What distinguishes individual stocks from the index?
comunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/8643
comunitat-uji-handle3:10234/8644
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http://dx.doi.org/10.1140/epjb/e2009-00358-1 |
Metadata
Title
What distinguishes individual stocks from the index?Date
2010Publisher
Springer-VerlagISSN
1434-6028Bibliographic citation
The European Physical Journal B ( 2010), 73, 1, p 23-28Type
info:eu-repo/semantics/articlePublisher version
http://link.springer.com/article/10.1140/epjb/e2009-00358-1Subject
Abstract
Stochastic volatility models decompose the time series of financial returns into the product of a volatility factor and an iid noise factor. Assuming a slow dynamic for the volatility factor, we show via nonparametric ... [+]
Stochastic volatility models decompose the time series of financial returns into the product of a volatility factor and an iid noise factor. Assuming a slow dynamic for the volatility factor, we show via nonparametric tests that both the index as well as its individual stocks share a common volatility factor. While the noise component is Gaussian for the index, individual stock returns turn out to require a leptokurtic noise. Thus we propose a two-component model for stocks, given by the sum of Gaussian noise, which reflects market-wide fluctuations, and Laplacian noise, which incorporates firm-specific factors such as firm profitability or growth performance, both of which are known to be Laplacian distributed. In the case of purely Gaussian noise, the chi-squared probability for the density of individual stock returns is typically on the order of 10-20, while it increases to values of O(1) by adding the Laplace component. [-]
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(c) EDP Sciences, Società Italiana di Fisica, Springer-Verlag 2009
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- ECO_Articles [697]