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Field of Research : Econometrics
Australian State/Territory : VIC
Field of Research : Financial Econometrics
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  • Funded Activity

    Discovery Projects - Grant ID: DP0877424

    Funder
    Australian Research Council
    Funding Amount
    $231,000.00
    Summary
    Forecasting with single source of randomness state space models. The framework developed in this project, for identifying and extrapolating trends, seasonal patterns and economic cycles in time series, has a large and diverse range of useful applications in Australia. Some examples include its potential use in the development of appropriate monetary policy, its use to better inform finance markets of risk levels associated with shares, its use to forecast demand in supply chains to provide .... Forecasting with single source of randomness state space models. The framework developed in this project, for identifying and extrapolating trends, seasonal patterns and economic cycles in time series, has a large and diverse range of useful applications in Australia. Some examples include its potential use in the development of appropriate monetary policy, its use to better inform finance markets of risk levels associated with shares, its use to forecast demand in supply chains to provide a better service to customers, and its use in call centres to better tailor staff schedules to meet customer calls.
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    Funded Activity

    Discovery Projects - Grant ID: DP0987589

    Funder
    Australian Research Council
    Funding Amount
    $170,000.00
    Summary
    The US Interest Rate Conundrum and its Implications for Australia. The project generalises existing factor models of interest rates. The project will result in several benefits nationally as well as internationally. As U.S. interest rates and U.S. monetary policy in general are important determinants of interest rates in Australia, the project will lead to an improved understanding of the international mechanism linking interest rates. This will also provide a better framework in which to unders .... The US Interest Rate Conundrum and its Implications for Australia. The project generalises existing factor models of interest rates. The project will result in several benefits nationally as well as internationally. As U.S. interest rates and U.S. monetary policy in general are important determinants of interest rates in Australia, the project will lead to an improved understanding of the international mechanism linking interest rates. This will also provide a better framework in which to understand and monitor monetary policy in Australia. An important aspect of the project is the development of new testing procedures that improve upon existing nonparametric methods.
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    Funded Activity

    ARC Future Fellowships - Grant ID: FT0991045

    Funder
    Australian Research Council
    Funding Amount
    $834,200.00
    Summary
    A Bayesian State Space Methodology for Forecasting Stock Market Volatility and Associated Time-varying Risk Premia. Accurate prediction of stock market volatility is critical for effective financial risk management. Along with information on volatility embedded in historical stock market returns, the prices of options written on the underlying stocks also reflect the option market's assessment of future volatility. This project will exploit this dual data source in a completely new way, using it .... A Bayesian State Space Methodology for Forecasting Stock Market Volatility and Associated Time-varying Risk Premia. Accurate prediction of stock market volatility is critical for effective financial risk management. Along with information on volatility embedded in historical stock market returns, the prices of options written on the underlying stocks also reflect the option market's assessment of future volatility. This project will exploit this dual data source in a completely new way, using it to produce forecasts of both volatility itself and the premia factored into asset prices as a result of traders' perceptions of volatility risk. State-of-the-art statistical methods will be used to produce up-dates of the probability of extreme volatility and/or extreme risk aversion, as new market data becomes available each trading day.
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    Funded Activity

    Discovery Projects - Grant ID: DP0664121

    Funder
    Australian Research Council
    Funding Amount
    $220,000.00
    Summary
    New Statistical Procedures for Analysing Dependence in Non-Gaussian Time Series Data. In the economic, finance and business spheres, statistical data is often discrete, binary, strictly positive, or characterized by an uneven distribution of values above and below the average. Prominent examples are the high frequency financial data that have become accessible with the computerization of financial markets, including the number of trades in successive time intervals, the direction of price change .... New Statistical Procedures for Analysing Dependence in Non-Gaussian Time Series Data. In the economic, finance and business spheres, statistical data is often discrete, binary, strictly positive, or characterized by an uneven distribution of values above and below the average. Prominent examples are the high frequency financial data that have become accessible with the computerization of financial markets, including the number of trades in successive time intervals, the direction of price changes, the time between trades and the return on a financial asset over short periods. This project develops a range of new statistical tools that will enable both researchers and practitioners to analyze the dynamic behaviour in such data and thereby validate and implement a range of financial models.
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    Funded Activity

    Discovery Projects - Grant ID: DP0664926

    Funder
    Australian Research Council
    Funding Amount
    $250,000.00
    Summary
    New Procedures for Multiple Testing of Econometric Models. In discipline areas ranging from biological and medicine sciences to economics and commerce, very important decisions are made on the basis of statistical or econometric models. There is usually a high degree of uncertainty about the exact form the model should take and the data available to help decide on the best form of the model is often limited. The new procedures developed in this project will help statisticians and econometricians .... New Procedures for Multiple Testing of Econometric Models. In discipline areas ranging from biological and medicine sciences to economics and commerce, very important decisions are made on the basis of statistical or econometric models. There is usually a high degree of uncertainty about the exact form the model should take and the data available to help decide on the best form of the model is often limited. The new procedures developed in this project will help statisticians and econometricians make better decisions about the best form of their models. Our approach gives a new method of validating an estimated model before it is put to use to make critical decisions.
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    Funded Activity

