Tony Hall holds a PhD in econometrics (London School of Economics, 1976). He has taught econometrics at the Australian National University and the University of California, San Diego and finance at the School of Business, Bond University and the University of Technology, Sydney. He has publications in a number of the leading international journals in econometrics, economics and finance including the Review of Economics and Statistics, Review of Economic Studies, International Economic Review, Journal of Econometrics, Econometric Theory, Journal of Business & Economic Statistics, Biometrika, Journal of Futures Markets, Journal of Financial Markets and Journal of Banking and Finance. His research interests cover all aspects of financial econometrics.
Can supervise: YES
Applied financial econometrics, interest rate modelling, time series methods in econometrics and statistical inference in econometrics.
Finance; Financial Econometrics; Applied Finance.
Hall, AD, Satchell, SE & Spence, PJ 2015, 'Evaluating the impact of inequality constraints and parameter uncertainty on optimal portfolio choice', Applied Economics, vol. 47, no. 45, pp. 4801-4813.View/Download from: UTS OPUS or Publisher's site
We present new analytical results for the impact of portfolio weight constraints on an investor's optimal portfolio when parameter uncertainty is taken into account. While it is well known that parameter uncertainty and imposing weight constraints results in reduced certainty equivalent returns, in the general case, there are no analytical results. In a special case, commonly used in the funds management literature, we derive analytical expression for the certainty equivalent loss that does not depend on the risk aversion parameter. We illustrate our theoretical results using hedge fund data, from the perspective of a fund-of-fund manager. Our contribution is to formalize the framework to investigate this problem, as well as providing tractable analytical solutions that can be implemented using either simulated or asset manager returns.
This study contributes to our understanding of the liquidity replenishment process in limit order book markets. A measure of resiliency is proposed and quantified for different liquidity shocks through the impulse response functions generated from a high frequency vector autoregression. The model reveals a rich set of liquidity dynamics. Liquidity shocks were found to have immediate detrimental effects on other dimensions of liquidity but the replenishment process generally occurs quickly, indicating limit order books are resilient. Cross-sectionally, resiliency is found to be consistently high across all large stocks, consistent with competition for liquidity provision coming from computerized algorithms. For other stocks, greater variation in resiliency is observed, indicating more selective participation by these liquidity providers.
This article re-examines portfolio higher moments, skewness and kurtosis, to see whether this information can be used to improve portfolio construction and to diagnose any mis-specification of models for portfolio returns. In common with most discussion of quantitative portfolio risk, we assume a linear factor model framework, and some empirical calculations using data from the components of the Dow Jones Industrial Index are carried out. The major insight that we glean from this exercise is that a well-diversified portfolio of skewed stocks can have a symmetric distribution unless we pay some attention to the third moment structure. These ideas are likely to have some potential application to fund of fund construction and the matching of bespoke portfolios to the risk attributes of high-net worth investors.
Szidarovszky, F, Coppola, E, Long, J, Hall, T & Poulton, MM 2007, 'A Hybrid Artificial Neural Network-Numerical Model for Ground Water Problems', Journal of Ground Water, vol. 45, no. 5, pp. 590-600.View/Download from: UTS OPUS or Publisher's site
Numerical models constitute the most advanced physical-based methods for modeling complex ground water systems. Spatial and/or temporal variability of aquifer parameters, boundary conditions, and initial conditions (for transient simulations) can be assigned across the numerical model domain. While this constitutes a powerful modeling advantage, it also presents the formidable challenge of overcoming parameter uncertainty, which, to date, has not been satisfactorily resolved, inevitably producing model prediction errors. In previous research, artificial neural networks (ANNs), developed with more accessible field data, have achieved excellent predictive accuracy over discrete stress periods at site-specific field locations in complex ground water systems. In an effort to combine the relative advantages of numerical models and ANNs, a new modeling paradigm is presented. The ANN models generate accurate predictions for a limited number of field locations. Appending them to a numerical model produces an overdetermined system of equations, which can be solved using a variety of mathematical techniques, potentially yielding more accurate numerical predictions. Mathematical theory and a simple two-dimensional example are presented to overview relevant mathematical and modeling issues. Two of the three methods for solving the overdetermined system achieved an overall improvement in numerical model accuracy for various levels of synthetic ANN errors using relatively few constrained head values (i.e., cells), which, while demonstrating promise, requires further research. This hybrid approach is not limited to ANN technology; it can be used with other approaches for improving numerical model predictions, such as regression or support vector machines (SVMs).
