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fundamental importance. We propose a simple statistical method for short-term real-time forecasting of the number of Covid-19 …
Persistent link: https://www.econbiz.de/10012817060
series forecasting. We consider both linear and nonlinear alternatives. Among the linear methods we pay special attention to …
Persistent link: https://www.econbiz.de/10012817069
It is widely known that Google Trends has become one of the most popular free tools used by forecasters both in academics and in the private and public sectors. There are many papers, from several different fields, concluding that Google Trends improve forecasts' accuracy. However, what seems to...
Persistent link: https://www.econbiz.de/10012817073
In this paper we consider modeling and forecasting of large realized covariance matrices by penalized vector …
Persistent link: https://www.econbiz.de/10010491375
Persistent link: https://www.econbiz.de/10011807281
Does volatility reflect a continuous reaction to past shocks or changes in the markets induce shifts in the volatility dynamics? In this paper, we provide empirical evidence that cumulated price variations convey meaningful information about multiple regimes in the realized volatility of stocks,...
Persistent link: https://www.econbiz.de/10011807356
flexible for purposes of forecasting volatility. …
Persistent link: https://www.econbiz.de/10011807368
We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time-series models. We assume that both the number of covariates in the model and the number of candidate variables can increase with the sample size (polynomially orgeometrically). In other...
Persistent link: https://www.econbiz.de/10011807460
This paper evaluates the economic gains associated with following a volatility timing strategy based on a multivariate model of realized volatility. To study this issue we build a high frequency database with the most actively traded Brazilian stocks. Comparing with traditional volatility...
Persistent link: https://www.econbiz.de/10010402112
We study the asymptotic properties of the Adaptive LASSO (adaLASSO) in sparse, high-dimensional, linear time-series models. We assume that both the number of covariates in the model and the number of candidate variables can increase with the sample size (polynomially or geometrically). In other...
Persistent link: https://www.econbiz.de/10010505038