Research Project 8
RP8. Financial models, volatility risk, and variable annuities (Hanxue Yang)
Leading Partner: TUT. Supervisor: Prof. Juho Kanniainen
Before the recent financial crisis, change in the volatility of the equities market has typically not been hedged for variable annuities. Consequently, a sharp rise in volatility led to a dramatic increase in the cost of hedging variable annuities, and hedging against changes in volatility became necessary for successful operation with variable annuities, a topic considered in the present RP. This RP takes a closer look at the hedging performance of different stochastic volatility models, incorporating Lévy jump components in both stock price and volatility processes, and the valuation and risk management strategies will be discussed using these advanced models. This RP has clear connections with RPs 1-5 and 6, 7. Specifically, whereas RP 7 focuses on modelling and estimating volatility risk, this RP, as applied research, analyzes ways of taking the volatility risk into account in managing financial risks for variable annuities. On the computational front the researcher will collaborate with WP5 (RP 11-14).
DELIBERABLE 3.5 on project 8 (H. Yang, TUT): "Option Pricing Performance of Different Option Pricing Models"
- Cover letter [download]
- Kanniainen, J., B. Lin and H. Yang (2014), "Estimating and Using GARCH Models with VIX Data for Option Valuation", Journal of Banking and Finance, 43, 200-211 [link]
- Yang, H. and J. Kanniainen (2015), "Jump and Volatility Dynamics for the S&P500: Evidence for Infinite-Activity Jumps with Non-Affine Volatility Dynamics from Stock and Option Markets", SSRN working paper, to appear in Review of Finance [link]
- Yang, H., PhD Thesis (2015-11-13): Markov Chain Monte Carlo Estimation of Stochastic Volatility Models with Infinite Activity Lévy Jumps. Evidence for Efficient Models and Algorithms
- Yang, H. and J. Kanniainen (2016), "Jump and Volatility Dynamics for the S&P500: Evidence for Infinite-Activity Jumps with Non-Affine Volatility Dynamics from Stock and Option Markets", forthcoming in the Review of Finance.
- Martino, L., H. Yang, D. Luengo, J. Kanniainen, J. Corander (2015), "A Fast Universal Self-tuned Sampler within Gibbs sampling", Digital Signal Processing, 47, 68-83.
- Kanniainen, J., Lin, B. & Yang, H. (2014), "Estimating and using GARCH models with VIX data for option valuation", Journal of Banking and Finance, Vol. 43, pp. 200-211. [download]
Hanxue Yang (Tampere University of Technology): Financial models, volatility risk, and Bayesian algorithms