The pricing puzzle : the default term structure of collateralised loan obligations

Ambivalence in the regulatory definition of capital adequacy for credit risk has recently stirred the financial services industry to collateral loan obligations (CLOs) as an important balance sheet management tool. CLOs represent a specialised form of Asset-Backed Securitisation (ABS), with investors acquiring a structured claim on the interest proceeds generated from a portfolio of bank loans in the form of tranches with different seniority. By way of modelling Merton-type risk-neutral asset returns of contingent claims on a multi-asset portfolio of corporate loans in a CLO transaction, we analyse the optimal design of loan securitisation from the perspective of credit risk in potential collateral default. We propose a pricing model that draws on a careful simulation of expected loan loss based on parametric bootstrapping through extreme value theory (EVT). The analysis illustrates the dichotomous effect of loss cascading, as the most junior tranche of CLO transactions exhibits a distinctly different default tolerance compared to the remaining tranches. By solving the puzzling question of properly pricing the risk premium for expected credit loss, we explain the rationale of first loss retention as credit risk cover on the basis of our simulation results for pricing purposes under the impact of asymmetric information. Klassifikation: C15, C22, D82, F34, G13, G18, G2

Asset pricing and investor risk in subordinated asset securitisation

As a sign of ambivalence in the regulatory definition of capital adequacy for credit risk and the quest for more efficient refinancing sources collateral loan obligations (CLOs) have become a prominent securitisation mechanism. This paper presents a loss-based asset pricing model for the valuation of constituent tranches within a CLO-style security design. The model specifically examines how tranche subordination translates securitised credit risk into investment risk of issued tranches as beneficial interests on a designated loan pool typically underlying a CLO transaction. We obtain a tranchespecific term structure from an intensity-based simulation of defaults under both robust statistical analysis and extreme value theory (EVT). Loss sharing between issuers and investors according to a simplified subordination mechanism allows issuers to decompose securitised credit risk exposures into a collection of default sensitive debt securities with divergent risk profiles and expected investor returns. Our estimation results suggest a dichotomous effect of loss cascading, with the default term structure of the most junior tranche of CLO transactions (“first loss position”) being distinctly different from that of the remaining, more senior “investor tranches”. The first loss position carries large expected loss (with high investor return) and low leverage, whereas all other tranches mainly suffer from loss volatility (unexpected loss). These findings might explain why issuers retain the most junior tranche as credit enhancement to attenuate asymmetric information between issuers and investors. At the same time, the issuer discretion in the configuration of loss subordination within particular security design might give rise to implicit investment risk in senior tranches in the event of systemic shocks. JEL Classifications: C15, C22, D82, F34, G13, G18, G2

The Missing Link - Economic Exposure and Pension Plan Risk

The funding position of a defined benefit pension plan is often closely linked to the performance of the sponsoring company's business. For example, a plan sponsor whose financial health is dependent on high oil prices may struggle during periods of oil price weakness. If the pension plan’s assets perform poorly at this time, the ability of the sponsor to address any funding requirement could be restricted precisely when the need for funding is heightened. In this paper, we propose an approach to dealing with joint plan and sponsor risk that can provide protection against extreme adverse events for the sponsor. In particular, adopt a strategy of minimising a portfolio’s expected losses in the event of an assumed drop of x% in the oil price. Our methodology relies on an asset allocation framework which takes into account the impact of serial correlation in asset returns, as well as the negative skewness and leptokurtosis resulting from the non-normal shape of marginal distributions of historical asset returns. We also make use of copulas to measure the dependence between asset class returns

Insurer Climate Risk Disclosure Survey: 2012 Findings and Recommendations

2012 was the warmest year on record in the Lower 48 states and the second most extreme weather year in U.S. history. This is not a coincidence. Extreme weather -- stronger, more damaging storms, unprecedented drought and heat in some regions and unprecedented rainfall and flooding in others -- are the predictable consequences of rising global temperatures.Eleven extreme weather events each caused at least a billion dollars in losses last year in the United States. A single event, Hurricane Sandy, caused more than $50 billion in economic losses. Insurance companies are on the hook for tens of billions of dollars in claims as a result of Sandy and other severe weather events. And American taxpayers are on the hook for tens of billions of dollars themselves, thanks to losses sustained by the National Flood Insurance Program as well as disaster relief spendingThis raises a fundamental question: Is the insurance industry prepared? Have insurers analyzed and measured their climate-related risk? Are they planning for life in a warmer world? These should be essential questions for insurance regulators in all 50 states to be asking, and some are

