty: An Application to the Premium on Equities.” Mimeo, Dept. of Economics, Univ. of California at Los Angeles (1992).Google Scholar
Davis, S. J., and Haltiwanger, J. C.. “Gross Job Creation, Gross Job Destruction, and Employment Reallocation.” Quarterly Journal of Economics, 107 (08 1992), 819–863.Google Scholar
DeGroot, M.Probability and Statistics. Reading, MA: Addison-Wesley (1985).Google Scholar
Detemple, J. B. “Asset Pricing in a Production Economy with Incomplete Information.” Journal of Finance, 41 (06 1986), 383–391.Google Scholar
Detemple, J. B. “Further Results on Asset Pricing with Incomplete Information.” Journal of Economic Dynamics and Control, 15 (07 1991), 425–453.CrossRefGoogle Scholar
Detemple, J. B., and Murthy, S.. “Intertemporal Asset Pricing with Heterogeneous Beliefs.” Journal of Economic Theory, 62 (04 1994), 294–320.CrossRefGoogle Scholar
Dothan, U., and Feldman, D.. “A Theory of Asset Prices and the Term Structure of Interest Rates in a Partially Observable Economy.” Journal of Finance, 41 (06 1986), 369–382.CrossRefGoogle Scholar
Engle, R. F.; Lilien, D. M.; and Robbins, R. P.. “Estimating Time Varying Risk Premia in the Term Structure.” Econometrica, 55 (1987).CrossRefGoogle Scholar
Gennotte, G. “Optimal Portfolio Choice under Incomplete Information.” Journal of Finance, 41 (07 1986), 733–749.Google Scholar
Greene, W.Econometric Analysis. Englewood Cliffs, NJ: Prentice Hall, Second Ed. (1993).Google Scholar
Haberman, R.Elementary Partial Differential Equations: With Fourier Series and Boundary Value Problems. Englewood Cliffs, NJ: Prentice Hall (1990).Google Scholar
Hakansson, N. H. “Optimal Investment and Consumption Strategies under Risk for a Class of Utility Functions.” Econometrica, 38 (09 1970), 587–607.Google Scholar
Hamilton, J. D. “A New Approach to the Economic Analysis of Non-Stationary Time Series and the Business Cycle.” Econometrica, 57 (03 1989), 357–384.Google Scholar
Ingersoll, J.Theory of Financial Decision Making. Savage, MD: Rowman and Littlefield (1988).Google Scholar
Jazwinski, A.Stochastic Processes and Filtering Theory. New York, NY: Academic Press (1970).Google Scholar
Jones, R., and Ostroy, J.. “Flexibility and Uncertainty.” Review of Economic Studies, 51 (01 1985), 13–32.CrossRefGoogle Scholar
Karlin, S., and Taylor, H.. A Second Course in Stochastic Processes. New York, NY: Academic Press (1982).Google Scholar
Karatzas, I., and Xue, X.. “A Note on Utility Maximization under Partial Observations.” Mathematical Finance, 1 (04 1991), 57–70.CrossRefGoogle Scholar
Krishnan, V.Non-Linear Filtering and Smoothing: An Introduction to Martingales, Stochastic Integrals and Estimation. New York, NY: Wiley (1982).Google Scholar
Lilien, D. M. “Sectoral Shifts and Cyclical Employment.” Journal of Political Economy, 90 (08 1982), 777–793.CrossRefGoogle Scholar
Liptser, R., and Shiryayev, A.. Statistics of Random Processes I. New York, NY: Springer-Verlag (1978).CrossRefGoogle Scholar
Loungani, P.; Rush, M.; and Tave, W.. “Stock Market Dispersion and Employment.” Journal of Monetary Economics, 25 (06 1990), 367–388.CrossRefGoogle Scholar
Lucas, R. “Asset Prices in an Exchange Economy.” Econometrica, 46 (11 1978), 1429–1445.CrossRefGoogle Scholar
Merton, R. “An Intertemporal Capital Asset Pricing Model.” Econometrica, 41 (09 1973), 867–887.CrossRefGoogle Scholar
Merton, R.Continuous-Time Finance. Cambridge, MA: Blackwell (1990).Google Scholar
Nelson, D. “Conditional Heteroscedasticity in Asset Returns: A New Approach.” Econometrica, 59 (03 1991), 347–370.Google Scholar
Ostroy, J., and Potter, S.. “Pricing with Commitments.” Mimeo, Dept. of Economics, Univ. of California at Los Angeles (1995).Google Scholar
Pagan, A., and Schwert, W.. “Alternative Models for Conditional Stock Volatility.” Journal of Econometrics, 45 (07–08 1990), 267–290.Google Scholar
Samuelson, P. “Lifetime Portfolio Selection by Dynamic Stochastic Programming.” Review of Economics and Statistics, 51, (08 1969), 239–246.CrossRefGoogle Scholar
Schwert, W. “Why Does Stock Market Volatility Change over Time.” Journal of Finance, 44 (12 1989), 1115–1153.CrossRefGoogle Scholar
Stokey, N.; Lucas, R.; and Prescott, E.. Recursive Methods in Economic Dynamics. Cambridge, MA: Harvard Univ. Press (1989).CrossRefGoogle Scholar
Turner, C.; Startz, R.; and Nelson, C.. “A Markov Model of Heteroscedasticity, Risk, and Learning in the Stock Market.” Journal of Financial Economics, 25 (1989), 3–22.CrossRefGoogle Scholar