The sharp and sudden selling pressure that characterized equity market action in December appears to have subsided in the new year – at least for now. In examining the causes of downside volatility, the most commonly cited reasons were fears of an escalated trade war with China, Fed tightening, and increasing chances of U.S. recession.
These are all valid concerns, of course. But they offer only limited insight into what was actually causing erratic selling pressure, in my view.
Our analysis here at Zacks Investment Management shows that little has fundamentally changed over the past two months with regards to interest rate expectations, earnings expectations and the potential length of a trade war with China. I posited in a previous column that we must look elsewhere to understand the dramatic onset of volatility. One key place to look is: inside the realm of programmatic trading, i.e., algorithmic trading.
Several researchers recently delved into the institutional investor world to gain more insight. What they discovered is that one of the main reasons large institutional portfolio managers sell during market corrections is because stock prices are falling. Read that again: institutional investors sold because prices were falling.1 This active decision means institutional investors were largely reacting to price movements instead of changing fundamentals – which is the precise opposite of what long-term investors should do, in my view.
Evidence suggests that algorithmic trading exacerbates this lemming-like behavior of selling stocks because other investors are selling stocks. Essentially, by analyzing past price movements independently through various means, multiple firms have come to the same conclusion that behavioral finance experts realized long ago – that during large negative market movements, selling accelerates. It follows that algorithms were programmed to sell when these conditions were met.
As a result, mild selling pressure in the markets has the capacity to snowball much more quickly in today’s market than it has historically, in my view. These strategies ultimately reinforce volatility since they react to major price swings by crowding into the same trade. And since many of the firms using algorithmic trading are also focused on using leverage to generate returns on a very short-term time horizon, the impact is more dramatic.
Algorithms May be Changing the Landscape, But There’s Good News
Algorithms may be altering the short-term investment landscape as we know it, but there’s an upshot for retail, everyday investors who choose to focus on long-term returns and resist trying to time the markets: these algorithmic trading models have not been proven to work effectively over time. In fact, the opposite may be true.
The Société Générale SG Trend Index, which is compiled from “trend-following” (algorithm-based) fund returns, ended 2018 down -8%. For all the promises of modern technology, that is not a good result, especially when compared to the returns an investor could have generated by simply owning the S&P 500 for the year: -4.4%.2 Still negative, but also twice as good as the Trend Index.
As far as the current environment is concerned, The Wall Street Journal reported on January 9, that these “trend-following investment strategies have gone from bullish to bearish to a degree not seen in a decade.” The strategies were said to have shifted from being long the four major asset classes – stocks, bonds, currencies and commodities – to being short everything but bonds in 2019. 3 The problem, in my view, is an obvious one: stocks have gone up solidly since the turn of the year! And because our outlook remains constructive for 2019, I’d argue that the strategies have gone maximally bearish at just the wrong time.
Bottom Line for Investors
One of the biggest concerns for many investors is that algorithms and programmatic trading may ultimately prevent markets from functioning normally, since such large amounts of capital are deployed in response to price changes instead of fundamental changes. While I share this concern, my belief today is that the total return produced by stocks over the long-term will not be affected. Since stocks measure the value created over time by corporations in the global economy, I’m not convinced that algorithms can fundamentally change the arc of that value creation, and how it is ultimately priced.