Showing 1 - 10 of 3,325
This paper proposes a new combined semiparametric estimator of the conditional variance that takes the product of a parametric estimator and a nonparametric estimator based on machine learning. A popular kernel-based machine learning algorithm, known as the kernel-regularized least squares...
Persistent link: https://www.econbiz.de/10012814196
Monitoring economic conditions in real time, or nowcasting, is among the key tasks routinely performed by economists. Nowcasting entails some key challenges, which also characterise modern Big Data analytics, often referred to as the three "Vs": the large number of time series continuously...
Persistent link: https://www.econbiz.de/10012259379
The forecasting literature has identi ed two important issues: (i) several predictors have substantial and … learned about forecasting in the presence of instabilities. The empirical evidence raises a multitude of questions. If in …-sample tests provide poor guidance to out-of-sample forecasting ability, what should researchers do? If there are statistically …
Persistent link: https://www.econbiz.de/10014177227
This short report deals with the recent rise of programmatic time series methods. This decade has witnessed the proliferation of commercial and open source time-series tooling, which calls for an exposition of what is publicly available. In tandem with this survey, AtsPy, an open source...
Persistent link: https://www.econbiz.de/10014099339
Representation of continuous-time ARMA, CARMA, models is reviewed. Computational aspects of simulating and calculating the likelihood-function of CARMA are summarized. Some numerical properties are illustrated by simulations. Some real data applications are shown.
Persistent link: https://www.econbiz.de/10009388633
Representation of continuous-time ARMA, CARMA, models is reviewed. Computational aspects of simulating and calculating the likelihood-function of CARMA are summarized. Some numerical properties are illustrated by simulations. Some real data applications are shown. -- CARMA ; maximum-likelihood ;...
Persistent link: https://www.econbiz.de/10009685469
Forecasting-volatility models typically rely on either daily or high frequency (HF) data and the choice between these … forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the assumptions of jumping …
Persistent link: https://www.econbiz.de/10011730304
Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these … these two family forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the …
Persistent link: https://www.econbiz.de/10011674479
We simulate a simplified version of the price process including bubbles and crashes proposed in Kreuser and Sornette (2018). The price process is defined as a geometric random walk combined with jumps modelled by separate, discrete distributions associated with positive (and negative) bubbles....
Persistent link: https://www.econbiz.de/10012836362
The multi-fractal analysis has been applied to investigate various stylized facts of the financial market including market efficiency, financial crisis, risk evaluation and crash prediction. This paper examines the daily return series of stock index of NASDAQ stock exchange. Also, in this study,...
Persistent link: https://www.econbiz.de/10013273743