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on Risk Management |
| By: | David E Allen (School of Accounting Finance & Economics, Edith Cowan University); Akhmad R. Kramadibrata (School of Accounting Finance & Economics, Edith Cowan University); R. J. Powell (School of Accounting Finance & Economics, Edith Cowan University); Abhay Kumar Singh (School of Accounting Finance & Economics, Edith Cowan University) |
| Abstract: | The mining industry can be extremely volatile during times of economic downturn. We compare extreme risk in mining share portfolios from each of the worldÕs seven leading mining areas using Conditional Value at Risk (CVaR) which measures those risks beyond traditional Value at Risk (VaR) metrics. We also show how CVaR can be used to optimise portfolios and minimise extreme risk. We find significant differences between countries in CVaR as compared to standard deviation risk rankings, as well as differences in portfolios optimised using CVaR compared to portfolios using traditional variance methodology. This indicates that investors will not adequately minimise risk using traditional approaches.Classification-JEL: |
| Keywords: | Value at risk; Conditional value at risk; Mining share portfolios. |
| Date: | 2011–11 |
| URL: | http://d.repec.org/n?u=RePEc:ecu:wpaper:2011-06&r=rmg |
| By: | David E Allen (School of Accounting Finance & Economics, Edith Cowan University); Akhmad R. Kramadibrata (School of Accounting Finance & Economics, Edith Cowan University); R. J. Powell (School of Accounting Finance & Economics, Edith Cowan University); Abhay Kumar Singh (School of Accounting Finance & Economics, Edith Cowan University) |
| Abstract: | Whilst the Australian economy is widely considered to have fared better than many of its global counterparts during the Global Financial Crisis, there was nonetheless extreme volatility experienced in Australian financial markets. To understand the extent to which emerging Australia entities were impacted by these extreme events as compared to established entities, this paper compares entities comprising the Emerging Markets Index (EMCOX) to established entities comprising the S&P/ASX 200 Index using four risk metrics. The first two are Value at Risk (VaR) and Distance to Default (DD), which are traditional measures of market and credit risk. The other two focuses on extreme risk in the tail of the distribution and include Conditional Value at Risk (CVaR) and Conditional Distance to Default (CDD), the latter metric being unique to the authors, and which applies CVaR techniques to default measurement. We apply these measures both prior to and during the GFC, and find that Emerging Market shares show higher risk for all metrics used, the spread between the emerging and established portfolios narrows during the GFC period and that the default risk spread between the two portfolios is greatest in the tail of the distribution. This information can be important to both investors and lenders in determining share or loan portfolio mix in extreme economic circumstances. Classification-JEL: |
| Keywords: | Conditional value at risk; Conditional distance to default; Australian emerging markets |
| Date: | 2011–11 |
| URL: | http://d.repec.org/n?u=RePEc:ecu:wpaper:2011-11&r=rmg |
| By: | David E Allen (School of Accounting Finance & Economics, Edith Cowan University); Akhmad R. Kramadibrata (School of Accounting Finance & Economics, Edith Cowan University); R. J. Powell (School of Accounting Finance & Economics, Edith Cowan University); Abhay Kumar Singh (School of Accounting Finance & Economics, Edith Cowan University) |
| Abstract: | The severe bank stresses of the Global Financial Crisis (GFC) have underlined the importance of understanding and measuring extreme credit risk. The Australian economy is widely considered to have fared much better than the US and most other major world economies. This paper applies quantile regression and Monte Carlo simulation to the Merton structural credit model to investigate the impact of extreme asset value fluctuations on default probabilities of Australian companies in comparison to the USA. Quantile regression allows modelling of the extreme quantiles of a distribution which allows measurement of capital and PDs at the most extreme points of an economic downturn, when companies are most likely to fail. Daily asset value fluctuations of over 600 Australian and US investment and speculative entities are examined over a ten year period spanning pre-GFC and GFC. The events of the GFC also showed how the capital of global banks was eroded as defaults increased. This paper therefore also examines the impact of these fluctuating default probabilities on the capital adequacy of Australian and US banks. The paper finds highly significant variances in default probabilities and capital between quantiles in both Australia and the US, and shows how these variances can assist banks and regulators in calculating capital buffers to sustain banks through volatile times.Classification-JEL: |
| Keywords: | Probability of default; Quantile regression; Australian banks; United States banks. |
| Date: | 2011–11 |
| URL: | http://d.repec.org/n?u=RePEc:ecu:wpaper:2011-04&r=rmg |
| By: | Rania Hentati-Kaffel (Centre d'Economie de la Sorbonne); Jean-Luc Prigent (THEMA - Université de Cergy-Pontoise) |
| Abstract: | This paper deals with performance measurement of financial structured products. For this purpose, we introduce the SharpeOmega ratio, based on put as downside risk measure. This allows to take account of the asymmetry of the return probability distribution. We provide general results about the optimization of some standard structured portfolios with respect to the SharpeOmega ratio. We determine in particular the optimal combinaison of risk free, stock and call / put instruments with respect to this performance measure. We show that, contrary to Sharpe ratio maximization (Goetzmann et al., 2002), the payoff of the optimal structured portfolio is not necessarily increasing and concave. We also discuss about the interest of the asset management industry to reward high Sharpe Omega ratios. |
| Keywords: | Structured portfolio, performance measure, SharpeOmega ratio. |
| JEL: | C61 G11 |
| Date: | 2012–01 |
| URL: | http://d.repec.org/n?u=RePEc:mse:cesdoc:12002&r=rmg |
| By: | David E Allen (School of Accounting Finance & Economics, Edith Cowan University); Akhmad R. Kramadibrata (School of Accounting Finance & Economics, Edith Cowan University); R. J. Powell (School of Accounting Finance & Economics, Edith Cowan University); Abhay Kumar Singh (School of Accounting Finance & Economics, Edith Cowan University) |
