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Showing 1 to 8 of 8 for “"Student's t distribution"”.
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Volatility Modeling Using the Student's t Distribution
… overparameterization. This dissertation uses the Student's t distribution and follows the Probabilistic Reduction (PR) methodology to modify and extend the univariate and multivariate volatility models viewed as alternative to the GARCH models. Its most important advantage is that it gives rise to …
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Volatility Modeling and Risk Measurement using Statistical Models based on the Multivariate Student's t Distribution
… exchange rate and stock market data, we proposed Student's t Autoregressive models to estimate expected return and volatility to measure risk, using Value at Risk (VaR) and Expected Shortfall (ES). The misspecification testing analysis shows that our proposed models can adequately capture the …
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Censored Regression Models With Applications to Infrastructure Degradation Studies
… of the Tobit censored regression model using Student's t distribution instead of the normal. Thus additional flexibility is achieved varying the degrees of freedom. The variance function can be estimated by using additional regression steps. Nonparametric methods are extended to apply to …
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Robust Prediction of Large Spatio-Temporal Datasets
… describes a robust and efficient design of Student-t based Robust Spatio-Temporal Prediction, namely, St-RSTP, to provide estimation based on observations over spatio-temporal neighbors. It is crucial to many applications in geographical information systems, medical imaging, urban planning, …
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Investigating the performance of process-observation-error-estimator and robust estimators in surplus production model: a simulation study
… process-observation-error-estimator with normal distribution (POE_N), observation-error-estimator with normal distribution (OE_N), and process-error-estimator with normal distribution (PE_N). The estimators with fat-tailed distributions including Student's t distribution and Cauchy distribution …
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Time Series Models for Analyzing Financial Data
… generally estimated assuming conditional error distribution as normal. Therefore, under this set up, the standardized residuals are supposed to behave like IID N(0,1). Several studies, including Hansen (1994), Lye, Martin and Teo (1996), and Harvey and Siddique (1999), argue that there is no …
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On modeling the volatility in speculative prices
… Reduction(PR) Approach, this paper proposes the Student’s Autoregressive (St-AR) Model, Student’s t Vector Autoregressive (St-VAR) Model and their heterogeneous versions, as an alternative to the various ARCH type models, to capture univariate and multivariate volatility. The St-AR and St-VAR …
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Three Essays in Applied Econometrics: with Application to Natural Resource and Energy Markets
… Smith (1990) to investigate the univariate tail distribution of the returns on various energy products such as Crude Oil, Gasoline, Heating Oil, Propane and Diesel. The bivariate threshold exceedance model of Ledford and Tawn (1996) is also used to study the tail dependence between returns on …