Forecasting financial stress indices in Korea: a factor model approach
Diebold–Mariano–West statistic, Financial stress index, In-sample fit, Out-of-sample forecast, PANIC, Principal component analysis
© 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.
Kim, Hyeongwoo; Shi, Wen; and Kim, Hyun Hak, "Forecasting financial stress indices in Korea: a factor model approach" (2020). Faculty Bibliography. 2651.