Matthias Pelster

This paper studies how the interplay of posting and trading behaviors within a social network influences an individual’s decision to adopt cryptocurrency. We exploit a unique dataset from a large social trading platform and find a pronounced social learning effect in cryptocurrency adoption. Individuals are more inclined to adopt cryptocurrency when their peers do, especially when the trading behavior of those peers aligns with their expressed opinions. When uncertainty or returns are high, investors tend to rely more on positive opinions, regardless of the actual trading behavior of others. We observe significant heterogeneity across user demographics: Users who are older, are more experienced, are more willing to take risks, and have higher incomes are especially responsive to credible signals from adopters. Younger users exhibit greater skepticism toward positive sentiment, possibly because of greater familiarity with noise in social media environments. Our results offer actionable insights for practitioners. Developers and marketers of emerging technologies can foster adoption by leveraging transparent, credible communication—preferably from peers whose actions are visible and aligned with their expressed opinions.

This paper exploits individual trading records from a large brokerage service to investigate the trading patterns of retail investors who take short positions in stocks using contracts for differences (CFDs). Their risk tolerance, as reported in MiFID II questionnaires, and their leverage usage indicate greater risk-seeking behavior. Short positions, compared to long positions, constitute larger portions of overall portfolios and are more highly leveraged. Yet, short sellers’ research activity does not suggest that they increase the amount of attention paid to stocks before taking short positions. Compared with other CFD traders, short sellers perform worse, and their profit variability is greater.

Social trading is an emerging market in the sharing economy, allowing investors (followers) to duplicate the trades of other investors (leaders) in real time. We analyze the formation and dissolution of links in a large social trading network. Such networks are characterized by the rapid dissolution of links, increasing the importance of studying network dissolution. We investigate how social communication, along with financial performance and demographics, affects dynamic network evolution. We show that different types of social communication, such as posts and comments, have different implications for link formation and dissolution. Moreover, we find financial performance to be highly important for link formation and dissolution, whereas demographic characteristics are only relevant for link formation. In social trading, the extreme flexibility of followers in dissolving links and thereby, terminating their relationship instantaneously brings about large income uncertainty for leaders. Thus, a thorough understanding of network evolution and its determinants is crucial for leaders. Our results can provide guidance on when and how to communicate with followers. As vocal leaders on social media may exert a significant influence on financial markets—as demonstrated by recent the GameStop frenzy—a better understanding of the evolution of investment networks is also important for regulators.

We study environmental, social, and governance (ESG) investing in private markets, focusing on the universe of US private equity funds from 1980 to 2019. We extend the asset pricing model of Gupta and Van Nieuwerburgh (2021) by including ESG factors and uncover three main findings. First, private equity funds are significantly exposed to ESG risks, with exposures varying in horizon across fund types (buyouts, funds of funds, and venture capital). Second, accounting for ESG risk confirms recent findings that the average fund risk-adjusted performance of private equity funds after fees is negative. Third, the risk exposure of funds to ESG risks does not correlate with their transparency regarding their sustainable investing practices. Low-transparency funds perform worse than high-transparency ESG funds do, but the difference in performance is not explained by exposure to ESG risk.

Cryptocurrencies have gained increasing attention over the last few years. Due to the lack of standardized information, social media has become a main information channel for individuals to decide whether to trade cryptocurrencies. This reliance on social media presents a unique challenge: The vast and unregulated nature of social media can often lead to disseminating information of questionable credibility. We exploit a unique dataset from a large social trading platform and study how the interplay of opinions and behaviors within social networks influences an individual's decision to adopt cryptocurrency. Using investment opinions and actual trading behaviors, we find a pronounced social learning effect in cryptocurrency adoption. Individuals are more inclined to adopt cryptocurrencies when their network peers do, especially when these peers' trading actions are consistent with their expressed opinions. We also find that traders who align their opinions with their trading actions are more influential, write longer posts, and hold assets for a longer period of time. Additionally, our findings suggest that, on average, social trading users tend to share information based on their genuine beliefs. Our findings shed light on implications for cryptocurrency stakeholders.