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A Utility Based Comparison of Some Models of Exchange Rate Volatility

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  • Kenneth D. West
  • Hali J. Edison
  • Dongchul Cho

Abstract

When estimates of variances are used to make asset allocation decisions, underestimates of population variances lead to lower expected utility than equivalent overestimates: a utility based criterion is asymmetric, unlike standard criteria such as mean squared error. To illustrate how to estimate a utility based criterion, we use five bilateral weekly dollar exchange rates, 1973-1989, and the corresponding pair of Eurodeposit rates. Of homoskedastic, GARCH, autoregressive and nonpararnetric models for the conditional variance of each exchange rate, GARCI-J models tend to produce the highest utility, on average. A mean squared error criterion also favors GARCH, but not as sharply.

Suggested Citation

  • Kenneth D. West & Hali J. Edison & Dongchul Cho, 1992. "A Utility Based Comparison of Some Models of Exchange Rate Volatility," NBER Technical Working Papers 0128, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberte:0128
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    1. Eun, Cheol S & Resnick, Bruce G, 1984. "Estimating the Correlation Structure of International Share Prices," Journal of Finance, American Finance Association, vol. 39(5), pages 1311-1324, December.
    2. Schwert, G. William, 1989. "Business cycles, financial crises, and stock volatility," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 31(1), pages 83-125, January.
    3. Pagan, Adrian R. & Schwert, G. William, 1990. "Alternative models for conditional stock volatility," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 267-290.
    4. McCulloch, Robert & Rossi, Peter E., 1990. "Posterior, predictive, and utility-based approaches to testing the arbitrage pricing theory," Journal of Financial Economics, Elsevier, vol. 28(1-2), pages 7-38.
    5. Breen, William & Glosten, Lawrence R & Jagannathan, Ravi, 1989. " Economic Significance of Predictable Variations in Stock Index Returns," Journal of Finance, American Finance Association, vol. 44(5), pages 1177-1189, December.
    6. Richard A. Meese & Andrew K. Rose, 1991. "An Empirical Assessment of Non-Linearities in Models of Exchange Rate Determination," Review of Economic Studies, Oxford University Press, vol. 58(3), pages 603-619.
    7. Schwert, G William, 1989. " Why Does Stock Market Volatility Change over Time?," Journal of Finance, American Finance Association, vol. 44(5), pages 1115-1153, December.
    8. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
    9. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    10. Richard A. Ippolito, 1989. "Efficiency with Costly Information: A Study of Mutual Fund Performance, 1965–1984," The Quarterly Journal of Economics, Oxford University Press, vol. 104(1), pages 1-23.
    11. Friedman, Benjamin M & Kuttner, Kenneth N, 1992. "Time-Varying Risk Perceptions and the Pricing of Risky Assets," Oxford Economic Papers, Oxford University Press, vol. 44(4), pages 566-598, October.
    12. Diebold, Francis X. & Nason, James A., 1990. "Nonparametric exchange rate prediction?," Journal of International Economics, Elsevier, vol. 28(3-4), pages 315-332, May.
    13. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    14. Robert F. Engle & Che-Hsiung Hong & Alex Kane, 1990. "Valuation of Variance Forecast with Simulated Option Markets," NBER Working Papers 3350, National Bureau of Economic Research, Inc.
    15. Meltzer, Allan H., 1989. "IMF policy advice, market volatility, commodity price rules, and other essays," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 31(1), pages 1-6, January.
    16. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    17. Akgiray, Vedat, 1989. "Conditional Heteroscedasticity in Time Series of Stock Returns: Evidence and Forecasts," The Journal of Business, University of Chicago Press, vol. 62(1), pages 55-80, January.
    18. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
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