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Stochastic Volatilities and Correlations, Extreme Values and Modeling the Macroeconomic Environment, Under Which Brazilian Banks Operate

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  • Marcos Souto
  • Theodore M. Barnhill
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    Abstract

    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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    Bibliographic Info

    Paper provided by International Monetary Fund in its series IMF Working Papers with number 07/290.

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    Length: 52
    Date of creation: 01 Dec 2007
    Date of revision:
    Handle: RePEc:imf:imfwpa:07/290

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    Related research

    Keywords: Emerging markets; Banks; Interest rates; Credit risk; covariances; time series; probability; forecasting; probabilities; statistics; normal distribution; covariance; correlation; statistic; linear regression; correlations; econometrics; stochastic processes; standard deviation; random walk; optimization; sampling error; forecast performance; normal distributions; sampling; forecasting models; simulation results; simulation approach; exponential smoothing; regression model; economic statistics; samples; predictability; sample forecasting; outliers; econometric theory; stochastic models; equation; monte carlo simulation; forecasting model; regression models; equations; absolute error; stochastic model;

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    1. Akgiray, Vedat & Booth, G Geoffrey, 1988. "The Stable-Law Model of Stock Returns," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(1), pages 51-57, January.
    2. Taimur Baig & Ilan Goldfajn, 2000. "The Russian Default and the Contagion to Brazil," IMF Working Papers 00/160, International Monetary Fund.
    3. Kate Adjaoute & Martin Bruand & Rajna Gibson-Asner, 1998. "On the Predictability of the Stock Market Volatility: Does History Matter?," European Financial Management, European Financial Management Association, vol. 4(3), pages 293-319.
    4. Andersen, Torben G. & Bollerslev, Tim & Lange, Steve, 1999. "Forecasting financial market volatility: Sample frequency vis-a-vis forecast horizon," Journal of Empirical Finance, Elsevier, vol. 6(5), pages 457-477, December.
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