Work in progress
We explore the 2020 and early 2021 price variation of four stocks: GameStop, AMC Entertainment Holdings, Blackberry and Nokia. The four stocks were subject to a decentralized short squeeze that exploited the short positions of institutional investors. This investor movement was likely initiated by retail investors concentrated mostly around the subreddit r/WallStreetBets (WSB). We demonstrate that part of the next day’s price variation can be explained by an increase in activity on the WSB subreddit relative to Google searches (terms related to the event). We discuss implications for future research.
Over the last few decades, large banks worldwide have become more interconnected. As a result, the failure of one can trigger the failure of many. In finance, this phenomenon is often known as financial contagion, which can act like a domino effect. In this paper, we show an unprecedented increase in bank interconnectedness during the outbreak of the Covid-19 pandemic. We measure how extreme negative stock market returns from one bank can spill over to the other banks within the network. Our contribution relies on the establishment of a new systemic risk index based on the cross-quantilogram approach of Han et al. (2016). The results indicate that the systemic risk and the density of the spillover network among 83 banks in 24 countries have never been as high as during the Covid-19 pandemic – much higher than during the 2008 global financial crisis. Furthermore, we find that US banks are the most important risk transmitters, and Asian banks are the most important risk receivers. In contrast, European banks were strong risk transmitters during the European sovereign debt crisis. These findings may help investors, portfolio managers and policymakers adapt their investment strategies and macroprudential policies in this context of uncertainty.
We test the safe haven properties of the largest stablecoins (USDT, USDC, TUSD, PAX, DAI, GUSD) against the standard “nonstable” coins (BTC, ETH, XRP, BCH, LTC). Our dataset comprises high-frequency 1-minute data calculated as volume-weighted averages across 18 exchanges where these cryptocurrencies are traded, thus capturing the entire price movement around the world. Using a quantile coherency cross-spectral measure, we find that only TUSD, PAX, and GUSD can serve as safe havens.