Market volatility: Do algorithms play a role?

April 29, 2019

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Stock markets around the world were caught in a downdraft in December, and once again algorithmic trading—automated buying and selling based on predetermined triggers—took some of the blame. Speculation that machines are running, and perhaps ruining, the markets is not new. Algorithms are often portrayed in the financial press as big, bad autonomous robots wreaking havoc by mindlessly trading, magnifying volatility, and triggering flash crashes.

Vanguard experts offer a different perspective. "If you look at the ways in which algorithms are used in trading today, the impact is largely positive," said Jim Rowley, head of active/passive portfolio research in Vanguard Investment Strategy Group. "That's true whether you're talking about algorithms deployed in electronic market-making, quantitative investing, or market-cap-weighted index investing."

Who's running the algorithms?

Understanding how algorithms affect or don't affect markets can help investors stay focused on their long-term financial plans.

Who's running the algorithms infographic
Who's running the algorithms infographic

Source: Vanguard.

Market makers: Providing liquidity

The bulk of algorithmic trading is conducted by electronic market makers. They are not asset managers buying or selling to build portfolios; rather, they are middlemen using algorithms to set bid and offer prices on stocks and ETFs. They take on the risk of buying securities from one investor in order to sell them at a higher price to another investor. Electronic market makers play a crucial role in providing liquidity (that is, making it easy for investors to buy and sell securities), increasing competition, and reducing transaction costs.

Many high-frequency traders (HFTs) fall into this category. They are essentially making bids and offers even as they execute much higher trading volumes at much faster speeds. However, questions occasionally are raised about HFT profitability and market volatility:

Do HFTs harvest unreasonable amounts of profit?
"That's a great question to ask about any line of business—from auto manufacturing to baby food," said John Ameriks, global head of Vanguard Quantitative Equity Group. "But the fact that you've seen so many HFT shops closing their doors suggests that, today at any rate, it's a very competitive marketplace. And that's a good thing for investors from a trading-cost perspective."

Do HFTs cause volatility and flash crashes?
"There's a long history of volatility in the marketplace that pre-dates HFTs," Ameriks said. "And you didn't need algorithms to have a flash crash. When investors get hesitant about transacting and you don't have good price discovery, the market seizes up."

Rowley said that "stock and ETF trades have to follow a stock exchange's rules. In the case of the August 2015 flash crash, for example, there was an issue with the up limit, down limit process." (Those are maximum daily price movements determined by each exchange.) "So I see flash crashes as more of a market structure issue than a problem with HFTs."

Quantitative investors: Seeking alpha

Quantitative investors build portfolios they hope will outperform the market by setting up algorithms that essentially crunch numbers to mine alpha. Their algorithms might sift through income statements, balance sheets, and price/earnings ratios just like good old-fashioned human stock pickers would; they might try to isolate factors, such as value or momentum, that are expected to produce outperformance over time; or they might try to match some "smart" index that weights stocks by something other than market capitalization. In every case, however, human critical thinking creates, corrects, and refines the sets of instructions that make up these algorithms.

Some quant strategies have come under scrutiny for contributing to volatility. Momentum strategies are sometimes blamed for fueling both market run-ups and sell-offs. Risk-parity funds, which use leverage and try to control volatility, also have been charged with exacerbating downturns, because they tend to reduce exposure to riskier assets when volatility increases. That effectively means the algorithms behind those funds sell when markets are declining

"Those strategies may be selling when markets are declining, but they are not the only ones operating in the market by a long shot," Rowley said. "The marketplace is a very complex ecosystem affected by a lot of different strategies and forces, so to lay the responsibility at the feet of just a couple of quant strategies seems misplaced."

Market-cap-weighted index fund managers: Aiming to mirror benchmarks

Traditional index fund managers build portfolios that match a target benchmark, such as the Standard & Poor's 500 Index. Their trading, however, is limited to index changes and cash flow management. When the constituents in a fund's benchmark index change, algorithms can be used to realign the fund's holdings. And if cash comes into or goes out of a fund, algorithms can help the fund manager generate buy or sell orders for each stock in the index.

Some active managers have blamed index funds for indiscriminate buying that distorts the market and for investing "disproportionately" in large-capitalization stocks. "That logic is flawed," Rowley said. "Index fund managers buy purposefully—they buy or sell according to the market-cap-weighted index they are tracking. And if a certain amount of money flows into a cap-weighted index fund, 3% of that sum will go to buying a stock weighted 3% in the index—no more and no less."

A scapegoat in volatile markets

The truth is, there often isn't an easy answer as to why the market zigged when it was expected to zag. If anything, algorithms contribute to the smooth and efficient functioning of the marketplace more often than they detract from it. Volatility is part of investing. There will also be speculation after it spikes, but investors might be better off ignoring the noise and preparing for short-term market ups and downs by holding a broadly diversified balanced portfolio for the long term.

Notes:

  • All investing is subject to risk, including the possible loss of the money you invest.
  • Diversification does not ensure a profit or protect against a loss.