Title

Forecasting financial stress indices in Korea: a factor model approach

Document Type

Article

Publication Date

12-1-2020

Publication Title

Empirical Economics

Volume

59

First Page

2859

Last Page

2898

Keywords

Diebold–Mariano–West statistic, Financial stress index, In-sample fit, Out-of-sample forecast, PANIC, Principal component analysis

Abstract

© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. We propose factor-based out-of-sample forecast models for Korea’s financial stress index and its 4 subindices that are developed by the Bank of Korea. We extract latent common factors by employing the method of the principal components for a panel of 198 monthly frequency macroeconomic data after differencing them. We augment an autoregressive-type model of the financial stress index with estimated common factors to formulate out-of-sample forecasts of the index. Our models overall outperform both the stationary and the nonstationary benchmark models in forecasting the financial stress indices for up to 12-month forecast horizons. The first common factor that represents not only financial market but also real activity variables seems to play a dominantly important role in predicting the vulnerability in the financial markets in Korea.

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