Continuous-time models, realized volatilities, and testable distributional implications for daily stock returns

Journal of Applied Econometrics

Volumn 25, Issue 2, 2010, Pages 233-261

  Andersen, Torben G ^a   Bollerslev, Tim ^b   Frederiksen, Per ^c   Nielsen, Morten Ørregaard ^d  

^a NORTHWESTERN UNIVERSITY   (United States)

^b DUKE UNIVERSITY   (United States)

^c Nordea Markets   (Denmark)

^d QUEEN S UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 75849144466     PISSN: 08837252     EISSN: 10991255     Source Type: Journal    
DOI: 10.1002/jae.1105     Document Type: Article

References (77)

1. Ait-Sahalia Y, Mykland PA, Zhang L. 2005. How often to sample a continuous-time process in the presence of market microstructure noise. Review of Financial Studies 18: 351-416.
2. Andersen TG. 1996. Return volatility and trading volume: an information flow interpretation of stochastic volatility. Journal of Finance 51: 169-204.
3. Andersen TG, Bollerslev T. 1998a. Answering the skeptics: yes, standard volatility models do provide accurate forecasts. International Economic Review 39: 885-905.
4. Andersen TG, Bollerslev T. 1998b. Deutchemark-dollar volatility: intraday activity patterns, macroeconomic announcements, and longer run dependencies. Journal of Finance 53: 219-265.
5. Andersen TG, Bollerslev T, Diebold FX, Labys P. 2000a. Exchange rate returns standardized by realized volatility are (nearly) Gaussian. Multinational Finance Journal 4: 159-179.
6. Andersen TG, Bollerslev T, Diebold FX, Labys P. 2000b. Great realizations. Risk 13: 105-108.
7. Andersen TG, Bollerslev T, Diebold FX, Labys P. 2001a. The distribution of exchange rate volatility. Journal of the American Statistical Association 96: 42-55.
8. Andersen TG, Bollerslev T, Diebold FX, Ebens H. 2001b. The distribution of realized stock return volatility. Journal of Financial Economics 61: 43-76.
9. Andersen TG, Benzoni L, Lund J. 2002. An empirical investigation of continuous-time equity return models. Journal of Finance 57: 1239-1284.
10. Andersen TG, Bollerslev T, Diebold FX, Labys P. 2003a. Modelling and forecasting realized volatility. Econometrica 71: 579-625.
11. Andersen TG, Bollerslev T, Diebold FX, Vega C. 2003b. Micro effects of macro announcements: real-time price discovery in foreign exchange. American Economic Review 93: 38-62.
12. Andersen TG, Bollerslev T, Christoffersen P, Diebold F. 2006a. Volatility forecasting. In Handbook of Economic Forecasting, Elliott G, Granger C, Timmermann A (eds). North-Holland: Amsterdam; 777-878.
13. Andersen TG, Bollerslev T, Frederiksen PH, Nielsen M. 2006b. Comment on Peter R. Hansen and Asger Lunde: realized variance and market microstructure noise. Journal of Business and Economic Statistics 24: 173-178.
14. Andersen TG, Bollerslev T, Huang X. 2009. A semiparametric framework for modelling and forecasting jumps and volatility in speculative prices. Journal of Econometrics (forthcoming).
15. Andersen TG, Bollerslev T, Diebold FX. 2007a. Roughing it up: including jump components in the measurement, modeling, and forecasting of return volatility. Review of Economics and Statistics 89: 701-720.
16. Andersen TG, Bollerslev T, Dobrev D. 2007b. No-arbitrage semi-martingale restrictions for continuous-time volatility models subject to leverage effects, jumps and i.i.d. noise: theory and testable distributional implications. Journal of Econometrics 138: 125-180.
17. Ane T, Geman H. 2000. Order flow, transaction clock, and normality of asset returns. Journal of Finance 55: 2259-2284.
18. Baillie RT, Bollerslev T. 1989. The message in daily exchange rates: a conditional variance tale. Journal of Business and Economic Statistics 7: 297-305.
19. Bandi FM, Russell JR. 2008. Microstructure noise, realized variance, and optimal sampling. Review of Economic Studies 75: 339-369.
20. Barndorff-Nielsen OE, Shephard N. 2002. Econometric analysis of realized volatility and its use in estimating stochastic volatility models. Journal of the Royal Statistical Society Series B 64: 253-280.
