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Closing the GARCH gap: Continuous time GARCH modeling [PDF]
Journal of Econometrics, 1996 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bas J M Werker, Feike C Drost
exaly +9 more sources
Improving GARCH volatility forecasts with regime-switching GARCH [PDF]
Empirical Economics, 2002 Many researchers use GARCH models to generate volatility forecasts. Using data on three major U.S. dollar exchange rates we show that such forecasts are too high in volatile periods. We argue that this is due to the high persistence of shocks in GARCH forecasts.
Franc Klaassen
exaly +7 more sources
Revista de Administração Contemporânea, 2021 ABSTRACT Context: modeling volatility is an advanced technique in financial econometrics, with several applications for academic research. Objective: in this tutorial paper, we will address the topic of volatility modeling in R. We will discuss the underlying logic of GARCH models, their representation and estimation process, along with a descriptive
Marcelo Scherer Perlin +3 more
openaire +5 more sources
Forecasting gains by using extreme value theory with realised GARCH filter
IIMB Management Review, 2021 Early empirical evidence suggests that the realised generalised autoregressive conditional heteroskedasticity (GARCH) model provides significant forecasting gains over the standard GARCH models in volatility forecasting.
Samit Paul, Prateek Sharma
doaj +1 more source
Reviews of Management Sciences, 2022 Purpose: The purpose of this paper is to predict the volatility of the KSE-100 index using econometric and machine learning models. It also designs hybrid models for volatility forecasting by combining these two models in three different ways ...
Komal Batool +2 more
doaj +1 more source
Value-at-risk predictive performance: a comparison between the CaViaR and GARCH models for the MILA and ASEAN-5 stock markets [PDF]
Journal of Economics Finance and Administrative Science, 2021 Purpose – This paper tests the accuracies of the models that predict the Value-at-Risk (VaR) for the Market Integrated Latin America (MILA) and Association of Southeast Asian Nations (ASEAN) emerging stock markets during crisis periods.
Ramona Serrano Bautista +1 more
doaj +1 more source
Challenges of integrated variance estimation in emerging stock markets [PDF]
Zbornik radova Ekonomskog fakulteta u Rijeci : časopis za ekonomsku teoriju i praksu, 2019 Estimating integrated variance, using high frequency data, requires modelling experience and data crunching skills. Although intraday returns have attracted much attention in recent years, handling these data is challenging because of their ...
Josip Arnerić, Mario Matković
doaj +1 more source
Risks, 2023 Cryptocurrencies have increasingly attracted the attention of several players interested in crypto assets. Their rapid growth and dynamic nature require robust methods for modeling their volatility.
Rhenan G. S. Queiroz, Sergio A. David
doaj +1 more source
Exploring the Effectiveness of ARIMA and GARCH Models in Stock Price Forecasting: An Application in the IT Industry [PDF]
Informatică economică, 2023 his study aims to develop a predictive model for stock prices using time-series analysis. The primary objective is to identify volatility patterns through the implementation of the GARCH model and forecast future stock prices for Microsoft company ...
Lavinia Roxana TOMA
doaj +1 more source
GARCH Modeling of Cryptocurrencies [PDF]
SSRN Electronic Journal, 2017 With the exception of Bitcoin, there appears to be little or no literature on GARCH modelling of cryptocurrencies. This paper provides the first GARCH modelling of the seven most popular cryptocurrencies. Twelve GARCH models are fitted to each cryptocurrency, and their fits are assessed in terms of five criteria.
Chu, Jeffrey +3 more
openaire +2 more sources