Investment Tracking Based On Second-order Cone Optimization

Investment tracking means tracking an investment target,i.e.,analyzing the spe-cific investment direction and the fund allocation situation of the investment target,in order to build a portfolio to replicate the market performance of this investment target.For large institutional investors(such as public funds),their investment is more stable,and each investment is a result of carefully study.Many small companies do not have the enough human and material resources to conduct detailed research.They hope that they can analyze the investment status of public funds to provide reference for their own investment.This thesis tries to track the weights(in stock sectors)in the investment portfolio of an open fund company.The model is based on maximizing the Pearson correlation coefficient.The resulting optimization problem is further reformulated as a second-order cone optimization problem,which is theoretically guaranteed and can be solved very efficiently.Preliminary numerical results as well as possible improvements are also discussed.