Stochastic volatility in mean model for capturing the conditional variance in volatile time series data

RAVINDRA SINGH SHEKHAWAT; K N SINGH; AJAY KUMAR; KRISHNA PADA SARKAR; RIPI DONI; BISHAL GURUNG

doi:10.56093/ijas.v88i10.84258

Stochastic volatility in mean model for capturing the conditional variance in volatile time series data

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Authors

RAVINDRA SINGH SHEKHAWAT Scientist, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012
K N SINGH Principal Scientist and Head, Division of Forecasting and Agriculture Systems modelling, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012
AJAY KUMAR Research Associate, NAHEP KAB-II, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012
KRISHNA PADA SARKAR Research Scholar, ICAR-Indian Agricultural Research Institute, New Delhi 110 012
RIPI DONI Research Scholar, ICAR-Indian Agricultural Research Institute, New Delhi 110 012
BISHAL GURUNG Scientist, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012

https://doi.org/10.56093/ijas.v88i10.84258

Keywords:

Particle filter, Stochastic volatility in mean model, Time-series, Volatility

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References

Bauwens L, Hafner C M and Laurent S. 2012. Handbook of Volatility Models and their Applications. Wiley, USA. DOI: https://doi.org/10.1002/9781118272039

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Box G, Jenkins G M and Reinsel G. 2008. Time Series Analysis: Forecasting and Control, 4 edn, p 746. John Wiley & Sons, Hoboken, New Jersey. DOI: https://doi.org/10.1002/9781118619193

Deo M., Devanadhen, K. and Srinivasan, K. 2008. An empirical analysis of implied volatility in Indian options market. International Research Journal of Finance and Economics 18: 108–26.

Engle R F. 1982. Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica 50(4): 987–1007. DOI: https://doi.org/10.2307/1912773

Fan J and Yao Q. 2003. Nonlinear Time Series: Nonparametric and parametric Methods. Springer, New York.

Jordi C and Josep P. 2012 Maximum likelihood approach for several stochastic volatility models. Journal of Statistical Mechanics: Theory and Experiment 8: 8–16. DOI: https://doi.org/10.1088/1742-5468/2012/08/P08016

Koopman S J and Hol Uspensky E. 2002. The stochastic volatility in mean model: empirical evidence from international stock markets. Journal of Applied Econometrics 17: 667–89. DOI: https://doi.org/10.1002/jae.652

Taylor S J. 1994. Modelling stochastic volatility: A review and comprehensive study. Mathematical Finance 4: 183–204. DOI: https://doi.org/10.1111/j.1467-9965.1994.tb00057.x

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Submitted

2018-10-24

Published

2018-10-24

Issue

Vol. 88 No. 10 (2018)

Section

Short-Communication

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How to Cite

SHEKHAWAT, R. S., SINGH, K. N., KUMAR, A., SARKAR, K. P., DONI, R., & GURUNG, B. (2018). Stochastic volatility in mean model for capturing the conditional variance in volatile time series data. The Indian Journal of Agricultural Sciences, 88(10), 1644-1647. https://doi.org/10.56093/ijas.v88i10.84258