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Author/Editor:
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Barnhill, Theodore M. ; Souto, Marcos
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Publication Date:
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December 01, 2007
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Electronic Access:
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Free Full text
(PDF file size is 648KB).
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Disclaimer: This Working Paper should not be reported as representing the views of the IMF.
The views expressed in this Working Paper are those of the author(s) and do not necessarily represent those of the IMF or IMF policy. Working Papers describe research in progress by the author(s) and are published to elicit comments and to further debate
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Summary:
Using monthly data for a set of variables, we examine the out-of-sample performance of various variance/covariance models and find that no model has consistently outperformed the others. We also show that it is possible to increase the probability mass toward the tails and to match reasonably well the historical evolution of volatilities by changing a decay factor appropriately. Finally, we implement a simple stochastic volatility model and simulate the credit transition matrix for two large Brazilian banks and show that this methodology has the potential to improve simulated transition probabilities as compared to the constant volatility case. In particular, it can shift CTM probabilities towards lower credit risk categories.
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Series:
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Working Paper No. 07/290
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Subject(s):
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Emerging markets | Brazil | Banks | Interest rates | Credit risk
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Author's Keyword(s):
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Forecasting | multivariate stochastic volatility | fat-tail distributions | Monte Carlo estimation |
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