| The development of stock index futures market can help improving the trading structure of acountry’s capital markets, and building a more healthy and comprehensive multi-level financialmarket system. Thus it can promote the development of economic healthy and safe. With thereform and innovation of China’s financial market, China’s stock index futures market has entered arapid development period. It become the focus that regulators and investors concerned aboutmarket efficiency and the function which the market should perform in the operation of the market.According to the actual operation and the characteristics of China’s stock index futures market, thispaper built an objectively efficiency evaluation system of stock index futures market that based onreasonable economic theory and scientific quantitative methods and makes a fully measurement ofmarket efficiency, also found the factors affecting the market efficiency. It can service perfect forour country economy development.The main contents are as follows:In Chapter1, this paper introduced the theory of evaluating market efficiency, and alsoreviewed the relevant research home and abroad.In Chapter2, this paper Introduced China’s stock index futures development process, thecharacteristics of contract, operating characteristics, and built an efficiency evaluation system.First,it reviewed the development process of China’s stock index futures market, and Carding the Chinaconcept stock index futures contracts have been already existing countries in financial markets, andcompared with CSI300index futures by focusing on the contracts design of each clause. It foundthat the design of CSI300index futures contracts was relatively scientific and reasonable in manyChina concept stock index futures. It gave consideration to both the construction demand of capitalmarket and new varieties starting safe and smoothly. But at the same time, along with theenlargement of the market scale and the demand for investment, the more conservative the terms ofthe contracts strictly designed couldn’t attract more investors to participate in the market. To acertain extent, it reduced the market liveness and restricted the effective function of the market.Subsequently, we analyzed the operating characteristics of CSI300index futures market, and foundthe market run smoothly after its listing. There weren’t obvious risk events occurred. Finally, basedon existing research and market efficiency evaluation theory, we built an efficiency evaluationsystem of China’s stock index futures market from four aspects: Information efficiency, operationalefficiency, price discovery efficiency and hedging efficiency as a target for further research andguidance. Information Efficiency of Chapter3introduced is the foundation of the stock index futuresmarket efficiency study. First，we divided the trading data to four uniform sub-sample periods afterthe listing of CSI300index futures market. Based on the random walk process of the EfficientMarket Hypothesis theoretical, we used auto-correlation test, runs test and variance ratio test tomake a comparative research on the information efficiency in daily trading and five-minutes highfrequency trading in China’s stock index futures market. The results showed that With thecontinuous development of China’s stock index futures market, the high and low frequenciesmarket information efficiency don’t change significantly, and there were some differences in them.The daily yield data showed the market can meet the weak-form efficient market characteristics inevery stages in the development of the stock index futures market. Five minutes yield data showedthe market can not meet the market the weak-form efficient market characteristics in the four stages,the information efficiency of the market was also not upgrade with the development of the market.Subsequently, based on Fractal Market Hypothesis, we used ADF-KPSS test, Autocorrelation testand R/S test method to test the long memory of returns and volatility in the full range sample ofCSI300index futures on the daily data and five minutes high frequency data. The empiricalresults showed that: return and volatility on daily data don’t exist significant long memory, and itmeant China’s stock index futures market on daily data is an efficient information market, whilevolatility on five-minute data has significant long memory. The existing of long memory meanthistory information of the stock index futures market can affect the change of current price, andalso showed that the information efficiency of China’s stock index futures market need to beupgrade.In Chapter4, based on financial market microstructure theory, we studied on the operatingefficiency of the stock index futures market from the market transaction costs and market liquidity.First, we analyzed the transaction costs of China’s index futures market and discussed the systemcan optimized the cost of the stock index futures. Secondly, according to behavioral finance theory,we divided the sub-sample periods by the different stages of price changes, and used the methodthat combined of volume and price to study China’s stock index futures market liquidity.Theresults showed that with the development of the market, CSI300index futures trading volume andpositions have significantly improved, the market size has been significantly expanded. The firstyear after stock index futures listed, trading frequency in different stages of price fluctuations werehigher than the frequency of the corresponding stage of the transaction in the subsequent threeyears. The rising stage had the highest frequency trading and deepest market depth in everysub-sample period. It can explained the statistical results by investors structure and behavior.Further more, we used a price impact model to study the liquidity of the stock index futures market,which considering transaction costs constructed by Brennan and Subrahmanyan model based ontrading volume and transaction price. The empirical results showed that: with the development of market, the impact on the liquidity of the market by fixed costs and variable transaction costs showa low to high and then gradually reduce trend. But the change path was not same. In the fourthyear, the liquidity was highest, and market efficiency also was highest. In addition, liquidity ofdifferent stages of price volatility had asymmetry, in which market efficiency in rising stages werehighest, and market efficiency also were highest.Chapter5mainly studied on the efficiency of price discovery of China’s stock index futuresmarket. First, it introduced the connotation of price discovery function in futures markets,generalized the definition and causes of price discovery in futures market. It also gave the pricecharacteristics discovered by futures of the conditions could realize price discovery function infutures markets. Subsequently, we applied Granger causality test, Chan model, GS model andvector error correction model to play a qualitative analysis on the price discovery efficiency inChina’s stock index futures market. We found CSI300index futures have a causal relationship withCSI300index in the four years after listing, and the price changes could guide each other andhad long-term equilibrium relationships. It showed that China’s stock index futures have afunction of price discovery in different stages of market development. Meanwhile, empiricalstudies showed that stock index futures market is at a relative disadvantage compared to stockindex in the first three years after stock index futures listing.In the fourth year, futures marketbegan to dominate the price discovery,and the function showed a process of change from weak tostrong. After that, we used correction information share model and factor share model to measurethe contribution of CSI300index futures in price discovery. We assessed price discovery efficiencyof China’s stock index futures market from the perspective of energy and found that thecontribution of price discovery by stock index futures also show an process from little to big. Untilthe fourth year, the contribution of price discovery by stock index futures was more than thecontribution of price discovery by CSI300index.In Chapter6, we made a study on the most important goals of the stock index futures market-hedging efficiency. After reviewed the theories about hedging,we used HUATAI BAIRUI CSI300ETF as the research object, and used the static hedging ratio estimation model (OLS, B-VAR,VECM) and the dynamic hedging ratio estimation model (VECM-BGARCH, DBEKK-GARCH,DCC-GARCH) to estimate the optimal hedging ratio based on actual transaction data of CSI300stock index futures. Then we cotrasted the effect of risk aversion by these model. The empiricalresults showed that: both in the sample and out-sample period, the hedging efficiency by using CSI300index futures was high for each model. DBEKK-GARCH model had advantage of existinghedging ratio estimation models and could be able to hedge stock risk by greatest degree. But inpractical applications, the hedge ratio of the model is dynamic that may cause transfer positionshigh cost. Therefore, OLS model could also be applied to practice, so that the CSI300indexfutures could play the role of risk aversion. Finally, We used DBEKK-GARCH model to test theeffect of hedging by CSI300index futures for stock and equity portfolio in SME board and board,and found that hedging efficiency is not ideal.Furthermore, we lead the corresponding virtual indexfutures into hedging and tested the effect of hedging, and we found the level of hedging risk have been significantly improved. Therefore, in order to effectively function in hedging by stock indexfutures market for spot market and improved the hedging efficiency,we need to enrich the stockindex futures to provide a variety of risk management tools for the market.
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