Anomalous waiting times in high-frequency financial data

Enrico Scalas; Rudolf Gorenflo; Hugh Luckock; Francesco Mainardi; Maurizio Mantelli; Marco Raberto

doi:10.1080/14697680500040413

Anomalous waiting times in high-frequency financial data

Enrico Scalas
, Rudolf Gorenflo
, Hugh Luckock
, Francesco Mainardi
, Maurizio Mantelli
, Marco Raberto

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Pages (from-to)	695-702
Number of pages	8
Journal	Quantitative Finance
Volume	4
Issue number	6
DOIs	https://doi.org/10.1080/14697680500040413
Publication status	Published - Dec 2004
Externally published	Yes

Access to Document

10.1080/14697680500040413

Cite this

@article{f26b36222fdf4aa793ea82161d3ce0b1,

title = "Anomalous waiting times in high-frequency financial data",

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.",

author = "Enrico Scalas and Rudolf Gorenflo and Hugh Luckock and Francesco Mainardi and Maurizio Mantelli and Marco Raberto",

note = "Funding Information: We would like to acknowledge useful discussions with Sergio Focardi of The Intertek Group. This work was supported by grants from the Italian MIUR Project COFIN 2003 {\textquoteleft}Order and Chaos in nonlinear extended systems: coherent structures, weak stochasticity and anomalous transport{\textquoteright} and by the Italian MIUR FISR Project {\textquoteleft}Ultra-high frequency dynamics of financial markets{\textquoteright}.",

year = "2004",

month = dec,

doi = "10.1080/14697680500040413",

language = "English",

volume = "4",

pages = "695--702",

journal = "Quantitative Finance",

issn = "1469-7688",

publisher = "Taylor and Francis Ltd.",

number = "6",

}

TY - JOUR

T1 - Anomalous waiting times in high-frequency financial data

AU - Scalas, Enrico

AU - Gorenflo, Rudolf

AU - Luckock, Hugh

AU - Mainardi, Francesco

AU - Mantelli, Maurizio

AU - Raberto, Marco

N1 - Funding Information: We would like to acknowledge useful discussions with Sergio Focardi of The Intertek Group. This work was supported by grants from the Italian MIUR Project COFIN 2003 ‘Order and Chaos in nonlinear extended systems: coherent structures, weak stochasticity and anomalous transport’ and by the Italian MIUR FISR Project ‘Ultra-high frequency dynamics of financial markets’.

PY - 2004/12

Y1 - 2004/12

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/18544373378

U2 - 10.1080/14697680500040413

DO - 10.1080/14697680500040413

M3 - Article

SN - 1469-7688

VL - 4

SP - 695

EP - 702

JO - Quantitative Finance

JF - Quantitative Finance

IS - 6

ER -

Anomalous waiting times in high-frequency financial data

Abstract

Access to Document

Other files and links

Fingerprint

Cite this