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Crowd-sourced Alpha: The Search
for the Holy Grail of Investing
Jessica Stauth, PhD – VP Quant Strategy
Justin Lent, Director of Fund Development
Thomas Wiecki, PhD – Lead Data Scientist
Uncorrelated returns streams are the
Holy Grail of investing. – Ray Dalio*
*http://www.scribd.com/doc/134432415/Ray-Dalio-Whats-Going-on-in-the-World-Presentation-pdf#scribd
Why is it so hard to find the Holy Grail?
 Positive Sharpe returns streams are a moving target – requires
ongoing research efforts to keep finding the holy grail over and over.
 Most investment teams are ‘narrow and deep’ in terms of expertise,
making it challenging to surface new uncorrelated strategies.
 Large multi-manager firms can be extremely successful (Millenium,
Highbridge, Barclays nQuants), BUT…
 The barriers to entry with a traditional model are high.
Quantopian has a non-traditional model: crowdsourcing.
Crowdsourcing – the process of obtaining needed services, ideas or content by
soliciting contributions from a large group of people, and especially an online
community, rather than from traditional employees or suppliers.
http://en.wikipedia.org/wiki/Crowdsourcing
The Quantopian Open
launched in January 2015
The Quantopian Open
launched in January 2015
Many of the algorithms submitted to the Open show strong
correlation to the market, and consequently to each other.
In a historical simulation only 20-60 algorithms passed our
maximum threshold for correlation per month.
We need a larger pool of uncorrelated returns streams for the
fund. Last month we adjusted the contest rules accordingly...
What we look for:
Low Exposure to the Market
We want algorithms that aren't correlated to the rest of the stock
market. We are looking for algorithms with a market beta between -0.3
and +0.3.
We want algorithms that show stable profits. If your algorithm is losing
money, or makes money in a volatile way, it isn't very helpful. We are
looking for algorithms that consistently have a Sharpe ratio over 1.0.
What we look for:
Consistent Profitability
Your algorithm has to actively trade. We measure that by looking at
how often your portfolio turns over per year. We are looking for
algorithms that turn over their portfolio between 12 and 500 times/year.
What we look for:
Active Trading
We look for algorithms with between -30% and +30% average pairwise
correlation with the other algorithms in our portfolio.
What we look for:
Low Correlation to Peers
We are are looking for algorithms that are driven by underlying
economic reasoning.
What we look for:
Strategic Intent
What we look for:
Strategic Intent
What we don’t look for…
 Overfitting
 Data snooping
 Spurious correlations
CONSISTENCY
0.85
To help you better analyze your algo
and get into the fund…
We’ll give you the same tear sheet analysis we built in-
house to evaluate our own portfolio.
Coming soon to /research …
Your algorithm gets selected for the
fund, what happens now?
 You license your algorithm to Quantopian for use in our
fund.
 You get paid a 10% royalty based on the profits earned
by your algorithm.
 You retain ownership of your intellectual property.
 Quantopian takes responsibility for operating your
algorithm, allocating capital, and managing risk.
www.quantopian.com/open
Thank you.
Questions?

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Crowd-sourced Alpha: The Search for the Holy Grail of Investing

  • 1. Crowd-sourced Alpha: The Search for the Holy Grail of Investing Jessica Stauth, PhD – VP Quant Strategy Justin Lent, Director of Fund Development Thomas Wiecki, PhD – Lead Data Scientist
  • 2. Uncorrelated returns streams are the Holy Grail of investing. – Ray Dalio* *http://www.scribd.com/doc/134432415/Ray-Dalio-Whats-Going-on-in-the-World-Presentation-pdf#scribd
  • 3. Why is it so hard to find the Holy Grail?  Positive Sharpe returns streams are a moving target – requires ongoing research efforts to keep finding the holy grail over and over.  Most investment teams are ‘narrow and deep’ in terms of expertise, making it challenging to surface new uncorrelated strategies.  Large multi-manager firms can be extremely successful (Millenium, Highbridge, Barclays nQuants), BUT…  The barriers to entry with a traditional model are high. Quantopian has a non-traditional model: crowdsourcing.
  • 4. Crowdsourcing – the process of obtaining needed services, ideas or content by soliciting contributions from a large group of people, and especially an online community, rather than from traditional employees or suppliers. http://en.wikipedia.org/wiki/Crowdsourcing
  • 7. Many of the algorithms submitted to the Open show strong correlation to the market, and consequently to each other. In a historical simulation only 20-60 algorithms passed our maximum threshold for correlation per month. We need a larger pool of uncorrelated returns streams for the fund. Last month we adjusted the contest rules accordingly...
  • 8.
  • 9. What we look for: Low Exposure to the Market We want algorithms that aren't correlated to the rest of the stock market. We are looking for algorithms with a market beta between -0.3 and +0.3.
  • 10. We want algorithms that show stable profits. If your algorithm is losing money, or makes money in a volatile way, it isn't very helpful. We are looking for algorithms that consistently have a Sharpe ratio over 1.0. What we look for: Consistent Profitability
  • 11. Your algorithm has to actively trade. We measure that by looking at how often your portfolio turns over per year. We are looking for algorithms that turn over their portfolio between 12 and 500 times/year. What we look for: Active Trading
  • 12. We look for algorithms with between -30% and +30% average pairwise correlation with the other algorithms in our portfolio. What we look for: Low Correlation to Peers
  • 13. We are are looking for algorithms that are driven by underlying economic reasoning. What we look for: Strategic Intent
  • 14. What we look for: Strategic Intent
  • 15. What we don’t look for…  Overfitting  Data snooping  Spurious correlations CONSISTENCY 0.85
  • 16. To help you better analyze your algo and get into the fund… We’ll give you the same tear sheet analysis we built in- house to evaluate our own portfolio. Coming soon to /research …
  • 17. Your algorithm gets selected for the fund, what happens now?  You license your algorithm to Quantopian for use in our fund.  You get paid a 10% royalty based on the profits earned by your algorithm.  You retain ownership of your intellectual property.  Quantopian takes responsibility for operating your algorithm, allocating capital, and managing risk.

Editor's Notes

  1. Demo prototype.
  2. In May we announced a scoring change in the contest to attract a larger pool of uncorrelated algorithms. We introduced a ‘beta badge’ and moved all algorithms with a trailing 12 month beta to spy of < +/-0.3 to the top of the leaderboard. We’re seeing signs that the ‘crowd’ is starting to move in the right direction. But it’s still early and there is a huge opportunity right now to get out in front, win the contest and get your strategy into the fund. Up next I’m going to talk a bit more the things we are looking FOR when selecting algorithms for the fund.
  3. Examples of economic reasoning could be a supply and demand imbalance, a mixture of technical and fundamental drivers of stock price or a structural mispricing between an index ETF and its constituent stocks.