Trading Bases: A Story About Wall Street, Gambling, and Baseball (Not Necessarily in That Order )
Joe Peta
Language: English
Pages: 384
ISBN: 0525953647
Format: PDF / Kindle (mobi) / ePub
After the fall of Lehman Brothers, Joe Peta needed a new employer. He found a new job in New York City but lost that, too, when an ambulance mowed him down as he crossed the street on foot. In search of a way to cheer himself up while he recuperated in a wheelchair, Peta started watching baseball again, as he had growing up. That's when inspiration hit: Why not apply his outstanding risk-analysis skills to improve on sabermetrics, the method made famous by Moneyball--and beat the only market in town, the Vegas betting line? Why not treat MLB like the S&P 500?
In Trading Bases, Peta shows how to subtract luck--in particular "cluster luck," as he puts it--from a team's statistics to best predict how it will perform in the next game and over the whole season. His baseball "hedge fund" returned an astounding 41 percent in 2011-- with daily volatility similar to funds he used to trade for. Peta takes readers to the ballpark in San Francisco, trading floors and baseball bars in New York, and sports books in Vegas, all while tracing the progress of his wagers.
The Work: My Search for a Life That Matters
Relish: My Life in the Kitchen
My Bondage and My Freedom (Penguin Classics)
The Hypocrisy of Disco: A Memoir
Pascal, not only my boss but a fellow technology stock trader on the Nomura desk, knew this and wasn’t about to cede his distinction as not only the most profitable trader at Barclays Capital (formerly Lehman Brothers) but possibly on the entire Street since 2007. The culture and energy of trading desks have always suited me, and be it 7 A.M. in New York or 4 A.M. in San Francisco, I’ve never dreaded coming to work. The dynamic on this desk, even in my mid-forties, had me leaping out of bed each
projection. As shown on page 78, the projection yielded a win probability of .5762 for the Reds and .4238 for the Brewers. Oddsmakers deemed this an even matchup, with both teams listed on the money line at -105. That converts into an implied chance of winning of 51.22 percent for both teams. My calculation deemed the Reds had a 6.4 percent (.5762–.5122) better chance of winning than the implied odds. Applying the same steps as I had for the Brewers and Reds, I came up with the following list of
personnel with an eye to the save metric. Managers and relievers (and their agents) are addicted to the save. To maximize the chances of winning ball games, a change in that way of thinking must take place, and it must come from the top of an organization. The best manager and motivator of people I have ever seen ran the NASDAQ trading desk at Lehman Brothers the first eight years I worked there. To say he had a presence is a vast understatement. Mad Men’s Don Draper, who’s nearly a spitting
investment fund really is—betting other people’s money) by putting on a pairs* trade in support of his opinion. He just smugly insisted, “Apple has no idea what it’s doing in the phone business. We’ll see in the end.” My aggravation manifested itself in speechlessness and probably a red face. It’s almost beyond my comprehension how someone could perform research, form a strong opinion, and then not want to express his conviction in that opinion—in other words, back up the work he’s done, with
entertaining college bowl preview e-mails, I used that same mailing list to create a similar NCAA tournament preview. In what I thought clearly established the e-mail as entertainment and not serious analysis, the first sentence read, “My annual quest to go 63-0 in the tournament begins in a few hours, and I have a feeling this year is the year I pull it off.” Later that afternoon, as the last of the first set of four games was ending—dooming me to a 0-4 start to the day—I sent another e-mail
