“… and we three were there alone in the middle of a great white plain with snowy hills and mountains staring at us; and it was very still; but there were whispers.” – Black Elk
Money Quote: “…fundamental discretionary traders” account for only about 10 percent of trading volume in stocks. Passive and quantitative investing accounts for about 60 percent, more than double the share a decade ago…”
Just 10% of trading is regular stock picking, JPMorgan estimates
- “Fundamental discretionary traders” account for only about 10 percent of trading volume in stocks today, JPMorgan estimates.
- “The majority of equity investors today don’t buy or sell stocks based on stock specific fundamentals,” said JPMorgan’s Marko Kolanovic.
- JPMorgan believes the recent sell-off in technology stocks may have been related to quantitative and computer trading and not traditional fundamental investors.
Tuesday, 13 Jun 2017 | 4:49 PM ETCNBC.com
Quantitative investing based on computer formulas and trading by machines directly are leaving the traditional stock picker in the dust and now dominating the equity markets, according to a new report from JPMorgan.
“While fundamental narratives explaining the price action abound, the majority of equity investors today don’t buy or sell stocks based on stock specific fundamentals,” Marko Kolanovic, global head of quantitative and derivatives research at JPMorgan, said in a Tuesday note to clients.
Kolanovic estimates “fundamental discretionary traders” account for only about 10 percent of trading volume in stocks. Passive and quantitative investing accounts for about 60 percent, more than double the share a decade ago, he said.
In fact, Kolanovic’s analysis attributes the sudden drop in big technology stocks between Friday and Monday to changing strategies by the quants, or the traders using computer algorithms.
In the weeks heading into May 17, Kolanovic said funds bought bonds and bond proxies, sending low volatility stocks and large growth stocks higher. Value, high beta and smaller stocks began falling in a rotation labeled “an unwind of the ‘Trump reflation’ trade,” Kolanovic said.
“Upward pressure on Low Vol and Growth, and downward pressure on Value and High Vol peaked in the first days of June (monthly rebalances), and then quickly snapped back, pulling down FANG stocks” — Facebook, Amazon.com, Netflix and Google parent Alphabet, the report said.
Along with Apple, the big tech-related names fell more than 3 percent each last Friday and dropped again Monday, sending the Nasdaq composite lower in its worst two-day decline since December.
However, “the contribution coming from quant rebalances to this snapback is now likely over,” Kolanovic said, noting that S&P derivatives have supported market gains at the beginning of this week.
“$1.3T of S&P 500 options expire on Friday, and this will change dealers’ positioning,” he said. “This can result in a modest increase of market volatility starting on Friday and into next week.”
Tech recovered Tuesday, helping U.S. stocks close higher with the Dow Jones industrial average at a record.
Derivatives, quant fund flows, central bank policy and political developments have contributed to low market volatility, Kolanovic said. Moreover, he said, “big data strategies are increasingly challenging traditional fundamental investing and will be a catalyst for changes in the years to come.”
Figures from market structure research firm Tabb Group point to similar gains in machine-driven trade volume, while the overall number of shares traded has declined.
A subset of quantitative trading known as high-frequency trading accounted for 52 percent of May’s average daily trading volume of about 6.73 billion shares, Tabb said. During the peak levels of high-frequency trading in 2009, about 61 percent of 9.8 billion of average daily shares traded were executed by high-frequency traders.
To be sure, not everyone on Wall Street is giving ground to the machines so easily.
AllianceBernstein analysts made the case in an April 28 note that artificial intelligence is unable to generate significantly different results — by the mere fact that analyzing more and more data results in increasingly similar strategies.