Stock price reactions to reopening announcements after China abolished its zero-COVID policy

The COVID-19 pandemic significantly impacted global economies and financial markets, causing substantial stock price drops. While research exists on the pandemic's negative effects, the impact of reopening announcements remains under-explored. This study addresses this gap by causally analyzing the effect of China's post-Zero-COVID reopening policies on Chinese stock prices. China's prolonged Zero-COVID policy resulted in substantial economic costs, including rising unemployment and business closures. The abrupt policy shifts in late 2022, including the announcement of 20 new measures on November 11th, ten additional measures on December 7th, and the full reopening announcement on December 26th, provide a unique setting to examine the effects of reopening on stock markets. The study hypotheses are: 1) Reopening announcements will positively impact the stock market; 2) The impact will vary depending on the degree of restriction relaxation; and 3) Reopening policies may not cause a substantial short-term stock price boost unlike restrictive measures. The study aims to determine the causal impact of these announcements on stock prices, filling a critical knowledge gap and offering insights applicable to other economies.

Existing literature extensively documents the negative impact of the COVID-19 pandemic and lockdowns on stock markets globally. Studies cite significant declines in major indices like the Dow Jones and FTSE All-Share. Research also highlights the challenges faced by businesses, particularly SMEs, during the pandemic and their hesitant return to operations even with the advent of vaccines. Prior studies have explored the stock market's reaction to pandemic-related reopening announcements, focusing primarily on the price of the underlying asset during the ongoing pandemic, not after it's end. This study uniquely focuses on the causal impact of post-pandemic reopening announcements on stock market recovery, filling a gap in the literature and using China's experience with its extreme Zero-COVID policy as a case study.

The study employs two primary methodologies: Regression Discontinuity Design (RDD) and Difference-in-Differences (DID). The RDD approach examines the immediate impact of each reopening announcement on stock prices by analyzing price discontinuities around the announcement dates. The regression model (Eq. 1) includes a binary variable indicating post-announcement periods, a running variable representing days relative to the announcement, and control variables such as firm, monthly, and weekday fixed effects. The DID approach evaluates the medium-term effects by comparing the stock price changes of Mainland China firms listed on the Hong Kong stock exchange to those of firms from other regions. Equation (2) employs a two-way fixed-effects model with a treatment variable indicating firms located in Mainland China and a post-announcement dummy variable. Data was obtained from the Wind Economic Database, covering 4976 firms in Mainland China and 2557 in Hong Kong (1087 from Mainland China) from November 1, 2022, to February 28, 2023. The study acknowledges limitations such as potential impacts of other events and focuses primarily on stock price reactions without exploring underlying reasons for the fluctuations.

RDD analysis reveals that the November 11th and December 7th announcements had minimal to negative impacts on stock prices. However, the December 26th full reopening announcement led to a significant 1.4% (and 2.5% with a wider bandwidth) increase in stock prices in Mainland China. DID regression results show that Chinese firms listed in Hong Kong outperformed other firms by 1.6% two months after the December 26th announcement, indicating a positive medium-term effect. These findings suggest a positive relationship between China’s full reopening announcement and stock prices, while earlier announcements showed little to no positive impact. The visual inspection of stock prices around each announcement date also supports these results and highlights the notable reaction to the December 26th announcement. Tables 2 and 3 present detailed regression results, showing the statistical significance of the findings.

The study's findings address the research questions by demonstrating a causal link between the full reopening announcement and a positive impact on stock prices in China. The differential responses to the various announcements highlight the importance of policy communication and investor sentiment. The December 26th announcement, clearly signaling a complete shift in policy, generated the most positive market response, possibly due to alleviating concerns about future lockdowns. The relatively moderate increase in stock prices over the medium term, however, suggests a longer recovery period is needed to rebuild complete market confidence. The findings contribute significantly to the understanding of post-pandemic economic recovery and the impact of government policies on market behavior.

This study makes several contributions: It is the first to causally analyze the impact of post-pandemic reopening announcements on Chinese firms' stock prices. It utilizes both RDD and DID methodologies to provide a robust analysis, showing that the full reopening announcement had a positive impact on stock prices, while previous announcements had little or negative impacts. The findings emphasize the importance of well-timed and clearly communicated policy announcements to instill market confidence. Future research could investigate the influence of firm-specific factors, investor sentiment, and macroeconomic conditions on stock price reactions.

The study acknowledges limitations: It primarily focuses on stock price reactions without exploring underlying causes. Firm-specific characteristics are not considered in detail, and the analysis does not address the impact on other aspects of firms' operations. The data availability from the Wind Economic Database is limited, preventing the exploration of additional aspects impacting these findings. Future research should address these limitations to provide a more comprehensive understanding of the relationship between policy decisions and economic outcomes.