Get Anatomy of Global Stock Market Crashes: An Empirical PDF

By Gagari Chakrabarti, Chitrakalpa Sen

ISBN-10: 813220462X

ISBN-13: 9788132204626

This paintings is an exploration of the worldwide industry dynamics, their intrinsic natures, universal traits and dynamic interlinkages through the inventory marketplace crises during the last twelve years. The learn isolates varied stages of predicament and differentiates among any difficulty that is still constrained to the area and people who soak up a world measurement. The latent constitution of the worldwide inventory industry, the inter-regional and intra-regional inventory industry dynamics round the crises are analyzed to get an entire photograph of the constitution of the worldwide inventory marketplace. The learn extra probing into the inherent nature of the worldwide inventory marketplace in producing quandary reveals the worldwide industry to be chaotic hence making the process intrinsically risky or at most sensible to stick with knife-edge balance. The findings have major bearing at theoretical point and on coverage decisions.

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Extra info for Anatomy of Global Stock Market Crashes: An Empirical Analysis

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Over the first phase of study, the US markets were not characterized by any leadlag relationship among them. However, there has been some lead-lag relationship among the European and the US markets. During the second phase, the European and the American regions have been mostly characterized by an absence of strong lead-lag relationship. The presence of intra-regional association, however, has been stronger in the Asian region. However, the markets, even if they belong to the same group, can individually explain only a small portion of the other markets’ return variance.

Wik Xk ð3:2Þ where, Ai1 is the standardized multiple regression coefficient of variable i on factor j; Vi is the standardized regression coefficient of variable i on unique factor i; m is the number of common factors; Wi’s are the factor scores and k is the number of variables. The unique factors are uncorrelated with each other and with common factors. The appropriateness of using EFA on a data set could be judged by Bartlett’s test of sphericity and the Kaiser-Meyar-Olkin (KMO) measure. The Bartlett’s test of sphericity tests the null of population correlation matrix to be an identity matrix.

Hong Kong could explain 8% of the Chinese market variability. However, in these cases, a large portion of variability in each of these markets remains unexplained by the variability in the region. 12 shows the percentage of variance of any American market return that could be explained by the other markets within the same construct. As is evident from the results, percentage of return variance of any market can hardly be explained uniquely by the other markets within the same construct. 12 could reveal some interesting result.

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Anatomy of Global Stock Market Crashes: An Empirical Analysis by Gagari Chakrabarti, Chitrakalpa Sen


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