21. Barndorff-Nielsen OE, Shephard N. 2004. Power and bipower variation with stochastic volatility and jumps. Journal of Financial Econometrics 2: 1-48.
22. Barndorff-Nielsen OE, Shephard N. 2006. Econometrics of testing for jumps in financial economics using bipower variation. Journal of Financial Econometrics 4: 1-30.
23. Barndorff-Nielsen OE, Shephard N, Winkel M. 2006. Limit theorems for multipower variation in the presence of jumps. Stochastic Processes and their Applications 116: 796-806.
24. Barndorff-Nielsen OE, Hansen PR, Lunde A, Shephard N. 2008. Designing realised kernels to measure the ex-post variation of equity prices in the presence of noise. Econometrica 76: 1481-1536.
25. Bates D. 1996. Jumps and stochastic volatility: exchange rate processes implicit in Deutschemark options. Review of Financial Studies 9: 69-107.
26. Bates DS. 2000. Post-87 crash fears in the S&P 500 futures option market. Journal of Econometrics 94: 181-238.
27. Black F. 1976. The pricing of commodity contracts. Journal of Financial Economics 3: 167-179.
28. Bollerslev T. 1987. A conditional heteroskedastic time series model for speculative prices and rates of return. Review of Economics and Statistics 69: 542-547.
29. Bollerslev T, Jubinski D. 1999. Equity trading volume and volatility: latent information arrivals and common long-run dependencies. Journal of Business and Economic Statistics 17: 9-21.
30. Bollerslev T, Litvinova J, Tauchen G. 2006. Leverage and volatility feedback effects in high-frequency data. Journal of Financial Econometrics 4: 353-384.
31. Bollerslev T, Kretschmer U, Pigorsch C, Tauchen G. 2008. A discrete-time model for daily S&P500 returns and realized variations: jumps and leverage effects. Journal of Econometrics 150: 151-166.
32. Bontemps C, Meddahi N. 2005a. Testing distributional assumptions: a GMM approach. Working paper, University of Montreal.
33. Bontemps C, Meddahi N. 2005b. Testing normality: a GMM approach. Journal of Econometrics 124: 149-186.
34. Chernov M, Gallant AR, Ghysels E, Tauchen G. 2003. Alternative models of stock price dynamics. Journal of Econometrics 116: 225-257.
35. Christensen K, Podolski M. 2007. Realized range-based estimation of integrated variance. Journal of Econometrics 141: 323-349.
36. Christie AA. 1982. The stochastic behavior of common stock variances: value, leverage and interest rate effects. Journal of Financial Economics 3: 145-166.
37. Clark PE. 1973. A subordinated stochastic process model with finite variance for speculative prices. Econometrica 41: 135-155.
38. Cont R, Tankov P. 2004. Financial Modeling with Jump Processes. Chapman & Hall: London.
39. Dacorogna MM, Gencay R, Müller UA, Pictet OV, Olsen RB. 2001. An Introduction to High-Frequency Finance. Academic Press: San Diego, CA.
40. Dambis KE. 1965. On the decomposition of continuous submartingales. Theory of Probability Applications 10: 401-410.
41. de Pooter M, Martens M, van Dijk D. 2008. Predicting the daily covariance matrix for S&P100 stocks using intraday data: but which frequency to use? Econometric Reviews 27: 199-229.
42. Dubins L, Schwartz G. 1965. On continuous martingales. Proceedings of the National Academy of Sciences 53: 913-916.
43. Engle RF. 2004. Nobel lecture. Risk and volatility: econometric models and financial practice. American Economic Review 94: 405-420.
44. Epps TW, Epps ML. 1976. The stochastic dependence of security price changes and transaction volumes: implications for the mixture-of-distributions hypothesis. Econometrica 44: 303-321.
45. Eraker B. 2004. Do stock prices and volatility jump? Reconciling evidence from spot and option prices. Journal of Finance 59: 1367-1403.
46. Eraker B, Johannes M, Polson N. 2003. The impact of jumps in volatility and returns. Journal of Finance 58: 1269-1300.
47. Fama E. 1965. The behavior of stock prices. Journal of Business 38: 34-105.
48. Fleming J, Paye BS. 2006. High-frequency returns, jumps and the mixture of normals hypothesis. Working paper, Jones Graduate School of Management, Rice University.
