| Topic : Credit risk mitigation |
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Credit Risk Management
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Activity:
49 views;
last activity : 07 06 2010 20:18:09 +0000
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default rates
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Combined model -diffusion and Markov matrices
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The Default rates rise (fall) during a recession (boom). In principal, one might forecast the business cycle to gain insight into default rates. Tom Wilson of McKinsey is pursuing this idea. Unfortunately, decades of research have taught us only that the stock market predicts the business cycle as well as everything else combined, so I think that Wilson's explorations will lead to dry holes.
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I also think so. By analysing default rate, credit risk can be assessed...
Default probablility I think can pretty much asess the credit risk. VAR can be figured out from this. I feel in India since we don't have a secondary bond market assesing credit risk of companies is accurately possible. Then probably one has to go by the Stock prices.
I think default rate which is none other than default probability can do the trick. Diversity scores published by s&p or moodys generely gives the probable number from which one can get the default probabilities for the number of defaults we are expecting in a class of debts. Individual asessment can be done using the procedures adopted by the same rating agencies. I think default rates are already predicting credit risks and I don't know what further research can achieve.
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The state of the art model seems to be along the lines of VaR, but with more mathematics, combining diffusion and Markov matrices. JP Morgan's CreditMetrics takes this approach. Currently, their model assumes that the forward curve is constant, to isolate credit deterioration from market risk. However, most credit deterioration comes from unfavorable market moves.
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I also think so. By the combined model-diffusion and Markov matrices, credit risk can be assessed.
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