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Decisionmetrics: A decision-based approach to econometric modelling

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  • Skouras, Spyros

Abstract

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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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 137 (2007)
Issue (Month): 2 (April)
Pages: 414-440

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Handle: RePEc:eee:econom:v:137:y:2007:i:2:p:414-440

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Web page: http://www.elsevier.com/locate/jeconom

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References

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  1. 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.
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  8. Sullivan, Ryan & Timmermann, Allan G & White, Halbert, 1998. "Data-Snooping, Technical Trading Rule Performance and the Bootstrap," CEPR Discussion Papers 1976, C.E.P.R. Discussion Papers.
  9. J. A. Hausman, 1976. "Specification Tests in Econometrics," Working papers 185, Massachusetts Institute of Technology (MIT), Department of Economics.
  10. 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.
  11. Spyros Skouras, 2001. "Decisionmetrics: A Decision-Based Approach to Econometric Modeling," Working Papers 01-11-064, Santa Fe Institute.
  12. Klein, Roger W, et al, 1978. "Decisions with Estimation Uncertainty," Econometrica, Econometric Society, vol. 46(6), pages 1363-87, November.
  13. 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.
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  18. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
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Citations

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Cited by:
  1. Patton, Andrew J & Timmermann, Allan G, 2003. "Properties of Optimal Forecasts," CEPR Discussion Papers 4037, C.E.P.R. Discussion Papers.
  2. Patton, Andrew J. & Timmermann, Allan, 2007. "Properties of optimal forecasts under asymmetric loss and nonlinearity," Journal of Econometrics, Elsevier, vol. 140(2), pages 884-918, October.
  3. Gonzalez-Rivera, Gloria & Lee, Tae-Hwy & Mishra, Santosh, 2004. "Forecasting volatility: A reality check based on option pricing, utility function, value-at-risk, and predictive likelihood," International Journal of Forecasting, Elsevier, vol. 20(4), pages 629-645.
  4. Skouras, Spyros, 2007. "Decisionmetrics: A decision-based approach to econometric modelling," Journal of Econometrics, Elsevier, vol. 137(2), pages 414-440, April.
  5. Haas, Markus & Mittnik, Stefan & Mizrach, Bruce, 2005. "Assessing central bank credibility during the EMS crises: Comparing option and spot market-based forecasts," CFS Working Paper Series 2005/09, Center for Financial Studies (CFS).
  6. Stanislav Anatolyev, 2006. "Dynamic modeling under linear-exponential loss," Working Papers w0092, Center for Economic and Financial Research (CEFIR).
  7. Stefania D'Amico, 2005. "Density selection and combination under model ambiguity: an application to stock returns," Finance and Economics Discussion Series 2005-09, Board of Governors of the Federal Reserve System (U.S.).
  8. Halbert White & Karim Chalak, 2008. "Identifying Structural Effects in Nonseparable Systems Using Covariates," Boston College Working Papers in Economics 734, Boston College Department of Economics.
  9. Bruce Mizrach, 2006. "The Enron Bankruptcy: When did the options market in Enron lose it’s smirk?," Review of Quantitative Finance and Accounting, Springer, vol. 27(4), pages 365-382, December.
  10. Jin, Xin & Maheu, John M, 2014. "Modeling Covariance Breakdowns in Multivariate GARCH," MPRA Paper 55243, University Library of Munich, Germany.
  11. Stanislav Anatolyev & Natalia Kryzhanovskaya, 2009. "Directional Prediction of Returns under Asymmetric Loss: Direct and Indirect Approaches," Working Papers w0136, Center for Economic and Financial Research (CEFIR).
  12. Bruce Mizrach, 2007. "Recovering Probabilistic Information From Options Prices and the Underlying," Departmental Working Papers 200702, Rutgers University, Department of Economics.
  13. Hansen, Peter Reinhard & Lunde, Asger, 2006. "Consistent ranking of volatility models," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 97-121.
  14. Alexander, Marcus & Christakis, Nicholas A., 2008. "Bias and asymmetric loss in expert forecasts: A study of physician prognostic behavior with respect to patient survival," Journal of Health Economics, Elsevier, vol. 27(4), pages 1095-1108, July.

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