A New Index Tracking Model And Its Application In Future Arbitrage

Considering that in the financial market the distribution of index return rate is not normal distribution,it has the characteristics of "peak tail and thick tail".Therefore,we proposed an improved tracking model on traditional index tracking model in this paper,introducing the influencing factors of the skewness and the kurtosis.We use the sequential quadratic programming algorithm to solve the new index tracking model,taking the practical constraints such as transaction costs,short selling constraints,number of shares hold,and amount of funds into account.The empirical analysis of the tracking of Shanghai 50 shows that the improved tracking model greatly improves the fitting accuracy of the model and has smaller tracking error in the dynamic tracking of the benchmark index.Furthermore,we adopt a new clustering stock-picking method,which makes it possible to achieve better tracking effect with fewer constituent stocks within the error-controllable range.Finally,we further expands the application of the index tracking model,which substitutes the tracking portfolio of different models and methods as the benchmark assets,and studies the future-spot arbitrage strategies of stock index futures to find the risk-free arbitrage opportunities.