Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 70 for “"Heteroskedasticity"”.
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Modeling Conditional Heteroskedasticity in Time Series and Spatial Analysis
… distributional misspecification and conditional heteroskedasticity. I first derive a simple specification test for spatial autoregressive model using the information matrix (IM) test principle. As a byproduct of my test development, I obtain a general model that has similar features like …
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Some aspects of modeling conditional heteroskedasticity: Theory and applications
… (LM) test for autoregressive conditional heteroskedasticity (ARCH). Given Chesher's interpretation of the IM test as a test for parameter heterogeneity, this establishes a connection among the IM test, ARCH and parameter variation. The LM test for ARCH is interpreted as a test for the …
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Some applications of minimum norm quadratic estimation and eigenvalue-based test for heteroskedasticity
… of heteroskedastic models and tests for heteroskedasticity. We reconsider the minimum norm quadratic unbiased estimation (MINQUE) to obtain an alternative estimator of variance-covariance matrix in heteroskedastic models. We derive the analytical expressions for the mean square errors …
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The Hausman test, and some alternatives, with heteroskedastic data
… using a robust covariance matrix estimator if heteroskedasticity is suspected. If instruments are weak (not highly correlated with the endogenous regressors), however, no test procedure is reliable. If the test is designed to choose between the least squares estimator and a consistent …
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Essays On Spatial Econometrics: Estimation Methods And Applications
… the disturbance terms with an unknown form of heteroskedasticity in the innovations. We first prove that the maximum likelihood estimator (MLE) is generally inconsistent when heteroskedasticity is not taken into account in the estimation. We show that the necessary condition for consistency of …
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Essays in financial econometrics
… large. For the first time in the literature, heteroskedasticity is explicitly modelled in deriving the terms in higher order MSE. Using the selection criteria makes GEL estimator more efficient under heteroskedasticity. Chapter 3 is the product of joint work with Victor Chernozhukov and Konrad …
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Accurate estimation of risk when constructing efficient portfolios for the capital asset pricing model
… we were able to model the autocorrelation and heteroskedasticity of the residuals.
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Dynamic and robust estimation of risk and return in modern portfolio theory
… when there is significant autocorrelation and heteroskedasticity in the residuals. Furthermore, the presence of outlying observations in the data leads to unreliable estimates when the ordinary least squares method is used. We find significant correlation in the residuals from different shares …
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Time-varying hedge ratio estimation for selected agricultural commodities and products
The use of autoregressive conditional heteroskedasticity (ARCH) models to estimate time-varying hedge ratios suggests that conventional procedures may not provide the optimal hedge ratios. However, the initial results using ARCH models raise several questions regarding time-varying hedge ratios. …
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Stock price fragility in an emerging market
… controlling for endogeneity, autocorrelation and heteroskedasticity in the model.
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Detecting Irregular Energy Consumption Through Analytical Techniques
… by the presence of multiple seasonalities and heteroskedasticity. Most established time series methods were developed on the assumption that the errors are<br/>homoskedastic, hence the prediction limits that are created from such established method will often fail in detecting irregular …
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Daily and intradaily stochastic covariance : value at risk estimates for the foreign exchange market
… has been devoted to multivariate conditional heteroskedasticity, in spite of the fact that securities are typically held in portfolios rather than in isolation. Recently, Kroner and Ng (1995) have introduced a method for nesting the four most commonly used multivariate GARCH models, allowing …
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Essays in volatility modelling
… propose a new model that allows for conditional heteroskedasticity in the volatility of asset returns and incorporates current return information into the volatility nowcast and forecast. Our model can capture most stylised facts of asset returns even with Gaussian innovations and is simple to …
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Acid rain provisions of the 1990 clean air amendments: affects on residential electric customers
… using the regression model above corrected for heteroskedasticity and serial correlation and compared with three estimates of increases in electric bills made before the Bill was passed.
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An emprical investigation into the relationship between exchange rate volatility and economic growth in Liberia (1980 TO 2012)
… used the generalised autoregressive conditional heteroskedasticity model to estimate volatility. The order of integration of the variables was tested and the variables were found not to have the same order of integration. The bounds test confirmed co-integration between GDP growth, exchange rate …
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Return and volatility spillovers across financial markets in Central Europe
… VAR modelu identifikovaného prostřednictvím heteroskedasticity ve strukturálních šocích. Tyto me- tody nám umožnily popsat vztahy mezi trhy z různých pohledů, zachytit jejich časový vývoj a získat tak představu o transmisním mechanismu mezi těmito trhy ve střední Ev- ropě. Výsledky, mimo …
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Essays on Maximum Entropy Principle With Applications to Econometrics and Finance
… First, we propose ME autoregressive conditional heteroskedasticity model with demonstrating how we can extract informative functional from the data in the form of moment function. Second, the portfolio selection problem is considered using ME principle. We propose to use cross entropy measure as …
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Diameter Estimation of Eucalyptus spp. Plantations in Southern Brazil Using Global Ecosystem Dynamics Investigation Data and Support Vector Regression
… a robust model of tree diameter even given the heteroskedasticity and spatial auto correlation present in the GEDI data, which deleteriously impacted attempts at linear modeling. We could predict tree diameter in these plantations to within 1 cm using space-borne lidar, with broad implications …
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Essays on Testing Hypotheses When Non-stationarity Exists in Panel Data Models
… One caveat is that this may not be robust to heteroskedasticity of the error terms, but it is robust to heterogenous AR parameters across individuals. The Monte Carlo simulations in support of all the results are also provided in this essay.</p> <p>The second essay discusses testing hypotheses …
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Impacto da volatilidade na otimização de portfólios financeiros
… (generalized autoregressive conditional heteroskedasticity ou GARCH, na sigla em inglês) e a volatilidade implícita. Os dois primeiros métodos têm como subjacentes dados históricos dos instrumentos financeiros, sendo que a volatilidade implícita é a volatilidade esperada pelo mercado, …
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