
Stock-pickers take note: the quants are coming
Quant funds are turning their hand to fundamental investing
The chief executive of a discretionary equity hedge fund might seem an odd choice to include on a panel at a quant conference. But G Squared Capital’s presence at Battle of the Quants in New York earlier this month illustrates just how much crossover is occurring between the two philosophical encampments of the investing world.
G Squared takes a hybrid quant-fundamental approach, using artificial intelligence algorithms to analyse 10,000 data points per company and make investment calls.
The firm is in the vanguard of a quant fund push to mimic their fundamental cousins – now that the quants have a mounting pile of new data to crunch and machine learning algorithms to help make sense of it.
Michael Graves, chief executive of global stat arb hedge fund Nebula Research, who spoke on the same panel, said quants are starting to work on the questions fundamental investors used to see as their own: how is Apple’s new launch going down, or have Tesla’s plans hit a speed bump?
Nebula, for example, now trades an equity long/short strategy in a systematic fashion. “We are mixing some of their techniques with our techniques and trading on different timescales,” Graves said. He hopes the explosion of alternative data and improvements in computer processing power means the firm can do it better.
Michael Recce, chief data strategist at fundamental asset manager Neuberger Berman, predicted the amalgamation of systematic and fundamental methods of investment “will be larger than the original quant revolution”.
Neuberger acquired quant research firm Breton Hill Capital in 2017 to deepen its capabilities in that area.
Recce described fundamental investors as having knowledge “an inch wide and a mile deep”. In other words, they know a huge amount about the future value of just a handful of companies.
Imagine if you are building artificial intelligence that acts like a discretionary trader. You get the alpha of the discretionary guy and the leverage of the quant
Michael Recce, Neuberger Berman
They can generate a lot of alpha from those few select bets. But they are limited in their use of leverage by the high idiosyncratic risk in their portfolios.
Quants on the other hand, gather knowledge “an inch deep and a mile wide”. They do not know much about individual companies, but they rely on finding mispricing patterns that repeat across many stocks over time.
Although systematic strategies typically only have access to relatively little alpha, they can lever up to achieve comparable returns to discretionary managers, Recce said.
“But imagine if you are building artificial intelligence that acts like a discretionary trader. You get the alpha of the discretionary guy and the leverage of the quant.”
This is the sweet spot for quants – to include alternative and additional fundamental company data in their models. Recce insists machine learning analysis on alternative datasets will be an advantage to any quant firm looking for inefficiencies in the market.
He pointed to January 3 this year when Tim Cook announced that Apple had sold fewer phones than anticipated in China, wiping $75 billion off the company’s stock.
“Everyone was surprised, but all those phones have carriers, make calls and have apps. The data is absolutely in the world, but it is not in the market,” he added.
JP Morgan Asset Management and Golden Sachs Asset Management are among those to champion the use of algorithms to trawl though news and social media to understand what is happening at companies before anyone else.
“If you watch news and social media carefully and use algos to read it, then you can find out something is going to happen before everyone. Say Panasonic is going to opt out of investment in Tesla’s Gigafactory. You don’t know what the true value of Tesla is… but you know temporarily that Tesla stocks will go down so the race is on for who can trade on that the fastest,” Recce said.
The next big trend in quant, it seems, could be a return to fundamentals.
Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.
To access these options, along with all other subscription benefits, please contact info@risk.net or view our subscription options here: http://subscriptions.risk.net/subscribe
You are currently unable to print this content. Please contact info@risk.net to find out more.
You are currently unable to copy this content. Please contact info@risk.net to find out more.
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. Printing this content is for the sole use of the Authorised User (named subscriber), as outlined in our terms and conditions - https://www.infopro-insight.com/terms-conditions/insight-subscriptions/
If you would like to purchase additional rights please email info@risk.net
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. Copying this content is for the sole use of the Authorised User (named subscriber), as outlined in our terms and conditions - https://www.infopro-insight.com/terms-conditions/insight-subscriptions/
If you would like to purchase additional rights please email info@risk.net
More on Our take
Degree of influence 2023: Quants thrive on volatility
Climate, crypto and market impact also featured among the top research topics in 2023
Korea’s ‘worst-of’ times are here to stay
Chinese houses’ success in Korean autocalls could stymie hopes of diversifying the product mix
Could intraday FX swaps help reduce settlement risk?
New swap platform hopes to ease funding pains, but can it promote more use of PvP?
Talking Heads 2023: A turf war in credit markets
Banks are looking to reclaim territory they previously ceded to market-makers and private funds
FX-style crypto platforms could bridge gap with TradFi
Emergence of execution-only ECNs, prime brokers and clearing houses brings new confidence in crypto
Skew this: taking the computational burden off basket options
Dan Pirjol presents a snap formula for estimating implied volatility skew in an instant
Shhh, don’t tell: the struggle to keep skew under wraps
Liquidity recycling by clients has made it more difficult for banks to keep skews quiet
How a machine learning model closed a hidden FX arbitrage gap
MUFG Securities quant uses variational inference to control the mid volatility of options