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Implementing risky discounting or an additional option model for each product type was certainly plausible. Trades that were actively managed in this way were simply tagged and diverted from the reserve model. Aside from the obvious issues, e. The ultimate demise of the market model as a scalable solution was that the marginal price under the unilateral model was consistently higher than under the simulation model. Another detriment was the viability of having each trading desk manage credit risk or be willing to transfer it to a central CVA desk.

Having each desk manage credit risk meant that traders needed credit expertise in addition to knowledge of the markets they traded.

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In addition, systems had to be substantially upgraded. In short, the substantial set of issues with the market model caused firms to revisit the reserve model. Merger of the reserve and market models Attempts to move credit risk out of the reserve model and into a market model inspired important innovations in the simulation framework with regard to active management.

Counterparty Credit Risk Management

Banks had been executing macro or overlay CDS hedges with notional amounts set to potential exposure levels. The CDS hedges were effective in reducing capital requirements but ineffective in that the notional amount was based on a statistical estimate of the exposure, not a risk-neutral replication. In addition, that exposure notional varied over time. The next logical step was to address active management from the input end simulation.

There were several issues with this approach. Simulation of the entire portfolio could take hours and re-running it for each perturbed input restricted rebalancing frequency to weekly or longer. In addition, residual correlation risk remained, which had critical consequences over the past two years.

Correlation in portfolio simulation remains an open problem.

Simulators typically use the real or historical measures of volatility as opposed to risk-neutral or implied volatilities in projecting forward prices. One reason is that risk-neutral vols may not be available for some market inputs, e. The bigger reason is that historical vols already embed correlation.

Correlation is not directly observable in the market and the dimensionality of pairwise correlations causes substantial if not unmanageable complexity.

The end result is that correlation has been managed through portfolio diversification instead of replication. Current priorities Over the past two years, firms that had a comprehensive, integrated approach to credit risk management survived and emerged while those that had a fragmented approach struggled and failed. This punch line and the evolutionary process that helped deliver it have resulted in a general convergence toward the portfolio simulation model with an active management component.

Several global banks are at the cutting edge of current best practice whereas most mid-tier and regional banks are still balancing the need to comply with accounting requirements, which require CVA, with more ambitious plans. Banks that have robust simulation models are pushing the evolution in four main areas.

Credit Risk Pricing Models: Theory and Practice / Edition 2

First, with the recent monoline failures, there is a recognized need to incorporate wrong-way risk. Third, capturing as much of the portfolio as possible, including exotics, increases the effectiveness of centralized credit risk management and allows more accurate pricing of the incremental exposure of new transactions.

Finally, robust technology infrastructure is imperative to reliably capture the wide array of market and position data and then perform the simulation in a reasonable timeframe. Automation and standardized data formats like FIX speed implementation reduce errors and ultimately enhance the integrity of the results.

Credit risk pricing models : theory and practice

Counterparty credit risk remains a very complex problem and institutions have had to approach it in stages. Huge improvements have been made and current best practice is the result of a long and iterative evolutionary process. There is still much work to do and it will be exciting to see what new innovations lie ahead.

Technology — There is No End-game. Bringing the Sell-side to the Buy-side.

Credit Risk Pricing Models Theory by Schmid Bernd - AbeBooks

Portfolio Management Profiling. Boarding the Train to China. Building A Global Firm. Singapore Roundtable: Maximising Your Data. What issues and challenges should be addressed? And what lessons can be learned from the credit mess? Credit Risk Frontiers offers answers to these and other questions by presenting the latest research in this field and addressing important issues exposed by the financial crisis. It covers this subject from a real world perspective, tackling issues such as liquidity, poor data, and credit spreads, as well as the latest innovations in portfolio products and hedging and risk management techniques.

Provides a coherent presentation of recent advances in the theory and practice of credit derivatives. Contains information regarding various aspects of the credit derivative market as well as cutting edge research regarding those aspects. If you want to gain a better understanding of how credit derivatives can help your trading or investing endeavors, then Credit Risk Frontiers is a book you need to read.

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