Theories And Applications Of Stock Index Futures Hedging Strategies

Stock index futures hedging is basic investment strategy for investment portfolios of institutional investors in the developed international financial market. It will be an important vehicle to systematic risk hedging for domestic institutional investors after new investment vehicle, stock index future, is listed in china financial market. There has been no integrated study on this field, which has theoretical and practical significance.Six chapters consist of this dissertation. Chapter One introduction includes background, literature review, research contents, research methodologies and contribution; In Chapter Two, we explained the definition of stock index futures hedging, analyzed the theories of hedging and proposed the framework on stock index futures hedging. Then we detail discussed two important issues about Beta prediction, which are stability test and time-varying estimation, and introduced those models to stock index futures hedging in Chapter Three. In Chapter Four, we conducted theoretical and empirical study on constant hedging ratio estimation models, time-varying hedging ratio estimation models and nonlinear correlation hedging ration estimation models. In Chapter Five, We created a complete operational procedure of stock index futures hedging for institutional investors and did simulate analysis based on the Chinese practice. In the end, we concluded the dissertation and discussed the limitation and further research that can be explored from results.The major contributions of this dissertation include: Above all, we completely summarized the theories and analysis framework on the stock index futures hedging strategy, clarified the logistic of stock index futures hedging strategy by analyzing the relationship of different models. Secondarily, we studied the characters of BETA, which is systematical risk sensitive index of stock market, and we conducted the empirical study on the hedging effectiveness using time-varying BETA estimation models. More importantly, this dissertation summarized the logistic relationship of risk optimal hedging ratio estimation models, completely introduced , analyzed and evaluated the formats and parameter estimation methods on different models, and especially introduced the dynamic conditional correlation multi-variate GARCH and nonlinear correlation multi-variate GARCH to risk optimal hedging ratio estimation models. In addition, we created a complete operational procedure hedging for the domestic institutional investors, simulated the whole operation using introduced models, and provided the theoretical and practical support for the coming stock index futures hedging Operation.