CVaR portfolio model based on K-means clustering with the constraint of generalized entropy

doi:10.7523/j.issn.2095-6134.2016.01.005

›› 2016, Vol. 33 ›› Issue (1): 31-36.DOI: 10.7523/j.issn.2095-6134.2016.01.005

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CVaR portfolio model based on K-means clustering with the constraint of generalized entropy

WU Wendi, CHENG Xijun, LIU Feng

School of Management, University of Science and Technology of China, Hefei 230026, China

Received:2014-12-05 Revised:2015-08-31 Online:2016-01-15

Abstract

Abstract:

The present work constructs the CVaR linear programming model of portfolio with the constraint of generalized entropy. We generate scenarios and probabilities of each asset yield in the portfolio using the K-means clustering method. Then we substitute them into the model. Finally we get the optimal investment weights for various assets. The feasibility of this model is certificated by testing a portfolio which contains eight selected stocks in Shenzhen stock market. Compared with MV model, this model not only incorporates more decentralized investment principle, but also has better performance in the future yields. This model has strong practicability.

Key words: K-means clustering method, generalized entropy, CVaR model, portfolio

CLC Number:

F830

WU Wendi, CHENG Xijun, LIU Feng. CVaR portfolio model based on K-means clustering with the constraint of generalized entropy[J]. , 2016, 33(1): 31-36.

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CVaR portfolio model based on K-means clustering with the constraint of generalized entropy

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