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Field of Research : Stochastic Analysis And Modelling
Field of Research : Financial Econometrics
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  • Funded Activity

    Discovery Projects - Grant ID: DP0773965

    Funder
    Australian Research Council
    Funding Amount
    $450,000.00
    Summary
    The Modelling and Assessment of Credit Default Risk. This project will deliver an enhanced set of methodologies for the quantification and management of credit default risk. These outcomes will benefit researchers both in academia and in Australian financial institutions as research into credit risk has been active in recent years, due to the impending adoption by financial institutions of the Basel II accord on risk assessment. The outcomes will provide a strong academic methodology applied to .... The Modelling and Assessment of Credit Default Risk. This project will deliver an enhanced set of methodologies for the quantification and management of credit default risk. These outcomes will benefit researchers both in academia and in Australian financial institutions as research into credit risk has been active in recent years, due to the impending adoption by financial institutions of the Basel II accord on risk assessment. The outcomes will provide a strong academic methodology applied to credit default risk by Australian financial institutions and the Australian financial regulator. This research has the potential to enhance the competitivemess of Australia's financial sector.
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    Funded Activity

    Discovery Projects - Grant ID: DP1095177

    Funder
    Australian Research Council
    Funding Amount
    $285,000.00
    Summary
    The modelling and estimation of volatility in energy markets. The growing trend of deregulation of energy markets poses important problems for users and suppliers of energy as well as for government policy makers. In particular it has become necessary to manage the risk of unexpected load and price fluctuations. One of the main challenges concerns the extreme volatility of prices and the evaluation of derivative prices and hedging ratios to take account of volatility. The outcomes of project wil .... The modelling and estimation of volatility in energy markets. The growing trend of deregulation of energy markets poses important problems for users and suppliers of energy as well as for government policy makers. In particular it has become necessary to manage the risk of unexpected load and price fluctuations. One of the main challenges concerns the extreme volatility of prices and the evaluation of derivative prices and hedging ratios to take account of volatility. The outcomes of project will be of benefit to all participants in Australian energy markets who need to use derivative positions to hedge energy risk. This issue has become important due to the increasing national focus on efficient use of energy resources.
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    Funded Activity

    Linkage Projects - Grant ID: LP0347295

    Funder
    Australian Research Council
    Funding Amount
    $69,099.00
    Summary
    Censored Regression Techniques for Credit Scoring. This project will apply censored regression techniques to a loans database from the industry partner, the ANZ bank. We will accurately estimate the actual time to loan repayment, rather than simply the risk of default. In a novel approach for credit scoring we will build a model using current, right-censored, rather than historic data, incorporating loans that are not yet repaid but are underway and clearly have a length of loan longer than obse .... Censored Regression Techniques for Credit Scoring. This project will apply censored regression techniques to a loans database from the industry partner, the ANZ bank. We will accurately estimate the actual time to loan repayment, rather than simply the risk of default. In a novel approach for credit scoring we will build a model using current, right-censored, rather than historic data, incorporating loans that are not yet repaid but are underway and clearly have a length of loan longer than observed. This approach has the immense advantage of being able to reflect contemporary borrowing patterns in the model, rather than relying on historic trends.
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