Return asymmetry is a topic that emerges over and over again on PM Jar. It’s a topic that spans across investments strategies and philosophies (see the end of this article for links to previous PM Jar articles on return asymmetry). This is no coincidence – creating (positive) return asymmetry over time is the hallmark of great investors. So why is it so important to achieve positive return asymmetry (through decreasing the number of left tail / negative return occurrences)? Because positive return asymmetry saves investors from wasting valuable time and effort digging out of the negative return hole (compounding math is not symmetric: losing 50% in one period requires gaining 100% in the next period just to breakeven). This holds true for all investors, regardless of investment strategy and philosophy, hence why the theme of return asymmetry comes up so often.
Our last article on Howard Marks discussing the ability of a fund manager to outperform and add-value by reducing risk reminded me of article that a kind Reader sent me earlier this summer (Comgest Commentary 2013 July) in which the author describes with refreshing clarity the importance of creating positive return asymmetry and the interplay between compounding, capital preservation, and risk management. Compounding, Capital Preservation, Trackrecord
“The Asymmetry of Returns Dictates the Compounding of Returns:
Berkshire Hathaway CEO and legendary investor Warren Buffett is often quoted as saying, “Rule No.1: Never lose money. Rule No. 2: Never forget rule No. 1.” But why are these the most important two (well, one) rules of investing? The answer lies in the inherent asymmetry of returns, which is the basis for how returns compound over time.
If you start with $100 and subsequently gain 10% and then lose 10%, it may be surprising that you don’t end up back with the same $100 you had at the beginning. The reason is that your 10% loss hurt more, because it came off the larger asset base you had after your 10% gain. In sequence: $100 → gain 10% ($10) → $110 → lose 10% ($11) → $99. You can reverse the order of the gain and loss and the end result is still the same: $100 → $90 → $99, where your percentage loss is still based on a higher amount of capital than is your percentage gain. The end result is a net loss of 1%, hence the asymmetry – gains and losses of equal percentages have different impacts. As your returns swings get larger, this effect becomes more pronounced. For instance, starting with $100 and then gaining/losing 20% leaves you with a net loss of 4%, while gaining/losing 50% leaves you with a net loss of 25%. At the extreme, gaining/losing 100% leaves you with a net loss of 100% – all your capital, resulting on complete ruin. It doesn’t matter what any of the other payoffs are for someone who at any one point loses his or her entire bankroll.
Another way to look at this is to see what kind of return is necessary to get back to even after a loss. If you lose 10%, you need an 11% gain to get back to even. If you lose 20%, you need a 25% gain to close the gap. Losing 50% requires a doubling of your money, while losing 90% means you need a 900% return (!) to compensate. While 100% losses are rare in equity portfolios and thus true ruin is unlikely, this exercise shows how large losses cripple the long-term returns of a portfolio.”
“...the goal is to avoid an 'extinction' event, which I’ve put in quotes because extinction for an investment portfolio doesn’t only mean complete disappearance. It can also be seen as irreparable damage to a long-term track record.”
“Risk Management and Higher Math Are Not Natural Partners:
…The prevailing view of risk management in today’s investment world seems to be that it must be done with a lot of math and only a set of numbers, preferably from a complicated model, can describe an approach to risk. That’s just not how we see it. Instead, we think understanding the companies’ profitability characteristics is a far more effective way to understand the risk embedded in a portfolio. We side with James Montier, who wrote, “The obsession with the quantification of risk (beta, standard deviation, VaR) has replaced a more fundamental, intuitive, and important approach to the subject. Risk clearly isn’t a number. It is a multifaceted concept, and it is foolhardy to try to reduce it to a single figure.” Even the revered father of modern security analysis, Benjamin Graham, tips his cap to a more fundamental and less market-price-driven approach to risk: “Real investment risk is measured… by the danger of a loss of quality and earnings power through economic changes or deterioration in management.” It’s important to realize that our view of risk is at the fundamental security level, while standard industry risk models start from price volatility and covariance matrices, which are market-level inputs. In other words, we focus on what’s happening in the business, not what’s going on in the market, to understand risk. We think that our approach to risk management, that of decreasing the left tail of the distribution of potential outcomes by buying quality stocks is a more time-tested approach that runs a far lower risk of model specification error.”