The Golden, Ugly, and Often Times Complicated Truth of Profitable Portfolio Management
“Ask, and it shall be given you; seek, and ye shall find; knock, and it shall be opened unto you”- Matthew 7:7–8
You were probably not expecting a quote from the Bible to spearhead an article on profitable portfolio management, but that’s besides the point. The quote is relevant because it paints a truth about life in plain and stark terms: you will find what you’re looking for.
OK, it might not be quite that simple. I cannot begin trading and proclaim: I am guaranteed to make money trading today! But I can find what I’m looking for, meaning, I fully validate and justify any trading strategy based on historical, past information.
Let me repeat that in more direct terms. Suppose I have a hypothesis: when the US dollar falls 5% against the Pound during a given time-span, I will buy the Greenback and sell the Pound. The next, logical step is to pull up market data and begin back-testing — that is, to simulate my strategy on past data and extrapolate how well my strategy would have performed in the past. Any experienced quantitative trader will unabashedly tell you that if you spend enough time, the market data will only validate your hypothesis. Your strategy has a very good chance at having succeeded in the past.
How is that possible?
In Classical/Traditional Game Theory, the assumption is that rationality is king. If you’ve watched A Beautiful Mind, starring Russell Crowe, the character’s breakthrough comes from discovering the Nash Equilibrium, which is a state wherein participants are in a state of equilibrium and cease to take any further actions, based on the fact that this is a mutual best response, meaning, at this point in time, it does not make any sense for either party to take any further action based on the rational premise that each actor is aware of the rationality of the other individuals in the room.But in real life, these states don’t happen in such a discreet manner. Life is fluid, with many unknown actors and variables. In this nice Medium article by Gayatri Sarkar, she writes that although the Nash Equilibrium is a great classical theory on paper, in the stock markets, it simply does not hold up. Instead, a better “all in one” explanation has more to do with probabilities, and less with fixed mathematical “equilibrium” states. In the stock markets, probabilities drive everything, but there’s more at play here than just the way we attempt to describe the behaviors of the market participants.
Context, in this case, has to do with how we begin to understand how actors go about making their decisions. Rationality is not king. Instead, emotional acts of whimsical disobedience are to be expected.
Like it or not, this is how the stock markets operate.
OK great, so context is important when it comes to understanding Game Theory’s relevance in the stock markets. But what does this have to do with our original argument, which is that if you look hard enough, your backtests will inevitably do a very good job in (dangerously) “legitimizing” your hypothesis?
Because once you realize that the markets are not efficient, then it is your job to discover the inefficiencies. A discovery is done in an organic manner. That’s the very premise of a discovery!
At first, this may not seem important. But if you think about it, it makes all the difference in the world. Let’s go through an example.
Mitch is an aspiring quant. Although he’s just 20, he’s wise beyond his years! He loves reading up on company earnings reports in his free time and dabbles with long term investing strategies. One day, he’s looking at a daily chart of Apple and comes across an interesting phenomenon: he can see that, every 5–10 years, Apple’s stock prices form an upward slanting “W” when seen on a daily chart. Not only that, but there is a clear “W” formation being formed right now, an “obvious” buy signal. He looks up Apple’s earnings and sees that Apple is posting “strong” earnings, and he deems it undervalued. He buys the stock.
And then the stock falls. Bigtime.
What went wrong?
The scapegoat answer would be to say something along the lines of how the markets are random in nature, and therefore, it’s completely acceptable for the trade to have gone wrong. We are not arguing that the markets should not have fallen. What we are arguing, however, is that the idea of Apple having a need to form a “W” is nonsensical, unless Mitch has a very clear reason as to why he feels the W is a consequence of a more nuanced approach to the situation. If Mitch was to make his decision based on intimate knowledge of Apple’s underlying supply/demand levels through the formation of each “W”, and he could substantively prove that he had access to certain pieces of information before others (highly unlikely) — then, he could potentially make the claim that his model was expected to work. Otherwise, he needs to validate any sort of idea with more concrete information, such as the Sharpe Ratio, win:loss ratio, etc.
In conclusion, when trading the financial/capital markets, context is key, specifically with regards to how a trader goes about defending her/his trading decision in terms of having access to information disparity. If the argument is that, despite not having any sort of advantage to any such information, this situation simply “exists”, then this argument can be difficult to back up unless backed with a decent sample size of real trades in conjunction with a sound argument as to how, and why, the state exists.
Anything otherwise is simply too good to be true.