Density Function Estimation Based on SVM: An Application in Estimating Liquidity Risk in Stock Market

Author

Yang, Yiwen ; Zhang, Chenxi

Author_Institution

Sch. of Manage., Northwestern Polytech. Univ., Xi´´an, China

fYear

2009

fDate

11-13 Dec. 2009

Firstpage

1

Lastpage

5

Abstract

This paper presents a method to compute liquidity risk of stock market with model of VaR. Firstly, a measure for liquidity is defined, which reflects the volatility of return caused by unite ratio of the position to be liquidated to the tradable shares. Secondly, the density function of the measure for liquidity is estimated with support vector machine, with which the liquidity VaR of stocks is calculated. Finally, some stocks of Shanghai and Shenzhen stock markets are chosen, according to their tradable shares, to compute liquidity VaR. The results show that the liquidity VaR is bigger than the traditional VaR that is calculated without considering liquidity, which means the latter does underestimate the risk.

Keywords

risk management; stock markets; support vector machines; VaR model; density function estimation; liquidity measure; liquidity risk; stock market; support vector machine; tradable shares; value-at-risk; volatility of return; Density functional theory; Position measurement; Probability density function; Random variables; Reactive power; Risk management; Statistical learning; Statistics; Stock markets; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-4507-3

Electronic_ISBN

978-1-4244-4507-3

Type

conf

DOI

10.1109/CISE.2009.5362895

Filename

5362895