Quantifying the Scene

Quantifying the Scene

While this isn’t fresh news, Quant Funds are the sign of the times for the hedge fund landscape more so today in the contemporary financial world than in its advent some good ten years back. Amidst the burgeoning buzz around quant funds and heightening appeal of computer-centric hedge funds, there is a budding presence of alternatives. The fundamental (haha…) question remains: What else is out there?

Growth of Quant Funds

In retrospect, despite the 2007 “Quant Quake”, the growth of such quant funds has been resiliently prosperous. A study conducted by Goldman Sachs revealed that investors are steering their interest towards quant and systematic strategies. Likewise, Barclays unveiled that hedge funds investors are most drawn in and keen on systematic/CTA funds alongside quant equity funds.

Investors are not the only movers in the quant paradigm shift. Celebrity veterans in the likes of Ray Dalio and Steve Cohen, at hand with the tech-savvier firms such as Two Sigma and Quantedge, are in the forefront of automating processes. This translates to employing the use of computer algorithms and integrating artificial intelligence technology. Consequently, effecting competencies in sifting market insights, attaining triggers/catalysts, deducing fruitful trades/investments, as well as expediting daily tasks.

The New Imperative

The precedented slant towards quant funds have irrepressibly led to a focused demand on managers with programming know-how’s or extensive mathematical prowess paired with quantitative knowledge.

The Quant Eco-System

According to a recent study carried out by Man Group, 34% of the total hedge fund assets under management (AUM) is currently managed by quantitative funds. In translation, this accounts for upwards of USD 1 trillion in total AUM.

(Value of Assets Managed by Hedge Funds Worldwide from 1997 to 2016, in Billion U.S. Dollars; Source: Statista)

Despite the steady growth of Global Hedge Fund AUM over the years, it is rather shortsighted to ignore the disruptors that may cannibalize the total assets, or even substantially alter the composition of allocation of the total assets. Without further ado, let us tour the quant scene today!

Institutional Quant Hedge Funds

Throw in “Institutional Quant Hedge Funds” onto any search engine, and you would be entertained by a barrage of links to articles circling about the flourishing ascent of quant hedge funds globally, as well as the stellar performances of prominent quant funds. Indubitably, when speaking of quant hedge funds, no one is susceptible to the overreaching influence, reputation and sheer weight of the funds (to mention a few) such as Bridgewater, Renaissance Technologies, Winton Capital and D.E. Shaw.

AI Quant Hedge Funds

While there is now a growing preference and interest for systematic over discretionary funds, pure AI quant hedge funds takes the term “systematic” up a notch. These funds make trades and decisions wholly dependent on AI, meaning there is no human intervention needed. Fundamentally, the idea of a pure AI quant hedge fund is to build a system and making alterations when necessary, thereafter the system is able to compose strategies, to buy a certain financial instrument, how long to hold, time of exit, even when to scale down exposure.

Aidyia

(Ben Boertzel, Chief Scientist of Aidyia, Speaking at Boao Forum for Asia; Credits: Boao Forum)

Founded in 2011, the Hong Kong based company launched a fund in 2015 using its AI system to trade in US equities. Binatix is another company that falls under the pure AI quant hedge fund category, best known for their application of machine-learning techniques, employing deep learning to trade.

Crowdsourced Quant Hedge Fund

Crowdsourced quant hedge funds as its name suggests, amalgamates the essence of a hedge fund and an online crowdsourcing platform. Members, or otherwise better addressed as “freelance quants” can peg on the resources provided by these hedge funds, charging, say 20% of profits. Additionally, these hedge funds crowdsource its algorithms, organizing contests for quants to compete in return for being the hand-picked few to receive capital allocation.

Quantopian

(John Fawcett, Founder of Quantopian, at QuantCon 2016; Credits: Youtube)

Born out of Boston in 2011, Quantopian is one of the more prominent and well-funded quant fund backed by investors from the likes of Steve Cohen’s Point72 and Andreessen Horowitz, who has similarly backed countless startups, namely Facebook, Airbnb and Twitter (Cohen’s Point72 Ventures allocated $250 million in investment capital to be distributed amongst the best models). Quantopian was also one of the selected few featured on a list of “America’s Most Promising Companies for 2014” by Forbes. On the platform, its more than 160,000 (and growing) users can distribute their unique investment algorithms. Quantopian then handpicks the most promising algorithms, licensing them in return for a share of the profits.

