Topic: Profiting from Information Arbitrage in the Financial Markets (Read 99 times)

Lesson from the traditional markets for crypto...https://hackernoon.com/profiting-from-information-arbitrage-in-the-financial-markets-3abfca9806d8

"On January 3rd 2019, Bristol-Myers Squibb (BMY) acquired Celegene (CELG) for $74 billion. CELG rose from 66.64 to 87.86 per share, giving it a 31.8% gain overnight. Although most professionals missed out on these gains, there were other hidden opportunities to be had, if you knew where and how to find them.

A group of equities that have relatively unknown and indirect relationships to CELG also rose in value but not immediately. The delay in their rise was sufficient enough that it gave time for any funds, traders or investors to take positions and profit. This is an example of information arbitrage in the financial markets. It happens from time to time and when it does, most people miss the opportunity.

This also relates to a paper titled “Contagious Speculation and a Cure for Cancer: A Non-Event that Made Stock Prices Soar,” (with Tomer Regev, Journal of Finance, February 2001, Vol. 56, №1, pp. 387–396). The research described an event with a company called EntreMed (ENMD was the symbol at the time):

“A Sunday New York Times article on a potential development of new cancer-curing drugs caused EntreMed’s stock price to rise from 12.063 at the Friday close, to open at 85 and close near 52 on Monday. It closed above 30 in the three following weeks. The enthusiasm spilled over to other biotechnology stocks. The potential breakthrough in cancer research already had been reported, however, in the journal Nature, and in various popular newspapers ~including the Times! more than five months earlier. Thus, enthusiastic public attention induced a permanent rise in share prices, even though no genuinely new information had been presented.”
Among the many insightful observations made by the researchers, one stood out in the conclusion:
“[Price] movements may be concentrated in stocks that have some things in common, but these need not be economic fundamentals.”
Capturing information arbitrage opportunities can be done using advanced techniques in the area of Natural Language Processing and Understanding (NLP/NLU). This also includes processing of correlation matrix datasets based on data such as public company profiles, encyclopedias, peer-reviewed scientific literature, news and patents located here.

Using a NLP/NLU correlation matrix dataset of US publicly traded equities, we generated a cluster (or basket) of companies that have relationships to CELG based on symbiotic, parasitic and sympathetic latent entanglement.

What we found, with the top five scoring equities, were unique opportunities to profit ahead of the market. We’ve produced the following slides with charts to show where gains should have been locked in."
https://hackernoon.com/profiting-from-information-arbitrage-in-the-financial-markets-3abfca9806d8