The Man Who Solved the Market by Gregory Zuckerman • Novel Investor
https://novelinvestor.com/notes/the-man-who-solved-the-market-by-gregory-zuckerman/
He hoped to recreate the fund in the image of a casino. If they had a small statistical edge, the law of large numbers would tilt the odds in their favor. The small edge was based on numerous recurring patterns that were faint but noticeable thanks to their trove of data.
“Their goal remained the same: scrutinize historic price information to discover sequences that might repeat, under the assumption that investors will exhibit similar behavior in the future.”
“What you’re really modeling is human behavior. Humans are most predictable in times of high stress — they act instinctively and panic. Our entire premise was that human actors will react the way humans did in the past…we learned to take advantage.” — Kresimir Penavic
“Medallion’s staffers had settled on a three-step process to discover statistically significant moneymaking strategies, or what they called their trading signals. Identify anomalous patterns in historic pricing data; make sure the anomalies were statistically significant, consistent over time, and nonrandom; and see if the identified pricing behavior could be explained in a reasonable way.”
“LTCM’s basic error was believing its models were truth. We never believed our models reflected reality — just some aspects of reality.” — Nick Patterson
“We’re right 50.75 percent of the time…but we’re 100 percent right 50.75 percent of the time. You can make billions that way.” — Robert Mercer
“For all the unique data, computer firepower, special talent, and trading and risk-management expertise Renaissance has gathered, the firm only profits on barely more than 50 percent of its trades, a sign of how challenging it is to try to beat the market — and how foolish it is for most investors to try.”
The team read hundreds of research papers but when they tested a paper’s proposed strategy proposed, most failed to live up to the published results.