Making Book and Making Trades

I had a paper route as a kid.  It was an evening paper, which meant that I made my deliveries after school.  One of my first stops was a barber shop that fronted for a bookmaking operation.  Even as a kid I could see that something was off because there were always a bunch of men sitting around in the afternoon without getting haircuts and the barber/owner had two telephones. 

Naturally, I wanted to get in on the action, but the proprietor (wisely) never even acknowledged that there was gambling on the premises.  However, he did agree to allow me to bet on the area football team’s game each week (the Buffalo Bills)  for his subscription.  If I picked the game right, he paid double and, if I missed, he got a free paper.  I generally won, but I suspect he considered it a loss leader for future business. 

Most people conceive of trading in a similar way.  The idea is to pick winners.  And they’re right to a point, but only to a point.  You see, whenever I’d get cocky about my winning record, my bookie would remind me that I wasn’t picking against the spread — I was picking outright.  Because stocks have prices, trading isn’t really about picking outright winners.  It’s like picking against the spread.

That’s the basic point that index advocates make with respect to beating the market.  They say that the market immediately prices in all information related to a stock’s value so that it’s impossible to win overall “against the spread.”  That’s false, of course, because the market is not a weighing machine — rationally weighing intrinsic value via price — it’s a voting machine — reflecting  popularity decisions about stocks, which can be wildly irrational.

A fallback position of index advocates is that the irrational judgments of individuals somehow add up to rationality, in a sort of Wisdom of Crowds effect.  But as these experiments show, crowds can lead to big mistakes and perversely give their members false confidence at the same time on account of social influence.  Moreover, a new study suggests that markets become more unstable and prone to bubbles precisely as they move closer to the ideal of information efficiency.  Finally, game theory helps clarify optimal (rational!) behaviors in simple strategic games, but it becomes largely irrelevant in complex games — many agents with many strategies (like markets). In that setting, as this study shows, dynamical systems theory offers far more insight into system dynamics.  We aren’t terribly rational much of the time.

The academic points outlined above are probably better made by another gambling example.  An old trader friend from New York got his start (of a sort) in trading by gambling in college.  This was in the days before cell phones and on-line gaming.  My friend would work a gambling arbitrage (subject to serious counterparty risk) by betting against the home team with a nearby bookie and against the visiting team with a bookie in the visiting team’s city to take advantage of the wide diversity of point spreads.  As with stock prices, point spreads do not reflect an objective assessment of the relative strengths of teams.  Rather, they reflect the betting habits of bettors and thus the irrational hopes and fears of fans.  Optimism bias is never more prevalent than among fans of sports teams.

None of this is to suggest that it’s easy to beat the market or to beat point spread with any consistency and persistency.  But as any bookie willing to share will tell you, spreads are made not to reflect the relative strength of the teams but, instead, to balance out the bets on each team.  Trading is no more rational than gambling.


I grew up in this business in the early 90s at what was then Merrill Lynch.  My decade of legal work in and around the industry didn’t prepare me for big-time Wall Street trading.  I’d ride the train to Hoboken early in the morning, hop on a ferry across the Hudson, walk straight into the World Financial Center, enter an elevator, and press 7. Once there, I’d walk into the fixed income trading floor, a ginormous open room, two stories high, with well over 500 seats and more than twice that number of computer terminals and telephones.  When it was hopping, as it typically was, especially after a big number release (like today’s non-farm payroll data), it was a cacophonous center of (relatively) controlled hysteria.  

It was a culture of trading, which makes sense since it was, after all, a trading floor.  Most discussions, even trivial ones, had a trading context.  One guy (and they were almost all guys) is a seller of a lunch suggestion.  Another likes the fundamentals of the girl running the coffee cart.  Bets were placed (of varying sorts) and fortunes were made and lost, even though customers did most of the losing because we were careful to take a spread on every trade.  The focus was always on what was rich and what was cheap and the what if possibilities of and from every significant event (earthquake in Russia – buy potato futures).  The objective was always to make the most money possible, the sooner the better.

Interestingly, value was almost never at issue.  The idea was to exploit inefficiencies and – especially – the weaknesses of whoever is on the other side of the trade right now.  Michael Lewis’s wonderful first book, Liar’s Poker, re-issued in 2010 and finally being made into a movie, captures this culture (in his case, at Salomon Brothers) pitch perfect.

