The Relationship Status is Complicated: A Commentary on Investing Without People
Traditional investing mainly looks at fundamentals and value, but as computing power increases, more funds and investors have access to sophisticated quantitative analysis and algorithm trading.
Investing Without People (IWP) is a memo on passive investing, quantitative trading, and AI by Howard Marks. It carried out very humbly as Marks stressed that he was not an expert on quantitative trading and Wikipedia was the source for most information. Nonetheless, Marks’ sentiment and understanding of the three subjects are still accurate and the memo provides me the inspiration to write this commentary along with my take on quantitative trading and the role of human input in investing. Now, I know that some people would see quantitative trading and algorithm trading as two different things, which I would agree at times; but for the sake of simplicity, let’s say that they are the same.
In IWP, Marks sees the formula or the rules that human set for computers to follow as the essence of quantitative trading. In addition, Marks points out that one of the biggest advantages of quant trading is the omission of human emotion, therefore avoiding “sells in panic”. I agree with these two points. Nonetheless, I do need to point out that if people think that quant trading has underperformed out expectations, it has underperformed precisely because of us.
I am making this argument on two levels. First, as flawed being ourselves, it is hard for us to develop the perfect algorithm for a machine to follow. And that is a good thing! Trading algorithms are designed to adapt different situations and cater to different strategies, and there is no perfect strategy to follow. On another level, even though automated trading has prevailed for a long time and actually make up the majority of trading volume, it is highly influenced by the other human and possibly irrational trades. One classical example would be the downward spiral: a lot of machines have the command of stop loss, and as the price of an asset drops and triggers the stop loss, more of the asset is sold, sending it further down. A lot of academics argue that this is one of the biggest catalysts of selloffs and I think it perfectly reflects Marks reflection on George Soro’s Theory of Reflexivity: that the actions of market participants change the market.
Given this argument, I see humans and machines in a complicated relationship, particularly in investing. Humans designed algo trading to produce better returns, but it is still flawed precisely because of humans.
There are already some answers to this dilemma, one of which is AI and the other is making it possible for algo trading to take in qualitative information. The value of AI lies within the ability to produce a more correct or accurate conclusion, given the same inputs. Generally speaking, it has been able to produce some nice results in small areas, but it is probably still far from having the ability to identifying the next big innovation or finding the next best and upcoming CEO. Some other industries have started to see adaptation of AI law consultants and news-based/twitter feed-based algorithms, but the development is still at an early stage and I hope for the best.
I am an analyst at HedgeVista, a platform that connects funds and investors. Learn more at www.HedgeVista.com.
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Reference Links:
https://www.oaktreecapital.com/docs/default-source/memos/investing-without-people.pdf?sfvrsn=8
