Conditional Annualised Volatility for the FIGARCH Models
Asymmetry and Leverage in Conditional Volatility Models
... known conditional volatility models, namely GARCH, GJR and EGARCH, from their respective underlying stochastic processes raises two important issues: (1) the regularity conditions for each ...
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Asymmetry and Leverage in Conditional Volatility Models
... known conditional volatility models, namely GARCH, GJR and EGARCH, from their respective underlying stochastic processes raises two important issues: (1) the regularity conditions for each ...
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On the conditional behavior of stock market volatility: a sub-sample analysis using the FIGARCH approach for developed and emerging markets
... S.R. Bentes ∗ Instituto Superior de Contabilidade e Administração de Lisboa (ISCAL), Lisboa, Portugal and Instituto Universitário de Lisboa (ISCTE-IUL), Business Research Unit (BRU-IUL), Lisboa, Portugal Long memory has ...
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Nonlinear volatility models in economics: smooth transition and neural network augmented GARCH, APGARCH, FIGARCH and FIAPGARCH models
... the conditional mean follows a two regime GARCH process in which the transition between the regimes are governed by a continuous, twice differentiable function such as the exponential or the logistic function to ...
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Granger-Causal Analysis of Conditional Mean and Volatility Models
... 3.6. GRANGER CAUSAL ANALYSIS OF US MONEY-INCOME DATA 151 These findings have particular consequences for the forecasting of the income. Despite the fact that past information about money does not change the forecast of ...
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Selection Criteria in Regime Switching Conditional Volatility Models
... linear conditional heteroskedastic models have been proposed in the literature and practitioners do not have always the tools to choose the correct ...of models: the Logistic Smooth Transition GARCH ...
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Model Selection and Testing of Conditional and Stochastic Volatility Models
... all models as equivalent; QLIKE prefers GJR; IF, PIF and RL indicate a preference for GARCH and GJR; while AD, SD and ASD suggest that the optimal models are EGARCH and ...all models are equivalent ...
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ARFIMA-FIGARCH and ARFIMA -FIAPARCH on Thailand Volatility Index
... proposed FIGARCH (Fractional Integrated GARCH) model which is effectively capture both volatility clustering and long memory because GARCH model exhibit short memory and cannot analyze hyperbolic memory in ...
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Change Point Detection in the Conditional Correlation Structure of Multivariate Volatility Models
... popular models, like every empirical model in econometrics, must account for changes in their parameters which might arise as a result of sudden shocks occurring in the economy, such as, market crashes, financial ...
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Change point detection in the conditional correlation structure of multivariate volatility models
... for models which asymmetry in the dynamics of conditional variance such as the cDCC model, a generalization to all asymmetric multivariate GARCH processes is not made here, but it will definitely be an ...
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Semi-parametric Conditional Quantile Models for Financial Returns and Realized Volatility
... Keywords: conditional quantiles, Value-at-Risk, quantile regression, realized measures ∗ We are indebted to Karim ...Realized Volatility/Vast Data (London, June 2009) and Non- and Semiparametric ...
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Modeling Long Memory and Structural Breaks in Conditional Variances: an Adaptive FIGARCH Approach
... memory volatility process, denoted by Adaptive F IGARCH, or A-FIGARCH, which is designed to account for both long memory and structural change in the volatility processes of economic and …nancial ...
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Scientific stochastic volatility models for the European carbon markets: forecasting and extracting conditional moments
... Stochastic volatility models have an intuitive and simple structure and can explain the major stylized facts of asset, currency and commodity ...price volatility investigation is important for ...
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Mortgage Terminations: The Role of Conditional Volatility
... 兩 A n a l y s i s In order to investigate the importance of conditional volatility to mortgage loan performance, separate Cox regression models for the hazards of default and prepayment were ...
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A Stochastic Volatility Model with Conditional Skewness
... stochastic volatility and conditional ...time-series volatility models is motivated by their tractability in empirical ...GARCH models that belong to the discrete-time affine class, and ...
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The Conditional Volatility Premium on Currency Portfolios
... currency volatility is associated with cross-sectional pricing models, while Bakshi and Panayotov (2013) explore the relationship in a time-series ...
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Forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models
... and volatility as measured by squared returns are usually subject to multiple breaks (see, Figures 1 to ...oil-return volatility generating process would result in unreliable estimates of oil ...
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Robust M-estimation of Multivariate FIGARCH Models for Handling Volatility Transmission: A Case study of Iran, United Arab Emirates and the Oil Global Price Index
... price volatility, as an important issue in stock markets, signicantly aects decision makers' ...autoregressive conditional heteroscedasticity (MVFIGARCH) model is ...with models in the literature, ...
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Conditional Volatility, Skewness, and Kurtosis: Existence and Persistence.
... Conditional Volatility, Skewness, and Kurtosis: Existence and Persistence Abstract: Recent portfolio choice, asset pricing, and option valuation models highlight the im- portance of skewness and ...a ...
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Target zones and conditional volatility: the role of realignments
... and conditional volatility in three ...forecasts conditional volatility during periods of speculative ...forecast conditional variance, the absolute value GARCH models of Taylor ...
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