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New approaches to the statistical modelling of financial risk: combining structural information with flexible, computationally-intensive non-parametric methods. The aims of this project are to provide a range of novel, rigorous, flexible, statistical methods to assess portfolio risk, with due attention to behaviour of its constituent components; to obtain greater understanding of the complexities of risk; and to give students research training in the nexus of statistics and finance. The anticip ....New approaches to the statistical modelling of financial risk: combining structural information with flexible, computationally-intensive non-parametric methods. The aims of this project are to provide a range of novel, rigorous, flexible, statistical methods to assess portfolio risk, with due attention to behaviour of its constituent components; to obtain greater understanding of the complexities of risk; and to give students research training in the nexus of statistics and finance. The anticipated outcomes of this project will be detailed knowledge of extremal behaviour in portfolios, improved methods for calibrating risk, advances in non-parametric methods in finance, a prototype practitioner toolkit for assessing risk, and high-calibre graduates to contribute to Australia's research capacity.Read moreRead less
Regional Dimensions: New Models for Analysis of the Spatial Effects of Policy, Socio-Demographic and Economic Changes. This project aims to substantially improve the decision-support tools available to State and Territory governments by providing them with, first, far more detailed small area data than has previously been available, via the creation of a synthetic small area household database and, second, with the capacity to assess the current and future impact of possible policy reforms and l ....Regional Dimensions: New Models for Analysis of the Spatial Effects of Policy, Socio-Demographic and Economic Changes. This project aims to substantially improve the decision-support tools available to State and Territory governments by providing them with, first, far more detailed small area data than has previously been available, via the creation of a synthetic small area household database and, second, with the capacity to assess the current and future impact of possible policy reforms and likely social, demographic and economic changes at the small area level, through the construction of microsimulation models on top of the synthetic household data.Read moreRead less
A new class of statistical methods for analysing long memory time series models with heteroskedasticity. This project will result in a class of statistical methods that will aid policy makers and financial analysts when examining and predicting key international and Australian macroeconomic and financial variables that exhibit long memory. Leading applications of long memory modelling in the literature include GDP, CPI, asset pricing models, stock returns, exchange rates and interest rates. It w ....A new class of statistical methods for analysing long memory time series models with heteroskedasticity. This project will result in a class of statistical methods that will aid policy makers and financial analysts when examining and predicting key international and Australian macroeconomic and financial variables that exhibit long memory. Leading applications of long memory modelling in the literature include GDP, CPI, asset pricing models, stock returns, exchange rates and interest rates. It will be possible to robustly and efficiently analyse such series in the presence of changes in variability, such as the overall reduction in variability that has occurred since the 1970's, called the "Great Moderation". The utility of the new methods will be demonstrated by a robust and efficient analysis of the Purchasing Power Parity hypothesis.Read moreRead less
Distributional Consequences of Mass-Market Higher Education in Business. Increased access to tertiary education has not been evaluated for its effects on the full spectrum of individuals served by the tertiary sector. Using longitudinal data on entire student populations at university business faculties, this project will provide the first Australian evidence on the trade-offs amongst the educational success of students with different levels of preparation that occur when those with poorer prep ....Distributional Consequences of Mass-Market Higher Education in Business. Increased access to tertiary education has not been evaluated for its effects on the full spectrum of individuals served by the tertiary sector. Using longitudinal data on entire student populations at university business faculties, this project will provide the first Australian evidence on the trade-offs amongst the educational success of students with different levels of preparation that occur when those with poorer preparation are added to classrooms. Short-term performance and medium-term attrition, a recent educational policy focus, will be evaluated. Theoretically grounded recommendations will result for undergraduate program design to suit a student population with varying levels of university preparation.Read moreRead less
Stochastic Index Numbers and Their Application in Accounting, Economics and Finance. Index numbers of prices, such as the Consumer Price Index and the All Ordinaries Index, are among the most important economic statistics for the whole economy. But despite their importance, currently constructed price indexes do not use all the information available in the underlying price data, namely the dispersion among the individual prices. This project will develop and apply a methodology for a new approa ....Stochastic Index Numbers and Their Application in Accounting, Economics and Finance. Index numbers of prices, such as the Consumer Price Index and the All Ordinaries Index, are among the most important economic statistics for the whole economy. But despite their importance, currently constructed price indexes do not use all the information available in the underlying price data, namely the dispersion among the individual prices. This project will develop and apply a methodology for a new approach to index numbers that incorporates this information and leads to tractable ways of estimating the whole distribution of the index value, rather than just one number. The practical usefulness of this mthodology will be demonstrated with applications in accounting (sustainable earnings), economics (real exchange rates) and finance (share prices).Read moreRead less
New Approaches to the Analysis of Count Time Series. The focus of this proposal is on the analysis of data that enumerate events over time. Occurrences of such count data abound in economics and business, examples being observations on insurance claims, loan defaults and individual product demand. This project develops a suite of innovative methods for modelling and predicting event counts. The methods explicitly accommodate both the discreteness of the data and possible complexities in its evo ....New Approaches to the Analysis of Count Time Series. The focus of this proposal is on the analysis of data that enumerate events over time. Occurrences of such count data abound in economics and business, examples being observations on insurance claims, loan defaults and individual product demand. This project develops a suite of innovative methods for modelling and predicting event counts. The methods explicitly accommodate both the discreteness of the data and possible complexities in its evolution over time. In so doing, they enable both accurate inferences regarding the dynamic structure of the data to be drawn and accurate forecasts of future event counts to be produced.Read moreRead less
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.Read moreRead less
New estimation and testing issues in nonlinear time series econometrics. The outcomes of this project will not only complement but also enhance the existing strengths of Australian researchers in the field of econometrics. The outcomes are also expected to help stabilise the national financial market for more accurate forecasts. It is also expected that the outcomes will provide novel models to respond to climate change and variability and to provide accurate warming estimates for improving the ....New estimation and testing issues in nonlinear time series econometrics. The outcomes of this project will not only complement but also enhance the existing strengths of Australian researchers in the field of econometrics. The outcomes are also expected to help stabilise the national financial market for more accurate forecasts. It is also expected that the outcomes will provide novel models to respond to climate change and variability and to provide accurate warming estimates for improving the policy making process.Read moreRead less
Modelling a portfolio of financial assets: structure, estimation, testing and forecasting. Information regarding financial returns and risk is essential for optimal portfolio selection and asset management. Returns and risk have typically been analysed for individual assets. The project provides a theoretical solution to the important practical problem of modelling a portfolio of financial assets in realistic situations. The significance of the research is the development of a new approach to an ....Modelling a portfolio of financial assets: structure, estimation, testing and forecasting. Information regarding financial returns and risk is essential for optimal portfolio selection and asset management. Returns and risk have typically been analysed for individual assets. The project provides a theoretical solution to the important practical problem of modelling a portfolio of financial assets in realistic situations. The significance of the research is the development of a new approach to analyse a portfolio of returns and risk, and the determination of its applicability using numerical simulation techniques. The expected outcomes are an optimal practical method for analysing a portfolio of assets, a scientific monograph, and publications in leading international journals.Read moreRead less
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.Read moreRead less