Russ Moro

Research Interests

• Company rating, risk evaluation, bankruptcy analysis, robust event forecasting
• Decision making under bounded rationality, behavioural finance, estimation of preferences and risk perception
• The propagation of shocks, macroeconomic analysis in frequency domain
• Non-parametric and semi-parametric statistical techniques esp. support vector machines, ensemble methods, boosting

Teaching

• 5503 Securities and Investment (from September 2009)
• 3XXX Risk Management (a new module for 2010)

Other Affiliations

• Senior Economist, German Institute for Economic Research econ (DIW econ)
• Consultant, Deutsche Bundesbank

Recent Publications

• Analysis of the Predictors of Default for Portuguese Firms, with A. I. Lacerda (December 2008).
  Abstract: The paper presents an insolvency risk analysis of Portuguese companies with three techniques: logistic regression, discriminant analysis and support vector machines (SVM). It identifies the most critical predictors of default based on the accounting, employee and debt concentration data. A comparison of the three methods reveals a superiority of SVM. Non-financial information such as employee data and the debt concentration index appear to be strong predictors of default.
• Modelling Default Risk with Support Vector Machines, with S. Chen and W. Härdle, Journal of Quantitative Finance (accepted for publication in January 2009, )
• Empirical Pricing Kernels and Investor Preferences, with K. Detlefsen and W. Härdle, Journal of Mathematical Methods in Economics and Finance (accepted for publication in March 2009)

Recent Presentations

• Methods of Economic Modelling, 14 August 2009, The Institute for Prospective Technological Studies (IPTS) of the European Commission.
  Outline: Estimation of non-linear dependencies (e.g. the dependence of entrepreneurial activity from income and age; estimation of the optimal growth rates). Non-parametric techniques (non-parametric regression and classification). Non-linear classification with support vector machines (SVM). Long-term economic forecasting (e.g. the Limits to Growth study). Stochastic forecasting; the Monte Carlo approach. Ensemble prediction as a way of incorporating "soft" information. Parallel computing in forecasting; reprogrammable microchips (FPGA) as an alternative to cluster computing.
• Structural Changes in the European Knowledge Economy and Society: Long-Term Economic Forecasting, 22 October 2009, Copenhagen Business School (CBS).

Announcements

• I am looking for postgraduate students who would like to write their PhD thesis in one of my research areas. Please contact me if you are interested.
• British Academy Funding News. Research funding to postdoctoral level scholars in all subjects within the remit of humanities and social sciences.
• Brunel university students can access Mathematica on L:\CC\math6021\userinfo\Mathematica 6.0.2.1 and MATLAB on L:\CC\matlab7r14sp3\userinfo\MATLAB 7.1\MATLAB 7.1. You can request a home use license for Mathematica at http://www.wolfram.com/siteinfo/homeuse. The form will require you to enter your license number. Please contact me to receive it.
• All staff members and studens of Brunel University have a possibility of setting up their own web page at people.brunel.ac.uk. The instructions you can find on the Brunel Intranet. The required software for setting up a page and uploading files is available here.

Safety Last or Risk Management in the Times of a Recession

Today finding a suitable solution for managing risks can spell a difference between a successful operation and a failure. Managers that could successfully navigate their companies through bull and bear markets alike know that company revenues are only half the story. Sustainability of cash streams and steady growth require protection against adverse effects of market volatility. Assessment of the downside potential of risk is an integral part of any long-term strategy.

Risk can affect a company in many ways. A company that borrows at fixed interest rates has changing revenues and may not be able to pay interest. At the same time its customers can default on their obligations. Macroeconomic situation, exchange rates, technological cycles are sources of uncertainty and have to be dealt with.

Measurement of risk is not as easy as calculating revenues since risk appears when something may go wrong. It also may not. The relation between risk and financial performance indicators is obscure and requires complex risk management solutions. The importance of choosing the suitable solution cannot be overestimated: a correct risk assessment is crucial in increasing efficiency and avoiding potential pitfalls.

This is especially true now when new financial regulations inspired by Basel Capital Accord II allow individual companies to estimate their risks independently. Excessive conservatism in assessing risks due to the application of unreliable risk management solutions leads to high capital reserve requirements and negatively affects profitability. Providing investors with a tool that they can trust is therefore a single most important step in assessing risks.

The evolving financial crisis has increased the demand for risk management. In my research I am looking for the most accurate methods of financial risk assessment and develop the procedures for risk mitigation based on statistical, behavioural and macroeconomic analysis.

Links

Compañero, no hay camino. Se hace camino al andar.                My friend, there is no road. You make the road as you walk.