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Bloomberg whitepapers - Sentiment

Twitter Finance Analytics

twitter-data-and-the-financial-markets

https://data.twitter.com/en/industries/finance

https://developer.twitter.com/en/enterprise/finance

Trending on Twitter: Social Sentiment Analytics February 20, 2014

Bloomberg seminars and extra

Signals, Not Noise

Predictive Analysis of Bloomberg Automated Intelligence
Trading News Sentiment Themes With pICA

  • extra

GENERATIONAL TRENDS AND COVID-19: NEW INSIGHTS AND RESEARCH

Once you put the price number in, it potentially destroys the effectiveness of that new data source.”

Bloomberg technical papers

Sentiment impact on stock prices of news with selected topic codes: Part One

We have found that sentiment as reflected in news stories in the Bloomberg End-of-Day News and Analytics File has an impact on the prices of large-cap U.S. stocks, with the impact differing across stories depending on the set of topic codes with which they are tagged

EMBEDDED VALUE IN BLOOMBERG NEWS & SOCIAL SENTIMENT DATA

When rational arbitrageurs have limited risk-bearing capacity and time horizons, the actions of irrational noise traders can affect asset prices (De Long, Shleifer, Summers, & Waldmann, 1990a). Such actions can be interpreted as being driven by fluctuating investor sentiment. This creates the possibility of trading profitably on the basis of investor sentiment, most obviously by being a contrarian, but, under some circumstances, it may be rational to “jump on the bandwagon” and bet with, rather than against, noise traders (De Long, Shleifer, Summers, & Waldmann, 1990b). Various proxies for investor sentiment have been proposed (Baker & Wurgler, 2006), but perhaps the most direct way to measure sentiment in the stock market is to analyze the words of those who are commenting on stocks. One traditional source of such comments is stories in the news media (Tetlock, 2007).
More recently, Google searches and Twitter feeds have been used (Mao, Counts, & Bollen, 2015).

Sentiment impact on stock prices of news with selected topic codes: Part Two Ivailo Dimov - 2018

We use Latent Semantic Analysis (LSA) with a suitable Independent Component Analysis (ICA)
regularization to retrieve latent, interpretable topic code factors in Bloomberg’s machine-readable
news dataset

three types of equity trading strategies based on sentiment data

Lei Huang Newsfeed dymistified

... paint a coherent picture: the divergence is striking between what people read and what moves the markets
so
IDEA - ... CONSTRUCT NEWS-DRIVEN fundamental context critical in the determination of longer-term price movements

Lei Huang Long-term performance of U.S. equity long/ short strategy- Based on Bloomberg news sentiment