Now that the focus of what I do has changed, I am primarily consumed with finding value through investing – which must be distinguished from trading.  As Barry Ritholtz put it recently, “[t]rading (as opposed to investing) is more about laying out probabilities of risk versus reward; investing is about valuations within the longer secular macro picture.”  I would suggest that trading is about selling what is rich and buying what is cheap while investing is about finding, acquiring and holding on to value.  That distinction is, I think, the key to why so many analysts misapprehend the market relevance of another terrific Michael Lewis book (which has been made into a recent movie), Moneyball (nicely satirized here).

Moneyball focuses on the 2002 season of the Oakland Athletics, a team with one of the smallest budgets in baseball.  At the time, the A’s had lost three of their star players to free agency because they could not afford to keep them.  A’s General Manager Billy Beane, armed with reams of performance and other statistical data, his interpretation of which was rejected by “traditional baseball men” (and also armed with three terrific young starting pitchers), assembled a team of seemingly undesirable players on the cheap that proceeded to win 103 games and the divisional title. 

Unfortunately, much of the analysis of Moneyball from an investment perspective is focused upon the idea of looking for cheap assets and outwitting the opposition in trading for those assets.  Instead, the crucial lesson of Moneyball relates to finding value via underappreciated assets (some assets are cheap for good reason) by way of a disciplined, data-driven process.  Instead of looking for players based upon subjective factors (a “five-tool guy,” for example) and who perform well according to traditional statistical measures (like RBIs and batting average, as opposed to on-base percentage and OPS, for example), Beane sought out players that he could obtain cheaply because their actual (statistically verifiable) value was greater than their generally perceived value. 

In some cases, the value difference is relatively small.  But compounded over a longer-term time horizon, small enhancements make a huge difference.  In a financial context, over 25 years, $100,000 at 5%, compounded daily, returns $349,004.42 while it returns nearly $100,000 more ($448,113.66) at 6%.

We live in a world that doesn’t appreciate value.  In the investment community, indexers are convinced that value doesn’t exist and most other would-be investors don’t have a good process for analyzing the data and are too focused on trading to recognize value when they see it.  While proper diversification across investments can mitigate risk and smooth returns within a portfolio, too much portfolio diversification (“protection against ignorance,” in Warren Buffett’s words) requires that value cannot be extracted. 

Similarly, behavioral finance shows us how difficult it is for us to be able to ascertain value.  Our various foibles and biases make us susceptible to craving the next shiny object that comes into view and our emotions make it hard for us to trade successfully and extremely difficult to invest successfully over the longer-term.  Recency bias and confirmation bias – to name just two – conspire to inhibit our analysis and subdue investment performance.  Investing successfully is really hard.

In another context, stockholders are not demanding value from the executives of the companies in which they invest and are frequently acquiescing to their being paid far more than they are worth.  For example, Stan O’Neil, the guy who ran my old firm Merrill Lynch into the ground, was rewarded with an astonishing $161 million for doing so. Ken Blanchard, who lives one neighborhood over from me, said in church just last week that the ridiculous explosion in executive pay is wrong but it’s the way the score is kept.  We’re nuts for allowing it.

To expand the idea (perhaps to the point of breaking), we must always resist the urge to trade – even a good trade – when investing makes more sense.  While I don’t mean to suggest that a one-off trip to Vegas for a week-end of fun can never be a good idea, too many trips like that can come between you and your goals and can thus be antithetical to a rewarding future.  My ongoing analysis of human nature suggests that we are not just subject to the whims of our emotions.  We are also meaning-makers, for whom long-term value (when achieved) can be fulfilling and empowering.  It simply (it is simple, but not easy) requires the process and the discipline to get there.  What we really need is not always what we expect or want at the time.

This point was driven home to me anew by the terrific movie, 50/50, written by Will Reiser about his ordeal with cancer.  As Sean Burns noted in Philadelphia Weekly, Reiser’s best friend was the kind of slovenly loudmouth that you’d usually find played in the movies by Seth Rogen, except that his best friend really was Seth Rogen.  Rogen’s fundamental, unexpected decency and supportive love grows more quietly moving as the film progresses.  Rogen was undervalued generally and his love and support provided great value to Reiser. 

As the cliché goes, nobody lies on his deathbed wishing he’d spent more time at the office.  We appreciate meaning and value more in the sometimes harsh reality of the rear-view mirror rather than in our mystical (and usually erroneous) projections into an unknown future.

Are you looking for value or just the next trade?