Deception And Truth Analysis DATAbase
DATAbase is a structured dataset that includes Deception And Truth Analysis Scores for all US equities´ regulatory filings and transcripts dating back to 2008 and is updated in near real time.
DATAbase is a structured dataset that includes Deception And Truth Analysis Scores for almost all US equities´ regulatory filings and transcripts dating back to 2008 and is updated in near real time. DATA is grounded in the 100+ year research of deception science. We use NLP to look for more than 30 known behavioral differences between deceivers and truth tellers in text-based communications.
DATAbase´s regulatory filings include 10(k)s, 10(q)s, 8(k)s, DEF14s (proxies), 20-Fs, and S-1s (IPOs). Transcripts include earnings calls, guidance updates, conference presentations, and so on. Total number of equites is greater than 5,800, including coverage of the S&P 500, 400, and 600, as well as the Russell 2000, 1000, and 3000.
DATA Scores have been demonstrated to be predictive of future stock price performance. They are 88.4% accurate in discriminating between deceptiveness and truthfulness in text-based communications, with a p-value <1.41648534942489E-11 and a Cohen´s d of 4.23. Our Type I error is 11.3%, while our Type II error is 14.3%.
Approximately 10 minutes after a new filing is made on EDGAR, D.A.T.A publish new DATA Scores for the regulatory filings.
From receipt from D.A.T.A take less than 1 minute to score a new document.