Understanding Stock Price Movement on the COVID-19 Period Using Dynamic Time Warping Algorithm

Abstract

Unlike the impact of MERS or SARS, the COVID-19 has had a huge impact on both social and economic environments. This study investigated the COVID-19 economic impact using the S&P 500 index by applying the DTW (Dynamic Time Warping) algorithm, an artificial intelligence technique. The DTW algorithm is designed for the identification of events the capital market impact resembles in the past. It is shown that the impact of the capital market on COVID-19 showed a completely different pattern from the patterns seen in MERS and SARS. Also, the results showed patterns similar to those of the 2015 China’s Stock Market Crash, the 2019 U.S.-China Trade Dispute, the 2008 Global Financial Crisis, which are specifically referred to as financial crises. However, it was unexpectedly similar to the shock of the U.S.-North Korea Conflict and the 2001 9·11 Terror. They were treated as political and diplomatic crises. These events are closely related to APEC countries, meaning that APEC countries’ economic and political activities are essential in the global economic crisis. The results imply that the policies implemented by APEC countries to overcome the economic crises are important to resolve the global economic crisis from COVID-19.