The Tail that Wags the Dog: Integrating Credit Risk in Asset Portfolios

Tails are of paramount importance in shaping the risk profile of portfolios with credit risk sensitive securities. In this context risk management tools require simulations that accurately capture the tails, and optimization models that limit tail effects. Ignoring the tails in the simulation or using inadequate optimization metrics can have significant effects and destroy portfolio efficiency. The resulting portfolio risk profile can be grossly misrepresented when long run performance is optimized without consideration of the short term tail effects. This paper illustrates the pitfalls and suggests models for avoiding them.

Extending Credit Risk (Pricing) Models for the Simulation of Portfolios of Interest Rate and Credit Risk Sensitive Securities

We discuss extensions of intensity based models for pricing credit risk and derivative securities to the simulation and valuation of portfolios. The stochasticity in interest rates, credit spreads (default intensities) and rating migrations are incorporated in a unified framework. Scenarios of future prices of all securities are calculated in a risk-neutral world. The calculated prices are consistent with observed prices and the term structure of default free and defaultable interest rates. Three applications are discussed: (i) study of the inter-temporal price sensitivity of credit bonds to changes in interest rates, default probabilities, recovery rates and rating migration, (ii) portfolio simulations with attribution of changes to credit events and interest rates and, (iii) tracking of corporate bond indices. Key words: credit risk, default risk, simulation, integrated product management

The climate-sovereign debt doom loop: what does the literature suggest?

The current literature documents significant effects of climate change on the cost of sovereign debt and debt levels. These effects are due to a complex nexus of climate change systemic effects on the economy, characterized by deep uncertainty, fat tails, feedback loops, and uncertain fiscal costs of climate policies. Investors believe that climate risks have begun to materialize but are underpriced. I give an overview of the multichannels and review the evidence on fiscal costs from climate change, climate premia for sovereign debt, and climate risk assessments of sovereign bond portfolios. Recent advances integrate forward-looking climate scenarios in debt sustainability analysis and credit ratings. The findings suggest several mechanisms may activate a doom loop between climate change and sovereign debt

What Drives the Performance of Financial Institutions?

The financial sector is one of the most, if not the most significant economic sector in modern societies. In advanced countries, it employs more people than major manufacturing industries combined and accounts for a high percentage of the Gross Domestic Product. But the financial services sector also plays a large indirect role in national economies. The financial sector mobilizes savings and allocates credit across space and time, and enables firms and households to cope with uncertainties by hedging, pooling, sharing and pricing risks. This ultimately improves the quantity and quality of real investments and increases income per capita and raises standards of living. Today financial institutions are experiencing unprecedented change in a competitive global environment. Economies of scale that lead to more integrated automation lead to further economies of scope. Technological innovation adds competitive pressures, and provides opportunities for new non-traditional providers. Consumers themselves may be the strongest force of change in the financial services industry since their needs are evolving quickly. Banking institutions are being transformed from financial intermediaries to retail service providers - they now formulate products for clients or intermediaries, sell and service a range of products to customers and also provide the support functions needed for the successful execution of its primary activities. The authors ask how they can measure performance of a financial institution in this changing landscape? Traditional productivity measures are difficult to compute and tell us less than they used to. The authors also seek to identify what drives performance and identify three dimensions of performance drivers to explore: strategy; execution of strategy; and the environment. To begin, the authors define performance to mean economic performance as measured by financial indicators. Quality of services and effective risk management help explain strong performance levels. Strategic decisions that affect an institution's success involve product mix, client mix, geographical location, and distribution channels. In terms of strategy execution, the authors cite x-efficiency, human resource management, use of technology, process design, and the successful alignment of all these components as important factors in successful firm performance. Creating the right technology environment also has a significant impact on performance. The remainder of this paper summarizes the fifteen chapters of a book edited by the authors on performance and its drivers. The book is divided into three section: General; Drivers of Performance; and Environmental Drivers of Performance. There are also two chapters at the end that discuss performance and risk management. The authors then briefly discuss possible future research directions, including the relationship between operational efficiency and quality of services, the balance between risk management and retail services in bank activities, and study of interorganizational issues.

