Results 41 to 50 of about 36,906 (198)
Beta Forecasting With Realized Beta Estimators and Machine Learning Algorithms
Journal of Forecasting, EarlyView.ABSTRACT This paper applies machine learning algorithms to the modeling of realized betas for the purposes of forecasting stock systematic risk. Higher levels of beta forecast accuracy are demonstrated, relative to other studies in the literature. These improvements are also highly significant, both statistically and economically.
Bao Doan +3 more
wiley +1 more source
Forecasting volatilities in the energy sector: a comparison of GAS, GARCH and GJR models
, 2023 openQuesta relazione confronta la capacità dei modelli GAS, GARCH e GJR di prevedere la volatilità dei rendimenti di due beni appartenenti al settore energetico, cioè il petrolio greggio e il gas naturale.
PIATTELLA, LUNA
core
EkonometriaAim: The main object of this study was to present a comparison between GARCH models, i.e. the standard GARCH model, asymmetric GJR-GARCH, and logarithmic EGARCH on exchange rate (IDR/USD) volatility.
Juwita Suwondo +3 more
doaj +1 more source
Estimating Value at Risk of Portfolio of Oil and Gold by Copula-GARCH Method [PDF]
تحقیقات مالی, 2014 Copula functions are powerful tools that describe dependence structure of multi- dimension random variables and are considered as one of the newest tools for risk management.
Saeed Fallahpour, Ehsan Ahmadi
doaj +1 more source
Journal of Forecasting, EarlyView.ABSTRACT This paper develops Masked Asset–Regime Scenario Diffusion (MARS‐Diff), a leakage‐disciplined framework for probabilistic forecasting of multiday portfolio losses. The framework combines a regularized heterogeneous autoregressive model with exogenous predictors (HAR‐X) as its anchor, a train‐only masked representation of a high‐dimensional ...
Çağlar Sözen, Mervenur Sözen
wiley +1 more source
Real Estate Management and Valuation, 2023 The presence of volatility in residential property market prices helps investors generate substantial profit while also causing fear among investors since high volatility implies a high return with a high risk.
Suleiman Ahmad Abubakar +6 more
doaj +1 more source
COVID-19 Pandemic and Volatility Persistence of the Nigerian Crude Oil Price
Journal of Applied Sciences and Environmental Management, 2022 Impacts of COVID-19 pandemic on the global economy cannot be overemphasized, especially with Nigeria, which largely depends on crude oil as a major source of her revenue.
T. K. Samson, M. A. Raheem
doaj +1 more source
Brexit and Its Impact on EU Financial Markets
International Journal of Finance &Economics, EarlyView.ABSTRACT We investigate the impact of Brexit on volatility spillovers across the EU countries. We introduce a Brexit intensity measure that assigns an intensity score reflective of the financial markets' reaction to the events that occurred as Brexit negotiations began to unfold.
Marwan Izzeldin +3 more
wiley +1 more source
, 2018 Back-testing results following Bayesian MS-GJR-GARCH(1,1) Student’s-t and Frank copula-EVT VaR models.
Haslifah M. Hasim (4839987) +2 more
core +1 more source
An Analysis of the Exchange Rate Volatility in Poland using the GARCH, GJR-GARCH and EGARCH Models
Earthline Journal of Mathematical Sciences, 2022 This paper employs the symmetric GARCH and the asymmetric GJR-GARCH(1,1) and E-GARCH(1,1) models to explain the dynamics of the PLN/EUR and PLN/USD exchange rates in Poland for the periods of January 2015 to July 2022. The result of our study shows that the USD rate is more susceptible to market fluctuations and events than the EUR rate.
Nneka Karen Enumah +1 more
openaire +1 more source