Lessons on winning and losing as an investor from “The Art of Execution”
I recently read Lee Freeman Shor’s “The Art of Execution” and thought I would publish a brief review/overview as it resonated with me. This is more of a Cliff Notes summary than anything thoughtful btw.
Shor was an allocator at Old Mutual Global Investors. While he was there, he created a “Best Ideas” portfolio by funding 45 of what he believed to be the world’s greatest investors with between $20 and $150m each and the proviso that they own a maximum of 10 stocks at any single point in time. He managed this “Best Ideas” fund of funds from June 2006 through October 2013 and he had complete transparency (likely via SMAs) into the 1,866 investments and 30,874 trades made by these 45 managers during the 7 year life of the fund. His analysis of these investments and trades is the foundation of the book.
He analyzed every investment and trade made by these 45 managers and found that on average they only made money on 49% of their investments with some of the best ones only making money on 30% of their investments. Despite this, almost all of them made money overall — and yes, slugging % vs. batting average is well understood by anyone reading this. Shor’s most powerful point is that investment performance is largely dictated by what an investor does after they buy a stock, specifically by how they deal with both losing and winning positions over time (obviously an investor needs to be correct in their initial purchase decision at least some of the time). This was interesting to me as was the data he supplied to support his conclusions.
Shor categorized investors into 5 different “tribes” based on their behavior with respect to losing and profitable positions. Investors dealt with losses by being either “Rabbits,” “Assassins,” or “Hunters.” Investors dealt with gains by either being a “Connoisseur” or a “Raider.” To jump ahead, an investor should strive to be either an “Assassin” or a “Hunter” when losing money on a position and a “Connoisseur” when making money on a position. Based on his data, being a “Rabbit” or a “Raider” must be avoided at all costs.
The “Rabbits” did nothing when they were losing money. They were more interested in “being right than making money” to quote Ned Davis and always defended their losing positions after re-underwriting them. To quote from the book, “They were capable of constantly adjusting their mental story and time frame so that the stock always looked attractive…It never ceased to amaze me how many times the same two villains popped up in the stories told by Rabbits harboring a losing position: Mr. Market (‘The market is being stupid’) and his sidekick Mr. Unlucky (‘It wasn’t my fault, I was unlucky because of XYZ that no one could have foreseen’).” I loved this line. I have never known a good investor who blamed underperformance on either the market being wrong or bad luck. But I have known many bad investors who regularly did both. As my friend and mentor Steve says, “there are only two things in investing, numbers and excuses, and if you don’t have the first, no one cares about the second.”
The following statistic was astonishing to me with respect to losing positions: “Out of the 941 investments that lost money, when measured from the moment the investor bought the stock to the moment they sold, only 32 (3%) made money thanks to the trading activity of the managers whilst they were invested (by trading activity I mean buying shares in the company after the initial purchase and before the final sale)…Of the 131 investments that fell more than 40%, only 21 went on to produce returns of over 100%.” So many investors have said that being willing to take a loss is critical to being a great investor, but I was still surprised to see those numbers lay it out in living color. The book makes it obvious that one should not be a “Rabbit” and that one should almost always take action with losing positions, either by reducing them or increasing them.
The “Assassins” were those investors who were quick to take losses. The “Assassins” consistently sold losing positions when they were down 20 to 33%. That is a much bigger loss than most traditional stop-loss levels, but this does keep one from being whip sawed. His data suggested that of the 421 losing positions that were sold when they were down less than 10%, 59% of these went on to make money — i.e. in his data set a 10% stop loss was too tight. Shor’s analysis of the 946 losing positions in his data set suggested that the fund managers would have been better cutting the losing position after it fell by more than 33% roughly 2/3 of the time based on his analysis of the relative returns of each position after it began to lose money. As a sidenote, Shor quotes both 946 and 941 as the number of losing positions. I am unsure why the discrepancy exists — perhaps it is the difference between realized losses and positions that were losing money at one point in time.
