Conditional Annualised Volatility for the IGARCH 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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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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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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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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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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Asymmetric Conditional Volatility in International Stock Markets
... asymmetric models when one is analysing data on stock market ...Autoregressive Conditional Heteroskedasticity (TARCH) and the Exponential Generalised Autoregressive Conditional Heteroskedasticity ...
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Long memory conditional volatility and asset allocation
... multivariate conditional volatility models, including the multivariate RiskMetrics EWMA model, multivariate GARCH models and multivariate Stochastic Volatility models, have been ...
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Asymmetric Conditional Volatility on the Romanian Stock Market
... asymmetric volatility, I employ econometric models like the EGARCH, the TGARCH and a partially nonparametric ARCH model as introduced by Engle and Ng ...These models seem to capture the ...
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Estimation of Volatility and Correlation with Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models: An Application to Moroccan Stock Markets
... GARCH models should insure the positive-definiteness of the resulted variance covariance’s ...constant volatility or in case of the use of insufficient observation in ...
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Forecasting Value at Risk and Expected Shortfall using Fractionally Integrated Models of Conditional Volatility: International Evidence
... the conditional variance specification improves the accuracy of the VaR and ES forecasts produced, particularly for longer time ...the conditional variance model does not appear to improve the accuracy of ...
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