Search results for "Hawkes processe"

showing 6 items of 6 documents

Learning Automata-based Misinformation Mitigation via Hawkes Processes

2021

AbstractMitigating misinformation on social media is an unresolved challenge, particularly because of the complexity of information dissemination. To this end, Multivariate Hawkes Processes (MHP) have become a fundamental tool because they model social network dynamics, which facilitates execution and evaluation of mitigation policies. In this paper, we propose a novel light-weight intervention-based misinformation mitigation framework using decentralized Learning Automata (LA) to control the MHP. Each automaton is associated with a single user and learns to what degree that user should be involved in the mitigation strategy by interacting with a corresponding MHP, and performing a joint ra…

Computer Networks and CommunicationsComputer scienceDistributed computingStochastic optimizationSocial media Misinformation02 engineering and technologyCrisis mitigationArticleTheoretical Computer ScienceLearning automata020204 information systemsConvergence (routing)0202 electrical engineering electronic engineering information engineeringState spaceSocial mediaMisinformationVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550Social networkLearning automatabusiness.industryAutomaton020201 artificial intelligence & image processingStochastic optimizationbusinessHawkes processesSoftwareInformation Systems
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Modelling systemic price cojumps with Hawkes factor models

2015

Instabilities in the price dynamics of a large number of financial assets are a clear sign of systemic events. By investigating a set of 20 high cap stocks traded at the Italian Stock Exchange, we find that there is a large number of high frequency cojumps. We show that the dynamics of these jumps is described neither by a multivariate Poisson nor by a multivariate Hawkes model. We introduce a Hawkes one factor model which is able to capture simultaneously the time clustering of jumps and the high synchronization of jumps across assets.

Multivariate statisticsEconomicsSystemic shockPoisson distribution01 natural sciencesSynchronizationEconometrics and Finance (all)2001 EconomicsFOS: Economics and business010104 statistics & probabilitysymbols.namesakeHigh frequency data0502 economics and businessEconomicsEconometricsCojumps0101 mathematicsCojumps; Hawkes processes; High frequency data; Systemic shocks; Finance; Economics Econometrics and Finance (all)2001 Economics Econometrics and Finance (miscellaneous)Time clusteringFactor analysisSettore SECS-S/06 - Metodi mat. dell'economia e Scienze Attuariali e FinanziarieStatistical Finance (q-fin.ST)050208 financeSystemic shocksHawkes processe05 social sciencesQuantitative Finance - Statistical FinanceEconomics Econometrics and Finance (all)2001 Economics Econometrics and Finance (miscellaneous)Econometrics and Finance (miscellaneous)symbolsCojumpHawkes processesGeneral Economics Econometrics and FinanceFinanceSign (mathematics)Quantitative Finance
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Towards the specification of a self-exciting point process for modelling crimes in Valencia

2023

A number of papers have dealt with the analysis of crime data using self-exciting point process theory after the analogy drawn between aftershock ETAS models and crime rate. With the aim to describe crime events that occurred in Valencia in the last decade, in this paper, we justify the need for a self-exciting point process model through spatial and temporal exploratory analysis.

Self-exciting point processeSpatio-temporal point processesHawkes processeCovariateCrime dataSpatial StatisticSettore SECS-S/01 - Statistica
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Hawkes processes on networks for crime data

2022

Motivated by the analysis of crime data in Bucaramanga (Colombia), we propose a spatio-temporal Hawkes point process model adapted to events living on linear networks. We first consider a non-parametric modelling strategy, for both the background and the triggering components, and then we include a parametric estimation of the background based on covariates, and a non-parametric one of the triggering effects. Our network model outperforms a planar version, improving the fitting of the self-exciting point process model.

Spatio-temporal point processesHawkes processeCovariateLinear networkCrime dataSettore SECS-S/01 - Statistica
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Self-exciting point process modelling of crimes on linear networks

2022

Although there are recent developments for the analysis of first and second-order characteristics of point processes on networks, there are very few attempts in introducing models for network data. Motivated by the analysis of crime data in Bucaramanga (Colombia), we propose a spatiotemporal Hawkes point process model adapted to events living on linear networks. We first consider a non-parametric modelling strategy, for which we follow a non-parametric estimation of both the background and the triggering components. Then we consider a semi-parametric version, including a parametric estimation of the background based on covariates, and a non-parametric one of the triggering effects. Our mode…

Statistics and Probability22/3 OA procedureHawkes processeCovariatecrime datacovariatesself-exciting point processesSelf-exciting point processeSpatio-temporal point processesITC-ISI-JOURNAL-ARTICLELinear networklinear networksspatio-temporal point processesCrime dataStatistics Probability and UncertaintySettore SECS-S/01 - StatisticaHawkes processesStatistical modelling
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Modeling foreign exchange market activity around macroeconomic news: Hawkes-process approach

2015

We present a Hawkes-model approach to the foreign exchange market in which the high-frequency price dynamics is affected by a self-exciting mechanism and an exogenous component, generated by the pre-announced arrival of macroeconomic news. By focusing on time windows around the news announcement, we find that the model is able to capture the increase of trading activity after the news, both when the news has a sizable effect on volatility and when this effect is negligible, either because the news in not important or because the announcement is in line with the forecast by analysts. We extend the model by considering noncausal effects, due to the fact that the existence of the news (but not…

news arrivalTime windowsforeign exchange marketHawkes processehigh frequency financeEconomicsMonetary economicsVolatility (finance)Time seriesForeign exchange marketComputingMilieux_MISCELLANEOUS
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