Early Warning Systems for identifying financial instability

Financial crises prediction is an essential topic in finance. Designing an efficient Early Warning System (EWS) can help prevent catastrophic losses resulting from financial crises. We propose different EWSs for predicting potential market instability conditions, where market instability refers to large asset price declines. The EWSs are based on the logit regression and employ Early Warning Indicators (EWIs) based on the realized variance (RV) and/or price-volatility feedback rate. The latter EWI is supposed to describe the ease of the market in absorbing small price perturbations. Our study reveals that, while RV is important in predicting future price losses in a given time series, the EWI employing the price-volatility feedback rate can improve prediction further. (c) 2022 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

Automated summary

Financial crises prediction is crucial in finance, and an efficient Early Warning System (EWS) can help prevent significant losses. This study proposes different EWSs based on logit regression and Early Warning Indicators (EWIs) using realized variance (RV) and/or price-volatility feedback rate. The findings suggest that incorporating the price-volatility feedback rate improves the prediction accuracy of future price losses.