0000000000826383

AUTHOR

Guido Caldarelli

showing 4 related works from this author

Networks of equities in financial markets

2004

We review the recent approach of correlation based networks of financial equities. We investigate portfolio of stocks at different time horizons, financial indices and volatility time series and we show that meaningful economic information can be extracted from noise dressed correlation matrices. We show that the method can be used to falsify widespread market models by directly comparing the topological properties of networks of real and artificial markets.

Statistical Finance (q-fin.ST)Statistical Mechanics (cond-mat.stat-mech)Financial marketINDEXESFOS: Physical sciencesQuantitative Finance - Statistical FinanceCondensed Matter PhysicsElectronic Optical and Magnetic MaterialsSettore FIS/02 - Fisica Teorica Modelli e Metodi MatematiciFOS: Economics and businessEconomic informationDYNAMIC ASSET TREESEconometricsEconomicsPortfolioVolatility (finance)INTERNETVOLATILITYCondensed Matter - Statistical Mechanics
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Topology of correlation-based minimal spanning trees in real and model markets

2003

We present here a topological characterization of the minimal spanning tree that can be obtained by considering the price return correlations of stocks traded in a financial market. We compare the minimal spanning tree obtained from a large group of stocks traded at the New York Stock Exchange during a 12-year trading period with the one obtained from surrogated data simulated by using simple market models. We find that the empirical tree has features of a complex network that cannot be reproduced, even as a first approximation, by a random market model and by the one-factor model.

Spanning treeStatistical Mechanics (cond-mat.stat-mech)FOS: Physical sciencesTopology (electrical circuits)Complex networkMinimum spanning treeTopologyTree (graph theory)Settore FIS/02 - Fisica Teorica Modelli e Metodi MatematiciCorrelationStock exchangeSimple (abstract algebra)Condensed Matter - Statistical MechanicsMathematics
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Coupling News Sentiment with Web Browsing Data Improves Prediction of Intra-Day Price Dynamics

2015

The new digital revolution of big data is deeply changing our capability of understanding society and forecasting the outcome of many social and economic systems. Unfortunately, information can be very heterogeneous in the importance, relevance, and surprise it conveys, affecting severely the predictive power of semantic and statistical methods. Here we show that the aggregation of web users' behavior can be elicited to overcome this problem in a hard to predict complex system, namely the financial market. Specifically, our in-sample analysis shows that the combined use of sentiment analysis of news and browsing activity of users of Yahoo! Finance greatly helps forecasting intra-day and dai…

0301 basic medicineINFORMATIONEconomicsComputer scienceBig datalcsh:MedicineSocial SciencesQuantitative Finance - Computational Financesocial and economic systemsMathematical and Statistical TechniquesSociologybig dataEconometrics050207 economicsComputer NetworksCapital Marketslcsh:ScienceFinancial Marketsmedia_common050208 financeMultidisciplinary05 social sciencesCommerceSocial CommunicationSettore FIS/02 - Fisica Teorica Modelli e Metodi MatematiciSurpriseModels EconomicSocial NetworksPhysical SciencesSocial SystemsEngineering and TechnologyComputational sociologyBEHAVIORStatistics (Mathematics)Network AnalysisResearch ArticleComputer and Information SciencesExploitmedia_common.quotation_subjectTwitterComputational Finance (q-fin.CP)Research and Analysis MethodsFOS: Economics and business03 medical and health sciencesSEARCH0502 economics and businessHumansRelevance (information retrieval)Web navigationInvestmentsStatistical MethodsInternetStatistical Finance (q-fin.ST)STOCK-MARKETbusiness.industrylcsh:RSentiment analysisFinancial marketATTENTIONQuantitative Finance - Statistical FinanceCommunicationsNoise ReductionFinancial Firms030104 developmental biologySignal ProcessingPredictive powerlcsh:QStock marketbusinessSocial MediaFinanceMathematicsForecastingPLOS ONE
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The Structure of Financial Networks

2010

We present here an overview of the use of networks in Finance and Economics. We show how this approach enables us to address important questions as, for example, the structure of control chains in financial systems, the systemic risk associated with them and the evolution of trade between nations. All these results are new in the field and allow for a better understanding and modelling of different economic systems.

FinanceStructure (mathematical logic)EconophysicsFinancial networksbusiness.industryGeography of financeHedge fundSettore FIS/02 - Fisica Teorica Modelli e Metodi MatematiciGravity model of tradeNetworks Finance EconophysicsSystemic riskEconomicsFinancial modelingbusinessIndustrial organization
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