    Discovery Projects - Grant ID: DP130104229

    Funder
    Australian Research Council
    Funding Amount
    $270,000.00
    Summary
    Trending time series models with non- and semi-parametric methods. The outcomes of this project will not only complement but also enhance the existing strengths and reputation of Australian researchers in the field of econometrics. The outcomes are also expected to help improve model building and forecasting from better models in climatology, economics, environmetrics and financial econometrics.
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    Funded Activity

    Discovery Projects - Grant ID: DP1095838

    Funder
    Australian Research Council
    Funding Amount
    $195,000.00
    Summary
    Nonparametric estimation of regression models with unknown error distributions. In discipline areas ranging from bioinformatics to economics and commerce, researchers make important decisions based on regression models, where the error density is often unknown. This project will result in a new sampling procedure that aims to choose bandwidth parameters for estimating the regression function and error density in nonparametric regression models. Our approach is of practical importance and can be .... Nonparametric estimation of regression models with unknown error distributions. In discipline areas ranging from bioinformatics to economics and commerce, researchers make important decisions based on regression models, where the error density is often unknown. This project will result in a new sampling procedure that aims to choose bandwidth parameters for estimating the regression function and error density in nonparametric regression models. Our approach is of practical importance and can be used to investigate relationships between variables that are observable in our economy and community. The nation will benefit from the output of this project by having its own experts in the area of proposed research, raising Australia's academic profile in econometrics and statistics.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP220100321

    Funder
    Australian Research Council
    Funding Amount
    $312,355.00
    Summary
    High-frequency Estimation of Term Structure Models at the Zero Lower Bound. This project aims to quantify monetary policy shocks as shifts of the entire term structure of interest rates, when the central bank’s policy rate is constrained at the near-zero level. The proposed method will use a high-dimensional panel of high frequency government bond data. The term structure and resultant policy shocks estimated at intra-day frequencies for major economies including Australia, will be made publicly .... High-frequency Estimation of Term Structure Models at the Zero Lower Bound. This project aims to quantify monetary policy shocks as shifts of the entire term structure of interest rates, when the central bank’s policy rate is constrained at the near-zero level. The proposed method will use a high-dimensional panel of high frequency government bond data. The term structure and resultant policy shocks estimated at intra-day frequencies for major economies including Australia, will be made publicly available. This project expects to deepen our understanding of how monetary policy decisions affect the macroeconomy in a near-zero interest-rate environment. This should provide significant benefits to policymakers for implementing and monitoring monetary policy in achieving desired economic outcomes.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP200101963

    Funder
    Australian Research Council
    Funding Amount
    $208,000.00
    Summary
    Australia's Resilience to Recession. This project aims to study why Australia differs from its OECD peers in that it has not had a recession for 27 years. It intends to generate knowledge by using economic models to solve 3 puzzles relating to Australia’s success: (i) why did foreign financial market shocks not spill over to the economy?; (ii) how has the resource curse that affects economies with a booming resource sector been avoided?; and (iii) what makes Australia special? Expected outcomes .... Australia's Resilience to Recession. This project aims to study why Australia differs from its OECD peers in that it has not had a recession for 27 years. It intends to generate knowledge by using economic models to solve 3 puzzles relating to Australia’s success: (i) why did foreign financial market shocks not spill over to the economy?; (ii) how has the resource curse that affects economies with a booming resource sector been avoided?; and (iii) what makes Australia special? Expected outcomes include the development of theoretical and empirical models that reflect the unique features of the Australian economy. This should provide significant benefits, including guidance to Australian and international policymakers on macroeconomic policies for resource-rich countries.
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    Funded Activity

    Discovery Projects - Grant ID: DP0985234

    Funder
    Australian Research Council
    Funding Amount
    $210,000.00
    Summary
    Non-parametric estimation of forecast distributions in non-Gaussian state space models. The production of accurate forecasts is arguably one of the most challenging tasks in economics, business and finance, where data often assume strictly positive, integer or binary values, or are characterized by many extreme values far from the average. This project will produce new, state-of-the-art statistical methods for generating accurate estimates of the probabilities attached to different possible futu .... Non-parametric estimation of forecast distributions in non-Gaussian state space models. The production of accurate forecasts is arguably one of the most challenging tasks in economics, business and finance, where data often assume strictly positive, integer or binary values, or are characterized by many extreme values far from the average. This project will produce new, state-of-the-art statistical methods for generating accurate estimates of the probabilities attached to different possible future values of such variables. Although far-ranging in scope, the techniques advocated will have particular impact in the financial sphere, where the concept of future risk is inextricably linked to the probability of occurrence of extreme values and, hence, to the future probability distribution of the financial variable.
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