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Socio-Economic Objective : Mathematical sciences
Field of Research : Econometrics
Australian State/Territory : NSW
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  • Funded Activity

    Discovery Projects - Grant ID: DP0985505

    Funder
    Australian Research Council
    Funding Amount
    $148,000.00
    Summary
    Bayesian Inference for Flexible Parametric Multivariate Econometric Modelling. The anticipated outcomes include the development of enhanced multivariate econometric models and innovative computationally intensive methods for their estimation. These models are used in numerous and diverse applications which are data-intensive and where more complete models will greatly enhance data-based decision-making. Results include improved information use in the wholesale electricity markets, in financial m .... Bayesian Inference for Flexible Parametric Multivariate Econometric Modelling. The anticipated outcomes include the development of enhanced multivariate econometric models and innovative computationally intensive methods for their estimation. These models are used in numerous and diverse applications which are data-intensive and where more complete models will greatly enhance data-based decision-making. Results include improved information use in the wholesale electricity markets, in financial market investment decision-making and for the assessment of the impact of internet advertising.
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    Funded Activity

    Discovery Projects - Grant ID: DP0666351

    Funder
    Australian Research Council
    Funding Amount
    $260,000.00
    Summary
    Bayesian choice modelling. Discrete choice models are important as they provide tools to help understand choice processes of decision makers. It remains a challenge to specify models with covariance structures flexible enough to capture complex patterns of cross-substitution between choices while being able to capture heterogeneity present in individual behaviour. We will develop a Bayesian approach to choice modelling that uses covariance selection to overcome these problems. This will train re .... Bayesian choice modelling. Discrete choice models are important as they provide tools to help understand choice processes of decision makers. It remains a challenge to specify models with covariance structures flexible enough to capture complex patterns of cross-substitution between choices while being able to capture heterogeneity present in individual behaviour. We will develop a Bayesian approach to choice modelling that uses covariance selection to overcome these problems. This will train researchers and raise the profile of Australia in an active research area that is important in the social sciences; substantive applications will be in health economics, but developments will also be relevant to cognate areas of biostatistics, epidemiology, and ecology.
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    Funded Activity

    Discovery Projects - Grant ID: DP0988579

    Funder
    Australian Research Council
    Funding Amount
    $520,000.00
    Summary
    Building flexible multivariate models and their application in Finance. The project will develop methods for analyzing the properties of dependent measurements that may evolve through time. The new methods will significantly improve on current best statistical practice and will be applied to important problems in the financial sector such as asset allocation and risk management. The financial sector is a vital part of the Australian economy and it is important to understand the joint behavior of .... Building flexible multivariate models and their application in Finance. The project will develop methods for analyzing the properties of dependent measurements that may evolve through time. The new methods will significantly improve on current best statistical practice and will be applied to important problems in the financial sector such as asset allocation and risk management. The financial sector is a vital part of the Australian economy and it is important to understand the joint behavior of financial assets in order to understand and allow for risk. The methods will have immediate application in other disciplines such as medicine, engineering and the environmental sciences. The project will train a postdoctoral student and three PhD students in cutting edge financial econometrics.
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