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Application of Genetic Algorithm to Index Tracking

Author: ChenYuSi
Tutor: LiShengHong
School: Zhejiang University
Course: Operational Research and Cybernetics
Keywords: Index Replication Genetic Algorithms Stock index futures Of arbitrage CSI 300
CLC: F224
Type: Master's thesis
Year: 2009
Downloads: 54
Quote: 0
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Abstract


To compensate for a lack of market instruments to avoid systemic risk to the investor status and adding new investment products, China is about to launch CSI 300 stock index futures . Since launch, is likely to lead to market overreaction , A-share market volatility short-term enhancement, there is a lot of arbitrage opportunities. Of arbitrage in to win a place , it must have an excellent index replication method . This article first overview of the basics of the stock index futures to introduce the definition of the background and three functions , and its pricing and arbitrage boundary analysis ; Then simply review the index replication methods , and details three typical replication methods : power re- collocation method , power re- optimize the allocation method and sector weighting configuration method ; then enter the article focus on the genetic algorithm is applied to try to track the CSI 300 Index , introduced algorithm, and then construct the model implemented in software ; Last day of trading data even with high frequency data, empirical research, get a series Conclusion: ① whether used to build 20, 40 or 60 stock portfolio , using genetic algorithms to simulate the portfolio of stocks of the CSI 300 Index correlation coefficient is very high, the effect is also very good - sample track ; with the increase in the number of shares to build a combination of genetic algorithm tracking effect will be more robust. ② replicate the index, genetic algorithm is the preferred method of tracking effect has obvious advantages, and Optimizing Weights and industry weighted combination collocation method in building a larger number of stocks to track with good results, this article describes several methods of secondary selection. ③ In the case where data were sufficient to ensure , considering the objective function of the genetic algorithm for time-weighting the tracking effect , than the objective function does not consider the time-weighting . ④ genetic algorithm uses five minutes transaction data is still applicable. Short-term arbitrage , the use of high frequency data transactions can solve the problem of lack of data . Genetic Algorithms to practice arbitrage index replication link provides a powerful tool , based on the experimental results together with the subjective forecast for the next phase , arbitrage will greatly enhance the likelihood of success .

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CLC: > Economic > Economic planning and management > Economic calculation, economic and mathematical methods > Economic and mathematical methods
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