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Are Feedback Factors Important In Modelling Financial Data?

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Helena Veiga ()

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Abstract

This paper provides empirical evidence that continuous time models with one factor of volatility are, in some circumstances, able to fit the main characteristics of financial data and reports insights about the importance of introducing feedback factors for capturing the strong persistence caused by the presence of changes in the variance. We use the Efficient Method of Moments (EMM) by Gallant and Tauchen (1996) to estimate and to select among logarithmic models with one and two stochastic volatility factors (with and without feedback).

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Paper provided by Universidad Carlos III, Departamento de Estadística y Econometría in its series Statistics and Econometrics Working Papers with number ws060101.

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Date of creation: Jan 2006
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Handle: RePEc:cte:wsrepe:ws060101

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  1. Chernov, Mikhail & Gallant, A. Ronald & Ghysels, Eric & Tauchen, George, 2002. "Alternative Models for Stock Price Dynamic," Working Papers 02-03, Duke University, Department of Economics. [Downloadable!]
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  2. Francis X. Diebold & Atsushi Inoue, 2000. "Long Memory and Regime Switching," NBER Technical Working Papers 0264, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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  3. Gallant, A Ronald & Rossi, Peter E & Tauchen, George, 1992. "Stock Prices and Volume," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 5(2), pages 199-242. [Downloadable!] (restricted)
  4. Clive W.J. Granger & Namwon Hyung, 1999. "Occasional Structural Breaks and Long Memory," University of California at San Diego, Economics Working Paper Series 99-14, Department of Economics, UC San Diego. [Downloadable!]
  5. Gallant, A. Ronald & Tauchen, George, 1997. "Reprojecting Partially Observed Systems with Application to Interest Rate Diffusions," Working Papers 97-09, Duke University, Department of Economics.
  6. Beine, Michel & Laurent, Sebastien, 2003. "Central bank interventions and jumps in double long memory models of daily exchange rates," Journal of Empirical Finance, Elsevier, vol. 10(5), pages 641-660, December. [Downloadable!] (restricted)
  7. repec:cup:etheor:v:12:y:1996:i:4:p:657-81 is not listed on IDEAS
  8. Gallant, A. Ronald & Tauchen, George, 2002. "Efficient Method of Moments," Working Papers 02-06, Duke University, Department of Economics. [Downloadable!]
  9. Coppejans, Mark & Gallant, A. Ronald, 2002. "Cross-validated SNP density estimates," Journal of Econometrics, Elsevier, vol. 110(1), pages 27-65, September. [Downloadable!] (restricted)
  10. Chernov, Mikhail & Ronald Gallant, A. & Ghysels, Eric & Tauchen, George, 2003. "Alternative models for stock price dynamics," Journal of Econometrics, Elsevier, vol. 116(1-2), pages 225-257. [Downloadable!] (restricted)
  11. Ait-Sahalia, Yacine, 1996. "Nonparametric Pricing of Interest Rate Derivative Securities," Econometrica, Econometric Society, vol. 64(3), pages 527-60, May. [Downloadable!] (restricted)
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  12. Elena Andreou & Eric Ghysels, 2002. "Detecting multiple breaks in financial market volatility dynamics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 579-600. [Downloadable!]
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  13. Ait-Sahalia, Yacine, 1996. "Testing Continuous-Time Models of the Spot Interest Rate," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 9(2), pages 385-426. [Downloadable!] (restricted)
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  14. Brandt, Michael W. & Santa-Clara, Pedro, 2002. "Simulated likelihood estimation of diffusions with an application to exchange rate dynamics in incomplete markets," Journal of Financial Economics, Elsevier, vol. 63(2), pages 161-210, February. [Downloadable!] (restricted)
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