| Abstract: | Using quantile regression, this article examines default risk of emerging and speculative companies in Australia and the United States as compared to established investment entities. We use two datasets for each of the two countries, one speculative and one established. In the US we compare companies from the S&P 500 to those on the Speculative Grade Liquidity Ratings list (Moody's Investor Services, 2010). For Australia, we compare entities from the S&P/ASX 200 to those on the S&P/ASX Emerging Companies Index (EMCOX). We also divide the datasets into GFC and Pre-GFC periods to examine default risk over different economic circumstances. Quantile Regression splits the data into parts or quantiles, thus allowing default risk to be examined at different risk levels. This is especially useful in measuring extreme risk quantiles, when corporate failures are most likely. We apply Monte Carlo simulation to asset returns to calculate Distance to Default using a Merton structural credit model approach. In both countries, the analysis finds substantially higher default risk for speculative as compared to established companies. The spread between speculative company and established company default risk is found to remain constant in Australia through different economic circumstances, but to increase in the US during the GFC as compared to pre-GFC. These findings are important to lenders in understanding, and providing for, default risk for companies of different grades through varying economic cycles.Classification-JEL: |
| Keywords: | Quantile regression; Emerging and speculative companies; extreme risk and return. |
| Date: | 2011–11 |
| URL: | http://d.repec.org/n?u=RePEc:ecu:wpaper:2011-05&r=rmg |
| By: | David E Allen (School of Accounting Finance & Economics, Edith Cowan University); R.R Boffey (School of Accounting Finance & Economics, Edith Cowan University); R. J. Powell (School of Accounting Finance & Economics, Edith Cowan University) |
| Abstract: | We apply a novel Quantile Monte Carlo (QMC) model to measure extreme risk of various European industrial sectors both prior to and during the Global Financial Crisis (GFC). The QMC model involves an application of Monte Carlo Simulation and Quantile Regression techniques to the Merton structural credit model. Two research questions are addressed in this study. The first question is whether there is a significant difference in distance to default (DD) between the 50% and 95% quantiles as measured by the QMC model. A substantial difference in DD between the two quantiles was found. The second research question is whether relative industry risk changes between the pre-GFC and GFC periods at the extreme quantile. Changes were found with the worst deterioration experienced by Energy, Utilities, Consumer Discretionary and Financials; and the strongest improvement shown by Telecommunication, IT and Consumer goods. Overall, we find a significant increase in credit risk for all sectors using this model as compared to the traditional Merton approach. These findings could be important to banks and regulators in measuring and providing for credit risk in extreme circumstances. |
| Keywords: | Asset Selection, Factor Model, DEA, Quantile Regression |
| Date: | 2011–02 |
| URL: | http://d.repec.org/n?u=RePEc:ecu:wpaper:2011-02&r=rmg |
| By: | David E Allen (School of Accounting Finance & Economics, Edith Cowan University); R.R Boffey (School of Accounting Finance & Economics, Edith Cowan University); R. J. Powell (School of Accounting Finance & Economics, Edith Cowan University) |
| Abstract: | The relative success of Australian and Canadian banks in weathering the Global Financial Crisis (GFC) has been noted by a number of commentators. Their earnings, capital levels and credit ratings have all been a source of envy for regulators of banks in Europe, America and the United Kingdom. The G-20 and the European Union have tried to identify the features of the Canadian and Australian financial systems which have underpinned this success in order to use them in shaping a revised international regulatory framework. Despite this perceived success, the impaired assets (also known as non-performing loans) of banks in both countries increased several fold over the GFC, and we investigate the determinants of this, using impaired assets as our measure of bank risk. Previous studies in other countries have tended to focus on the impact of bank specific factors, such as size and return on equity, in explaining bank risk. Our approach involves including those traditional variables, plus Distance to Default (DD), and a novel contagion variable, which is the effect of major global bank DD on Australian and Canadian banks. Using panel data regression over the period 1999-2008, we find that various balance sheet and income statement factors are not good explanatory variables for bank risk. In contrast, the contagion variable is significant in explaining Canadian and Australian bank risk, which suggests that prudential regulators should look to specifically allocate a portion of regulatory capital to deal with contagion effects.Classification-JEL: |
| Keywords: | Bank risk; Distance to default; Impaired assets; Panel regression. |
| Date: | 2011–11 |
| URL: | http://d.repec.org/n?u=RePEc:ecu:wpaper:2011-03&r=rmg |
| By: | Frank Schmielewski (Leuphana University of Lüneburg, Germany) |
| Abstract: | The present study is centered primarily on determining whether the German banking system is to be characterized by procyclical behavior from 2000 to 2011 and to what extent specific sectors of the German banking system showed significant balance sheet operations to increase their leverage within years of booming asset prices. First, the results of this study show that the different sectors of the German banking system operate their business more or less procyclically. Second, the study provides some empirical evidence that banks increasing their leverages during periods of extraordinary high returns provided in the financial markets preferred funding their assets by shortterm lending in the interbank market. Third, the study clarified that banks, preferring high leverages, can apparently be characterized by a high volatility of return on assets and low distances to default over the observation period. Finally, the examined regression models provide some empirical evidence that requirements on countercyclical capital buffers should be considered by regulatory authorities in the context of macroeconomic indicators. |
| Keywords: | Liquidity and leverage; financial crises, asset pricing; information and market efficiency; government policy and regulation, international financial markets, funding policy; financial risk and risk management; capital and ownership structure; countercyclical capital buffers; distance to default |
| JEL: | G01 G12 G14 G28 G15 G32 |
| Date: | 2012–01 |
| URL: | http://d.repec.org/n?u=RePEc:lue:wpaper:229&r=rmg |