Dynamic Long Memory High Frequency Multipower Variation Volatility Evaluations for S&P500

Abstract

This study explores the multipower variation integrated volatility estimates using high frequency data in financial stock market. The different combinations of multipower variation estimators are robust to drastic financial jumps and market microstructure noise. In order to examine the informationally market efficiency, we proposed a rolling window estimate procedures of Hurst parameter using the modified rescale-range approach. In order to test the robustness of the method, we have selected the S&P500 as the empirical data. The empirical study found that the long memory cascading volatility is fluctuating across the studied period and drastically trim down after the subprime mortgage crisis. This time-varying long memory analysis allow us to understand the informationally market efficiency before and after the subprime mortgage crisis in U.S.

A empirical study on annuity pricing with minimum guarantees

“…In the future work, we intend to study the impact of stochastic interest rate and stochastic mortality rates on annuity pricing with minimum guarantees. Other volatility models such as [34], [35], [36] and [37] can also be considered in the pricing framework.…”

A study of impact of stochastic volatility on variable annuity pricing

“…This study suggests the use of stochastic volatility in the estimation of M&E fee of these guaranteed minimum benefits to reflect the realistic financial market. Future work can include different volatility models such as a time series model mentioned by [25] and [26]. Also, we can consider incorporating the stochastic interest rate for the evaluation of M&E fee ( [27] and [28]).…”