Results 61 to 70 of about 2,079 (206)
Volatility forecasts: a continuous time model versus discrete time models [PDF]
, 2006 This paper compares empirically the forecasting performance of a continuous time stochastic volatility model with two volatility factors (SV2F) to a set of alternative models (GARCH, FIGARCH, HYGARCH, FIEGARCH and Component GARCH).
Veiga, Helena
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International Journal of Financial StudiesThe aim of this study is to enhance the understanding of volatility dynamics in commodity returns, such as gold and cocoa, as well as the financial market index S&P500. It provides a comprehensive overview of each model’s efficacy in capturing volatility
Apostolos Ampountolas
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A new hyperbolic GARCH model [PDF]
, 2015 There are two commonly used hyperbolic GARCH processes, the FIGARCH and HYGARCH processes, in modeling the long-range dependence in volatility. However, the FIGARCH process always has infinite variance, and the HYGARCH model has a more complicated form ...
Li, G, Li, M, Li, WK
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Application of FIGARCH and EWMA Models on Stock Indices PX and BUX [PDF]
Acta Oeconomica Pragensia, 2011 Volatility of the financial time series belongs to the crucial estimated parameters in finance (e.g. in risk management, derivative pricing). It is well known, that volatility varies in time, so that new approaches of volatility modeling have appeared.
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Economies, 2019 The impact that oil market shocks have on stock markets of oil-related economies has several implications for both domestic and foreign investors. Thus, we investigate the role of the oil market in deriving the dynamic linkage between stock markets of ...
Manel Youssef, Khaled Mokni
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INTERNATIONAL TOURISTS’ EXPENDITURES IN THAILAND: A MODELLING OF THE ARFIMA-FIGARCH APPROACH [PDF]
Annals of the University of Petrosani: Economics, 2010 Forecasting is an essential analytical tool for tourism policy andplanning. This paper focuses on forecasting methods based on ARFIMA(p,d,q)-FIGARCH(p,d,q). Secondary data was used to produce forecasts of international tourists’expenditures in Thailand for the period 2009-2010.
Kanchana Chokethaworn +5 more
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A hybrid ExpAR-FIGARCH-ANN model for time series forecasting
Journal of Statistical Sciences and Computational IntelligenceFinancial time series forecast is challenging due to nonlinear mean dynamics, volatility clustering, and long-memory effects. Traditional hybrid models such as Autoregressive Integrated Moving Average – Generalised Autoregressive Conditional Heteroscedasticity (ARIMA–GARCH) and Fractional Generalised Integrated Autoregressive Conditional ...
Abba Bello Muhammad +5 more
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East Asian Economic Review, 2014 This paper examines the effects of financial crises on the long memory volatility dependency of daily exchange returns focusing on the Asian crisis in 97-98 and the Global crisis in 08-09.
Young Wook Han
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On the Predictability of Green Finance Markets: An Assessment Based on Fractal and Shannon Entropy
Fractal and FractionalEconophysics is an interdisciplinary field that applies physics concepts to economic and financial systems. By utilizing tools such as statistical physics, including fractal analysis and entropy measures, econophysics helps model the complex and non ...
Sonia Benghiat, Salim Lahmiri
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Volatility dynamics of stock returns, liquidity and exchange rates in ASEAN Countries [PDF]
AccountingIn this study, we examined the volatility trend of stock return in eight ASEAN stock markets. These includes the Singapore Exchange (SGX), Bursa Malaysia Stock Exchange (YSX), the Stock Exchange of Thailand (SET), Indonesia stock exchange, the Vietnam ...
David Umoru +3 more
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