A conditional extreme value volatility estimator based on high-frequency returns

Journal of Economic Dynamics and Control

Volumn 31, Issue 2, 2007, Pages 361-397

  Bali, Turan G ^a   Weinbaum, David ^b  

^a CITY UNIVERSITY OF NEW YORK   (United States)

^b Dyson School of Applied Economics and Management   (United States)

Author keywords

Extreme value; GARCH; High frequency returns; Implied volatility; Realized volatility

Indexed keywords

EID: 33846318162     PISSN: 01651889     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jedc.2005.10.002     Document Type: Article

References (73)

1. Akgiray V. Conditional heteroskedasticity in time series of stock returns: evidence and forecasts. Journal of Business 62 (1989) 55-80
2. Andersen T.G., and Bollerslev T. Answering the skeptics: yes standard volatility models do provide accurate forecasts. International Economic Review 39 (1998) 885-905
3. Andersen T.G., and Bollerslev T. Deutsche Mark-Dollar volatility: intraday activity patterns, macroeconomic announcements, and longer run dependencies. Journal of Finance 53 (1998) 219-265
4. Andersen T.G., Bollerslev T., and Lange S. Forecasting financial market volatility: sample frequency vis-à-vis forecast horizon. Journal of Empirical Finance 6 (1999) 457-477
5. Andersen T.G., Bollerslev T., Diebold F.X., and Labys P. Great realizations. Risk 13 (2000) 105-108
6. Andersen T.G., Bollerslev T., Diebold F.X., and Ebens H. The distribution of realized stock return volatility. Journal of Financial Economics 61 (2001) 43-76
7. Andersen T.G., Bollerslev T., Diebold F.X., and Labys P. The distribution of realized exchange rate volatility. Journal of the American Statistical Association 96 (2001) 42-55
8. Andersen T.G., Bollerslev T., Diebold F.X., and Labys P. Modeling and forecasting realized volatility. Econometrica 71 (2003) 579-626
9. Andersen T.G., Bollerslev T., Christoffersen P.F., and Diebold F.X. Volatility and correlation forecasting. In: Elliott G., Granger C.W.J., and Timmerman A. (Eds). Handbook of Economic Forecasting (2006), North-Holland, Amsterdam, forthcoming
10. Andersen T.G., Bollerslev T., and Meddahi N. Correcting the errors: volatility forecast evaluation using high-frequency data and realized volatilities. Econometrica 73 (2005) 279-296
11. Andreou E., and Ghysels E. Rolling-sample volatility estimators: some new theoretical, simulation and empirical results. Journal of Business and Economic Statistics 20 (2002) 363-376
12. Bali T.G. Testing the empirical performance of stochastic volatility models of the short term interest rate. Journal of Financial and Quantitative Analysis 35 (2000) 191-215
13. Bali T.G. An extreme value approach to estimating volatility and value at risk. Journal of Business 76 (2003) 83-108
14. Bali, T.G., 2005. Modeling the dynamics of interest rate volatility with skewed fat-tailed distributions. Annals of Operations Research, forthcoming.
15. Bali T.G., and Neftci S. Disturbing extremal behavior of spot rate dynamics. Journal of Empirical Finance 10 (2003) 455-477
16. Barndorff-Nielsen O.L., and Shephard N. Non-Gaussian OU based models and some of their uses in financial economics. Journal of the Royal Statistical Society B 63 (2001) 167-241
17. Barndorff-Nielsen O.E., and Shephard N. Econometric analysis of realized volatility and its use in estimating stochastic volatility models. Journal of the Royal Statistical Society B 64 (2002) 253-280
18. Barndorff-Nielsen O.L., and Shephard N. Estimating quadratic variation using realized variance. Journal of Applied Econometrics 17 (2002) 457-477
19. Berndt E.K., Hall B.H., Hall R.E., and Hausmann J.A. Estimation and inference in non-linear structural models. Annals of Economic and Social Measurement 4 (1974) 653-665
