Michael Mauboussin has been the among the most erudite of investment strategists who can combine the practicality and psychology of investing yet articulate the same in a lucid way. This is one such paper from him which drills into the essence of investing like no other. Whilst the introduction and conclusion capture the essence in a succinct way, the paper in its entirety helps understand the nuances of investing as a probabilistic endeavour.
“Finding securities with gaps between price and value is the foundation of generating excess returns…Price is the relatively easy part….Value is the hard part.”
Why?
“This is because value is really “expected value,” which represents a range of potential payoffs with associated probabilities. Investing is an inherently probabilistic activity.
One of the most challenging aspects of understanding expected value is that excess returns can be the product of high probability events with relatively low payoffs, or low probability events with relatively high payoffs. In other words, how often you are right is not all that matters. What is vital is how much money you make when you are right versus how much you lose when you are wrong.”
But how does one go about assessing probabilities and payoffs:
“There are recognized approaches to setting probabilities, including frequentist, propensity, and subjective belief. Most forecasts in investing are based on subjective beliefs, which follow the laws of probability but require updating with new information. Probabilities also come with varying degrees of confidence—sometimes a belief can be held but with low confidence. Using probabilities instead of words is essential for clarity of communication and as a basis for feedback and learning.
Best practices in setting payoffs and probabilities include using base rates, applying sensitivity analysis and simulation, and, above all, always insisting on a margin of safety. The margin of safety reflects the size of the gap between price and value and allows for incorrect analysis and bad luck.”
He elaborates on each of these methods to assess probabilities and payoffs.
Once you assess the probabilities and payoffs, how does one size the bet to make sure you win big when right:
“The Kelly criterion is an investment guideline based on geometric mean maximization. The Kelly criterion offers two useful lessons even for those who do not use the principle in practice. The first is that every investment opportunity should include edge. The second is that it is possible to bet too much. Sometimes increasing the size of an attractive opportunity leads to a lower, not higher, expected return.
Volatility creates the difference between an asset’s arithmetic and geometric returns. This is called volatility drag. Many of the best investments over time are volatile and have large drawdowns.”
Whilst all this might sound rational, we aren’t particularly rational all the time:
“There are psychological challenges in dealing with probabilistic realms. One example is loss aversion, the idea that we suffer roughly twice as much from losses as we enjoy gains of comparable size. While the coefficient of loss aversion is around two on average, there is a great deal of variation by individual. Perhaps more importantly, our loss aversion coefficients tend to go up after we have suffered losses. This means that people may react differently to a financial opportunity based on the circumstances.
Time horizon is also very important. Markets tend to go up in the long term, but losses are common in the short term. Investors who evaluate their portfolios frequently are more likely to see losses and hence suffer from loss aversion. This means that the appetite for risk depends to some degree on the investor’s time horizon.
Excess returns are a function of skill and opportunity set. Skill can be assessed through batting average, how often you make money, and slugging ratio, how much you make when you are right versus how much you lose when you are wrong. Dispersion is a useful way to look at investment opportunities.”
He then touches upon the dispersion among asset classes:
“The opportunity sets of public equities, buyouts, and venture capital vary substantially. For example, based on the figures we used, 25 percent of public equity investments lost money over 5 years compared to 62 percent of venture capital investments. Offsetting that average is the fact that venture had more very high return investments than did public markets.”
Whilst a lot of this is intuitive in nature yet hard to follow in practice, making investing a challenging yet fulfilling craft, for those who are interested in the rationale, the paper digs deeper into these concepts.
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