Hall, AD & Hautsch, N 2007, 'Modelling the Buy and Sell Intensity in a Limit Order Book Market', Journal of Financial Markets, vol. 10, no. 3, pp. 249-286.View/Download from: UTS OPUS or Publisher's site
In this paper, we model the buy and sell arrival process in the limit order book market at the Australian Stock Exchange. Using a bivariate autoregressive intensity model we analyze the contemporaneous buy and sell intensity as a function of the state of the market. We find evidence that trading decisions are both information as well as liquidity driven. Confirming predictions from market microstructure theory traders submit market orders by inferring from the recent order flow and the book with respect to upper and lower tail expectations as well as trading directions. However, traders also tend to take liquidity when the liquidity supply is high. Moreover, we findevidence that traders pay more attention to recent order arrivals and the current state of the order book than to the past order flow.
Bird, R, Hall, T, Momente, F & Reggiani, F 2007, 'What Corporate Social Responsibility Activities are Valued by the Market?', Journal of Business Ethics, vol. 76, no. 2, pp. 189-206.View/Download from: UTS OPUS or Publisher's site
Corporate management is torn between either focusing solely on the interests of stockholders (the neo-classical view) or taking into account the interests of a wide spectrum of stakeholders (the stakeholder theory view). Of course, there need be no conflict where taking the wider view is also consistent with maximising stockholder wealth. In this paper, we examine the extent to which a conflict actually exists by examining the relationship between a company's positive (strengths) and negative (concerns) corporate social responsibility (CSR) activities and equity performance. In general, we find little evidence to suggest that managers taking a wider stakeholder perspective will jeopardise the interest of its stockholders. However, our findings do suggest that the market is not only influenced by the independent CSR activities, but also the totality of these activities and that the facets that they value do vary over time. It seems that most recently, the market has valued most firms that satisfied minimum requirements in the areas of diversity and environmental protection but were most proactive in the area of employee-relations.
In this paper, we study the determinants of order aggressiveness and traders' order submission strategy in an open limit order book market. Applying an order classification scheme, we model the most aggressive market orders, limit orders as well as cance
Hall, AM, Kofman, P & Manaster, S 2006, 'Migration of price discovery in semiregulated derivatives markets', Journal Of Futures Markets, vol. 26, no. 3, pp. 209-241.View/Download from: UTS OPUS or Publisher's site
This study investigates the information content of futures option prices when the underlying futures price is regulated and the futures option price is not. The New York Board of Trade (NYBOT) provides the empirical setting for this regulatory mismatch.
Gerlach, R, Bird, R & Hall, A 2002, 'Bayesian variable selection in logistic regression: Predicting company earnings direction', Australian and New Zealand Journal of Statistics, vol. 44, no. 2, pp. 155-168.View/Download from: Publisher's site
This paper presents a Bayesian technique for the estimation of a logistic regression model including variable selection. As in Ou & Penman (1989), the model is used to predict the direction of company earnings, one year ahead, from a large set of accounting variables from financial statements. To estimate the model, the paper presents a Markov chain Monte Carlo sampling scheme that includes the variable selection technique of Smith & Kohn (1996) and the non-Gaussian estimation method of Mira & Tierney (2001). The technique is applied to data for companies in the United States and Australia. The results obtained compare favourably to the technique used by Ou & Penman (1989) for both regions.
