OpenAI’s new flagship model, ChatGPT-4o, released on 13 May 2024, offers enhanced natural language understanding and more coherent responses. This paper investigates ChatGPT-4o’s capabilities in financial data analysis, including zero-shot prompting, time series analysis, risk and return analysis, and ARMA-GARCH estimation. ChatGPT-4o’s performance is generally comparable to traditional statistical software like Stata, though some errors and discrepancies arise due to differences in implementation. Despite these issues, our findings indicate that ChatGPT-4o has significant potential for real-world financial analysis. Integrating ChatGPT-4o into financial research and practice may lead to more efficient data processing, improved analytical capabilities, and better-informed investment decisions.

This paper examines the relationship between a firm’s working capital policy and the volatility of its stock returns. We find that a firm with an aggressive working capital policy tends to exhibit a higher level of return volatility. This finding is robust across years and industries after controlling for factors such as financial stability and sales growth. Our results further indicate that aggressively managed working capital policy affects return volatility through idiosyncratic risk. A decrease in working capital results in the contemporaneous and subsequent increases of return volatility. Our evidence is consistent with the conjecture that there is an important link between a firm’s working capital policy and its stock return volatility. Thus, firm managers must incorporate the potential costs associated with higher stock return volatility into their working capital decision-making when adopting a tightened working capital policy.

Why do some firms choose to be ‘born global’ and become early internationalizing firms (EIFs) while others choose to be ‘born-again global’ and develop into late internationalizing firms (LIFs)? What are the main factors impacting a firm’s decision on the timing of global diversification? Based on the theories of diversification, this study examines the role of peer influence and desire for growth on the timing of a firm’s globalization decision. We further study the idiosyncratic risk and the adoption of technological innovation hypotheses on global diversification. Our results document that innovation efficiency strongly enhances EIFs’ propensity to global diversification. On the other hand, peer pressure and idiosyncratic risk level significantly influence EIFs not to globalize. In contrast, LIFs are positively influenced by their industry peers, showing how young and mature companies respond to the market competition in a different manner.