European Parliament Library

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

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
Table Of Contents
Table of Contents; 1. Introduction; 2. Forecasting Volatilities and Covariances; 2.1. Historical Realized Volatilities and Covariances; 2.2. Initial Volatilities and Covariances; 2.3. Stochastic Volatility and Covariances Models; 2.4. Forecast Errors; 3. Monte Carlo and the Distribution of Simulated Returns; 3.1. Historical Returns: Fat Tail Distribution; 3.2. Simulation Methodology; 3.2.1. Simulating Interest Rates; 3.2.2. Simulating Asset Returns and Prices; 3.2.3. Cholesky Decomposition; 3.2.4. Stochastic Volatilities and Covariances; 3.3. Simulation Results
Language
eng
Literary Form
non fiction
Note
Description based upon print version of record
Physical Description
1 online resource (54 p.)
Specific Material Designation
remote
Form Of Item
online
Isbn
9781452706719

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