Financial Risk Processes: Stochastic and Statistical Models and their Applications. On the one hand, the misuse of complex financial instruments has contributed to recent major disasters in the Australian financial and insurance industries; on the other hand, great benefits can be obtained by correct use of these kinds of instruments, to share risk between markets and segments of markets. The overall research effort in Australia in these areas is relatively small. This project will target the de ....Financial Risk Processes: Stochastic and Statistical Models and their Applications. On the one hand, the misuse of complex financial instruments has contributed to recent major disasters in the Australian financial and insurance industries; on the other hand, great benefits can be obtained by correct use of these kinds of instruments, to share risk between markets and segments of markets. The overall research effort in Australia in these areas is relatively small. This project will target the development of cutting edge technologies underlying the use of financial derivatives, not presently studied in this country or elsewhere, by bringing together a variety of top level international researchers in an integrated effort to lift the Australian understanding and application of this methodology.Read moreRead less
Stochastic Analysis with a View to Applications in Financial Risk Processes. Recent decades have seen explosive growth in applications of probability theory and statistics to the modelling of risk in finance and insurance. An intensive theoretical investigation into passage time and other problems for Levy and other continuous time processes will be applied to financial risk analyses. Related investigations will involve perpetuities and stochastic volatility models for price series. Outcomes ....Stochastic Analysis with a View to Applications in Financial Risk Processes. Recent decades have seen explosive growth in applications of probability theory and statistics to the modelling of risk in finance and insurance. An intensive theoretical investigation into passage time and other problems for Levy and other continuous time processes will be applied to financial risk analyses. Related investigations will involve perpetuities and stochastic volatility models for price series. Outcomes will include the development of new theory in probability and statistics, the initiation and reinforcement of collaborative ties with major international research figures, and the fostering of contacts with the finance industry.Read moreRead less
Problems of identification and inference for 'non-standard' models in complex systems with special reference to finance and teletraffic. The project is concerned with 'non-standard' models needed to deal with complex systems, such as those exhibiting scaling and fractal properties. There is a focus on methods for dealing with heavy tailed distributions and long range dependent observations, for which most standard statistical methods break down, and on applications in finance and telecommunicati ....Problems of identification and inference for 'non-standard' models in complex systems with special reference to finance and teletraffic. The project is concerned with 'non-standard' models needed to deal with complex systems, such as those exhibiting scaling and fractal properties. There is a focus on methods for dealing with heavy tailed distributions and long range dependent observations, for which most standard statistical methods break down, and on applications in finance and telecommunications. An important part of the project concerns model validation for Heyde's fractal activity time geometric Brownian motion model, a candidate minimal description risky asset model to replace the geometric Brownian motion paradigm.Read moreRead less
Stochastic analysis and the development and application of financial risk processes. Ensuring the stability of Australia's financial system requires an understanding of the complex financial instruments, strategies and technologies that have evolved in recent years. A strong well-integrated research effort in stochastic analysis with particular application to financial markets is fundamental for measuring and managing risk, to protect and preserve a well functioning system, and to inform policy ....Stochastic analysis and the development and application of financial risk processes. Ensuring the stability of Australia's financial system requires an understanding of the complex financial instruments, strategies and technologies that have evolved in recent years. A strong well-integrated research effort in stochastic analysis with particular application to financial markets is fundamental for measuring and managing risk, to protect and preserve a well functioning system, and to inform policy debate on financial strategies and insurance liabilities.
