Our research community continues to expand with the increased adoption of Alphien’s platform as a teaching tool in universities
With the start of a new academic term, our research community has grown by almost 35% over the last month. New joiners, mostly students, mainly come from Ecole Polytechnique and ESILV, where professors have used Alphien‘s platform for financial engineering practical applications and tutorials. We are glad to see such enthusiasm from academics to use Alphien as a tool to assist their teaching. We look forward to expanding into more universities and attract the best talents onto our platform.
Beat the next market crash challenge concluded with 83 participants
Lastly this month, we have asked the community to practise the way we build strategies on the platform through an educational challenge: use any machine learning technique to design a market timing strategy that limits downside on a single asset (the S&P future) long-short investment.
The motivation behind the challenge was to give an opportunity to users, especially newcomers on the platform, to get familiar with Alphien’s strategy building library by applying it to a concrete case study. In order to create a systematic strategy that is replicable, the way users generate their buy/sell signals - or as we call it on the platform, their payout function - has to follow some key principles. The gist was to let users deal with designing their algorithm from scratch as a first step in order to understand the difficulties and challenges raised by such a task, especially in order to avoid overfitting and forward looking bias. At the end of the challenge, we will give all participants a template example that they can directly copy, allowing them to work from a replicable payout and to customise it with their own ideas. With this approach, we make sure that users are familiar enough with Alphien’s strategy logic to be ready to participate in future Alphathons.
Investment managers can look forward to accessing the Alphien platform very soon to browse and select readily available quantitative strategies
We have upgraded our display of leaderboards for Alphathons, giving the sponsor access to details for each individual contribution. Besides from typical strategy or portfolio summary statistics, we also display the total return chart over the backtesting period, the validation period(s) - period(s) hidden to participants to avoid overfitting - and paper replication. Performance is broken down on a monthly basis to spot any seasonality in the strategy. For portfolios, we also strip out the performance of underlying assets over the whole period.
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