한・중・미 ChatGPT산업의 주가 상호연관성에 관한 실증연구

Abstract

The proliferation of ChatGPT, a sophisticated language model, into diverse domains such as commerce, academia, and healthcare has accentuated the prominence of its affiliated industries, which span sectors like cloud computing, artificial intelligence, and semiconductors. Given the unique economic and technological landscapes of Korea, China, and the United States, the stock performances within ChatGPT-centric sectors in these countries have garnered substantial attention and analysis. This study seeks to empirically examine the interplay of stock indices among these nations in the context of ChatGPT and its related industries, aiming to provide crucial insights for stakeholders, policymakers, and industry experts. For this investigation, we aggregated and analyzed stock performance data from key corporations within Korea, China, and the United States. A Vector Autoregression (VAR) model was utilized to explore the time-series dynamics of stock indices across these countries. This model, by design, captures the intricate interrelations and potential causalities among the studied variables. The results highlight significant volatility in the stock trends for both Korea and China following the emergence of ChatGPT. Specifically, Chinese stock trends exhibited a pronounced pattern of rises and falls. In contrast, the U.S. showcased a more stable stock performance, consistently ascending over the studied period. Moreover, preliminary statistical assessments revealed that the volatility inherent in Korea's stock trends outpaced that of both China and the In summary, the advent of ChatGPT has instigated discernible shifts in the stock performances of its associated sectors across the evaluated countries, with especially notable fluctuations observed in Korea and China. This study sheds light on the time-series patterns of stock indices linked to ChatGPT-associated sectors in the three countries, offering a comprehensive understanding of the interconnected dynamics influencing their respective stock markets. Key words : ChatGPT, stock markets, VAR model, Granger causality.