Scenario Modeling for the Management of International Bond Portfolios

We address the problem of portfolio management in the international bond markets. Interest rate risk in the local market, exchange rate volatility across markets, and decisions for hedging currency risk are integral parts of this problem. The paper develops a stochastic programming optimization model for integrating these decisions in a common framework. Monte Carlo simulation procedures, calibrated using historical observations of volatility and correlation data, generate jointly scenarios of interest and exchange rates. The decision maker's risk tolerance is incorporated through a utility function, and additional views on market outlook can also be incorporated in the form of user specified scenarios. The model prescribes optimal asset allocation among the different markets and determines bond-picking decisions and appropriate hedging ratios. Therefore several interrelated decisions are cast in a common framework, while in the past these issues were addressed separately. Empirical results illustrate the efficacy of the simulation models in capturing the uncertainties of the Salomon Brothers international bond market index.

Risk Factor Analysis and Portfolio Immunization in the Corporate Bond Market

In this paper we develop a multi-factor model for the yields of corporate bonds. The model allows the analysis of factors which influence the changes in the term structure of corporate bonds. More than 98% of the variability in the corporate bond market is captured by the model, which is then used to develop credit risk immunization strategies. Empirical results are given for the U.S. market using data for the period 1992-1999.

Asset and Liability Modeling for Participating Policies with Guarantees

We study the problem of asset and liability management of participating insurance policies with guarantees. We develop a scenario optimization model for integrative asset and liability management, analyze the tradeoffs in structuring such policies, and study alternative choices in funding them. The nonlinearly constrained optimization model can be linearized through closed form solutions of the dynamic equations. Thus large-scale problems are solved with standard methods. We report on an empirical analysis of policies offered by Italian insurers. The optimized model results are in general agreement with current industry practices. However, some inefficiencies are identified and potential improvements are highlighted.

Scenario Modeling of Selective Hedging Strategies

We study currency risk management in the context of scenario analysis. We develop scenario-based optimization models that jointly determine the portfolio composition and the hedging strategy within each currency. Thus the model prescribes optimal selective hedging policies. We then study empirically the performance of the models. The new elements of our empirical analysis are: various horizons (one month and one semester), various currency bases, explicit incorporation of realistic transaction costs. The results show that transaction costs are very important in determining the profitability of various currency risk management strategies for both stocks and bonds at the one month horizon.

The Value of Integrative Risk Management for Insurance Products with Guarantees

Insurers increasingly offer policies that converge with the products of the capital markets, and they face a need for integrative asset and liability management strategies. In this paper we show that an integrative approach -- based on scenario optimization modeling -- adds value to the risk management process, when compared to traditional methods. Empirical analysis with products offered by the Italian insurance industry are presented. The results have implications for the design of competitive insurance policies, and some examples are analyzed.

Pricing and hedging GDP-linked bonds in incomplete markets

We model the super-replication of payoffs linked to a country’s GDP as a stochastic linear program on a discrete time and state-space scenario tree to price GDP-linked bonds. As a byproduct of the model we obtain a hedging portfolio. Using linear programming duality we compute also the risk premium. The model applies to coupon-indexed and principal-indexed bonds, and allows the analysis of bonds with different design parameters (coupon, target GDP growth rate, and maturity). We calibrate for UK and US instruments, and carry out sensitivity analysis of prices and risk premia to the risk factors and bond design parameters. We also compare coupon-indexed and principal-indexed bonds. Further results with calibrated instruments for Germany, Italy and South Africa shed light on a policy question, whether the risk premia of these bonds make them beneficial for sovereigns. Our findings affirm that designs are possible for both coupon-indexed and principal-indexed bonds that can benefit a sovereign, with an advantage for coupon-indexed bonds. This finding is robust, but a nuanced reading is needed due to the many inter-related risk factors and design parameters that affect prices and premia