Quantamental investing, which combines the best of fundamental and quantitative strategies, is redefining how asset managers handle their portfolios.
Just look at the hedge fund industry in 2016 when investors lost confidence and pulled out US$70 billion, only for quantitative funds to add $13.3 billion in new money amid the turmoil.
And on the day after the United Kingdom voted to leave the European Union, hedge funds on average were down 0.18 percent compared with trend-following machine-based strategies which gained 0.71 percent, according to industry tracker Hedge Fund Research.
Advances in technology and access to massive data sets have opened up new possibilities for seeking alpha; possibilities that never even crossed the minds of fundamental investors.
Demand for data scientists and other technical talent
However, this emerging and continuously evolving way of exploring data to find new strategies and boost returns doesn’t come easy.
It requires a high degree of technical knowledge to work with data and harness the information that can help pinpoint a differentiated investment strategy that the rest of the market doesn’t see.
Top quant funds employ armies of technical talent to drive these strategies forward.
At Renaissance Technologies, one of the world’s largest hedge funds with $65 billion in assets under management, it takes no less than eight dozen scientists with doctorates in physics, math and other fields to keep the firm at the top of its game.
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Finding qualified people to fill these roles isn’t easy and Wall Street now finds itself competing with Silicon Valley and the tech start-up ecosystem for talent.
As more firms look to adopt quantitative investment strategies, and demand for tech talent increasingly reaches across industries, it’s only going to get harder.
And despite all the time, effort and resources being put into quant funds, they’re not infallible.
While systematic investing has already proven that it can identify new and innovative trading strategies, nothing will ever be a silver bullet for guaranteeing returns.
It’s been ten years since the “Quant Quake” when trading algorithms faltered, causing a chain reaction and billions of dollars in losses over only a few days.
Quant funds have done a lot to learn from that incident, and they’ve been able to mostly put it behind them as their share of trading continues to skyrocket. But even so, they’ve experienced periods of weakness.
In fact, returns from the first half of this year served as the most recent reminder. Quant funds returned a mere 3.17 percent through the first six months of the year while traditional funds nearly doubled that, gaining 5.99 percent.
A quantamental future
Despite a few slips, quantitative investment strategies will undoubtedly play a significant role in the future of finance — but that doesn’t mean that fundamental strategies will completely fall by the wayside.
One path forward is to combine the best of both worlds into a quantamental future.
Right now, it looks like engineers and mathematicians are being groomed to play leading roles on Wall Street. But at the end of the day, would you rather have techies learning finance, or fundamental managers learning tech?
Until recently, the tools needed to implement systematic investment strategies have been primarily available to quants.
As technology improves however, people with a traditional financial background and knowledge are being given the tools to implement quantitative strategies without having to program or code software.
With these advances, everyone will be able to leverage quant techniques if they so choose.
The road for a true hybrid approach will be the sure path forward for quantamentals. And, quants will be delighted with new technologies that can make their life easier.
Watch video — Introducing Thomson Reuters QA Point
As a result, it is now possible to easily build, modify, and backtest complex financial models, helping you take advantage of advanced investment techniques and data science without requiring a quant skill set.