Forecasting financial stress indices in Korea: a factor model approach

Hyeongwoo Kim (), Wen Shi () and Hyun Hak Kim
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Wen Shi: Columbus State University

Empirical Economics, 2020, vol. 59, issue 6, No 11, 2859-2898

Abstract: Abstract 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.

Keywords: Financial stress index; Principal component analysis; PANIC; In-sample fit; Out-of-sample forecast; Diebold–Mariano–West statistic (search for similar items in EconPapers)
JEL-codes: E44 E47 G01 G17 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (7)

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Related works:
Working Paper: Forecasting Financial Stress Indices in Korea: A Factor Model Approach (2019)
Working Paper: Forecasting Financial Stress Indices in Korea: A Factor Model Approach (2018)
Working Paper: Forecasting Financial Stress Indices in Korea: A Factor Model Approach (2018)
Working Paper: Forecasting Financial Stress Indices in Korea: A Factor Model Approach (2016)
Working Paper: Forecasting Financial Stress Indices in Korea: A Factor Model Approach (2015)
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DOI: 10.1007/s00181-019-01744-y

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