Asset Market Interconnectedness and Exotic Options: The Mean Impact Surface. The project intends to develop models to price financial risk more accurately during periods of financial stress and increasing global interconnectedness. Specifically, it plans to develop a new class of latent factor models with time-varying loadings to model the interconnectedness of global financial markets during periods of financial stress. A key feature of the proposed model is the role of second-order conditional ....Asset Market Interconnectedness and Exotic Options: The Mean Impact Surface. The project intends to develop models to price financial risk more accurately during periods of financial stress and increasing global interconnectedness. Specifically, it plans to develop a new class of latent factor models with time-varying loadings to model the interconnectedness of global financial markets during periods of financial stress. A key feature of the proposed model is the role of second-order conditional moments of the underlying innovation processes in modelling asset return dynamics. The proposed model is characterised by higher order nonlinear structures which are captured graphically by the mean impact surface. The project also plans to develop a new class of tests to detect higher order dependencies among asset returns in the presence of time-varying volatility, and to investigate the implications for constructing portfolios with exotic options to hedge risk during financial crises.Read moreRead less
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.
Discovery Early Career Researcher Award - Grant ID: DE150100708
Funder
Australian Research Council
Funding Amount
$352,000.00
Summary
Understanding the Linkage of Public and Private Risk in the Global Economy. This project aims to develop a richly detailed model of the global financial system including both public and private institutions. By treating the system as a network of interconnected entities, this project aims to introduce new techniques to map and to trace the evolution of risk in the financial system, to forecast the spillover of risk between entities in the system, and to conduct counterfactual analysis of potenti ....Understanding the Linkage of Public and Private Risk in the Global Economy. This project aims to develop a richly detailed model of the global financial system including both public and private institutions. By treating the system as a network of interconnected entities, this project aims to introduce new techniques to map and to trace the evolution of risk in the financial system, to forecast the spillover of risk between entities in the system, and to conduct counterfactual analysis of potential policy measures. This project will investigate the link between spillover intensity and the existing research on extreme events in financial data. By studying how the recent crisis spread through the global financial system, this project aims to enhance our ability to foresee future crises and to mitigate their impact and costs.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
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 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
The econometrics of gravity models of trade: a re-assessment. This research will lead a much greater understanding of the empirical determinants of trade flows between countries. This project will apply cutting-edge data econometric techniques to the popular Gravity model of international trade flows. These more appropriate techniques will shed more light on some previous puzzling findings, such that regional trade agreements had little, or no, affect on trade.
Discovery Early Career Researcher Award - Grant ID: DE170100644
Funder
Australian Research Council
Funding Amount
$371,000.00
Summary
Nonlinear econometric panel models with fixed effects. This project aims to develop effective quantitative methods tailored to policy questions in public health and international trade. Many nonlinear panel models are essential to answer policy-relevant research questions, but cannot estimate key objects of interest, while default procedures for inference are often misleading, making magnitudes of identified effects impossible to quantify. This project will develop methods to overcome these limi ....Nonlinear econometric panel models with fixed effects. This project aims to develop effective quantitative methods tailored to policy questions in public health and international trade. Many nonlinear panel models are essential to answer policy-relevant research questions, but cannot estimate key objects of interest, while default procedures for inference are often misleading, making magnitudes of identified effects impossible to quantify. This project will develop methods to overcome these limitations for many econometric models, and apply them to important models in health economics and international trade. Such improvements are expected to reduce risk in public decision-making, resulting in better and more effective policies.Read moreRead less