20. Black F., and Scholes M. The pricing of options and corporate liabilities. Journal of Political Economy 81 (1973) 637-654
21. Blair B.J., Poon S.-H., and Taylor S.J. Forecasting S&P 100 volatility: the incremental information content of implied volatilities and high-frequency index returns. Journal of Econometrics 105 (2001) 5-26
22. Bliemel F. Theil's forecast accuracy coefficient: a clarification. Journal of Marketing Research 10 (1973) 444-446
23. Bollerslev T. Generalized autoregressive conditional heteroscedasticity. Journal of Econometrics 31 (1986) 307-327
24. Bollerslev T. A conditionally heteroscedastic time series model for security prices and rates of return data. Review of Economics and Statistics 59 (1987) 542-547
25. Bollerslev T., Chou R.Y., and Kroner K.F. ARCH modeling in finance: a review of the theory and empirical evidence. Journal of Econometrics 52 (1992) 5-59
26. Bollerslev T., Engle R.F., and Nelson D.B. ARCH models. In: Engle R.F., and McFadden D.L. (Eds). Handbook of Econometrics vol. 4 (1994), Elsevier, Amsterdam 2959-3038
27. Brailsford T.F., and Faff R.W. An evaluation of volatility forecasting techniques. Journal of Banking and Finance 20 (1996) 419-438
28. Canina L., and Figlewski S. The informational content of implied volatility. Review of Financial Studies 6 (1993) 659-681
29. Castillo E. Extreme value theory in engineering (1988), San Diego, CA, Academic Press
30. Christensen B.J., and Prabhala N.R. The relation between implied volatility and realized volatility. Journal of Financial Economics 50 (1998) 125-150
31. Day T.E., and Lewis C.M. Stock market volatility and the informational content of stock index options. Journal of Econometrics 52 (1992) 267-287
32. Diebold, F.X., Lopez, J.A., 1995. Modeling volatility dynamics. In: Hoover, K. (Ed.), Macroeconometrics: Developments, Tensions and Prospects.
33. Diebold, F.X., Schuermann, 1999. In: Embrechts, P., Kluppelberg, C., Mikosch, T. (Eds.), Modelling extremal events for insurance and finance. Risk 12, 63.
34. Diebold F.X., Schuermann T., and Stroughair J. Pitfalls and opportunities in the use of extreme value theory in risk management. In: Refenes A.-P.N., Burgess A.N., and Moody J.D. (Eds). Advances in Computational Finance 3-12 (1998), Kluwer Academic Publishers, Amsterdam 30-36 (Reprinted in Journal of Risk Finance, 1 (Winter 2000))
35. Duan J.-C. Augmented GARCH(p,q) process and its diffusion limit. Journal of Econometrics 79 (1997) 97-127
36. Embrechts P., Kluppelberg C., and Mikosch T. Modeling Extremal Events (1997), Springer, Berlin Heidelberg
37. Engle R.F. Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica 50 (1982) 987-1007
38. Engle R.F., and Ng V.K. Measuring and testing the impact of news on volatility. Journal of Finance 48 (1993) 1749-1778
39. Figlewski S. Forecasting volatility. Financial Markets, Institutions and Instruments 6 (1997) 1-88
40. Fisher R.A., and Tippett L.H.C. Limiting forms of the frequency distribution of the largest or smallest member of a sample. Proceedings of the Cambridge Philosophical Society 24 (1928) 180-190
41. Fleming J. The quality of market volatility forecasts implied by S&P 100 index option prices. Journal of Empirical Finance 5 (1998) 317-345
42. Fleming J., Ostdiek B., and Whaley R.E. Predicting stock market volatility: a new measure. Journal of Futures Markets 15 (1995) 265-302
43. Fleming J., Kirby C., and Ostdiek B. The economic value of volatility timing using realized volatility. Journal of Financial Economics 67 (2003) 473-509
44. Frances P.H., and Van Dijk D. Forecasting stock market volatility using (non-linear) GARCH models. Journal of Forecasting 15 (1995) 229-235
