A Quantile Monte Carlo approach to measuring extreme credit risk

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.Asset Selection, Factor Model, DEA, Quantile Regression

Comparing Australian and US Corporate Default Risk using Quantile Regression

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:Probability of default; Quantile regression; Australian banks; United States banks.

Tail Risk for Australian Emerging Market Entities

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:Conditional value at risk; Conditional distance to default; Australian emerging markets

Volatility and correlations for stock markets in the emerging economies of Central and Eastern Europe : implications for European investors

This paper examines the European investment implications of the recent European Union (EU) expansion to encompass former Eastern bloc economies. What are the risk and return characteristics of these markets pre- and post-EU? What are the implications for investors within the Euro zone? Should investors diversify outside the Central and Eastern Europe (CEE)? The former Eastern bloc economies constitute emerging markets which typically offer attractive risk-adjusted returns for international investors. In this paper, we explore a number of aspects of this important issue and their implications for CEE based investors, culminating in a Markowitz efficient frontier analysis of these markets pre- and post-EU expansion

Circular dichroism of four-wave mixing in nonlinear metamaterials

Metamaterial engineering offers a route to combine unusual and interesting optical phenomena in ways that are rare or nonexistent in nature. As an exploration of this wide parameter space, we experimentally demonstrate strong cross-phase modulation and f

Socially-distributed cognition and cognitive architectures: towards an ACT-R-based cognitive social simulation capability

ACT-R is one of the most widely used cognitive architectures, and it has been used to model hundreds of phenomena described in the cognitive psychology literature. In spite of this, there are relatively few studies that have attempted to apply ACT-R to situations involving social interaction. This is an important omission since the social aspects of cognition have been a growing area of interest in the cognitive science community, and an understanding of the dynamics of collective cognition is of particular importance in many organizational settings. In order to support the computational modeling and simulation of socially-distributed cognitive processes, a simulation capability based on the ACT-R architecture is described. This capability features a number of extensions to the core ACT-R architecture that are intended to support social interaction and collaborative problem solving. The core features of a number of supporting applications and services are also described. These applications/services support the execution, monitoring and analysis of simulation experiments. Finally, a system designed to record human behavioral data in a collective problem-solving task is described. This system is being used to undertake a range of experiments with teams of human subjects, and it will ultimately support the development of high fidelity ACT-R cognitive models. Such models can be used in conjunction with the ACT-R simulation capability to test hypotheses concerning the interaction between cognitive, social and technological factors in tasks involving socially-distributed information processing

Critical Pedagogy and Teaching Mathematics for Social Justice

In this article, the authors explore critical pedagogy within the context of mathematics classrooms. The exploration demonstrates the evolving pedagogical practices of mathematics teachers when teaching mathematics is explicitly connected to issues of social justice. To frame the exploration, the authors provide brief overviews of the theoretical tenets of critical pedagogy and of teaching mathematics for social justice. Through using narrative and textual data, the authors illustrate how a graduate-level, critical theory and teaching mathematics for social justice course assisted, in part, in providing not only a new language but also a legitimization in teachers becoming critical mathematics pedagogues

Four Decades of Andean Timberline Migration and Implications for Biodiversity Loss with Climate Change

Rapid 21st-century climate change may lead to large population decreases and extinction in tropical montane cloud forest species in the Andes. While prior research has focused on species migrations per se, ecotones may respond to different environmental factors than species. Even if species can migrate in response to climate change, if ecotones do not they can function as hard barriers to species migrations, making ecotone migrations central to understanding species persistence under scenarios of climate change. We examined a 42-year span of aerial photographs and high resolution satellite imagery to calculate migration rates of timberline–the grassland-forest ecotone–inside and outside of protected areas in the high Peruvian Andes. We found that timberline in protected areas was more likely to migrate upward in elevation than in areas with frequent cattle grazing and fire. However, rates in both protected (0.24 m yr-1) and unprotected (0.05 m yr-1) areas are only 0.5–2.3% of the rates needed to stay in equilibrium with projected climate by 2100. These ecotone migration rates are 12.5 to 110 times slower than the observed species migration rates within the same forest, suggesting a barrier to migration for mid- and high-elevation species. We anticipate that the ecotone will be a hard barrier to migration under future climate change, leading to drastic population and biodiversity losses in the region unless intensive management steps are taken

Survival Of The Fittest: Contagion as a Determinant of Canadian and Australian Bank Risk

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