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  Issue 17 | Archive November 2013

RMI Research Seminars
July - August 2013

On 23 July, Jorge Antonio Chan-Lau, a senior fellow at the Fletcher School of the Tufts University and a senior economist at the International Monetary Fund, gave a seminar at RMI. His paper analyzed different bank funding practices using contingent claim analysis, and contrary to earlier work built on the fundamental asset value of the bank rather than on its equity value. The results suggest that the incremental costs of bail-in debt and asset encumbrance are relatively small which may encourage their regulatory application. In addition, the use of bail-in debt could reduce risk-shifting incentives and reduce systemic risk in the banking sector. Jorge is author of the comprehensive how-to-manual, Systemic Risk Assessment and Oversight (Risk Books, 2013) and his research work, which has been published widely, covers capital markets, risk analysis, financial regulation, macro-prudential policy and asset allocation.

Separately, on 12 August Prof. Poon Ser-Huang, Professor of Finance at Manchester Business School, gave a research seminar themed ¡°Explaining Cross Sectional Variations in Risk Neutral to Real Default Probabilities Ratio¡±. Based on the Merton framework, her paper developed a model for the ratio of risk neutral to real default probabilities (DP). To test the model empirically, she and her co-authors used risk neutral default probabilities derived from daily Markit CDS spread from 2002 to 2011 and the corresponding physical measure default probabilities produced by RMI¡¯s CRI. Given that RMI DP estimates are available for over 60,400 firms from 106 economies, they suggested the model can help to meet the mandate in Basel III that requires the use of risk neutral DP in calculating the capital reserve for the protection against counter party risk.

CVI Coverage Expansion
2 August 2013

The coverage of the Corporate Vulnerability Index (CVI) has been expanded to include indices for Denmark, Norway, Sweden, Australia and Taiwan since 2 August. This added to its coverage across three geographic categories and a special portfolio, which already included the United States (USA), Eurozone (EMU), France (FRA), Germany (DEU), United Kingdom (GBR), China (CHN), Japan (JPN), Singapore (SGP) and the S&P 500 Index (SPP).

The CVI is a suite of indices produced by RMI's Credit Research Initiative (CRI), which use RMI’s Probabilities of Default of individual firms to produce bottom-up measures of credit risk in economies, regions and portfolios of special interest. The suite of CVIs is available in three distinctive types, namely, Value-weighted CVI, Equally-weighted CVI and Tail CVI.

RMI Joint Seminars
13 and 21 August 2013

On 13 August, Prof. Wolfgang Karl Härdle spoke at a Joint Seminar by RMI and the Department of Statistics and Applied Probability. Together with his co-authors, they analysed functional magnetic resonance imaging (fMRI) data on 17 subjects which were exposed to an investment decision task from Mohr et al. (2010b). Their classification analysis successfully confirms the estimated risk attitudes derived directly from subjects’ decision behaviour. Prof. Härdle is the Ladislaus von Bortkieviecz Chair Professor of Statistics, Humboldt-Universität zu Berlin. He is also Director of CASE – Center for Applied Statistics & Economics and Director of the Collaborative Research Center “Economic Risk”. His research focuses on dimension reduction techniques, computational statistics and quantitative finance.

On 21 August, Prof. Fan Jianqing gave a talk themed “A Random Walk in Big Data” at a collaborative research seminar organized by the RMI and the Department of Statistics and Applied Probability. Prof. Fan is Frederick L. Moore Professor of Finance at Bendheim Center for Finance, Chairman of Department of Operations Research and Financial Engineering, and Director of Committee of Statistical Studies at Princeton University, where he also directs both financial econometrics and statistics labs.

RMI Pedagogical Lectures
23 and 26 August 2013

Prof. Fan Jianqing of Princeton University gave two pedagogical lectures entitled “Estimation of Large Volatility Matrix” on 23 and 26 August respectively. During the two tutorial lectures, each lasting for two hours, he first gave an overview on the estimation of large volatility matrices and associated covariance matrices, which are prominently featured in risk assessment, portfolio allocation as well as financial econometrics. He then outlined the methods for large volatility matrix estimation based on factor models with known factors, which exhibit the conditional sparsity structure and include sparse covariance estimation as a specific case. Large covariance estimation with Latent Factors was also introduced.

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Published quarterly by Risk Management Institute, NUS
Editor: Ivy Wang (rmiwy@nus.edu.sg)