Integration, Kointegration und die Langzeitprognose von Kreditausfallzyklen

Wagatha, Matthias (2007): Integration, Kointegration und die Langzeitprognose von Kreditausfallzyklen.

Abstract

Summary: This paper examines the longterm forecast performance of cointegrated systems relative to forecast performance of comparable VAR that fails to recognize that the system is characterized by cointegration. I use Monte Carlo simulation, real data sets, and multi-step-ahead forecasts to study this question. The cointegrated system I examine is composed of six vectors, five macoreconomic variables, and a credit-default-cycle. The forecasts produced by the vector error correction modell associated with this system are compared with those obtained from a corresponding differenced vector autoregression, as well as a vector autoregression based upon the levels of the data. Alternative measures of forecast accuracy (full-system) are discussed. My findings suggest that selective forecast performance improvement may be observed by incorporating knowledge of cointegration rank. Furthermore the results indicate that a cointegration modeling of credit risk should be favored against the prevalent level or differenced estimation.

• Item Type: MPRA Paper
• English Title: Integration, Cointegration and Long-Horizont Forecasting of Credit-Default-Cycles
• Language: German
• Keywords: Integration; Cointegration; Forecasting; Credit-default-cycle; Integration; Kointegration; Langzeitprognose; Kreditausfallzyklus
• Subjects: C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and Selection

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