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Professor John Stachurski

Professor John Stachurski

Prof. Stachurski receives ARC Future Fellowship

8 November 2016

Professor John Stachurski from the ANU Research School of Economics has been recognised for outstanding research in the field of computational methods for solving modern asset pricing models, in the most recent round of Australian Research Council (ARC) funding.

A recipient of a Future Fellowship announced by ARC last week, Professor Stachurski has been awarded more than $AU800,000 to further his research.

The Future Fellowships scheme supports research in areas of critical national importance by giving outstanding researchers incentives to conduct their research in Australia.

Professor Stachurski’s research aims to solve a broad range of asset pricing models. The project will use modern hardware and computational tools, insights from economics literature and numerical analysis to provide a set of solution methods for such asset pricing models, and is expected to improve policy analysis and decision making under uncertainty.

CBE Communications sat down with Professor Stachurski to gain further insights into the project.

Can you provide a brief background on how the project came about?

The problem of pricing assets is a very interesting one. For example, consider the value of a holding a share in a company. The value of that share is determined by the expected net benefits it confers on the owner. One such benefit is future dividends. Another is the right to sell the share, possibly for a capital gain.  Thus, when we think of a fair price for the share, we need to take into account both dividends and future price, the latter being what we gain when we sell the share.  

Notice that we already have a kind of "tail-chasing" problem, where today's price depends on tomorrow's price, which in turn depends on the next day's price and so on ad infinitum.  This self-referential property adds an interesting layer of complexity to the mathematical analysis.

On top of that complexity, we also need to account for randomness (since dividends are random) and how individuals react to this randomness.  In other words, how do people react to risk? 

Yet another important factor is how people gather and respond to new information.

Economists are always striving to build better models of asset prices, and as they do so these models become more and more difficult to solve. When I visited New York University last year and discussed these issues with colleges there, I realized that some of the mathematical and computational problems associated with solving modern asset pricing models are closely related to certain techniques that I have managed to apply in other fields, such as optimal savings and investment. I felt sure that I could make a contribution to our understanding. That's how the project came about.

Is there a novel approach you’re taking to the project?

The approach is quite novel, both mathematically and computationally.  Here's one example: Previous approaches to solving asset pricing models tended to assume that random shocks could only occur within certain bounds.  That assumption can be reasonable, but increasingly we see the importance of what are called "tail events" --- large shocks, or just the risk of large shocks, that drive many market outcomes.  So the approach I'm proposing allows us to consider arbitrarily large shocks in any direction. 

Can you provide an example of the outcomes of the project on academia, public policy and everyday society/people?

The aim of the project is less about predicting prices of individual assets and more about developing useful models of asset prices.  Asset prices contain a great deal of information about people's expectations and perceptions of risk. With better models we can extract that information and use it to make better policy decisions.

The problems considered in the project lie at the intersection of mathematics, computation, statistics, economics and finance. The project will involve applying the knowledge of outstanding academics from these fields, providing a foundation to train young scientists to build skills and make their own contributions in these exciting areas.

Updated:   2 March 2017 / Responsible Officer:  CBE Communications and Outreach / Page Contact:  College Web Team