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, traditional methods fail. Recently, new techniques have been developed, based on regularization, which can often produce accurate … models in these settings. This paper describes the basic principles underlying the method of regularization, then focuses on … those methods which exploit the sparsity of the predicting model. The potential merits of these methods are then explored by …
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We retrieve news stories and earnings announcements of the S&P 100 constituents from two professional news providers, along with ten macroeconomic indicators. We also gather data from Google Trends about these firms’ assets as an index of retail investors’ attention. Thus, we create an...
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In this paper we survey the most recent advances in supervised machine learning and highdimensional models for time series forecasting. We consider both linear and nonlinear alternatives. Among the linear methods we pay special attention to penalized regressions and ensemble of models. The...
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In this paper we survey the most recent advances in supervised machine learning and highdimensional models for time series forecasting. We consider both linear and nonlinear alternatives. Among the linear methods we pay special attention to penalized regressions and ensemble of models. The...
Persistent link: https://www.econbiz.de/10012390030