Predicting the Risk of Bankruptcy for ARO Stock

Abstract In the last several decades, many researchers have been focused on finding effective experimental methods to predict stocks with tendency of bankrupt. Recent financial crisis has caused extensive world-wide economic damages, predicting bankruptcy before it happens could help investors avoid large losses. In this article, by observing the market dynamics of its stock price and trading volume, we estimate the risk of bankruptcy of Aeropostale (ARO). GARCH and EGARCH series models with normal distribution and t-student distribution are used to estimate the volatilities and value-at-risk (VaR) of ARO stock. By analyzing the VaR, we conclude that there is a high probability that the company will be facing bankruptcy in the near future. Moreover, our study shows that the asymmetric EGARCH model with t-student distribution eventually is a better choice to predict the behavior of this stock.

Keywords— Asymmetric EGARCH model, GARCH model, normal distribution and t-student distribution, volatilities, Value-at-Risks.

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