The differential impact of corporate blockchain-development as conditioned by sentiment and financial desperation

White knight in dark days? Supply chain finance firms, blockchain, and the COVID-19 pandemic

“…In addition to the skewness-adjusted t- test, we also employ the adjusted Patell Z -test proposed by Kolari and Pynnonen [5] . The adjusted Patell Z-test, which is a modified version of the Patell Z-test, successfully captures the cross-correlation of the abnormal returns.…”

“…6 This belief is also noticed in the stock price movement of several firms associated with this new disruptive technology. For instance, Cioroianu et al [5] combine the blockchain “hype” on stock price [6] and the impact of sentiment on equity pricing [7] and show how firms can generate short-term value. On the contrary, another group of researchers opines that blockchain-enabled firms may not always be trustworthy to investors.…”

We Reddit in a Forum: The Influence of Message Boards on Firm Stability

“…Further, utilizing 400,000 S&P 500 stock-related Twitter messages, Sprenger et al (2014) found that returns before good news events are more pronounced than those associated with bad news events, while Renault, 2017 provided evidence of sentiment-driven noise trading at the intraday frequency. We further develop upon the work of Akyildirim et al (2020), Allen et al (2021), Cioroianu et al (2021), Philippi et al (2021), Meegan et al (2021) and Hu et al (2021), which have focused on the growth of fintech and cryptocurrencies, some of which have also been subjected to the attention of message-board sentiment. Identifying links in such induced sentiment generation is important, but we must develop methods of measuring abnormal returns, as our research attempts to do.…”

“…4 To develop significant methodological robustness with regard to developing a suitable lexicon, a variety of types were considered in the aftermath of the collection of r/WallStreetBets posts and comments. As per Cioroianu et al (2021), we initially expanded the Python package "pysentiment," which utilized the Harvard General Inquirer IV-4 dictionary and the Loughran and McDonald financial sentiment dictionary for sentiment analysis of the key posts and comments that had been identified. While working quite well with regard to sentiment analysis, it was identified that few these lexicons were representative of the crude and foul language commonly used by those posting in the r/WallStreetBets forum.…”

The differential influence of social media sentiment on cryptocurrency returns and volatility during COVID-19

“…This pandemic has generated substantial global financial market volatility and has driven investors to seek alternative assets to preserve their portfolios at a satisfactory risk-return trade-off level. Cryptocurrencies have attracted speculators as well as technology-fluent investors ( Lee et al, 2020 ), some of which have been attracted through the product validation provided by several widely known public figures and corporations, many of whom have had limited, if not no experience at all developing and selling technologically developed products ( Akyildirim et al, 2020 , Cioroianu et al, 2021 , Fletcher et al, 2021 ). As an asset, cryptocurrencies have been considered to be primarily employed for speculation purposes but not as an alternative currency and medium of exchange ( Fry, 2018 , Kyriazis et al, 2020 ).…”