In high-frequency financial data not only returns, but also waiting times between consecutive trades are random variables. Therefore, it is possible to apply continuous-time random walks (CTRWs) as phenomenological models of the high-frequency price dynamics. An empirical analysis performed on the 30 DJIA stocks shows that the waiting-time survival probability for high-frequency data is non-exponential. This fact imposes constraints on agent-based models of financial markets.
E. Scalas, R. Gorenflo, H. Luckock, F. Mainardi, M. Mantelli, M. Raberto (2004). Anomalous waiting times in high-frequency financial data. QUANTITATIVE FINANCE, 4, 695-702 [10.1080/14697680500040413].
Anomalous waiting times in high-frequency financial data
MAINARDI, FRANCESCO;
2004
Abstract
In high-frequency financial data not only returns, but also waiting times between consecutive trades are random variables. Therefore, it is possible to apply continuous-time random walks (CTRWs) as phenomenological models of the high-frequency price dynamics. An empirical analysis performed on the 30 DJIA stocks shows that the waiting-time survival probability for high-frequency data is non-exponential. This fact imposes constraints on agent-based models of financial markets.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
