Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0453870
Funder
Australian Research Council
Funding Amount
$102,900.00
Summary
Social science advanced data modelling, analysis and visualisation facility. This is an integrated facility for advanced social science data analysis, modelling and visualisation located at The University of Queensland. The collaborating institutions are UQ, ANU and Griffith University. The facility promotes deep collaborations between social scientists and quantitative methodologists (statisticians, biostatisticians, econometricians) to enable leading edge quantitative analyses of survey, spati ....Social science advanced data modelling, analysis and visualisation facility. This is an integrated facility for advanced social science data analysis, modelling and visualisation located at The University of Queensland. The collaborating institutions are UQ, ANU and Griffith University. The facility promotes deep collaborations between social scientists and quantitative methodologists (statisticians, biostatisticians, econometricians) to enable leading edge quantitative analyses of survey, spatial and population data, new developments in quantitative methodology for statistical modelling and data visualisation, enhanced international research linkages and advanced postgraduate research training.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
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. 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
Fractional Integration, Power Laws and Econometric Models: Some Methodological and Theoretical Developments. The fundamental objectives of this project are to: (i) Extend
current econometric practice and consider the use of power laws as
a basis for the construction of a more flexible and realistic
class of models for the analysis of economic and financial time
series. (ii) To develop inferential techniques appropriate for the
modelling of dynamic econometric systems that incorporate
struc ....Fractional Integration, Power Laws and Econometric Models: Some Methodological and Theoretical Developments. The fundamental objectives of this project are to: (i) Extend
current econometric practice and consider the use of power laws as
a basis for the construction of a more flexible and realistic
class of models for the analysis of economic and financial time
series. (ii) To develop inferential techniques appropriate for the
modelling of dynamic econometric systems that incorporate
structure characterized by power laws. This will be achieved by
building upon the class of fractionally integrated processes. New
econometric models and methodologies for the analysis of
non-stationarity series will be developed, along with the
associated theoretical results.Read moreRead less
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
Market Model of Implied Volatility. The outcomes of the project will constitute a new methodology with a wide range of tools to handle the market uncertainties with practical applications in the finance industry. Consequently, the benefits of this project to the nation include enhancing its scientific standing in the international community, the training of Australian researchers in forefront methods of modelling of complex stochastic systems and the benefits resulting from its commercially rele ....Market Model of Implied Volatility. The outcomes of the project will constitute a new methodology with a wide range of tools to handle the market uncertainties with practical applications in the finance industry. Consequently, the benefits of this project to the nation include enhancing its scientific standing in the international community, the training of Australian researchers in forefront methods of modelling of complex stochastic systems and the benefits resulting from its commercially relevant elements. Read moreRead less
Inference in partially non-stationary time series models. Economic theories typically specify the long-run relationship between economic variables. However, researchers usually examine the long-run features of the data by fitting a restrictive class of models using criteria that have only proven useful for short-term forecasting. In this project we consider alternative models and modelling strategies that are appropriate for the study of the long-run. We also develop computer intensive (bootstra ....Inference in partially non-stationary time series models. Economic theories typically specify the long-run relationship between economic variables. However, researchers usually examine the long-run features of the data by fitting a restrictive class of models using criteria that have only proven useful for short-term forecasting. In this project we consider alternative models and modelling strategies that are appropriate for the study of the long-run. We also develop computer intensive (bootstrap) methods, which will provide a much-needed improvement over the existing (asymptotic) methods for making inference about the long-run. Our research will lead to more reliable models for long-term planning in business, industry and government.Read moreRead less
Vector ARMA Models and Macroeconomic Modelling: Some New Methodology and Algorithms. Economic variables are strongly related to each other, as well as being strongly related to their recent history. As a result, good dynamic multivariate models are crucial for effective policy making and forecasting in areas of vital national importance such as monetary and fiscal policy, environmental policy and tourism. Our project advances the frontiers of knowledge in multivariate time series modelling. The ....Vector ARMA Models and Macroeconomic Modelling: Some New Methodology and Algorithms. Economic variables are strongly related to each other, as well as being strongly related to their recent history. As a result, good dynamic multivariate models are crucial for effective policy making and forecasting in areas of vital national importance such as monetary and fiscal policy, environmental policy and tourism. Our project advances the frontiers of knowledge in multivariate time series modelling. The outcome of this project will be immediately useful for macroeconomic policy makers such as the Reserve Bank of Australia and the Treasury, and for industry bodies such as Tourism Australia. 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