A random coefficient autoregressive Markov regime switching model for dynamic futures hedging

Journal of Futures Markets

Volumn 26, Issue 2, 2006, Pages 103-129

  Lee, Hsiang Tai ^b   Yoder, Jonathan K ^a   Mittelhammer, Ron C ^a   McCluskey, Jill J ^a  

^a WASHINGTON STATE UNIVERSITY   (United States)

^b NATIONAL CHI NAN UNIVERSITY   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 33645309922     PISSN: 02707314     EISSN: 10969934     Source Type: Journal    
DOI: 10.1002/fut.20193     Document Type: Review

References (31)

1. Alizadeh, A., & Nomikos, N. (2004). A Markov regime switching approach for hedging stock indices. The Journal of Futures Markets, 24, 649-674.
2. Baillie, R. T., & Myers, R. J. (1991). Bivariate GARCH estimation of the optimal commodity futures hedge. Journal of Applied Econometrics, 6, 109-124.
3. Bera, A. K., Garcia, P., & Roh, J. S. (1997). Estimation of time-varying hedge ratios for corn and soybean: BGARCH and random coefficient approaches. The Indian Journal of Statistics, 59, 346-368.
4. Bollerslev, T. (1986). Generalized autoregressive conditional heteroscedasticity. Journal of Econometric, 31, 307-327.
5. Bollerslev, T. (1990). Modelling the coherence in short-run nominal exchange rates: A multivariate generalized ARCH model. Review of Economics and Statistics, 72, 498-505.
6. Brooks, C. (1997). Linear and non-linear (non-) forecastability of high-frequency exchange rates. Journal of Forecasting, 16, 125-145.
7. Byström, H. N. E. (2003). The hedging performance of electricity futures on the Nordic Power Exchange. Applied Economics, 35, 1-11.
8. Chen, S. S., Lee, C. F., & Shrestha, K. (2003). Futures hedge ratios: A review. The Quarterly Review of Economics and Finance, 43, 433-465.
9. Dacco, R., & Satchell, S. (1999). Why do regime-switching models forecast so badly? Journal of Forecasting, 18, 1-16.
10. Ederington, L. H. (1979). The hedging performance of the new futures markets. The Journal of Finance, 34, 157-170.
11. Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of U.K. inflation. Econometrica, 50, 987-1007.
12. Engle, R. F., & Kroner, K. F. (1995). Multivariate simultaneous generalized ARCH. Econometric Theory, 11, 122-150.
13. Figlewki, S. (1984). Hedging performance and basis risk in stock index futures. The Journal of Finance, 39, 657-669.
14. Gagnon, L., & Lypny, G. (1995). Hedging short-term interest risk under time-varying distribution. The Journal of Futures Markets, 15, 767-783.
15. Hamilton, J. D. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle. Econometrica, 57, 357-384.
16. Hamilton, J. D. (1994). Time series analysis. Princeton, NJ: Princeton University Press.
17. Kavussanos, M. G., & Nomikos, N. K. (2000). Hedging in the freight futures market. Journal of Derivatives, 8, 41-58.
18. Kim, C. J. (1993a). Unobserved-component time-series models with Markov-switching heteroscedasticity: Changes in regime and the link between inflation rates and inflation uncertainty. Journal of Business and Economic Statistics, 11, 341-349.
19. Kim, C. J. (1993b). Source of monetary growth uncertainty and economic activity: The time-varying-parameter model with heteroskedastic disturbances. The Review of Economics and Statistics, 75, 483-492.
20. Kim, C. J. (1994). Dynamic linear models with Markov-switching. Journal of Econometrics, 60, 1-22.
21. Kim, C. J., & Nelson, C. R. (1999). State-space models with regime switching: Classical and Gibbs-sampling approaches with applications. Cambridge, MA: MIT Press.
22. Kroner, K. F., & Sultan, J. (1993). Time-varying distribution and dynamic hedging with foreign currency futures. Journal of Financial and Quantitative Analysis, 28, 535-551.
23. Lafuente, J., & Novales, A. (2003). Optimal hedging under departures from the cost-of-carry valuation: Evidence from the Spanish stock index futures market. Journal of Banking and Finance, 27, 1053-1078.
24. Lien, D., Tse, Y. K., & Tsui, A. (2002). Evaluating the hedging performance of the constant-correlation GARCH model. Applied Financial Economics, 12, 791-798.
25. Miffre, J. (2004). Conditional OLS minimum variance hedge ratios. The Journal of Futures Markets, 24, 945-964.
26. Myers, R. J. (1991). Estimating time-varying optimal hedge ratios on futures markets. The Journal of Futures Markets, 11, 39-53.
27. Myers, R. J., & Thompson, S. R. (1989). Generalized optimal hedge ratio estimation. American Journal of Agricultural Economics, 71, 858-868.
28. Park, T. H., & Switzer, L. N. (1995). Bivariate GARCH estimation of the optimal hedge ratios for stock index futures: A note. The Journal of Futures Markets, 15, 61-67.
29. Politis, D., & Romano, J. P. (1994). The stationary bootstrap. Journal of the American Statistical Association, 89, 1303-1313.
30. Sullivan, R., Timmermann, A., & White, H. (1999). Data-snooping, technical trading rule performance, and the bootstrap. Journal of Finance, 54, 1647-1692.
31. White, H. (2000). A reality check for data snooping. Econometrica, 68, 1097-1126.