Alpha 2.0 Challenge – A Quantum Leap in Investment Strategy

The Alpha 2.0 Challenge turns the traditional proprietary trading model on its head – whereas most of the industry is an exclusive club that draws on the talents of a select few, Alpha 2.0 draws on the unparalleled wisdom of an open marketplace of ideas.

Just as happened to the technology sector in the 90’s, the financial sector is learning that old-fashioned, insular ways of thinking will not deliver long-term results.

We are bringing the open-source model to trading based on our firm belief that enlightened team trial and error will always succeed over the efforts of the lone genius.

We assembled the technological, financial, legal, and logistical infrastructure to conduct large-scale black box trading operations – we now want to make that platform available to the best minds and ideas in the world.

Are you up for the Challenge?

We Provide the Infrastructure & Capital

We spent a year building the Alpha 2.0 infrastructure.


  • Up to $500,000 in dedicated capital
  • A direct pipe to the U.S. equities market
  • A world-class, highly-scalable cloud computing network

You Provide
the Strategy

Now we are making it available to you.



  • You submit your profitable algorithm and we work with you to deploy it in a live market using our existing Black Box infrastructure
  • We trade your algorithm with up to $500,000 in our capital
  • We share up to 50% of the net profits with you


Step 1 - Develop

  • Securities: Equities Only (may trade multiple simultaneously)
  • Indicators: Technical (e.g. price, volume, etc.)
  • Assumptions
    • - Shares: 1,000 to 10,000
    • - Trade Costs: $.03 per share per trade

Step 2 - Submit

  • Deadline: May 31, 2009
  • Submission Items:
    • - Algorithm overview, picture, pseudo-code
    • - MATLAB OR R (GNU S) script
    • - Securities and data fields used (e.g., price, volume)
    • - Holding periods and data intervals used

Step 3 - Profit

  • Net Profit Sharing: up to 50%
  • Your Capital: $0
  • BlueStone's Capital: up to half a million dollars

Click for Details

Click for Details

Click for Details



Step 1 - Develop a Black Box Algorithm

We are looking for Black Box strategies – algorithms that create trading signals without any real-time human involvement other than initial setup and monitoring. Don’t worry about error handling, trading condition exceptions, etc., we will handle all of that during implementation.

A simple example of a Black Box algorithm is one that generates trade signals based on the points where a stock price crosses its moving average. As illustrated in Figure 1, this algorithm generates a buy signal when the price comes up through the moving average, and sell signals when the price passes below the moving average.


Your algorithm must meet the following requirements:

  • Can only trade equities or indices listed on the NYSE, Amex, or NASDAQ
  • Must trade solely on technical indicators, such as price, volume etc.
  • Must show a positive absolute return over the most recent trailing 12 months, assuming per-share, per-trade fees and commissions of $0.03 (the algorithm must run / trade over the entire date range, unless predetermined reasons can be described)
  • Must be a Black Box - trading signals and order entry must be algorithmically determined with no human interaction beyond initial setup
  • There are no restrictions on price data intervals, though our strong preference is for shorter ones (e.g., tick-level data)
  • There are no restrictions on holding periods but shorter periods are preferable (holding positions overnight will be considered, but those that do not will receive favorable consideration in judging)
  • May trade one or multiple securities / indices simultaneously
  • Must be profitable trading lot sizes between 1,000 and 10,000 shares
  • Any security meeting the preceding requirements may be used, but our preference is for securities ranging in price from $20 - $50 and trading more than one million shares per day

Testing and Modeling

We assume the algorithms will be complex enough that they require at least some scripting for backtesting. We use MATLAB and R, an open-source alternative to MATLAB, (information available at for our testing and modeling, so we are asking for submissions in one of those two languages. If your algorithm is simple enough that it can be clearly communicated and fully tested in Excel, we will also accept that.


Due to licensing issues, we cannot provide any price data for you to use in your algorithm development and testing. Daily close data are freely available from sites such as Google Finance and Yahoo Finance. More granular (i.e., tick data) can be acquired from paid sources such as Bloomberg, NYSE TAQ, or IQFeed, and free sources such as

It is important to reiterate that your algorithm must run over a full year’s worth of data and show a profitable return. If there are time periods in which the algorithm is not trading, it must be due to pre-defined decisions made by the algorithm and your strategy (i.e., you cannot use the benefit of hindsight and simply "turn off" the algorithm during periods in which it loses money).  Remember, the algorithm will be used in a live market where there is no such thing as hindsight.

Step 2 - Register & Submit

Submission are due by 11:59 EST on May 31, 2009 and must follow the Submission Guide, which can be downloaded using the “Download and Sign Up” button at the top of this page. The legal documents should also be reviewed and signed by each team member. Finally, in order for us to provide participant-specific information throughout the Challenge, please email the team captain’s name and email address to:


We will evaluate submissions based on the promise they show for trading in a live market. This is an admittedly subjective criterion, but the market is a subjective beast.

We will base our decision on your testing results, our ability to produce profitable testing results with the introduction of live market variables, the complexity and scalability of implementing the algorithm, and our overall interest in trading with the algorithm.

Step 3 - Profit

If we select your algorithm, we will work with you to refine, implement, and trade it with exclusive rights for one year using up to $500,000 in our capital. At the end of the year, we will share the net trading profits from the algorithm with you based on the progressive scale shown below.

Profit Sharing Scale

Algorithm Return Percent of Profit You Receive
Up to 20% annual return rate 20% of the net trading profits
Greater than 20% and less than 50% Equivalent to the annual return rate
(e.g. a 32% return rate will share 32% of the profits)
Greater than or equal to 50% 50% of the net trading profits

After one year, we will retain the non-exclusive right to trade with the algorithm into perpetuity, but unlimited usage and licensing rights will revert back to you.

We are also using this competition as a vehicle for discovering new talent, so while we do not guarantee it, another potential outcome of a submission may be an offer of part-time or full-time employment with BlueStone Investments.


Rules, Eligibility Requirements, and Intellectual Property



Take the Alpha 2.0 Challenge

Click here to download the Alpha 2.0 Challenge Participation and Submission Pack to get started now

Download Registration Documents

Questions & News

If you have questions about the Alpha 2.0 Challenge or want to keep abreast of Challenge news, please visit our blog and be sure to review our FAQ.

If you still have questions or feedback, please feel free to contact us.

Take the Alpha 2.0 Challenge

Click here to download the Alpha 2.0 Challenge Participation and Submission Pack to get started now

Download Registration Documents



If you have any questions about the contest, the process, BlueStone, etc., please check our FAQ page first, and if you cannot find an answer, please contact us directly at info[at]bluestoneinvestment[dot]com