Abstract
SummaryDerivative traders are usually required to scan through hundreds, even thousands of possible trades on a daily basis. Up to now, not a single solution is available to aid in their job. Hence, this work is aimed to develop a trading recommendation system, and to apply this system to the so‐called Mid‐Curve Calendar Spread (MCCS) trade. To suggest that such approach is feasible, we used a list of 35 different types of MCCSs; a total of 11 predictive and 4 benchmark models. Our results suggest that linear regression with l1‐regularisation (Lasso) compared favourably to other approaches from a predictive and interpretability point of views.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Intelligent Systems in Accounting, Finance and Management
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
