0000000000165079
AUTHOR
Juan-pablo Ortega
Stochastic Nonlinear Time Series Forecasting Using Time-Delay Reservoir Computers: Performance and Universality
International audience; Reservoir computing is a recently introduced machine learning paradigm that has already shown excellent performances in the processing of empirical data. We study a particular kind of reservoir computers called time-delay reservoirs that are constructed out of the sampling of the solution of a time-delay diFFerential equation and show their good performance in the forecasting of the conditional covariances associated to multivariate discrete-time nonlinear stochastic processes of VEC-GARCH type as well as in the prediction of factual daily market realized volatilities computed with intraday quotes, using as training input daily log-return series of moderate size. We …
L’emploi de méthodes mathématiques pour détecter la présence de potentiels évoqués dans le coma : un aide ou un fardeau ?
Un des defis majeurs auxquels sont confrontes les services de reanimation est de pouvoir predire precisement et precocement vers quel etat evoluera la conscience des patients dans le coma pour anoxie cerebrale. Afin d’obtenir des indices directs sur l’etat cerebral fonctionnel, l’emploi des potentiels evoques est recommande, et notamment l’enregistrement de la negativite de discordance (MMN). La MMN est une onde cerebrale apparaissant entre 100 et 200 ms apres l’apparition d’un nouveau stimulus dans une sequence de stimuli identique et sa presence est un signe fort de recuperation. Le standard dans la determination de la presence d’une onde MMN en pratique clinique est l’analyse visuelle pa…
Forecasting US Growth During the Great Recession: Is the Financial Volatility the Missing Ingredient?
The Great Recession endured by the main industrialized countries during the period 2008-2009, in the wake of the financial and banking crisis, has pointed out the major role of the financial sector on macroeconomic fluctuations. In this respect, many researchers have started to reconsider the linkages between financial and macroeconomic areas. In this paper, we evaluate the leading role of the daily volatility of two major financial variables, namely commodity and stock prices, in their ability to anticipate the output growth. For this purpose, we propose an extended MIDAS model that allows the forecasting of the quarterly output growth rate using exogenous variables sampled at various high…
Multivariate GARCH estimation via a Bregman-proximal trust-region method
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…