Arbitrage With Csi 300 Index Futures

On on April 16th 2010, the CSI 300 index futures officially listed trading in China's financial futures exchange. Since then, the domestic stock index future is trading for inaugural futurarc prize. It will become one of the most important investment tools in China's capital market. On the basis of stock index futures, investors could establish a variety of investment strategy. For risk to bear ability general and pursuit of steady benefits with large capital of institutional investors, stock index futures offer for its performance of risk arbitrage opportunities. On the background of current policy, arbitrage strategies of period now and cross period arbitrage are implemented. As the world's most important financial derivatives, stock index futures in the international market has experienced 20 advance years development course, the investors in international market are very familiar with it. For domestic investors, it is relatively unfamiliar. This paper is on the basis of the research abroad, combined with the reality of China's domestic constitution, arbitrage with CSI 300 future as a whole.This paper firstly introduces the stock index futures arbitrage, the theoretical basis and function. Then elaborated on four arbitrage strategy, and its basis domestic actual situation chose feasible period now arbitrage and cross period arbitrage as the research object in the thesis. And on this basis, they build the join of transaction costs no-arbitrage interval model and cost pricing model, based on these two models, discusses the trading strategy operation step and selling point selection basis.Arbitrage strategy metaphase is the key is to construct arbitrage target index spot combination. Constructing the spot combinations on target index of tracking the better, the period of arbitrage risk is smaller. Therefore, this article is for period arbitrage the research emphases are spot combination method of building research. The author shares and etfs fund for two of the asset pool choose spot combination, respectively by a complete copy method, market capitalization weight method, the stratified sampling method and tracking error method to calculate the minimum combination weights. According to the empirical analysis results after comparison, this paper argues that by stepwise regression method of calculating the weights of stock portfolio and the three ETF funds to build up the combination of tracking the best effect.Now after a period of arbitrage, the article studies the stock index futures arbitrage across the stage. Cross period of arbitrage specific strategies that there is a bull market arbitrage strategy, bear arbitrage strategy and disc type arbitrage strategy. Specific introduced these three strategies after operation step to Shenzhen 300 index futures contract volume of four delivery month, according to market a comparative analysis of the impact of cost minimization principle analysis, and concluded that month contract and monthly contract for a transaction object is the safest. By 2010, April 16th 2010 September 10 data as the foundation, which use base poor trading methods and matching trade method, makes a positive analysis from trading opportunities choice of sensitivity and success rate of two methods were compared and analyzed, and found two methods is special. First of all, matching trading strategy relatively poor trading strategy well-alignment with sensitive, you can seize intra-day trading opportunities. Secondly, matching trading strategy success rate is relatively poor well-alignment trading strategy success rate is higher.This paper to generalize the finally summarized, and for future research are proposed. The carry trade is the international capital market that the mainstream of stock index futures arbitrage trades after officially launched, maintaining the market efficiency will be the important strength, and can obtain risk-free profits. Expect this to policy-makers and engaging in futures arbitrage investors to provide scientific and operability reference opinions.