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Decisionmetrics: A Decision-Based Approach to Econometric Modeling

  • Spyros Skouras

In many applications it is necessary to use a simple and therefore highly misspecified econometric model as the basis for decision-making. We propose an approach to developing a possibly misspecified econometric model that will be used as the beliefs of an objective expected utility maximiser. A discrepancy between model and ÔtruthÕ is introduced that is interpretable as a measure of the modelÕs value for this decision-maker. Our decision-based approach utilises this discrepancy in estimation, selection, inference and evaluation of parametric or semiparametric models. The methods proposed nest quasi-likelihood methods as a special case that arises when model value is measured by the Kullback-Leibler information discrepancy and also provide an econometric approach for developing parametric decision rules (e.g. technical trading rules) with desirable properties. The approach is illustrated and applied in the context of a CARA investorÕs decision problem for which analytical, simulation and empirical results suggest it is very effective.

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Paper provided by Santa Fe Institute in its series Working Papers with number 01-11-064.

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Date of creation: Nov 2001
Date of revision:
Handle: RePEc:wop:safiwp:01-11-064
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  1. Hausman, Jerry A, 1978. "Specification Tests in Econometrics," Econometrica, Econometric Society, vol. 46(6), pages 1251-71, November.
  2. Brock, W. & Lakonishok, J. & Lebaron, B., 1991. "Simple Technical Trading Rules And The Stochastic Properties Of Stock Returns," Working papers 90-22, Wisconsin Madison - Social Systems.
  3. Leitch, Gordon & Tanner, J Ernest, 1991. "Economic Forecast Evaluation: Profits versus the Conventional Error Measures," American Economic Review, American Economic Association, vol. 81(3), pages 580-90, June.
  4. John Y. Campbell & Luis M. Viceira, 1996. "Consumption and Portfolio Decisions When Expected Returns are Time Varying," NBER Working Papers 5857, National Bureau of Economic Research, Inc.
  5. Levy, H & Markowtiz, H M, 1979. "Approximating Expected Utility by a Function of Mean and Variance," American Economic Review, American Economic Association, vol. 69(3), pages 308-17, June.
  6. 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.
  7. Knight, J.L. & Stachell, S.E. & Tran, K.C., 1995. "Statistical Modeling of Asymetric Risk in Asset Returns," Papers 95-3, Saskatchewan - Department of Economics.
  8. Spyros Skouras, 2001. "Decisionmetrics: A Decision-Based Approach to Econometric Modeling," Working Papers 01-11-064, Santa Fe Institute.
  9. Ryan Sullivan & Allan Timmermann & Halbert White, 1999. "Data-Snooping, Technical Trading Rule Performance, and the Bootstrap," Journal of Finance, American Finance Association, vol. 54(5), pages 1647-1691, October.
  10. Diebold, Francis X & Mariano, Roberto S, 1995. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(3), pages 253-63, July.
  11. Christopher A. Sims, 2001. "Pitfalls of a Minimax Approach to Model Uncertainty," American Economic Review, American Economic Association, vol. 91(2), pages 51-54, May.
  12. Andrew Lo & Harry Mamaysky & Jiang Wang, 1999. "Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation," Computing in Economics and Finance 1999 402, Society for Computational Economics.
  13. Manski, Charles F, 1991. "Regression," Journal of Economic Literature, American Economic Association, vol. 29(1), pages 34-50, March.
  14. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
  15. Lawrence Blume & David Easley, 2001. "If You're So Smart, Why Aren't You Rich? Belief Selection in Complete and Incomplete Markets," Working Papers 01-06-031, Santa Fe Institute.
  16. Weiss, Andrew A, 1996. "Estimating Time Series Models Using the Relevant Cost Function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 539-60, Sept.-Oct.
  17. Yacine Aït-Sahalia, 2001. "Variable Selection for Portfolio Choice," Journal of Finance, American Finance Association, vol. 56(4), pages 1297-1351, 08.
  18. Chamberlain, Gary, 2000. "Econometrics and decision theory," Journal of Econometrics, Elsevier, vol. 95(2), pages 255-283, April.
  19. Klein, Roger W, et al, 1978. "Decisions with Estimation Uncertainty," Econometrica, Econometric Society, vol. 46(6), pages 1363-87, November.
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