Browsing by Author "Arratia Quesada, Argimiro Alejandro"
Now showing items 1-20 of 72
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A construction of continuous-time ARMA models by iterations of Ornstein-Uhlenbeck processes
Arratia Quesada, Argimiro Alejandro; Cabaña, Ana Alejandra; Cabaña Perez, Enrique (Institut d'Estadística de Catalunya, 2016-12)
Article
Open AccessWe present a construction of a family of continuous-time ARMA processes based on p iterations of the linear operator that maps a Lévy process onto an Ornstein-Uhlenbeck process. The construction resembles the procedure to ... -
A construction of continuous-time ARMA models by iterations of Ornstein-Uhlenbeck processes
Arratia Quesada, Argimiro Alejandro; Cabaña, Alejandra; Cabaña, Enrique M. (Institut d'Estadística de Catalunya, 2016-12-19)
Article
Open Access -
A graphical tool for describing the temporal evolution of clusters in financial stock markets
Arratia Quesada, Argimiro Alejandro; Cabaña, Ana Alejandra (2013-02-01)
Article
Restricted access - publisher's policy -
A note on first-order projections and games
Arratia Quesada, Argimiro Alejandro; Stewart, Iain A. (2003)
Article
Open AccessWe show how the fact that there is a first-order projection with successor from the problem TC (transitive clousure) to some other problem Ω enables us to automatically deduce that a natural game problem, LGΩ, whose instances ... -
American and exotic options in a market with frictions
Junike, Gero; Arratia Quesada, Argimiro Alejandro; Cabaña Nigro, Ana Alejandra; Schoutens, Wim (2020-01)
Article
Open AccessIn a market with frictions, bid and ask prices are described by sublinear pricing functionals, which can be defined recursively using coherent risk measures. We prove the convergence of bid and ask prices for various ... -
An alternative to CARMA models via iterations of Ornstein–Uhlenbeck processes
Arratia Quesada, Argimiro Alejandro; Cabaña, Ana Alejandra; Cabaña Perez, Enrique (Springer, 2015)
Conference report
Restricted access - publisher's policyWe present a new construction of continuous ARMA processes based on iterating an Ornstein–Uhlenbeck operator OUκ that maps a random variable y(t) onto OUκy(t)=∫t−∞e−κ(t−s)dy(s). This construction resembles the procedure ... -
An evaluation of equity premium prediction using multiple kernel learning with financial features
Arratia Quesada, Argimiro Alejandro; Belanche Muñoz, Luis Antonio; Fábregues de los Santos, Luis (2020-08)
Article
Open AccessThis paper introduces and extensively explores a forecasting procedure based on multivariate dynamic kernels to re-examine –under a non-linearframework– the experimental tests reported by Welch and ... -
Approximate formulae for a logic that capture classes of computational complexity
Arratia Quesada, Argimiro Alejandro; Ortiz, Carlos E. (Oxford University Press, 2009-02)
Article
Open AccessThis paper presents a syntax of approximate formulae suited for the logic with counting quantifiers SOLP. This logic was formalised by us in [1] where, among other properties, we showed the following facts: (i) In the ... -
Approximating the expressive power of logics in finite models
Arratia Quesada, Argimiro Alejandro; Ortiz, Carlos E. (Springer, 2004)
Conference report
Open AccessWe present a probability logic (essentially a first order language extended with quantifiers that count the fraction of elements in a model that satisfy a first order formula) which, on the one hand, captures uniform circuit ... -
Classifier selection with permutation tests
Arias Vicente, Marta; Arratia Quesada, Argimiro Alejandro; Duarte López, Ariel (IOS Press, 2017)
Conference report
Open AccessThis work presents a content-based recommender system for machine learning classifier algorithms. Given a new data set, a recommendation of what classifier is likely to perform best is made based on classifier performance ... -
clustAnalytics: An R package for assessing stability and significance of communities in networks
Renedo Mirambell, Martí; Arratia Quesada, Argimiro Alejandro (2023-11-01)
