Detection of structural breaks in a time-varying heteroskedastic regression model

Journal of Statistical Planning and Inference

Volumn 141, Issue 11, 2011, Pages 3367-3381

  Chen, Cathy W S ^a   Gerlach, Richard ^b   Liu, Feng Chi ^a  

^a FENG CHIA UNIVERSITY   (Taiwan)

^b UNIVERSITY OF SYDNEY   (Australia)

Author keywords

Bayesian; Deviance information criterion (DIC); Heteroskedasticity; MCMC; Model instability; Model selection; Structural break

Indexed keywords

EID: 79959794420     PISSN: 03783758     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jspi.2011.05.014     Document Type: Review

References (48)

1. Andrews D.W.K. Tests for parameter instability and structural change with unknown changepoint. Econometrica 1993, 61:821-856.
2. Ang, A., Bekaert, G., 2004. Stock return predictability: Is it there? Manuscript, Columbia University and NBER.
3. Bai J., Perron P. Estimating and testing linear models with multiple structural changes. Econometrica 1998, 66:47-78.
4. Balvers R.J., Cosimano T.F., McDonald B. Predicting stock returns in an efficient market. Journal of Financial Economics 1990, 45:1109-1128.
5. Bollerslev T. Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics 1986, 31:307-327.
6. Carlin B.P., Gelfand A.E., Smith A.F.M. Hierarchical Bayesian analysis of change point problems. Applied Statistics 1992, 41:389-405.
7. Chen C.W.S., Chan J.S.K., Gerlach R., Hsieh W. A comparison of estimators for regression models with change points. Statistics and Computing 2011, 21(3):395-414. doi:10.1007/s11222-010-9177-0.
8. Chen C.W.S., Gerlach R., Lin A.M.H. Falling and explosive, dormant and rising markets via multiple-regime financial time series models. Applied Stochastic Models in Business and Industry 2010, 26:28-49.
9. Chen, C.W.S., Gerlach, R., Lin, A.M.H. Multi-regime nonlinear capital asset pricing models. Quantitative Finance in press. doi:. http://10.1080/14697680902968013.
10. Chen C.W.S., Gerlach R., So M.K.P. Bayesian model selection for heteroskedastic models. Advances in Econometrics 2008, 23:567-594. (Special Issue on Bayesian Econometrics).
11. Chen C.W.S., Liu F.C., So M.K.P. Heavy-tailed distributed threshold stochastic volatility models in financial time series. Australian & New Zealand Journal of Statistics 2008, 50:29-51.
12. Chen C.W.S., So M.K.P. On a threshold heteroscedastic model. International Journal of Forecasting 2006, 22:73-89.
13. Chen W.S., So K.P., Gerlach R.H. Asymmetric response and interaction of US and local markets news in financial markets. Applied Stochastic Models in Business and Industry 2005, 21:273-288.
14. Chib S. Marginal likelihood from the Gibbs output. Journal of the American Statistical Association 1995, 90:1313-1321.
15. Chib S. Estimation and comparison of multiple change point models. Journal of Econometrics 1998, 86:221-241.
16. Chib S., Ergashev B. Analysis of multifactor affine yield curve models. Journal of the American Statistical Association 2009, 104:1324-1337.
17. Chib S., Greenberg E. Understanding the Metropolis-Hastings algorithm. The American Statistician 1995, 49:327-335.
18. Chib S., Jeliazkov I. Marginal likelihood from the Metropolis-Hastings output. Journal of the American Statistical Association 2001, 96:270-281.
19. Christoffersen P. Evaluating interval forecasts. International Economic Review 1998, 39:841-862.
20. Driesprong G., Jacobsen B., Maat B. Striking oil: Another puzzle?. Journal of Financial Economics 2008, 89:307-327..
21. Elliott, G., Müller, U., 2003 Optimally testing general breaking processes in linear time series models. Working Paper. Department of Economics, University of California, San Diego.
22. Engle R.F. Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflations. Econometrica 1982, 50:987-1007.
23. Engle R.F., Manganelli S. CAViaR: conditional autoregressive value at risk by regression quantiles. Journal of Business and Economic Statistic 2004, 22:367-381.
24. Fama E.F., French K.R. Dividend yields and expected stock returns. Journal of Financial Economics 1988, 22:3-25.
25. Goyal A., Welch I. Predicting the equity premium with dividend ratios. Management Science 2003, 49:639-654.
26. Gilks W.R., Richardson S., Spiegelhalter D. Markov Chain Monte Carlo in Practice: Interdisciplinary Statistics 1996, Chapman & Hall, CRC.
27. Hamilton J.D. Oil and the Macroeconomy Since World War II. Journal of Political Economy 1983, 91:228-248.
28. Hamilton, J.D., 2009. Oil prices and the economic downturn. In: Testimony Prepared for the Joint Economic Committee of the United States Congress.
29. Hansen B. Testing for structural change in conditional models. Journal of Econometrics 2000, 97:93-115.
30. Hastings W.K. Monte-Carlo sampling methods using Markov chains and their applications. Biometrika 1970, 57:97-109.
31. Jones C.M., Kaul G. Oil and the stock markets. The Journal of Finance 1996, 51:463-491.
32. Kim S., Shephard N., Chib S. Stochastic volatility: likelihood inference and comparison with ARCH models. Review of Economic Studies 1998, 65:361-393.
33. Kupiec P.H. Techniques for verifying the accuracy of risk measurement models. The Journal of Derivatives 1995, 3:73-84.
34. Lettau M., Ludvigsson S. Consumption, aggregate wealth, and expected stock returns. Journal of Finance 2001, 56:815-849.
35. Metropolis N., Rosenbluth A.W., Rosenbluth M.N., Teller A.H., Teller E. Equations of state calculations by fast computing machines. Journal of Chemical Physics 1953, 21:1087-1091.
36. Miller J.I., Ratti R.A. Crude oil and stock markets: stability, instability, and bubbles. Energy Economics 2009, 31:559-568.
37. Nelson C.R., Kim M.J. Predictable stock returns: the role of small sample bias. The Journal of Finance 1993, 48:641-661.
38. Paye B.S., Timmermann A. Instability of return prediction models. Journal of Empirical Finance 2006, 13:274-315.
39. Pesaran M.H., Pettenuzzo D., Timmermann A. Forecasting time series subject to multiple structural breaks. Review of Economic Studies 2006, 73:1057-1084.
40. Pesaran M.H., Timmermann A. Market timing and return prediction under model instability. Journal of Empirical Finance 2002, 9:495-510.
41. Sadorsky P. Oil price shocks and stock market activity. Energy Economics 1999, 2:449-469.
42. Schwert, G.W., 2003. Anomalies and market efficiency. In: Constantinides, G.M., Harris, M., Stulz, R. (Eds.), Handbook in Economic and Finance.
43. Shephard N. Partial non-Gaussian state space. Biometrika 1994, 81:115-131.
44. So M.K.P., Li W.K., Lam K. A threshold stochastic volatility model. Journal of Forecasting 2002, 21:473-500.
45. Spiegelhalter D., Best N.G., Carlin B.P., Van der Linde A. Bayesian measures of model complexity and fit (with discussion). Journal of the Royal Statistical Society B 2002, 64:583-616.
46. Stambaugh R.F. Predictive regression. Journal of Financial Economics 1999, 54:375-421.
47. Tierney L. Markov Chains for exploring posterior distributions. The Annals of Statistics 1994, 22:1701-1762.
48. Yao Y.C. Estimating the number of changepoints via Schwarz criterion. Statistics and Probability Letters 1988, 6:181-189.