45. Glosten L.R., Jagannathan R., and Runkle D.E. On the relation between the expected value and the volatility of the nominal excess return on stocks. Journal of Finance 48 (1993) 1779-1801
46. Gnedenko B.V. Sur la distribution limite du terme maximum d'une serie aleatoire. Annals of Mathematics 44 (1943) 423-453
47. Harvey C.R., and Whaley R.E. Dividends and S&P 100 index options. Journal of Futures Markets 12 (1992) 123-137
48. Hentschel L.E. All in the family: nesting symmetric and asymmetric GARCH models. Journal of Financial Economics 39 (1995) 71-104
49. Jenkinson A.F. The frequency distribution of the annual maximum (or minimum) values of meteorological elements. Quarterly Journal of the Royal Meteorology Society 87 (1955) 145-158
50. Joe H., Smith R.L., and Weissman I. Bivariate threshold methods for extremes. Journal of the Royal Statistical Society B 54 (1992) 171-183
51. Jorion P. Predicting volatility in the foreign exchange market. Journal of Finance 50 (1995) 507-528
52. Lamoureux C.G., and Lastrapes W.D. Forecasting stock-return variance: toward and understanding of stochastic implied volatilities. Review of Financial Studies 6 (1993) 293-326
53. Leadbetter M.R., Lindgren G., and Rootzen H. Extremes and Related Properties of Random Sequences and Processes (1983), Springer, New York
54. Leuthold R.M. On the use of Theil's inequality coefficients. American Journal of Agricultural Economics 57 (1975) 344-346
55. Longin F.M. From value at risk to stress testing: the extreme value approach. Journal of Banking and Finance 24 (2000) 1097-1130
56. Marshall A.W., and Olkin I. Domains of attraction of multivariate extreme value distributions. Annals of Probability 11 (1983) 168-177
57. McNeil A.J., and Frey R. Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach. Journal of Empirical Finance 7 (2000) 271-300
58. Meddahi N. A theoretical comparison between integrated and realized volatility. Journal of Applied Econometrics 17 (2002) 479-508
59. Mincer J., and Zarnowitz V. The evaluation of economic forecasts. In: Mincer J. (Ed). Economic Forecasts and Expectation (1969), Columbia University Press, New York 3-46
60. Nelson D.B. Conditional heteroscedasticity in asset returns: a new approach. Econometrica 59 (1991) 347-370
61. Newey W.K., and West K.D. A simple, heteroskedastic and autocorrelation consistent covariance matrix. Econometrica 55 (1987) 703-708
62. Pagan A. The econometrics of financial markets. Journal of Empirical Finance 3 (1996) 15-102
63. Palm F.C. GARCH models of volatility. In: Maddala G.S., and Rao C.R. (Eds). Handbook of Statistics vol. 14 (1996), Elsevier, Amsterdam 209-240
64. Pickands J. Statistical inference using extreme order statistics. Annals of Statistics 3 (1975) 119-131
65. Pindyck R.S., and Rubinfeld D.L. Econometric Models And Economic Forecast (1991), McGraw-Hill, New York
66. Resnick S.I. Extreme Values, Regular Variation, and Point Processes (1987), Springer, New York
67. Schwert G.W. Why does stock market volatility change over time?. Journal of Finance 44 (1989) 1115-1153
68. Stekler H.O. Forecasting with econometric models: an evaluation. Econometrica 36 (1968) 437-463
69. Tawn J.A. Bivariate extreme value theory: model and estimation. Biometrika 75 (1988) 397-415
70. Taylor S.J. Modeling Financial Time Series (1986), Wiley, New York
71. Theil H. Economic Forecasts and Policy (1961), North-Holland, Amsterdam
72. Whaley R.E. Derivatives on market volatility: hedging tools long overdue. Journal of Derivatives 1 (1993) 71-84
73. Zakoian J.-M. Threshold heteroscedastic models. Journal of Economic Dynamics and Control 18 (1994) 931-995