Dynamic Hedge Ratio Based On CVaR

From the existing research of hedging theory, most of them examine hedging from a portfolio standpoint. It is required to find the ratio between spot position and futures position under the minimal risk or maximal return, thus, how to determine hedge ratio is crucial.Under certain risk hypothesis, using CVaR to control the excess losses of hedged portfolio in extreme circumstances, some researches develop static optimal hedge ratio decision models. This article developed an optimal hedge ratio decision model based on the CVaR of hedged portfolio return as object, by controlling the tail loss of hedged portfolio under certain confidence level, and using moving window to achieving dynamic optimal hedge ratio.Firstly, CVaR was used to control the excess losses of hedged portfolio under extreme circumstances, to minimize CVaR of portfolio return and achieve optimal hedge ratio. Secondly, by using GARCH model to forecast portfolio variance and mean values, fluctuation ratio mass effect and time-varying variance effect were considered in the forecasting process; thereby the problem of dynamic hedging was solved. Lastly, in the empirical test part, sugar futures of Zhengzhou Commodity Exchange and HSI futures of Hong Kong Security Exchange were used as sample data. The result shows that, comparing VaR and Sharpe methods, this model has better performance in hedging position scope and effectiveness under certain risk-return conditions.