Copper is the most important commodity used for renewable energy. The transformation of the global economy toward a cleaner, more sustainable and greener energy will require an important consumption of copper. It is used in energy systems to generate power from solar, hydro, thermal and wind energy across the world. Copper helps reduce CO2 emissions and lowers the amount energy needed to produce electricity.

Copper is very volatile and in this competition the challenge is to create an overlay long and short strategy in copper. A systematic overlay strategy is a financial trading strategy or method conducted to manage copper exposure in general and can be used by company who are planning to consume copper in the years to come. It is particularly useful for institutions who have a pre-existing exposure to copper from their business as long signal can be used for their hedging. The strategy can also help producer of renewable energy systems to time the market to purchase the copper they need.

In this challenge, you are required to find the best hedging strategy for copper, long or short using the future contract traded on the London Metal Exchange (LME Copper CA).



You must build a long-short and non-leveraged portfolio.

Your objective is to maximize the Sharpe ratio of your portfolio, but also to minimize the drawdown expressed by the minimum 3-year rolling Sharpe ratio. These 2 metrics will be taken into consideration to select the winner(s).

Use the tutorial notebook to get started:

Investment universe

The Investment Universe is composed only of the (properly rolled) copper futures contract.

Ticker Name Asset Class Currency
LP LME Copper Commodity USD


The only available input data for this competition are:

  1. BB Live of the Copper
  2. Open Price, High Price, Low Price, Close Price and Volume of the copper generic futures contract.
  3. Open Price, High Price, Low Price, Close Price and (Volume) of several market indices.

The data can be called using the getTickersCopperChallenge function.

Ticker Field Description
LP BB Live Copper
LMCADY Comdty OHLCV LME Copper Cash Price
SPX Index OHLCV S&P 500 Index
USGG10YR Index OHLC US 10-year T-Note yield
DXY Curncy OHLC US Dollar Index


No benchmark (your implicit benchmark is a cash position in US dollars).

Portfolio constraints

Each time the weights are set, the following constraints must be satisfied (i.e. the constraints are not checked between 2 set dates):

Ticker Min Max
LP -100% 100%

Additional notes:

  • Weights have to be between -1 and 1
  • First weights have to be generated before/on 2004-01-02 (1 year calibration/training. Rolling/expanding windows are allowed)
  • Sharpe Ratio for the backtest period has to be > 0.25
  • Payout has to be replicable and contain no lookahead bias
  • All time series data has to be called via the DataFeatures object - no data calls in your payout.
  • Payout and its dependencies have to be attached and properly documented
  • Short summary of your model to be written at the start of the notebook -- Summary can include model used, why the model was selected, rationale for any data processing done, parameter selection etc...
  • Whole notebook has to be ran under 15 mins (excluding the testCopperSubmission function). Training of models/processing of data inclusive.
  • Only notebook that are well documented, code with clear comments will be accepted. The notebook need to explain the rationale of your approach and why you are using the techniques. A lack of clear documentation can induce disqualification even if your version of notebook has been accepted, make your code easily readable and clear to understand, create functions or classes to make your notebook cleaner. Also, put potential references in your notebooks.

Please also have a look at the payout pitfalls page for common issues faced by users.

Strategy transactions

Transaction costs: 1 basis point (bp) of the amount being transacted.

Transaction frequency: The maximum transaction frequency is daily (no intraday trades). All trades are executed at market close prices.

Transaction signals: Transaction signals must be based on data available at close-of-business on the day prior to the execution. Signals are 'executed' 1 day after they are generated. Please have a look at this page for more information on our '1-day lag convention'.

Rebalancing penalty: 2 basis points on the total AUM, each time you have a date with a set of weights, it will be considered as a 'rebalancing' day and you will incur the penalty. Please check the example notebook and check the page Rebalancing and transactions costs

Backtest period

The in-sample period runs from 1 Jan 2003 to 31 Dec 2018. To prevent any overfitting of the models, data for 2016-2018 will only be unveiled after your first model submission.

Note: Once your first submission is approved, you can revise it as much as you want.


You must use Notebook to submit your solution. You can only submit one notebook. However, there is no limitation in the number of revisions you can make on a submitted notebook. If the solution follows a theoretical or academic paper, the participants are encouraged to attach the document with the submission, any relevant document (own paper or other document) to explain the approach used will increase the robustness scoring.

Please visit our Submissions page for all details on how to submit.


The strategies will be ranked based on the weighted arithmetic mean of their following two rankings:

Performance Metrics Metric ranking Weight
Sharpe Ratio SR 50%
Robustness Rank RR 25%
Minimum Rolling Sharpe Ratio (*) MRSR 25%

(*) The Minimum Rolling Sharpe Ratio will be calculated over a period of 3 years.


  • The out-of-sample period will not be disclosed.
  • If there are multiple versions of the same notebook, only the latest version will be taken into consideration.


The winner(s) will receive either:

an iPad Air 64GB WIFI (team of one person), or

an Apple Watch model SE GPS 40 mm per team member (teams of 2 or 3 members).

Prize for Challenge.PNG

  • The opportunity to get your strategy licensed by Asset Managers looking for such asset allocation strategies


Alphathon Starts

Wednesday 03, march 2021.

Research Ends

Wednesday 14, April 2021.


The Challenge will be open to any Participants (academic or non-academic) in the world.

  • Individual: One person. Register as Individual
  • Team: A team is a group of individuals which have registered to participate in the Challenge. A Team can be composed of 2 to 3 individual(s). Register as a team


Submit early to earn points that will help you win the competition !
  • Starting from 17th of March 2021 and every Wednesday until 10th of April 2021, the top 5 users ranked by the selection criteria will earn Alphien Points allowing them to unlock special features for the Global Allocation Challenge!
    • 1 Extra Submission. Remember that you can only submit one solution by default.
    • 1 Special 30 min consultation with a Senior Quant.
  • You can request to unlock these features by commenting on the ticket generated after you make a submission.

Weekly point rewards

Ranking Points
1 15
2 11
3 7
4 3
5 1


Support tools

  • After you have joined the competition, click the "get started" button. You will be redirected to your dashboard. In "Public Notebooks", filter notebooks by competition tag using the "Global Allocation Challenge" tag.
  • Read about common payout pitfalls to maximise your chances to win.
  • Use the Forum to find help from the community or from Alphien support team.

Tips and advice

  • Use AlphienLab to conduct your research.
  • Once you have fine-tuned your model, document it in a notebook and submit the notebook for our review.
  • We highly recommend you use the Forum as much as you can to get support.


The Challenge will be open to any Participants (academic or non-academic) in the world, but Alphien reserves the right to reject some applicants if terms of the platform are violated. In particular, you must not copy code or intellectual property which is not your own or is not open sourced. You can not participate as a professional if your employer can claim ownership in any part of your work on the Alphien platform; in case of conflict please contact and discuss with the Alphien team. Alphien is open to free scientists who own their intellectual property.


Please refer to Alphien Terms of Use.