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The purpose of this paper is to evaluate the forecasting performance of linear and non-linear generalized … autoregressive conditional heteroskedasticity (GARCH)–class models in terms of their in-sample and out-of-sample forecasting accuracy … for forecasting the volatility of both the TASI and the TIPISI in the context of petrochemical industries, as this model …
Persistent link: https://www.econbiz.de/10011960525
The COVID-19 pandemic disrupts capital markets and confuses decision makers. This event represents an opportunity to better understand how financial analysts forecast earnings. We focus on forecasts for Real Estate Investment Trusts (REITs) in the United States, since REITs are relatively...
Persistent link: https://www.econbiz.de/10012628786
Machine learning (ML) is a novel method that has applications in asset pricing and that fits well within the problem of measurement in economics. Unlike econometrics, ML models are not designed for parameter estimation and inference, but similar to econometrics, they address, and may be better...
Persistent link: https://www.econbiz.de/10013475217
This paper considers a flexible class of time series models generated by Gegenbauer polynomials incorporating the long memory in stochastic volatility (SV) components in order to develop the General Long Memory SV (GLMSV) model. We examine the corresponding statistical properties of this model,...
Persistent link: https://www.econbiz.de/10011854876
Different forecasting behaviors affect investors’ trading decisions and lead to qualitatively different asset price … forecasting future price changes, and the nature of their confidence when price changes are forecast, determine whether price … forecasting models of all participants that best fit the observed forecasting data were of the type that cause price bubbles and …
Persistent link: https://www.econbiz.de/10011854982
The paper investigates whether Bitcoin is a good predictor of the Standard & Poor's 500 Index. To answer this question we compare alternative models using a point and density forecast relying on Dynamic Model Averaging (DMA) and Dynamic Model Selection (DMS). According to our results, Bitcoin...
Persistent link: https://www.econbiz.de/10012022045
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