Noorhan Elkhayat, PhD researcher, Technical University of Munich (TUM) 

Yewno Edge provides alternative data beyond fundamentals, and offers unique insights  into many trending topics or macro trends. With the massive income of data on an intraday  basis, it could be overwhelming to manually assess each relevant piece of news. The  platform enables users to conveniently assess how relevant key developments in the  economic, regulatory and political environment affect stocks in a direct or indirect way.  Moreover, the alternative data provided by Yewno’s AI technology could also be exploited  in financial research. Data analysis in financial research is extremely important. Many  researchers at one point of their research face the challenging task of managing very  large and complex datasets, as well as the need to construct and develop new  methodologies to manage and transform unstructured data. As part of my research  involves sentiment analysis and textual analysis, I discuss below this trending topic, and  how relevant data from the Yenwo Edge platform could be exploited.  

Sentiment analysis 

Overly optimistic firm-specific sentiment may be contagious across a network of closely  related firms. Moreover, sentiment may be contagious across international stock markets  (e.g, Baker, Wurgler and Yuan (2012)). Also, there is well-documented research on the pronounced effect of sentiment on small, young, highly volatile and difficult-to-arbitrage  stocks (e.g., Baker and Wurgler (2006)); and more recent research showing the strong  effect of sentiment on the time-series of aggregate market returns. Moreover, in the  anomalies literature, Stambaugh, Yu and Yuan (2012) document that mispricing is  stronger following periods of high investor sentiment. Therefore, the important role of  sentiment-driven noise trading is no longer debated in the community.  

There are several ways to measure sentiment, although online sentiment proxies have  become widely popular. Given the massive online traffic on platforms such as Twitter,  Reddit, among others, and the evidently large power they may exert on financial markets  (For e.g., the whole WallStreetBets fiasco), extracting the behavior of sentiment signals with high precision is an important but complex task. The Yewno AI technology makes  use of big data to perform sentiment analysis, and provides a firm-specific sentiment  measure that is easily accessible by the platform users. This saves researchers, analysts,  and investors a great deal of time and effort. Consequently, investors could for instance focus on forming sentiment-based investment strategies and generating abnormal  returns.  



Baker, M., & Wurgler, J. (2006). Investor sentiment and the crosssection of stock  returns. Journal of Finance, 61(4), 1645-1680. 

Baker, M., Wurgler, J., & Yuan, Y. (2012). Global, local, and contagious investor  sentiment. Journal of financial economics, 104(2), 272-287. 

Stambaugh, R. F., Yu, J., & Yuan, Y. (2012). The short of it: Investor sentiment and  anomalies. Journal of Financial Economics, 104(2), 288-302.

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