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Showing 1 to 20 of 45 for “"GARCH models"”.
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Volatility forecasting using Double-Markov switching GARCH models under skewed Student-t distribution
… of daily returns using a double Markov switching GARCH model with a skewed Student-t error distribution. The model was applied to individual shares obtained from the Johannesburg Stock Exchange (JSE). The Bayesian approach which uses Markov Chain Monte Carlo was used to estimate the unknown …
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Modelling of volatility of stock prices using GARCH models & its importance in portfolio construction
… the adequacy and effectiveness of univariate GARCH models such as the symmetric GARCH and a few other variations such as the EGARCH, TARCH and PARCH in modelling volatility in monthly returns of stocks traded on the Johannesburg Stock Exchange. This is further used to investigate the …
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Comparing GARCH models for gold price data, using a statistical loss function approach and an option pricing approach
… In this thesis, use is made of various GARCH models that are evaluated using both in-sample and out-of-sample criteria.
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A Study on GARCH volatility processes in pricing derivatives
In this thesis the GARCH models are applied to evaluate financial options and futures. In the first application, the GARCH models in parsimonious form are studied for pricing the S&P500 options. Unlike previous studies that focus on developed formulation, the results indicate that simplified models …
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Effects of Food Safety Events on U.S. Romaine Lettuce Prices
… Autoregressive Conditional Heteroskedasticity (GARCH) models. Importantly, the GARCH models allowed us to capture the effects of the recall and illness outbreaks on both the returns and volatility of the romaine price series. We find that three (3) of the seven (7) illness outbreaks resulted in …
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Contributions to Conditional Heteroscedastic Models: M-Estimation and Other Methods.
… contributions to conditional heteroscedastic models in financial time series. A class of M-estimators for time series models with asymmetric form of heteroscedasticity are developed. A weighted resampling method is used to approximate the sampling distribution of M-estimators. The primary …
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On modelling volatility and mortality for pension schemes
… research is to develop volatility and mortality models that could be used in asset liability management in pension schemes. This study provides a comprehensive study of various advance multivariate DCC GARCH models which are used for construction of optimal portfolios in modelling asset return …
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Risk neutral measures and GARCH model calibration
Empirical studies have shown that GARCH models can be successfully used to describe option prices. Pricing such option contracts requires the risk neutral return dynamics of underlying asset. Since under the GARCH framework the market is incomplete, there is more than one risk neutral measure. In …
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Higher moment models for risk and portfolio management
… extensions to the dynamics of the popular GARCH model, to capture time variation in higher moments, are considered in the univariate and multivariate context, with a special focus on the Generalized Hyperbolic distribution. In Chapter 1, I consider the extension of univariate GARCH …
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Forecasting volatilities in option pricing: An application of Bayesian inference
… forecasting volatilities used in option pricing models for live cattle and live hog futures. The forecast problem is cast in the framework of Bayesian inference. Six types of individual forecast models are used--GARCH models, ARIMA models, systems of simultaneous equations, systems of seemingly …
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Application of GARCH Type Models in Forecasting Value at Risk
… using four conditional volatility forecasting models: GARCH, TGARCH, GJRGARCH, and IGARCH, and compares the forecasting output of the suggested GARCH-based volatility models. Since the predictive accuracy of Value-at-Risk (VaR) models is crucial for adequate capitalization, we perform …
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The impact of news on the South African sovereign bond market
… in the zero-coupon yields are identified using GARCH models on the daily return series and news items that are classified into categories using supervised machine learning. A regression model is fitted to determine the link between the abnormal daily returns and news categories. The results …
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Daily and intradaily stochastic covariance : value at risk estimates for the foreign exchange market
… varying volatility in securities prices (e.g. GARCH) has by now been amply established in the literature, both in terms of the magnitude and pervasiveness of the phenomenon, and in terms of its significance for risk management in institutional portfolios. Less attention has been devoted to …
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Essays on economic value of intraday covariation estimators for risk prediction
… favour intra-day covariance matrix models instead of their daily counterparts. The constant conditional correlation (CCC) augmented with realized volatility produces the highest economic value when applied with a time-varying volatility timing strategy. Chapter 4 compares the …
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Essays on the economic value of intraday covariation estimators for risk prediction
… overwhelmingly favour intraday covariance matrix models instead of their daily counterparts. The constant conditional correlation (CCC) augmented with realized volatility produces the highest economic value when applied with a time-varying volatility timing strategy. Chapter 4 compares the …
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The Consequences of Euronext integration on the French, Belgian and Dutch stock markets.
… o f all the returns series is captured with ARMA-GARCH models. The returns exhibit volatil ity clusters in all sub- periods. Hence, the information efficiency of the m arket has not increased following Euronext integration. However, GARCH models do not include an asymmetric component for the …
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Volatility Modeling Using the Student's t Distribution
… produced a wealth of univariate and multivariate GARCH type models. While the univariate models have been relatively successful in empirical studies, they suffer from a number ofweaknesses, such as unverifiable parameter restrictions, existence of moment conditions and the retention of Normality. …
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Modelling the Dynamics of Credit Spreads of European Corporate Bond Indices
… period. Traditional quantitative credit risk models assume that changes in spreads are normally distributed but empirical evidence shows that they are likely to be skewed and fat-tailed, and if they are ignored then the calculation of loss probabilities will be seriously compromised. …
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Essays On Oil Price Volatility And Irreversible Investment
… <p>forecasting performance of several models for the volatility of daily spot</p> <p>crude oil prices. Empirical research over the past decades has uncovered</p> <p>significant gains in forecasting performance of Markov Switching GARCH</p> <p>models over GARCH models for the volatility …
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