Article
Open AccessThis paper introduces the R package clustAnalytics, which comprises a set of criteria for assessing the significance and stability of communities in networks found by any clustering algorithm. clustAnalytics works with ... -
Clustering assessment in weighted networks
Arratia Quesada, Argimiro Alejandro; Renedo Mirambell, Martí (2021-06-18)
Article
Open AccessWe provide a systematic approach to validate the results of clustering methods on weighted networks, in particular for the cases where the existence of a community structure is unknown. Our validation of clustering comprises ... -
Clustering of exchange rates and their dynamics under different dependence measures
Renedo Mirambell, Martí; Arratia Quesada, Argimiro Alejandro (2016)
Conference report
Open AccessThis paper proposes an improvement to the method for clustering exchange rates given by D. J. Fenn et al, in Quantitative Finance, 12 (10) 2012, pp.1493-1520. To deal with the potentially non linear nature of currency time ... -
Convolutional Neural Networks, image recognition and financial time series forecasting
Arratia Quesada, Argimiro Alejandro; Sepúlveda, Eduardo (2019)
Conference report
Restricted access - publisher's policyConvolutional Neural Networks (CNN) are best known as good image classifiers. This model is recently been used for financial forecasting. The purpose of this work is to show that by converting financial information into ... -
Cumulated burden of Covid-19 in Spain from a Bayesian perspective
Moriña, David; Fernandez Fontelo, Amanda; Cabaña Nigro, Ana Alejandra; Arratia Quesada, Argimiro Alejandro; Ávalos Villaseñor, Gustavo Eduardo; Puig, Pedro (2021-12)
Article
Open AccessBackground The main goal of this work is to estimate the actual number of cases of Covid-19 in Spain in the period 01-31-2020/06-01-2020 by Autonomous Communities. Based on these estimates, this work allows us to accurately ... -
Deep and wide neural networks covariance estimation
Arratia Quesada, Argimiro Alejandro; Cabaña Nigro, Ana Alejandra; León, José Rafael (Springer, 2020-10-14)
Article
Open AccessIt has been recently shown that a deep neural network with i.i.d. random parameters is equivalent to a Gaussian process in the limit of infinite network width. The Gaussian process associated to the neural network is fully ... -
Do Google Trends forecast bitcoins? Stylized facts and statistical evidence
Arratia Quesada, Argimiro Alejandro; López Barrantes, Albert (2019)
Conference report
Open AccessIn early 2018 Bitcoin prices peaked at USD 20,000 and, almost two years later, we still continue debating if cryptocurrencies can actually become a currency for the everyday life or not. From the economic point of view, ... -
Do Google Trends forecast bitcoins? Stylized facts and statistical evidence
Arratia Quesada, Argimiro Alejandro; López Barrantes, Albert (Springer, 2021-06)
Article
Open AccessIn early 2018 Bitcoin prices peaked at US$ 20,000 and, almost two years later, we still continue debating if cryptocurrencies can actually become a currency for the everyday life or not. From the economic point of view, ... -
Embedding in law of discrete time ARMA processes in continuous time stationary processes
Arratia Quesada, Argimiro Alejandro; Cabaña, Ana Alejandra; Cabaña Perez, Enrique (2018-12-01)
Article
Open AccessGiven any stationary time series {Xn : n ¿ Z} satisfying an ARMA(p, q) model for arbitrary p and q with infinitely divisible innovations, we construct a continuous time stationary process {xt : t ¿ R} such that the ... -
Estimated Covid-19 burden in Spain: ARCH underreported non-stationary time series
Moriña Soler, David; Fernandez Fontelo, Amanda; Cabaña Nigro, Ana Alejandra; Arratia Quesada, Argimiro Alejandro; Puig Casado, Pere (2023-03-28)
Article
Open AccessBackground The problem of dealing with misreported data is very common in a wide range of contexts for different reasons. The current situation caused by the Covid-19 worldwide pandemic is a clear example, where the data ...