Burst and inter-burst duration statistics as empirical test of long-range memory in the financial markets. Gontis, V. & Kononovicius, A. Physica A: Statistical Mechanics and its Applications, 2017. Paper doi abstract bibtex © 2017 Elsevier B.V. We address the problem of long-range memory in the financial markets. There are two conceptually different ways to reproduce power-law decay of auto-correlation function: using fractional Brownian motion as well as non-linear stochastic differential equations. In this contribution we address this problem by analyzing empirical return and trading activity time series from the Forex. From the empirical time series we obtain probability density functions of burst and inter-burst duration. Our analysis reveals that the power-law exponents of the obtained probability density functions are close to 3/2, which is a characteristic feature of the one-dimensional stochastic processes. This is in a good agreement with earlier proposed model of absolute return based on the non-linear stochastic differential equations derived from the agent-based herding model.
@article{
title = {Burst and inter-burst duration statistics as empirical test of long-range memory in the financial markets},
type = {article},
year = {2017},
keywords = {Financial markets,First passage times,Long-range memory,Scaling behavior,Trading activity,Volatility},
volume = {483},
id = {f5fc6456-216e-3b08-b03d-4210309f641b},
created = {2018-05-20T11:03:56.664Z},
file_attached = {true},
profile_id = {425903fc-29e3-3e93-b0fe-e189888ff33a},
last_modified = {2021-11-07T17:42:48.743Z},
read = {false},
starred = {false},
authored = {true},
confirmed = {false},
hidden = {false},
citation_key = {Gontis2017},
private_publication = {false},
abstract = {© 2017 Elsevier B.V. We address the problem of long-range memory in the financial markets. There are two conceptually different ways to reproduce power-law decay of auto-correlation function: using fractional Brownian motion as well as non-linear stochastic differential equations. In this contribution we address this problem by analyzing empirical return and trading activity time series from the Forex. From the empirical time series we obtain probability density functions of burst and inter-burst duration. Our analysis reveals that the power-law exponents of the obtained probability density functions are close to 3/2, which is a characteristic feature of the one-dimensional stochastic processes. This is in a good agreement with earlier proposed model of absolute return based on the non-linear stochastic differential equations derived from the agent-based herding model.},
bibtype = {article},
author = {Gontis, V. and Kononovicius, A.},
doi = {10.1016/j.physa.2017.04.163},
journal = {Physica A: Statistical Mechanics and its Applications}
}
Downloads: 0
{"_id":"ssWSkfpnmAYmDp358","bibbaseid":"gontis-kononovicius-burstandinterburstdurationstatisticsasempiricaltestoflongrangememoryinthefinancialmarkets-2017","author_short":["Gontis, V.","Kononovicius, A."],"bibdata":{"title":"Burst and inter-burst duration statistics as empirical test of long-range memory in the financial markets","type":"article","year":"2017","keywords":"Financial markets,First passage times,Long-range memory,Scaling behavior,Trading activity,Volatility","volume":"483","id":"f5fc6456-216e-3b08-b03d-4210309f641b","created":"2018-05-20T11:03:56.664Z","file_attached":"true","profile_id":"425903fc-29e3-3e93-b0fe-e189888ff33a","last_modified":"2021-11-07T17:42:48.743Z","read":false,"starred":false,"authored":"true","confirmed":false,"hidden":false,"citation_key":"Gontis2017","private_publication":false,"abstract":"© 2017 Elsevier B.V. We address the problem of long-range memory in the financial markets. There are two conceptually different ways to reproduce power-law decay of auto-correlation function: using fractional Brownian motion as well as non-linear stochastic differential equations. In this contribution we address this problem by analyzing empirical return and trading activity time series from the Forex. From the empirical time series we obtain probability density functions of burst and inter-burst duration. Our analysis reveals that the power-law exponents of the obtained probability density functions are close to 3/2, which is a characteristic feature of the one-dimensional stochastic processes. This is in a good agreement with earlier proposed model of absolute return based on the non-linear stochastic differential equations derived from the agent-based herding model.","bibtype":"article","author":"Gontis, V. and Kononovicius, A.","doi":"10.1016/j.physa.2017.04.163","journal":"Physica A: Statistical Mechanics and its Applications","bibtex":"@article{\n title = {Burst and inter-burst duration statistics as empirical test of long-range memory in the financial markets},\n type = {article},\n year = {2017},\n keywords = {Financial markets,First passage times,Long-range memory,Scaling behavior,Trading activity,Volatility},\n volume = {483},\n id = {f5fc6456-216e-3b08-b03d-4210309f641b},\n created = {2018-05-20T11:03:56.664Z},\n file_attached = {true},\n profile_id = {425903fc-29e3-3e93-b0fe-e189888ff33a},\n last_modified = {2021-11-07T17:42:48.743Z},\n read = {false},\n starred = {false},\n authored = {true},\n confirmed = {false},\n hidden = {false},\n citation_key = {Gontis2017},\n private_publication = {false},\n abstract = {© 2017 Elsevier B.V. We address the problem of long-range memory in the financial markets. There are two conceptually different ways to reproduce power-law decay of auto-correlation function: using fractional Brownian motion as well as non-linear stochastic differential equations. In this contribution we address this problem by analyzing empirical return and trading activity time series from the Forex. From the empirical time series we obtain probability density functions of burst and inter-burst duration. Our analysis reveals that the power-law exponents of the obtained probability density functions are close to 3/2, which is a characteristic feature of the one-dimensional stochastic processes. This is in a good agreement with earlier proposed model of absolute return based on the non-linear stochastic differential equations derived from the agent-based herding model.},\n bibtype = {article},\n author = {Gontis, V. and Kononovicius, A.},\n doi = {10.1016/j.physa.2017.04.163},\n journal = {Physica A: Statistical Mechanics and its Applications}\n}","author_short":["Gontis, V.","Kononovicius, A."],"urls":{"Paper":"https://bibbase.org/service/mendeley/425903fc-29e3-3e93-b0fe-e189888ff33a/file/7d93571a-ccef-0713-5084-ab97b4219d07/Published2017PhysA.pdf.pdf"},"biburl":"https://bibbase.org/service/mendeley/425903fc-29e3-3e93-b0fe-e189888ff33a","bibbaseid":"gontis-kononovicius-burstandinterburstdurationstatisticsasempiricaltestoflongrangememoryinthefinancialmarkets-2017","role":"author","keyword":["Financial markets","First passage times","Long-range memory","Scaling behavior","Trading activity","Volatility"],"metadata":{"authorlinks":{}}},"bibtype":"article","biburl":"https://bibbase.org/service/mendeley/425903fc-29e3-3e93-b0fe-e189888ff33a","dataSources":["iRDvFhYtnHmQzMjP8","ya2CyA73rpZseyrZ8","2252seNhipfTmjEBQ"],"keywords":["financial markets","first passage times","long-range memory","scaling behavior","trading activity","volatility"],"search_terms":["burst","inter","burst","duration","statistics","empirical","test","long","range","memory","financial","markets","gontis","kononovicius"],"title":"Burst and inter-burst duration statistics as empirical test of long-range memory in the financial markets","year":2017}