49. Fleming J, Kirby C, Ostdiek B. 2003. The economic value of volatility timing using realized volatility. Journal of Financial Economics 67: 473-509.
50. Gallant AR, Rossi PE, Tauchen G. 1992. Stock-prices and volume. Review of Financial Studies 5: 199-242.
51. Gillemot L, Farmer JD, Lillo F. 2005. Theres more to volatility than volume. Working paper, Santa Fe Institute.
52. Hansen L, Lunde A. 2005. A realized variance for the whole trading day based on intermittent high-frequency data. Journal of Financial Econometrics 3: 525-554.
53. Hansen PR, Lunde A. 2006. Realized variance and market microstructure noise. Journal of Business and Economic Statistics 24: 127-161.
54. Hsieh D. 1989. Modeling heteroskedasticity in foreign exchange rates. Journal of Business and Economic Statistics 7: 307-317.
55. Huang X, Tauchen G. 2005. The relative contribution of jumps to total price variance. Journal of Financial Econometrics 3: 456-499.
56. Hull JC, White A. 1987. The pricing of options on assets with stochastic volatilities. Journal of Finance 42: 281-300.
57. Jiang GJ, Oomen RCA. 2008. Testing for jumps when asset prices are observed with noise: a 'swap variance' approach. Journal of Econometrics 144: 352-370.
58. Johannes M. 2004. The statistical and economic role of jumps in interest rates. Journal of Finance 59: 227-260.
59. Kim D, Kon SJ. 1994. Alternative models for the conditional heteroskedasticity of stock returns. Journal of Business 67: 563-598.
60. Lai T, Siegmund D. 1983. Fixed accuracy estimation of an autoregressive parameter. Annals of Statistics 11: 478-485.
61. Lee SS, Mykland PA. 2008. Jumps in financial markets: a new nonparametric test and jump dynamics. Review of Financial Studies 21: 2535-2563.
62. Liesenfeld R. 1998. Dynamic bivariate mixture models: modeling the behavior of prices and trading volume. Journal of Business and Economic Statistics 16: 101-109.
63. Luu JC, Martens M. 2003. Testing the mixture of distributions hypothesis using 'realized' volatility. Journal of Futures Market 23: 661-679.
64. Maheu JM, McCurdy TH. 2004. News arrival, jump dynamics, and volatility components for individual stock returns. Journal of Finance 59: 755-793.
65. Mancini C. 2005. Disentangling the jumps of the diffusion in a geometric jumping Brownian motion. Working paper, Department of Mathematics, University of Florence.
66. Mandelbrot B. 1963. The variation of certain speculative prices. Journal of Business 36: 394-419.
67. Merton RC. 1976. Option pricing when underlying stock returns are discontinuous. Journal of Financial Economics 3: 125-144.
68. Murphy A, Izzeldin M. 2006. Order flow, transaction clock, and normality of asset returns: Ane and Geman (2000) revisited. Working paper, Oxford and Lancaster Universities.
69. Nelson DB. 1991. Conditional heteroskedasticity in asset returns: a new approach. Econometrica 59: 347-370.
70. Nielsen M, Frederiksen PH. 2008. Finite sample accuracy and choice of sampling frequency in integrated volatility estimation. Journal of Empirical Finance 15: 265-286.
71. Oomen R. 2006. Properties of realized variance under alternative sampling schemes. Journal of Business and Economic Statistics 24: 219-237.
72. Peters RT, de Vilder RG. 2006. Testing the continuous semimartingale hypothesis for the S&P 500. Journal of Business and Economic Statistics 24: 444-454.
73. Ploberger W. 2005. A generalization of the Skorohod embedding to random elements in Polish spaces. Working paper, University of Rochester.
74. Rosenbaum M. 2007. A new microstructure noise index. Working paper, Université Paris-Est and CRESTENSAE.
75. Tauchen G, Pitts M. 1983. The price variability-volume relationship on speculative markets. Econometrica 51: 485-505.
76. Todorov V. 2009. Econometric analysis of jump-driven stochastic volatility models. Journal of Econometrics forthcoming.
77. Zhou B. 1998. Parametric and nonparametric volatility measurement. In Nonlinear Modelling of High-Frequency Financial Time Series, Dunis C, Zhou B (eds). Wiley: London; 109-129.