Wanyi Wang

Abstract: Using two proxies for investors’ political affiliation, we document sharp differences in stock returns between firms likely dominated by Democratic investors (blue stocks) and those dominated by Republican investors (red stocks) during the COVID pandemic. Red stocks have 20 basis points higher risk-adjusted returns than blue stocks on COVID news days (Partisan Return Gap). Lockdown policies, COVID cases, industry and firm fundamentals only explain at most 40% of the return gap. Polarized political beliefs about COVID, revealed through people’s social distancing behaviors, contribute to about 40% of the return gap beyond the fundamental channel. Our paper provides partisanship as a novel aspect in understanding abnormal stock returns during the pandemic.

Abstract: This paper studies how partisanship affects mutual fund information processing at the firm level. Using textual analysis of earnings call transcripts, I identify discussions on partisan-sensitive topics, such as climate change, pandemic, and healthcare. I find that partisan funds react more strongly to topics aligned with their ideological beliefs and trade more after firms increase discussions on these topics. The effect is stronger for funds with higher polarization levels and for firms with larger weights in fund portfolios. Moreover, the observed pattern does not add value to fund performance, suggesting that the effect is not driven by rational expectations about future stock returns. Overall, these findings indicate that partisanship plays a role in mutual fund firm-level information processing.

Abstract: This paper studies how political alignment between a firm’s CEO and a state’s governor affects internal labor allocation. We find that firms increase employment in politically aligned states, especially when CEOs are more polarized and during periods of heightened polarization. This effect remains robust when we exploit close gubernatorial elections as a source of plausibly exogenous variation in political alignment. Further analysis suggests that these decisions are driven by CEO optimism about politically aligned states, rather than personal preferences. However, we find that employment expansions in politically aligned states are associated with lower stock returns in the following year.

Abstract: This paper examines how investors evaluate new technologies from the perspective of cryptocurrencies. Employing a machine learning method, we construct a novel Tech Index from whitepapers to capture technology sophistication of cryptocurrency. While cryptocurrencies with higher Tech Indexes are more likely to enjoy early success and a high first-day listing price, they tend to earn significantly lower subsequent returns after being listed. The return reversal is stronger when market sentiment is higher. Moreover, cryptocurrencies with higher Tech Index earn lower returns after the unexpected Luna Crash and FTX scandal. Overall, these findings suggest investors overreact to cryptocurrency technology.