Quantopian: the innovation funnel meets hedge funds

Quantopian: the hedge fund from the crowd

The world of hedge funds and proprietary algorithmic stock trading can seem murky, complex, and even dangerous to those unfamiliar with the inner workings of firms engaging in these activities.  One Boston-based firm, Quantopian, has built a business model on the idea that trading algorithms can be sourced from anyone, not just highly-paid traders, and is betting on a crowd-sourced model to disrupt equity trading.

Operating Model

Quantopian was founded five years ago by financial-technology (“fintech”) entrepreneur John Fawcett, who previously sold a fintech software company in 2008 for $28M in cash and stock.[1]  Heralding the Wall Street Journal’s reporting that “DIY’s newest frontier is algorithmic trading,” the company’s core value proposition is to link investor demand in the form of capital with algorithm supply in the form of crowd-sourced strategies. [2]

Quantopian’s community of 100,000 aspiring quantitative traders are equipped with the below tools to test market theses:

1. Software tools leveraging the coding language Python
2. Historical data from U.S. equity markets back to 2002
3. Backtesting features to simulate how a given strategic would have performed in real market conditions
4. Research tools to validate the strength of a given algorithm, and
5. Access to capital to trade.

Quantopian publishes its selection criteria and author upside on its website.  Successful quants will create strategies with five key attributes[3]:

1. Low exposure, with a market beta of between -0.3 and 0.3
2. Consistent returns given risk profiles of a Sharpe ratio consistently over 1.0
3. Active portfolios with a target turnover rate of 12 and 500 times a year
4. Low correlation to other selected authors
5. Strategic intent based on market trends and economic drivers

At the top of the innovation funnel, Quantopian offers incentives and competitions for users to submit ideas.  Any author can tie their code to their bank account and trade their own money. The company then acts as a gatekeeper by evaluating certain algorithms for six months, much like Threadless does with user submissions.  If backtesting and live simulations prove successful, the company may deploy capital to trade the company’s or its limited partners’ (currently, Point72 Ventures) capital, in which case the author will receive a portion of all returns.[4]  To be clear, authors own their algorithm’s IP.

The operating model relies strongly on providing powerful software and relevant datasets in order to attract coders, which drastically lowers the cost to attract hedge fund-level talent to create profitable trading strategies.  Andreessen Horowitz investor Alex Rampell, a Quantopian board member, thinks of Quantopian “as the next-generation Blackrock.”[5]  While the two firms have slightly divergent amounts of assets under management, Quantopian may have more favorable tailwinds.

Strategy & Business Model

The typical hedge fund business model relies on highly-paid and intelligent analysts to create a limited set of strategies and algorithms with which to trade capital raised from limited partners.  Hedge funds typically charge a 2% management fee and 20% of the positive returns.

Quantopian disrupts this model through crowdsourced strategies, very low labor costs (nearly zero) with a different fee structure, and an open innovation funnel.

In the HBR article Strategy and the Internet, Michael Porter argues that the structural attractiveness of an industry relies on five forces, including intensity of rivals, barriers to entry, and threats of substitute products (see below figure).  In this industry, Quantopian’s model proves to drastically lower the barriers to test and create trading models by democratizing access to anyone with Internet access and basic coding skills.  In addition, trading offerings are more difficult to keep proprietary, as anyone can build similar or identical trading models using the same available data to pressure test market theses.  The variable cost of experimenting with a new algorithm is close to zero under this model; at a traditional hedge fund, the firm may need to invest significantly in a trading strategy, and demonstrate its success, before it has the ability to raise capital from LPs.  Porter ultimately argues that “Internet technology provides better opportunities for companies to establish distinctive strategic positionings than did previous generations of information technology.”[6]

Additional Steps & Conclusion

Quantopian is well-positioned to expand its offerings.  The company can further democratize capital raising, or invest training and development to its top producing authors.  Finally, the company can act as a recruiting tool for hedge funds.

The classic hedge fund model is under siege, as investors question current fee structures and withdraw money from highly paid firms that struggle to beat market indexes.[7]  Quantopian developed a distinctive operating model that engages a broad community through the Internet to compete with hedge fund traders, and thus has the impact to fundamentally change the economic drivers within finance and technology.  (797 words)

 

 

 

[1] Advent Completes Acquisition of Tamale Software. 2016. Advent Completes Acquisition of Tamale Software. [ONLINE] Available at: https://www.advent.com/about-us/newsroom/pressreleases/advent-completes-acquisition-of-tamale-software. [Accessed 18 November 2016].

[2] Austen Hufford. 2016. Algorithmic Trading: The Play-at-Home Version – WSJ . [ONLINE] Available at: http://www.wsj.com/articles/an-algo-and-a-dream-for-day-traders-1439160100. [Accessed 18 November 2016].

[3] Quantopian . 2016. Quantopian . [ONLINE] Available at: https://www.quantopian.com/fund. [Accessed 18 November 2016].

[4] Bloomberg.com. 2016. Andreessen Horowitz, Point72 Invest in Crowd-Sourced Quantopian – Bloomberg. [ONLINE] Available at: http://www.bloomberg.com/news/articles/2016-11-14/andreessen-horowitz-point72-invest-in-crowd-sourced-quantopian. [Accessed 18 November 2016].

[5] Ibid.

[6] Harvard Business Review. 2016. Strategy and the Internet. [ONLINE] Available at: https://hbr.org/2001/03/strategy-and-the-internet. [Accessed 18 November 2016].

[7] Ft.com.  2016.  Investment: Rise of the DIY algo traders. [ONLINE] available at: https://www.ft.com/content/0a706330-5f28-11e6-ae3f-77baadeb1c93 [Accessed 16 November 2016].