6533b7d9fe1ef96bd126d647

RESEARCH PRODUCT

Modeling the Dynamics of a Financial Index after a Crash

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Supply and demand are perhaps the most fundamental concepts in economics. In a financial market they reflects the orders of the agents to buy or sell a given asset. In turn the fluctuations of supply and demand influence the dynamics of the price of an asset, as, for example, a stock or a financial index. Therefore the dynamics of the price of an asset is affected by the actions and of the beliefs of the agents. It is known that the dynamics of the price of an asset is far from simple, Several stylized facts has been empirically discovered such as, for example, the fat tails in the return distribution and the clustered volatility. These stylized facts has been detected by considering long time series of returns and by computing statistical quantities, such as probability density function and correlation coefficient, over these long period of time. As a matter of fact this implies that one considers the time series as stationary in these statistical analyses. It is well known that basic financial indicators, such as for example the volatility, display non-stationary patterns [1]. Statistical tests on the volatility fluctuation strongly reject the hypothesis of constant volatility [2]. It is therefore worth investigating the presence of stylized facts in financial markets which specifically refer to non-stationary periods. In this paper we report a recently discovered statistical regularity found in the empirical analysis of the dynamics of the time series of a financial index just after a major financial crash [3].