2004/10/29 by R. Bartiromo, Bartiromo, Rosario
Computer Science · Decision Sciences · Economics, Econometrics and Finance · #Complex Systems and Time Series Analysis #FOS: Economics and business #FOS: Physical sciences #Other Condensed Matter (cond-mat.other) #Statistical Finance (q-fin.ST) #Stock Market Forecasting Methods #Time Series Analysis and Forecasting
paper · pdf · doi:10.48550/arxiv.cond-mat/0410768
openalex publication_date 2004/10/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We exploit a continuous time random walk description of stock prices to obtain a fast and accurate evaluation of their volatility from intraday data. We show that financial markets are usefully described as open physical systems. Indeed we find that the process determining market volatility is not stationary while the market response to external volatility shocks stays constant over the time period of more than two years covered by our experimental data. Furthermore the autocorrelation function of volatility increments yields a value of about -0.4 at one-day time lag that is nearly equal for all stocks we analyze. Conditioning the evaluation of the autocorrelation function, we show that the market response is non-linear and strongly stabilizing when external shocks push for higher volatility. This market behavior can be explained by the action of participants with different time horizon.