The competition between prestigious schools
On 10th September, we launched the largest ever data science online Quant Hackathon 2020 with UBS. More than 2,500 talented students from 462 schools, based on 36 countries, are now competing to build the most innovative quantitative strategies to tackle real-life challenges from the financial industry.
The students are trying to make their schools stand out in the ranking of the Top Universities with the highest number of participants. So far, since the competition started, the National University of Singapore is leading the global ranking. In EMEA and Americas, the Imperial College London and the Columbia University in the City of New York are ahead correspondingly.
Is your school in the ranking?
The leaderboards are live!
371 ambitious teams are competing non-stop to build the strategies with the best performance and achieve a higher ranking. Find out all the teams’ position for each competition here:
- Outperform the S&P 500 Index competition leaderboard
- Machine Learning for Complex Pricing Models competition leaderboard
Get the best ideas with our webinars
Would you like to know which are the best practices to build a strategy with a good performance? We hosted 3 live webinars on our Youtube Channel during September and the beginning of October. If you missed the webinars, you can watch the video replays in the UBS Hackathon 2020 playlist on our Youtube Channel.
On September 18th, we hosted the Hacking the S&P Data for Machine Learning webinar, to provide ideas to start coding your stock picking strategy. The video got more than 500 views! Don’t stay behind, watch the webinar replay here to learn how to:
- retrieve data,
- explore a large data set with Alphien built-in functions,
- efficiently manage memory for rapid exploration,
- integrate data into a portfolio.
On September 25th, we conducted the Outperforming the equally-weighted S&P 500 index webinar. This video got more than 400 views and you can watch the replay here. Don’t miss the chance to learn more about:
- replicating the equally-weighted S&P 500 index,
- customizing the payout by adding more data,
- computing new features,
- selecting the stocks that will produce superior returns.
On October 5th, we also hosted the Machine Learning for Pricing Models Webinar with guest speakers Vinay Srinivas and Alexandre Cohen from UBS. Vinay Srinivas, APAC Head of Quant Analytics & Digital Transformation, Global Markets; and Alexander Cohen, APAC Head of Equity Derivatives Quantitative Analytics explained why quants are absolutely essential at UBS today and the diversity of positions UBS can offer. They also commented on their keen interest in the Machine Learning for Complex Pricing Models competition and answered questions from participants. If you want to know more, watch the video replay here.
