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The Human vs. The Quant

Validea

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Validea
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Co-Founder and President at Validea Capital

I have always thought I am a better discretionary investor than I am. I think I can predict where the market is headed. I think I know which investing styles will work best going forward. When I look back at the current crisis, I am pretty convinced that I saw it coming and that I could have sold at the top and then bought back at the bottom. Of course, none of that is actually true. And that is why I ultimately became a quant. The most important thing that happened to me in my investment career was my recognition that I am not able to control my emotions and biases, so my only solution is to run an investment strategy that limits their impact.

But despite the fact that I am a big believer in quant investing, I think all of us who are quants can sometimes fall into the trap of thinking that the way we do things is the only way. The possibility that an emotional human being who is negatively impacted by a myriad of biases could possibly do better than our computerized, emotion-free strategies is just not something we can fathom.

But I think that oversimplifies the problem.

Although I am just as strong a believer in quantitative strategies today as I was when I first started running them, the argument for quant is not as cut and dry as I think it is. Like most things in investing, this is a coin that has two sides.

The recent market decline related to COVID-19 showed off some of the great strengths of quant strategies, but also highlighted some of their weaknesses, so I thought now might be an interesting time to look at both sides of the argument.

Here are some thoughts on the plusses and minuses of a quant strategy relative to a discretionary one.

Quant Strategies Eliminate Emotion

Human beings are not built to be good investors. We have survived as a species due to our focus on fear and our aversion to risk, but that leads us to panic at the absolute worst times. We also have a tendency to get greedy during market rallies and add risk when we should be doing the opposite. Essentially, we are programmed to do the opposite of what we should.

And all of us tend to think this applies to everyone but ourselves. I know I certainly do. But the truth of the matter is understanding your biases doesn’t fix them. There is no way to train them out of you.

If I ever need to be reminded of this personally, a period of market panic will usually do it. And this period was no different. I usually keep a small position in my personal account in a tail risk type strategy. I don’t do that because I think the market is going to fall. I have learned I can’t predict that. I do it because I have learned that as a money manager, my life is heavily leveraged to the stock market. When the market falls, my income goes down, the value of my business goes down, and my portfolio goes down. For me, keeping a tail risk position helps me to hedge some of that risk.

What I did not do with my tail risk position is put in place a quantitative system that would determine if and when I would sell it. When the Coronavirus hit, this position did exactly what it was supposed to do. But once the S&P 500 was down 15% or so, market timer Jack reared his ugly head and I decided to eliminate the position and take profits, which meant I didn’t hold it when the major part of the decline came. Instead of focusing on the reason I had the strategy in the first place, which was as a hedge against a major market event, I decided I could call the bottom and got rid of my tail risk hedge right before one of the best performing periods ever for those types of strategies.

If you ever want to see an example of the benefits of a quant-based approach, that is it. No matter how much you learn about your biases and emotions, you can’t control them, and a quant strategy allows you to mostly remove those issues from the equation.

Humans Can Perform Better When Details Matter

Despite the fact that the recent Coronavirus situation offered a great example of the advantages of quant investing, it also offered an example of the other side of the coin. The crisis had an immediate and major impact on many businesses, but there was significant dispersion among those impacts. As quant investors, we are typically relying on past data to help us predict the future. We look at historical earnings and cash flows in our valuation models. We look at past growth rates as a means to predict future ones.

But that system can break down when you get a breaking point like the coronavirus. As an example, if two companies traded at similar valuations prior to the crisis, but one was an airline and the other makes cleaning supplies, their relative valuations based on future earnings were suddenly very different than their valuations based on the past.

Gavin Baker cited a great example of this in his podcast interview with Patrick O’Shaughnessy shortly after the crisis. He talked about how the most important metric many investors were looking at following the crisis was how long a company could last on zero revenue. You can certainly try to calculate that metric using a quant model, but it quickly becomes apparent that there is too much nuance to it. For example, to properly make that calculation, it is important to understand the lines of credit and other significant sources of financing that a company has available to it. It is also important to know its ability to defer or eliminate expenses. A human is better setup to tackle that problem than a quant model.

Behavior Can Trump Everything

As much as I am personally a big believer in quant investing, I also believe that an investor’s faith in their investment strategy ultimately trumps almost anything else. If knowing that a fund manager is picking stocks for your portfolio gives you greater confidence to stick with the strategy during the inevitable down periods, then that ultimately is probably a better strategy for you. Performance lost to bad behavior usually more than offsets the performance difference related to the details of an investment strategy.

In the end I don’t think this is a question that has a clear answer. Quant strategies help to limit the role of emotion and biases, and they can process large volumes of information in a way a human cannot. But they can also struggle relative to a discretionary strategy when a more detail-oriented approach is needed. For me, the benefits of a quant approach outweigh the negatives, but I also understand that there will be certain periods and certain situations where a more in-depth analysis that a discretionary manager can provide works best. As is the case with many things in investing, what works best for each person is largely a function of what they believe in and can stick with over time.

Originally Posted on June 17, 2020 – The Human vs. The Quant

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