These challenges are global and require extensive international research collaboration and interaction. The present project will enhance Australia's contributions in this area and facilitate its global impact more than is possible through individual efforts.Read moreRead less
Prediction, inference and their application to modelling correlated data. This project aims to create new, improved methods for prediction and making inference about predictions for a variety of correlated data types through inventing sophisticated and novel resampling schemes such as the generalised fast bootstrap and repeated partial permutation. The research will impact on both the theory and practice of statistics and on substantive fields which use mixed or compositional models to analyse d ....Prediction, inference and their application to modelling correlated data. This project aims to create new, improved methods for prediction and making inference about predictions for a variety of correlated data types through inventing sophisticated and novel resampling schemes such as the generalised fast bootstrap and repeated partial permutation. The research will impact on both the theory and practice of statistics and on substantive fields which use mixed or compositional models to analyse dependent data. This will be a significant improvement in the assessment and stability of statistical models in areas such as social, ecological and geological sciences.Read moreRead less
Dimension reduction and model selection for statistically challenging data. This project aims to develop a deep theoretical understanding of the relationship between various dimension reduction and model selection methods used in statistical model building, and then use this understanding to develop new, improved methods of model building for statistically challenging data. The research will impact on both the theory and practice of statistics, and on substantive fields which collect and analyse ....Dimension reduction and model selection for statistically challenging data. This project aims to develop a deep theoretical understanding of the relationship between various dimension reduction and model selection methods used in statistical model building, and then use this understanding to develop new, improved methods of model building for statistically challenging data. The research will impact on both the theory and practice of statistics, and on substantive fields which collect and analyse these kinds of data. This will provide a significant improvement in the statistical model building in areas such as epidemiology, chemical and ecological sciences. The project is timely because of the increasing collection of large-dimensional, complex, correlated data sets in these and many other fields.Read moreRead less
Building models for complex data. The purpose of this project is to better understand the process of building statistical models and construct new methods for building models for particular kinds of complex data. The expected outcomes include a new way of thinking about model building and practical tools which together enable us to get more value out of analysing complex data.
Novel statistical methods for data with non-Euclidean geometric structure. This project aims to develop new flexible regression models and classification algorithms, along with robust and efficient inference methods, applicable to a wide range of non-Euclidean data types which arise in many fields of science, business and technology. There are serious flaws with currently available methods of analysis for non-Euclidean data. This project expects to transform such analyses by providing new quanti ....Novel statistical methods for data with non-Euclidean geometric structure. This project aims to develop new flexible regression models and classification algorithms, along with robust and efficient inference methods, applicable to a wide range of non-Euclidean data types which arise in many fields of science, business and technology. There are serious flaws with currently available methods of analysis for non-Euclidean data. This project expects to transform such analyses by providing new quantitative tools within a unifying framework. The anticipated project outcomes will be of mathematical interest and valuable in applications such as finance (predicting Australian stock returns); modelling electroencephalography data; Australian geochemical data, relating to sediments; and Australian X-ray tumour image data. Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE180100220
Funder
Australian Research Council
Funding Amount
$369,075.00
Summary
Statistics for manifold-valued data. This project aims to develop, and then implement, a new suite of fully flexible, interpretable and tractable models for manifold-valued data, along with robust and accurate estimation techniques for their parameters. Multivariate data with complicated constraints, such as manifold-valued data, is frequently encountered in the physical, biological and medical sciences, however it is difficult to define tractable statistical models and estimate their parameters ....Statistics for manifold-valued data. This project aims to develop, and then implement, a new suite of fully flexible, interpretable and tractable models for manifold-valued data, along with robust and accurate estimation techniques for their parameters. Multivariate data with complicated constraints, such as manifold-valued data, is frequently encountered in the physical, biological and medical sciences, however it is difficult to define tractable statistical models and estimate their parameters due to the curvature and nonlinear geometry of the sample space. The outcomes of the project are of direct mathematical interest as well as having significant interest to science and business disciplines where manifold-valued data is commonly observed.Read moreRead less
Prognosis based network-type feature extraction for complex biological data. This project aims to develop statistical tools that integrate high-throughput molecular data with biological knowledge to make discoveries in complex diseases. This project uses machine learning methods, statistical models and proteomic platforms to identify relationships among clinico-pathologic and molecular measurements. It will produce tools and insights that are intended to accelerate the process of biologically an ....Prognosis based network-type feature extraction for complex biological data. This project aims to develop statistical tools that integrate high-throughput molecular data with biological knowledge to make discoveries in complex diseases. This project uses machine learning methods, statistical models and proteomic platforms to identify relationships among clinico-pathologic and molecular measurements. It will produce tools and insights that are intended to accelerate the process of biologically and clinically significant discoveries in biomedical research. This project will help Australian researchers in statistics and users of statistics (from fields as diverse as biology, ecology, medicine, finance, agriculture and the social sciences) to make better predictions that are easier to understand.Read moreRead less