出版社：Canadian Research & Development Center of Sciences and Cultures
摘要：Year after year stock markets of the world kept on breaking records. They reached new heights and plunged to new depths. During financial crisis of 2008 many markets shed as many points as they never did in their history. It is extremely difficult to predict future index value due to their high randomness but is it possible to know if markets are going to achieve a record fall in near future or not. Daily changes in stock market index are not normally distributed, analysis showed they exhibit fatter tails that normal distribution, while extreme fall and rise generally follow generalized extreme value distribution explained by Extreme Value theory. The study models worst losses suffered in a day by National Stock Exchange index CNX-Nifty by fitting GEV distribution on yearly and quarterly maximum losses. GEV distribution function hence obtained is used for predicting probability of obtaining a record maximum loss next year / quarter of 2008. As Indian markets shed maximum point in a day during financial crisis of 2008, study verifies if model gives indication about such extreme event. Key words: GEV distribution; Extreme Value Theory; Record Loss; Frechet Density Function; Block Maxima
其他摘要：Year after year stock markets of the world kept on breaking records. They reached new heights and plunged to new depths. During financial crisis of 2008 many markets shed as many points as they never did in their history. It is extremely difficult to predict future index value due to their high randomness but is it possible to know if markets are going to achieve a record fall in near future or not. Daily changes in stock market index are not normally distributed, analysis showed they exhibit fatter tails that normal distribution, while extreme fall and rise generally follow generalized extreme value distribution explained by Extreme Value theory. The study models worst losses suffered in a day by National Stock Exchange index CNX-Nifty by fitting GEV distribution on yearly and quarterly maximum losses. GEV distribution function hence obtained is used for predicting probability of obtaining a record maximum loss next year / quarter of 2008. As Indian markets shed maximum point in a day during financial crisis of 2008, study verifies if model gives indication about such extreme event. Key words: GEV distribution; Extreme Value Theory; Record Loss; Frechet Density Function; Block Maxima
关键词：GEV distribution;Extreme Value Theory;Record Loss;Frechet Density Function;Block Maxima