Concurrent Credit Portfolio Losses

We consider the problem of concurrent portfolio losses in two non-overlapping credit portfolios. In order to explore the full statistical dependence structure of such portfolio losses, we estimate their empirical pairwise copulas. Instead of a Gaussian dependence, we typically find a strong asymmetry in the copulas. Concurrent large portfolio losses are much more likely than small ones. Studying the dependences of these losses as a function of portfolio size, we moreover reveal that not only large portfolios of thousands of contracts, but also medium-sized and small ones with only a few dozens of contracts exhibit notable portfolio loss correlations. Anticipated idiosyncratic effects turn out to be negligible. These are troublesome insights not only for investors in structured fixed-income products, but particularly for the stability of the financial sector

Using stress testing methodology in evaluating banking institution’s exposure to risk

In order to correctly estimate the unpredictable effects on their transaction portfolios, the banks developed stress testing methods which turned out to be a very important tool in the bank supervision process. Moreover, the supervision authorities started using stress-testing methods for evaluating systemic risk and for determining the adequacy degree of capital in the banking sector. Taking into account the importance of these simulations, the present paper presents methodologies with which stress testing methods could be implemented by banks as well as their role in the management of credit risk, market risk and liquidity risk while also meeting the requirements imposed by the Basel II accord. By means of a case study we have simulated several scenarios in which the inter-bank market interest rate was varied, quantifying its impact on bank revenues as well as on the market value of their portfolios.stress testing, credit risk, market risk, liquidity risk, capital adequacy, Basel II Accord

WARNING: Physics Envy May Be Hazardous To Your Wealth!

The quantitative aspirations of economists and financial analysts have for many years been based on the belief that it should be possible to build models of economic systems - and financial markets in particular - that are as predictive as those in physics. While this perspective has led to a number of important breakthroughs in economics, "physics envy" has also created a false sense of mathematical precision in some cases. We speculate on the origins of physics envy, and then describe an alternate perspective of economic behavior based on a new taxonomy of uncertainty. We illustrate the relevance of this taxonomy with two concrete examples: the classical harmonic oscillator with some new twists that make physics look more like economics, and a quantitative equity market-neutral strategy. We conclude by offering a new interpretation of tail events, proposing an "uncertainty checklist" with which our taxonomy can be implemented, and considering the role that quants played in the current financial crisis.Comment: v3 adds 2 reference

Semi-parametric estimation of joint large movements of risky assets

The classical approach to modelling the occurrence of joint large movements of asset returns is to assume multivariate normality for the distribution of asset returns. This implies independence between large returns. However, it is now recognised by both academics and practitioners that large movements of assets returns do not occur independently. This fact encourages the modelling joint large movements of asset returns as non-normal, a non trivial task mainly due to the natural scarcity of such extreme events. This paper shows how to estimate the probability of joint large movements of asset prices using a semi-parametric approach borrowed from extreme value theory (EVT). It helps to understand the contribution of individual assets to large portfolio losses in terms of joint large movements. The advantages of this approach are that it does not require the assumption of a specific parametric form for the dependence structure of the joint large movements, avoiding the model misspecification; it addresses specifically the scarcity of data which is a problem for the reliable fitting of fully parametric models; and it is applicable to portfolios of many assets: there is no dimension explosion. The paper includes an empirical analysis of international equity data showing how to implement semi-parametric EVT modelling and how to exploit its strengths to help understand the probability of joint large movements. We estimate the probability of joint large losses in a portfolio composed of the FTSE 100, Nikkei 250 and S&P 500 indices. Each of the index returns is found to be heavy tailed. The S&P 500 index has a much stronger effect on large portfolio losses than the FTSE 100, although having similar univariate tail heaviness

Default risk sharing between banks and markets : the contribution of collateralized debt obligations

This paper contributes to the economics of financial institutions risk management by exploring how loan securitization a.ects their default risk, their systematic risk, and their stock prices. In a typical CDO transaction a bank retains through a first loss piece a very high proportion of the expected default losses, and transfers only the extreme losses to other market participants. The size of the first loss piece is largely driven by the average default probability of the securitized assets. If the bank sells loans in a true sale transaction, it may use the proceeds to to expand its loan business, thereby incurring more systematic risk. We find an increase of the banks' betas, but no significant stock price e.ect around the announcement of a CDO issue. Our results suggest a role for supervisory requirements in stabilizing the financial system, related to transparency of tranche allocation, and to regulatory treatment of senior tranches. JEL Klassifikation: D82, G21, D74