Statistical inference of co-movements of stocks during a financial crisis
AbstractIn order to figure out and to forecast the emergence phenomena of social systems, we propose several probabilistic models for the analysis of financial markets, especially around a crisis. We first attempt to visualize the collective behaviour of markets during a financial crisis through cross-correlations between typical Japanese daily stocks by making use of multi- dimensional scaling. We find that all the two-dimensional points (stocks) shrink into a single small region when a economic crisis takes place. By using the properties of cross-correlations in financial markets especially during a crisis, we next propose a theoretical framework to predict several time-series simultaneously. Our model system is basically described by a variant of the multi-layered Ising model with random fields as non-stationary time series. Hyper-parameters appearing in the probabilistic model are estimated by means of minimizing the 'cumulative error' in the past market history. The justification and validity of our approaches are numerically examined for several empirical data sets.
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Bibliographic InfoPaper provided by arXiv.org in its series Papers with number 1309.1871.
Date of creation: Sep 2013
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Web page: http://arxiv.org/
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-09-26 (All new papers)
- NEP-ETS-2013-09-26 (Econometric Time Series)
- NEP-FMK-2013-09-26 (Financial Markets)
- NEP-FOR-2013-09-26 (Forecasting)
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- H. Dewachter & R. Houssa & P.R. Kaltwasser, 2011. "Introduction," Review of Business and Economic Literature, Intersentia, vol. 56(4), pages 378-382, December.
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