Hall, T, Hwang, S & Satchell, SE 2002, 'Using bayesian variable selection methods to choose style factors in global stock return models', Journal of Banking and Finance, vol. 26, no. 12, pp. 2301-2325.View/Download from: UTS OPUS or Publisher's site
Gerlach, R., Bird, R. & Hall, A.D. 2002, 'Bayesian variable selection in logistic regression: predicting company earnings direction', Australian & New Zealand Journal of Statistics, vol. 42, no. 2, pp. 155-168.View/Download from: UTS OPUS or Publisher's site
Hall, T & Kofman, P 2001, 'Limits to Linear Price Behaviour: Future Prices Regulated by Limits', Journal of Future Markets, vol. 21, no. 5, pp. 463-488.View/Download from: UTS OPUS or Publisher's site
A smooth transition autoregressive model is estimated for the Southern Oscillation Index, an index commonly used as a measure of El Niño events. Using standard measures there is no indication of nonstationarity in the index. A logistic smooth transition autoregressive model describes the most turbulent periods in the data (these correspond to El Niño events) better than a linear autoregressive model. The estimated nonlinear model passes a battery of diagnostic tests. A generalised impulse response function indicates local instability, but as deterministic extrapolation from the estimated model converges, the nonlinear model may still be useful for forecasting the El Niño Southern Oscillation a few months ahead.
Hall, A.D. & Satchell, S.E. 2010, 'Computing optimal mean/downside risk frontiers: The role of ellipiticity' in Satchell, S. (ed), Optimizing Optimization: The Next Generation of Optimization Applications and Theory, Elsevier, USA, pp. 179-199.View/Download from: UTS OPUS
The purpose of this chapter is to analyze and calculate optimal mean/downside risk frontiers for financial portfolios. Focusing on the twO important cases of mean/value at risk and mean/semivariance, we compute analytic expressions for the optimal frontier in the two asset case, where the returns follow an arbitrary (nonnormal) distribution. Our analysis highlights the role of the normality/ellipticity assumption in this area of research. Formulae for mean/variance, mean/expected loss, and meanlsemistandard deviation frontiers are presented under normality/ellipticity. Computational issues are discussed and two propositions that facilitate computation are provided. Finally, the methodology is extended to nonelliptical distributions where simulation procedures are introduced. These can be presented jointly with our analytical approach to give portfolio managers deeper insights into the properties of optimal portfolios.
Hall, A.D. & Hautsch, N. 2008, 'Order aggressiveness and order book dynamics' in Bauwens, L., Pohlmeier, W. & Veredas, D. (eds), High Frequency Financial Econometrics: Recent Developments, Physica-Verlag, USA, pp. 133-165.View/Download from: UTS OPUS
Pagan, A.R., Hall, A.D. & Martin, V. 1996, 'Modeling the term structure' in Maddala, G.S. & Rao, C.R. (eds), Handbook of Statistics, Elsevier, US, pp. 91-118.
Hall, A.D., Jacobs, J. & Pagan, A.R. 2013, 'Macroeconometric system modelling @ 75', Ken@75: Conference in Honour of Kenneth F. Wallis, Warwick, UK.
Hall, AD & Hautsch, N, 'A Continuous-Time Measurement of the Buy-Sell Pressure in a Limit Order Book Market'.
In this paper, we investigate the buy and sell arrival process in a limit order book market. Using an intensity framework allows to estimate the simultaneous buy and sell intensity and to derive a
continuous-time measure for the buy-sell pressure in the market. Based on limit order book data from the Australian Stock Exchange (ASX), we show that the buy-sell pressure is particularly influenced
by recent market and limit orders and the current depth in the ask and bid queue. We find evidence for the hypothesis that traders use order book information in order to infer from the price setting
behavior of market participants. Furthermore, our results indicate that the buy-sell pressure is clearly predictable and is a significant determinant of trade-to-trade returns and volatility.