Quantiacs

(Example of Past Competitions and Payouts; Credit: Quantiacs)

Often hailed as the pioneer crowdsourced hedge fund, California-based Quantiacs was founded in the year 2014. Quantiacs provide algorithm authors to profit when their codes are used by investors. Simply put, they bridge algorithms freelance quants with institutional investors who have the means and capital. To date, Quantiacs has run eight competitions, where the best trading programs on its site stand to trade with up to $1 million of the firm’s capital. Akin to its predecessor, Quantopian, this provides an opportunity for a large pool of talented quants globally to boast their skills.

Social Trading Platforms

Similar to the concept of hitching a ride, non-institutional online investors can rely on the trades of other more experienced, semi-professional investors. Although the latter are not using quant strategies to make their investing decisions, these platforms ultimately still provide amateur retail investors a window to a myriad of strategies. To add on, some of the platforms even author a customized hedge fund that can be traded in an investor’s brokerage account. In my perspective, it is only a matter of time before such platforms allow retail investors to mimic the trades of various quant/ AI systems.

eToro

(Credits: eToro)

Commonly coined as the “Facebook of Forex”, eToro is one of the more well-known companies in the social trading platform arena. The company offers several interesting functions, such as “CopyTrader”, allowing users to copy the better traders on its vast network. Today, the Israeli investment social network that received “Best of Show” at Finovate 2015 and 2017 respectively, boasts an estimated 5 million registered users. Since its launch in 2007, eToro has amassed more than $70 million in funding, with Spark Capital, CommerzVentures GmbH and BRM Capital as lead investors.

Collective2

(Credits: Collective2)

Collective2 was founded in 2001 and headquartered in New York. Currently, it has upwards of 110,000 registered users and over 10,000 published strategies. According to a recent interview with Yahoo! Finance, more than $65 million dollars of investor capital has onboarded the Collective2 platform. The firm has a two-prong approach, it serves as a platform to track brokerage results in real time for traders, as well as allowing other investors to subscribe to these traders, automatically mirroring their trades using their own brokerage account.

Algorithmic Marketplace

OpenAI

(Sam Altman and Elon Musk, Credits: TechStory, Sep 2016)

One salient example of the growth of AI movement is OpenAI, the birthchild of Elon Musk alongside Sam Altman. The AI movement has been on a constant ascent, reinventing all technology that surrounds us. OpenAI builds free software for users to gain exposure towards AI. This includes deep learning algorithms that equips users with the ability to use face recognition. Algorithmia is another startup that looks at being an open marketplace for algorithms. While OpenAI shares AI research, Algorithmia provides fully functioning algorithms.

Online Quant Trader Communities

Quantconnect

(Credits: Quantconnect)

Quantconnect allows its users to construct and test their strategies in various programming languages. To add on, it supports users with hundreds of its servers to run back testing, to effectively analyzing strategies, be it in Equities, FX, CFD, Options or Futures Markets. The differentiating factor for Quantconnect is its opensource infrastructure, paired with the fact that they do not profit from strategies.

Can’t Code?

Algoriz

(Sample of Translation, Credits: TechCrunch, Mar 2017)

Soraya Taghavi, previously worked in Trading at Goldman Sachs, where she unraveled the inability of traders to code technical trading algorithms. The CEO and Founder of Algoriz then started the platform the enables traders to write algorithms in plain English. Additionally, Algoriz allows investors to back-test algorithms using historical data.

Portfolio123

Identical to its counterpart Algoriz, Portfolio123 translates your investment strategy into an algorithm. Portfolio123 may be the tool to help users efficiently sculpt quant strategies without coding skills.

What’s next?

The tremors of the Quant Quake of 2007 still resound, but hey, look at where we are now! Hence, groundless as it may seem, the failures of the abovementioned alternatives may very likely be a mere foreshadowing of its eventual success. Machine has surpassed man, and undoubtedly, there is an exaggerated emphasis on the preeminence of modern day computers. Over the past few minutes or so, the real takeaway lies in the linchpin, the realization of the ineffable amalgamation of man and machine.

23rd January 2018, Lee Jianyou