Algorithmic Trading: What It Means For Stock Market Volatility And Individual Investors

When the stock market turns volatile, algorithmic trading often gets the blame. Big banks, hedge funds and institutional investors use computer-driven trading algorithms routinely in bull or bear markets.

But when triggered by news events or financial rules, algo trading can escalate and worsen a stock market sell-off.

U.S. stocks plunged Aug. 14 as the main Treasury yield curve inverted, with the two-year yield above the 10-year Treasury yield for the first time since 2007. The inverted yield curve could mean a recession lies ahead.

The Dow Jones Industrial Average and Nasdaq exchanges also fell sharply Aug. 5  amid the escalating U.S.-China trade war. Apple stock dropped in high volume after China let its currency drop. That’s a problem for Apple (AAPL) stock, because iPhones will be more expensive in China.

Individual investors, also called retail investors, aren’t users of algorithmic trading tools. While there have been a few attempts to make algo trading software available to individual investors, they didn’t work out. And, the trading volume and costs associated with algorithmic trading make it impractical for retail investors.

Individual investors, however, can turn to investing tools such as IBD’s CAN-SLIM.

What Is Algorithmic Trading?

The internal trading desks of brokerages, hedge funds and institutional investors use computer-driven trading algorithms routinely.

Simply put, algorithms are complex math equations used to program computers to make decisions. They’re used in many industries.

On Wall Street, algo trading is used to buy and sell stocks automatically. Algorithmic trading can extend momentum trades as stocks make a big run.

How HFT Traders, Quants Use Algorithmic Trading

So-called “high-frequency traders” use algorithmic trading to move in and out of stocks at superfast speeds using powerful computers and robust internet connections.

Meanwhile, “quants” are mathematicians hired by Wall Street firms to create algorithms for automated trading purposes.

In routine trading, traders may use preset criteria to execute orders. For example, algo trading could use preprogrammed rules for when a stock reaches or falls below a 50-day or 200-day moving average.

A 2014 study claimed that one positive impact of algorithmic trading is that it made stock markets more liquid and efficient.

On the other hand, algo trading can hide the identity of large buyers and sellers. Some brokerages use algorithmic trading to split up orders so the size of their trades will not be observable.

Does Algorithmic Trading Worsen Stock Market Volatility?

Algorithmic trading also has been associated with stock market volatility and triggering sell orders. One example: the “flash crash” of May 2010, which wiped $860 billion from U.S. stock markets in less than 30 minutes.

Algorithmic trading may kick in when there’s a jump in the VIX index, a measure of anticipated market volatility. In addition, algo trading may initiate when odds of future market losses increase.

Preset sell orders also engage when odds of a recession suddenly increase. One sign of a recession, for example, has been an inverted yield curve.

In April 2019, Bitcoin suddenly jumped 20%. Some observers speculated algo trading might be behind the sudden move in the world’s most popular cryptocurrency.

Aside from stocks, traders now use algo trading more often for traditional currencies as well.

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