Search results for "Quantitative Finance - Computational Finance"

showing 4 items of 4 documents

The role of information in a two-traders market

2014

In a very simple stock market, made by only two \emph{initially equivalent} traders, we discuss how the information can affect the performance of the traders. More in detail, we first consider how the portfolios of the traders evolve in time when the market is \emph{closed}. After that, we discuss two models in which an interaction with the outer world is allowed. We show that, in this case, the two traders behave differently, depending on \textbf{i)} the amount of information which they receive from outside; and \textbf{ii)}the quality of this information.

Statistics and Probabilitymedia_common.quotation_subjectComputational Finance (q-fin.CP)Stock marketsCondensed Matter PhysicsAffect (psychology)MicroeconomicsFOS: Economics and businessQuantitative Finance - Computational FinanceOpen systemInformationStock marketQuality (business)BusinessSettore MAT/07 - Fisica MatematicaSimple (philosophy)media_common
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Multivariate GARCH estimation via a Bregman-proximal trust-region method

2011

The estimation of multivariate GARCH time series models is a difficult task mainly due to the significant overparameterization exhibited by the problem and usually referred to as the "curse of dimensionality". For example, in the case of the VEC family, the number of parameters involved in the model grows as a polynomial of order four on the dimensionality of the problem. Moreover, these parameters are subjected to convoluted nonlinear constraints necessary to ensure, for instance, the existence of stationary solutions and the positive semidefinite character of the conditional covariance matrices used in the model design. So far, this problem has been addressed in the literature only in low…

Statistics and ProbabilityMathematical optimizationPolynomialComputer scienceDiagonalComputational Finance (q-fin.CP)[QFIN.CP]Quantitative Finance [q-fin]/Computational Finance [q-fin.CP]FOS: Economics and businessQuantitative Finance - Computational FinanceDimension (vector space)0502 economics and business91G70 65C60050207 economicsMathematics050205 econometrics Trust regionStatistical Finance (q-fin.ST)Series (mathematics)Applied Mathematics05 social sciencesConstrained optimizationQuantitative Finance - Statistical Finance[QFIN.ST]Quantitative Finance [q-fin]/Statistical Finance [q-fin.ST]Computational MathematicsNonlinear systemComputational Theory and MathematicsParametrizationCurse of dimensionality
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Reduced Order Models for Pricing European and American Options under Stochastic Volatility and Jump-Diffusion Models

2016

European options can be priced by solving parabolic partial(-integro) differential equations under stochastic volatility and jump-diffusion models like the Heston, Merton, and Bates models. American option prices can be obtained by solving linear complementary problems (LCPs) with the same operators. A finite difference discretization leads to a so-called full order model (FOM). Reduced order models (ROMs) are derived employing proper orthogonal decomposition (POD). The early exercise constraint of American options is enforced by a penalty on subset of grid points. The presented numerical experiments demonstrate that pricing with ROMs can be orders of magnitude faster within a given model p…

Computational Engineering Finance and Science (cs.CE)FOS: Computer and information sciencesFOS: Economics and businessQuantitative Finance - Computational FinanceEuropean optionlinear complementary problemComputational Finance (q-fin.CP)reduced order modelAmerican optionComputer Science - Computational Engineering Finance and Scienceoption pricing
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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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