The “Assassins” also generally sold losing positions that were down less than 20% if the positions had not begun to rebound within 6 months after beginning to lose money. The “Assassins” sold 64% of their losing positions within 6 months of the initial purchase and 83% of their losing positions within 12 months of the initial purchase.” The “Assassins” stops were thus based on both $ losses and time. Shor quotes a study by Frazzini called “The disposition effect and underreaction to news” which was published in The Journal of Finance in 2006. Frazzini found that the highest returns were generated by those investors who sold out of losing positions at the highest rate and the worst returns were generated by those investors who sold out of losing positions at the lowest rate.
The “Hunters” were those investors who increased positions when they were losing money and averaged down. No statistics were shared on “Hunters,” which was disappointing and I inferred from the book that very few of Shor’s 45 underlying managers were “Hunters.” I would have liked to see the statistics on the “Hunters” as many of my best investments over time were positions that I added to significantly when they were down.
Since there was minimal detail on being a “Hunter” in the book, I will say that John Hempton’s post “When do you average down?” is the best thinking I have ever read on the topic. I would paraphrase his thinking as 1) limit your maximum cumulative losses to a set number, 2) do not average down in a business that is highly leveraged and 3) do not average down in a business at risk of technological obsolescence. This is a powerful framework. While I averaged down successfully many times (Nvidia in 2012/2013 and Facebook in 2012 come to mind), my long only track record would have been dramatically better if I had simply followed Hempton’s first two rules.
There is nothing more painful than losing roughly 1000 bps of performance over a 2–3 year period in a strong upmarket on a position that was never more than ~350 bps. And I managed to do this not once, but twice. I lost circa 1000 bps on both Nextel International and Accretive Health despite never having more than ~350 bps in either stock. Ouch. Based on my experience with Accretive Health, I would also add “do not average down in businesses that are facing increasing existential regulatory risk” to Hempton’s list. Regardless, as a “Hunter,” it is important to have a framework for when to stop “hunting” and stop averaging down.
Intellectually, it does make sense that one should either be a “Hunter” or an “Assassin” and not a “Rabbit” when faced with a loss as there is no scenario for future stock performance where doing nothing was the correct decision. i.e. If the stock outperforms, one should have bought more and if the stock underperforms further, one should have sold. Obviously this goes for all stocks at every point in time, but there is an immense amount of evidence from behavioral finance that investors are particularly irrational when it comes to losing positions. Thus the importance of having a discipline and bias towards action for these positions.
The “Raiders” were those investors who were quick to take gains and sell their winners. Unsurprisingly, this was not a winning strategy. Of the 611 stocks (66% of all winning investments) that were sold for a profit of less than 20%, 370 of them (61%) continued to go up with many of these going on to be significant winners. “Rabbits” were also often “Raiders,” which is a terrible combination given the kurtosis in the stock market. The only “Raider” who was successful was also an “Assassin.” The book suggests that one should not be a “Raider.”
The “Connoisseurs” were the investors who rode their winners. Interestingly, these investors had a worse batting average than Shor’s overall group of 45 portfolio managers and lost money 60% of the time on average. Shor did not share any more data on the “Connoisseurs,” although he did share numerous case studies of specific positions. This was less interesting to me because this is so well known. The only trait shared by all of the best investors that I know is that they let their winners run. They are all “connoisseurs.” This is true of the best deep value investors and the best aggressive growth investors — they all let their winners wrong. And yet this is so hard for me to do; I constantly struggle to be more of a “connoisseur.” Kaizen.
Shor distills all of this into what he calls “The Winners Checklist” which is 1) Best ideas only, 2) Position size matters, 3) Be greedy when winning, 4) Materially adapt when you are losing and 5) Only invest in liquid stocks. All good thoughts.
Quick, easy read and resonated with me as I really believe that success as an investor comes down to finding a philosophy and process that aligns with one’s own individual emotional makeup such that it is possible to be rational when wrong and thereby make high quality decisions when losing money. Whatever the investment process may be, the most important takeaway from “The Art of Execution” is that one must always take action when losing significant money — either by buying more or cutting the position as doing nothing and being a “Rabbit” is the worst possible course of action.
To forestall the inevitable Twitter commentary, yes I am aware that it is unlikely these conclusions are robust statistically and a 7 year time frame is far too short to draw really meaningful conclusions.
