The Measures And Application Of Volatility Based On High Frequency Data

Volatility,as an index for description of uncertainty of the asset prices and quantification of the market risk,has a high level of importance in most aspects of finance,such as derivatives,valuation and portfolio risk management.The study of volatility is the starting point of understanding the assets uncertainty;it helps the participants to broaden the knowledge of the risks and raise the risk management ability,enhances the supervision from the administration departments and assures the healthy development of the holistic financial market.Therefore,the research of volatility has never stopped ever since the establishment of the historical volatility model and has long been a hot topic along with the development of the volatility theory.This paper focuses on the volatility of the underlying from Shanghai 50ETF options,and analyzes the statistical characteristics of Realized Volatility(RV),Realized Range-based Volatility(RRV),Realized Bipower Variation(RBV)and their extend forms.The results suggest that the RBV is the most efficient volatility estimator for Shanghai 50ETF in fully consideration of the various microstructure noises.Further analysis is conducted to measure the relations between the prices of the underlying assets or options and the implied volatility of 28 options expired in September which is estimated from the Black-Scholes model,weighted by the volume of options.The strategy for trading volatility is set up according to the communication between implied volatility and RBV,realizing the application of volatility.Both in-sample and out-of-sample tests confirm that the strategy is effective to send long and short signals and guarantee investment returns.