A new report from JPMorgan suggests that the traditional stock picker is being in the dust and now dominating the equity markets are quantitative investing based on computer formulas and trading by machines directly.
"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 note to clients.
Only about 10 percent of trading volume in stocks is accounted for by "fundamental discretionary traders", Kolanovic estimates. Comparatively he says, more than double the share that was noted a decade ago (60%) are amounts that are invested by passive and quantitative investing modes.
Changing strategies by the quants, or the traders using computer algorithms, was identified to be the reason for the sudden drop in big technology stocks between Friday and Monday by Kolanovic's analysis.
Low volatility stocks and large growth stocks were send higher by funds that bought bonds and bond proxies in the weeks heading into May 17, Kolanovic said. Kolanovic said that in a rotation labeled "an unwind of the 'Trump reflation' trade," value, high beta and smaller stocks began falling.
"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.
The Nasdaq composite was sent lower in its worst two-day decline since December as along with Appel, the big tech-related names fell more than 3 percent each last Friday and dropped again Monday.
However, "the contribution coming from quant rebalances to this snapback is now likely over," Kolanovic said. But at the beginning of this week, S&P derivatives have supported market gains, Kolanovic noted.
"$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."
With the Dow Jones industrial average at a record, tech recovered Tuesday, helping U.S. stocks close higher.
Kolanovic said that contributing to the low market volatility were political developments, central bank policy, quant fund flows and derivatives. Moreover, he said, "big data strategies are increasingly challenging traditional fundamental investing and will be a catalyst for changes in the years to come."
While the overall number of shares traded has declined, similar gains in machine-driven trade volume, were pointed out by figures from market structure research firm Tabb Group.
Tabb said that accounting for 52 percent of May's average daily trading volume of about 6.73 billion shares was a subset of quantitative trading known as high-frequency trading. About 61 percent of 9.8 billion of average daily shares traded were executed by high-frequency traders during the peak levels of high-frequency trading in 2009.
But ground to the machines is not being given out so easily by everyone on Wall Street.
By the mere fact that analyzing more and more data results in increasingly similar strategies, artificial intelligence is unable to generate significantly different results, AllianceBernstein analysts made the case in an April 28 note.
(Source:www.cnbc.com)
"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 note to clients.
Only about 10 percent of trading volume in stocks is accounted for by "fundamental discretionary traders", Kolanovic estimates. Comparatively he says, more than double the share that was noted a decade ago (60%) are amounts that are invested by passive and quantitative investing modes.
Changing strategies by the quants, or the traders using computer algorithms, was identified to be the reason for the sudden drop in big technology stocks between Friday and Monday by Kolanovic's analysis.
Low volatility stocks and large growth stocks were send higher by funds that bought bonds and bond proxies in the weeks heading into May 17, Kolanovic said. Kolanovic said that in a rotation labeled "an unwind of the 'Trump reflation' trade," value, high beta and smaller stocks began falling.
"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.
The Nasdaq composite was sent lower in its worst two-day decline since December as along with Appel, the big tech-related names fell more than 3 percent each last Friday and dropped again Monday.
However, "the contribution coming from quant rebalances to this snapback is now likely over," Kolanovic said. But at the beginning of this week, S&P derivatives have supported market gains, Kolanovic noted.
"$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."
With the Dow Jones industrial average at a record, tech recovered Tuesday, helping U.S. stocks close higher.
Kolanovic said that contributing to the low market volatility were political developments, central bank policy, quant fund flows and derivatives. Moreover, he said, "big data strategies are increasingly challenging traditional fundamental investing and will be a catalyst for changes in the years to come."
While the overall number of shares traded has declined, similar gains in machine-driven trade volume, were pointed out by figures from market structure research firm Tabb Group.
Tabb said that accounting for 52 percent of May's average daily trading volume of about 6.73 billion shares was a subset of quantitative trading known as high-frequency trading. About 61 percent of 9.8 billion of average daily shares traded were executed by high-frequency traders during the peak levels of high-frequency trading in 2009.
But ground to the machines is not being given out so easily by everyone on Wall Street.
By the mere fact that analyzing more and more data results in increasingly similar strategies, artificial intelligence is unable to generate significantly different results, AllianceBernstein analysts made the case in an April 28 note.
(Source:www.cnbc.com)
