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 15 of 15 for “"Vector Autoregressive (VAR) model"”.
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Macroeconomic Forecasting: Statistically Adequate, Temporal Principal Components
… At the outset, PCA is viewed as a statistical model derived from the reparameterization of the Multivariate Normal model in Spanos (1986). To motivate a PCA forecasting framework prioritizing sound model assumptions, it is demonstrated, through simulation experiments, that model …
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Asymmetric effects of monetary policy: A Markov-Switching SVAR approach
… the effects of monetary policy on macroeconomic variables in Botswana as a developing small macro-economy using the Markov-switching structural vector autoregressive (MS-SVAR) framework, utilising time-series data from 1994: Q1 to 2019: Q4. The study makes use of bank rate (interest rate), …
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Effects of Foreign Aid in SADC Region: A Case for Malawi
… indicated a short term relationship among the variables, hence the Vector Autoregressive (VAR) Model was used together with Ordinary Least Squares (OLS) to study the effect of Official Development Aid to Human Development Index and the effect of Official Development Aid to Gross Domestic …
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On international monetary environment and stock returns
… However, all of these articles assume the error variance to be constant, i.e., the articles use homoscedastic models instead of more general heteroscedastic models. This thesis extends the existing literature in several ways. Firstly, the generalized autoregressive conditional heteroscadestic …
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Investigating the Insurance – Growth Nexus from a Low-Income Country: Perspective of Malawi
… augmented Auto Regressive Distributed Lag (ARDL) model to study the relationship between insurance market activities and economic growth using insurance penetration to stand for insurance activities in Malawi. The results showed that there was neither a linear nor non-linear long run relationship …
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Modeling Strategies for Large Dimensional Vector Autoregressions
The vector autoregressive (VAR) model has been widely used for describing the dynamic behavior of multivariate time series. However, fitting standard VAR models to large dimensional time series is challenging primarily due to the large number of parameters involved. In this thesis, we propose two …
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Modeling nonlinear, nonstationary, vector time series : methods and applications.
Methods for modeling nonlinear time series provide ways to extract and describe information from complex and dynamic processes. The class of nonlinear time series models is large. Rather than be exhaustive, we provide a review of two popular classes of nonlinear time series models: Momentum …
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Pre- and post-retirement asset allocation: a simulation of retirement investment strategies for agricultural producers
… of the farm land being leased. The analytical model simulates the annual cash flows of a commercial agricultural operation for each investment scenario over a 30-year period. Stochastic rates of return, generated using a vector-autoregressive (VAR) model, are incorporated into the simulation …
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The sectoral analysis of business cycles: the role of aggregate and disaggregate shocks
… of this study is a multi-sector business cycle model developed by Long and Plosser (1983). This model is used to motivate a trivariate Vector Autoregressive (VAR) model, called Sector-by-Sector model, to establish the causal link between sectoral and aggregate output fluctuations. Then the …
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Network Analysis of the Financial Sector: A Comprehensive Perspective with Adaptive Joint LASSO Method
… The thesis focuses on this important topic from various angles to answer the following questions: • How can machine learning techniques help to improve financial network studies, the analysis of high dimensional time series? • How can structural changes in financial networks efficiently examined …
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Positional Momentum and Liquidity Portfolio Management
… and trade volume changes predicted by a bivariate Vector Autoregressive (VAR) model. Chapter one provides some facts about the relationship between return and trade volume changes and the way they have been computed in general. It begins by investigating the simple VAR model to see if we …
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Three Essays in Financial Economics
… the Eurozone stock markets. Using a generalised vector autoregressive (VAR) model, we introduce a new measure of liquidity spillovers. We find strong evidence of interconnection across countries. We also test the existence of liquidity contagion using a dynamic version of our static spillover …
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Market Efficiency and Volatility Spillovers in the Amman Stock Exchange: A Sectoral Analysis
… the new industry grouping or applied the multivariate General Autoregressive Conditional Heteroscedasticity (GARCH) model to test for time-varying variance and correlations between sectoral index returns in the ASE. This thesis tries to fill this gap in the literature by investigating market …
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Does the inclusion of climate variables improve tourism demand forecasting performance?
… study is to assess whether incorporating climate variables in econometric and combination forecasting models can improve tourism demand forecasting performance. Climate conditions are important tourism resources which can influence tourists’ decision as to when and where to travel, however, our …
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Hierarchical Bayesian Models for Multimodal Neuroimaging Data
… First, we propose an integrative predictive modeling framework for neuroimaging data with spatial structure, such as positron emission tomography or structural MRI. The method provides a unified framework for the identification of pathologic subgroups, identification of imaging biomarkers …