Professor Tony Hall

Hall, A.D. & Satchell, S.E. 2009, 'Computing optimal mean/downside risk frontiers: The role of ellipiticity' in Stephen Satchell (eds), Optimizing optimization: The next generation of optimization applications and theory, Academic Press, US, pp. 179-199.

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.

Bird, R.G., Hall, A.D., 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.
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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.

Hall, A.D. & 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.
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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.

Szidarovszky, F., Coppola, E., Long, J., Hall, A.D. & Poulton, M.M. 2007, 'A Hybrid Artificial Neural Network-Numerical Model for Ground Water Problems', Journal of Ground Water, vol. 45, no. 5, pp. 590-600.
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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, A.D. & Hautsch, N. 2006, 'Order aggressiveness and order book dynamics', Empirical Economics, vol. 30, no. 4, pp. 973-1005.
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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, A.D., Szidarovszky, F. & Zhao, J. 2005, 'Some notes on a dynamic model of international fishing', Pure Mathematics and Applications, vol. 15, no. 1, pp. 45-54.

Cameron, A.C. & Hall, A.D. 2003, 'A survival analysis of Australian equity mutual funds', Australian Journal of Management, vol. 28, no. 2, pp. 209-226.

Gerlach, R., Bird, R.G. & 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.

Hall, A.D., Hwang, S. & Satchell, S.E. 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.
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Bird, R.G., Gerlach, R. & Hall, A.D. 2001, 'The Prediction of Earnings Movements Using Accounting Data: An Update & Extension of Ou and Penman', Journal of Asset Management, vol. 2, no. 2, pp. 180-195.
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Hall, A.D., Skalin, J. & Terasvirta, T. 2001, 'A Nonlinear Time Series Model of El Nino', Environmental Modelling & Software, vol. 16, no. 2, pp. 139-146.
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A smooth transition autoregressive model is estimated for the Southern Oscillation Index, an index commonly used as a measure of El Ni?o 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 Ni?o 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 Ni?o Southern Oscillation a few months ahead.

Hall, A.D. & Kofman, P. 2001, 'Limits to Linear Price Behaviour: Future Prices Regulated by Limits', Journal of Future Markets, vol. 21, no. 5, pp. 463-488.

Hall, A.D. & Kofman, P. 2001, 'Regulatory Tools & Price Changes in Futures Markets', Australian Economic Papers, vol. 40, no. 4, pp. 520-540.
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Hall, A.D., Hautsch, N. & McCulloch, J.D. 2003, 'Estimating the intensity of buy and sell arrivals in a limit order book market', Stockholm, Sweden, August 2003 in 58th European Meeting of the Econometric Society, ed --, European Meeting of Economtric Society, Stickholm, Sweden, pp. 1-23.

Mercorelli, L.R., Michayluk, D.M. & Hall, A.D. 2008, 'Modeling Adverse Selection on Electronic Order-Driven Markets', Seminar Presentation, UBS, Sydney, Australia, May 2008.

Mercorelli, L., Michayluk, D.M., Hall, A.D. 2007, 'Modelling Adverse Selection on Electronic Order-Driven Markets', Seminar Paper, Reserve Bank of Australia, Sydney, Australia, November 2007.