Over the last few years,algorithmic tradershave become alarge part of Tickmill’sclient base. The importance of machine learning and data science continues to grow in trading,so we’ve decided to take a step forward in this space by organising a machine learning competition for the Cypriot academic community. While we value the opportunity to support local academia, we also believe it is key to remain at the forefront of thisexciting field to better understand the world so many of our clients live in every day; thus, better serving them overall.

The competition focuses on students within the Republic of Cyprus to enable them to hone their skills in machine learning. We’ve set the students a task to predict the value of a financial asset using a financial data time series combined with several features provided by our Quant Team.

Ultimately, we’re going to evaluate the student submissions against the ground truth which has been developed in house by our experts. From there, we’ll be awarding first, second and third prizes to the students who have the closest scores.

We’re awarding first place with a 5,000 EUR prize followed by 3,000 EUR and 2,000 EUR for second and third place, respectively.

Our head of Quantitative Research, Chariton Christou explained the thinking behind the competition, stating that “Tickmill’s forecasting competition offers a unique opportunity to students by allowing them to experiment with real world financial time series data. It’ll give students who are considering a career in quantitative analysis with a broker the insight into some of the tasks that we are trying to solve so we can better serve our clients.”

Due to this, it’s important to us that we begin to develop a deeper relationship with the younger generation in Cyprus and encourage them to consider careers within the financial industry with technology and data at its forefront.

Chariton went on to explain that “as a team, we wanted to launch this kind of competition a long time ago. It allows us to identify future talent in the data science field. University students can apply state of the art machine learning models to predict the market; one of the most difficult tasks in Machine Learning.”

He concluded that one of the main benefits to both Students and the academic community overall is that “students are exposed to solving real world dataproblems and have access to previously unobtainable yet realistic financial data. It’ll also allow students to put their extensive knowledge to use while providing a comparison of their skills against students from other universities. Overall, universities will be able to benchmark their students and develop a close relationship with a large broker to bridge the gap between academia and industry. It’s a super exciting time to be a machine learning student in Cyprus!”

Find out more about the competition and its terms and conditions by clicking here.