August 23, 2022
“Moneyball,” by Michael Lewis, was published in 2003. It documents the 2002 season of the Oakland Athletics (or, as most fans refer to them, “the A’s”) and their General Manager, Billy Beane. The A’s had one of the lowest payrolls in Major League baseball, which conventional wisdom said would doom them to a season of losing to their richer counterparts. Yet 2002 marked the third consecutive season that the A’s had reached the playoffs. Over those three years, the team won more than 60% of the games it played.
How did a team with little money and low expectations buck the trend and become one of the great success stories in pro sports? The A’s completely re-thought the approach to constructing a baseball team. They replaced emotion with logic and subjectivity with objectivity. In doing so, they permanently changed the way the game is played, managed and discussed. They also provided some valuable lessons that can be ported to other endeavors, including investing. We explore one of those lessons here.
As long as humans are involved, neither sports nor investing will resemble science. Short-term results will be subject to randomness. However, in both cases, a basic understanding of probability increases the likelihood of long-term success.
The Oakland A’s approach to winning baseball games relied heavily on probability. It was grounded in the fact that a team’s number of wins over a full season was highly correlated with the total number of runs that team scored. So, while many other teams over-valued pitching and defense, the A’s were willing to sacrifice in those areas in exchange for a greater probability of scoring runs.
To build a team in that mold, they first needed to understand what factors maximized the probability of scoring runs. In analyzing statistical data on the performance of hitters, they discovered that many of the traditionally-emphasized offensive categories such as batting average and runs batted in had a lower correlation to team-wide run production than less-followed statistics such as on-base percentage and slugging percentage.
They found that on-base percentage was especially important. A batter’s on-base percentage is simply the probability that the batter will avoid using up one of the 27 valuable outs a team is allotted over a nine-inning game. It is calculated as the number of times he reaches base safely divided by his total number of plate appearances. Whether the batter reaches base by getting a hit, by walking, or by being hit with a pitch is irrelevant.
Logically, then, the A’s sought out players whose approach to hitting lent itself to reaching base more frequently. That meant finding patient hitters who were not prone to swinging at pitches outside of the strike zone. First, patient hitters tended to draw more walks. All else equal, more walks meant a higher on-base percentage.
Second, patient hitters were more likely to get ahead in the count against the pitcher. The A’s understood that after three pitches, a batter facing a count of two balls and one strike had a vastly higher probability of success than a batter facing a count of one ball and two strikes. Hitters who could resist swinging at bad pitches and work the count in their favor enjoyed a tremendous advantage over their less disciplined counterparts.
The A’s didn’t stop there. Once a batter reached base, they eschewed many of the traditional strategies that managers had employed since the game’s inception. These included sacrifice bunts, base stealing and the hit-and-run strategy. Though these tactics had been engrained in the game’s DNA for over a century, each of them also entailed the risk of making an out. The A’s analysis told them that utilizing these strategies did not increase the probability of scoring runs enough to offset the detrimental probability of making an out.
In the end, the basic calculus went something like this: To win a high percentage of games, increase the probability of scoring a large number of runs. To score a large number of runs, decrease the probability of making an out. To decrease the probability of making an out, fill your lineup with patient hitters and avoid tactics that risk using outs unproductively.
When viewed this way, it seems like a fairly simple and logical formula. Yet, despite the fact that statistics have always been an integral part of the game, the A’s were the first team to employ this approach in roster construction and game management.
For an investor, the equivalent to winning games is to successfully achieve as many financial goals as possible. While the exact goals of each investor may differ, as a general rule, the probability of success is increased by accumulating as much savings as possible over the course of the investing horizon.
What actions increase the probability of accumulating as much savings as possible?
Just as patient hitters shift the probability of success in their favor by getting ahead in the count, patient investors can do the same by saving consistently, by remaining invested, and by not trying to constantly time entry and exit points.
Historically, on any given trading day, the probability of a positive return for stocks is only slightly better than a coin flip. However, when the holding period is extended from a day to a month, the probability of a positive return increases to almost 60%. Extending it to a year increases the probability of success to about 67%.
Probability swings even further in the investor’s favor over multi-year periods. The probability of the return being positive over any given rolling 5-year period has been nearly 90%. Over 10 years, it has been 95%, and over 20 years, it has been 100%.1
One might argue that owning conservative assets is a better bet from a probability standpoint, since their prices go down less frequently than the prices of stocks. However, as noted above, the passage of time helps to smooth out the volatility of stock returns. It then ends up being the magnitude of the positive returns in stocks that drives greater wealth accumulation.
Over the 35 years ending in 2021, stocks have outperformed intermediate Treasury bonds by more than 5% annually and cash investments by more than 8% annually.2 The combination of the increasing probability of positive returns over time and the much larger magnitude of those returns argues for a healthy allocation to stocks for investors with all but very short time horizons.
Because many people are naturally loss-averse, they may under-allocate to stocks. This happens even though the time horizon is usually long enough to defuse most of the risk. Many investors and advisors resort to unnecessarily complex investment strategies to reduce the probability of a near-term drop in value, even though that near-term drop is highly unlikely to impact long-term success.
Covered call strategies, absolute return strategies, and annuities are examples of this. Each of these approaches sacrifices potential upside in exchange for a more limited downside. Yet, the long-term return profile of stocks argues for simply owning the stocks without any of the bells and whistles. In that respect, these more complicated approaches are akin to the hit-and-run and sacrifice bunt strategies that the A’s avoided. The benefit derived from some amount of near-term downside protection is generally not enough to offset the potential upside surrendered in the process.
The A’s knew there would be times when their strategy would not work. Many factors that impact the outcome of a given game are outside of a team’s control (e.g., weather and injuries). The idea was to focus on those factors over which they had control and to exercise that control to their maximum advantage.
In investing, cost is almost a completely controllable factor. All else equal, every dollar that is not sacrificed in fees, commissions, or other expenses stays in the portfolio and earns a long-term return. In any given year, the amount paid in advisory and fund expenses may seem relatively trivial in comparison to the amount invested. However, over time, the compounding effect of reduced fees tilts the probability of success further in the investor’s favor.
Smart tax management is another way to increase the probability of success.
Similar to high fees, every dollar taken away in taxes reduces the power of compounding in the portfolio. While it can sometimes be wise to realize a taxable gain by selling shares (e.g., when a particular holding has become too large as a percentage of the portfolio), excessive trading activity can be harmful. It is important to keep in mind that in order to come out ahead when selling an asset with a taxable gain, the replacement asset needs to generate enough extra return to more than offset the tax bill on the asset being sold.
On the other hand, selling an asset to harvest a deductible tax loss has the opposite impact. The required break-even return on the replacement asset is lower because of the money saved on taxes from the sale.
As a rule, people prefer certainty over uncertainty. Unfortunately, investing, like baseball, will always entail some degree of risk. However, there are actions that can be taken (or avoided) that can dramatically decrease that risk over time.
The success of the low-budget Oakland A’s was predicated on understanding which controllable factors they could leverage to tilt the odds as far in their favor as possible. The approach was data-driven, favoring proof over speculation and logic over intuition. Investing offers the same opportunity to use an understanding of probability to greatly enhance the likelihood of meeting long-term financial goals.
1. Probability of positive returns calculated by One Day In July using historical index data for the S&P 500 from 1928 through 2021. Periods of one year or less are calculated based upon the index price change, while periods of more than one year include the reinvestment of dividends.
2. Asset class returns sourced from Portfolio Visualizer for the period 1987 to 2021.
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