Quantitative Finance Research Presentations with LYNX and OQAM

Zoom link: https://us06web.zoom.us/j/89613416074

Interested in learning more about quantitative finance and data analytics? On Friday the 28th of January at 16:00 (with academic quarter) LINC’s Research and Analysis Trading and Quantitative Research team will present their collaborative research projects. The research has been performed in collaboration with LYNX Asset Management (lynxhedge.se) and OQAM (oqam.se).The event will start with a brief introduction from LYNX and OQAM. Then five project groups will each present for 15 minutes, and then answer questions from both the collaborating firms and the audience for 5 minutes. The topic for each group are as follows:

Sentiment analysis: Using sentiment analysis from Twitter and Reddit to predict movements in equities in the XLK index.

Momentum commodity trading vs machine learning: Evaluating traditional MACD approaches to machine learning (random forest model) in commodity trading (12 commodities).

Momentum and Turnover Strategies: Examining momentum strategies applied to different clusters of the Standard and Poor’s 500 index single equities based on share turnover.

Commodity trading with skewness strategies: Investing using return distribution skew as trading signals for hard and soft commodities.

Momentum Trading during Inflationary Reports: Comparing the results of momentum trades between days surrounding FED announcements of interest rate decisions versus outside of those events.

This event is a great way for you to get to know the field of quantitative finance, and what it is like being a part of TQR. The projects and research apply the powerful tools of programming and data science to tackle hard and interesting problems within finance. Applications for the TQR team are currently open, apply before the 30th of January with a CV and cover letter at: https://staging.linclund.com/ra-application-form/

Ambitious students from all faculties are welcome, however as you would be joining existing teams we are looking for experience in programming. Experience in machine learning is highly appreciated.

For any inquiries, contact the team leaders at tqr@linclund.com.