Detecting market crashes by analysing long-memory effects using high-frequency data

作者：Barany E^*; Varela M P Beccar; Florescu I; Sengupta I

来源：Quantitative Finance, 2012, 12(4): 623-634.

DOI：10.1080/14697688.2012.664937

• Long memory effects
• Data sampled with high frequency
• Levy processes
• Hurst parameter
• Detrended fluctuation analysis
• Truncated Levy flight

It is well known that returns for financial data sampled with high frequency exhibit memory effects, in contrast to the behavior of the much celebrated log-normal model. Herein, we analyse minute data for several stocks over a seven-day period which we know is relevant for market crash behavior in the US market, March 10-18, 2008. We look at the relationship between the Levy parameter alpha characterizing the data and the resulting H parameter characterizing the self-similar property. We give an estimate of how close this model is to a self-similar model.

• 出版日期2012