Thinking Derivatively – February 2021 Newsletter


In the world of quantitative finance, quant research & development help drive an institution’s strategy to the cutting-edge of “what’s next.” As innovation and creativity are the driving forces behind success, this issue of the newsletter highlights some of the latest breakthroughs in quantitative research and analysis in the derivatives arena. All recent research featuring Numerix quant leadership and other notable industry experts can always be explored here:


Quantitative Research in Brief: Explore the Latest Highlights | Live Webinar 2/23
Join this discussion and connect with the Numerix QRD team to discover the latest quantitative research and development that is driving new technologies for trading and risk innovation at Numerix. You will also learn about industry trends in quant research and gain insights and commentary across a collection of quant topics.
                                    REGISTER HERE>>

Machine Learning Techniques: Neural Networks
with Asymptotics Control

In this on-demand webinar, Numerix explores some
of the advantages and use cases for applying machine learning, deep learning, and neural networks in mathematical finance. The new research presented
in this session also covers areas such as neural
networks and their use in finance and spline as a
                                    control variate matching asymptotics.
                                    WATCH ON DEMAND>>

Risk Magazine Cutting Edge Research | Deep

Explore the details of this new research. Leading
industry quants explain the limitations of artificial
neural networks as accurate and fast approximators
in various derivatives pricing applications and introduce their development of a new type of neural network that
overcomes these limitations.

New Research Paper | Multi-Curve Cheyette-Style
Models with Lower Bounds on Tenor Basis Spreads

This paper presents a general multi-curve Cheyette-style model that allows precise control over tenor basis
spreads. The original specification for this model did not provide a solution for the no-arbitrage drift function. Drs. Michael Konikov and Andrew McClelland of Numerix recover the drift function and proceed to fully develop a model, providing an example with a level-dependent volatility function to secure lower bounds on spreads.
                                    ACCESS THE PAPER>>

Upcoming Events and Webinars

February 23 | Quantitative R&D Innovations Update

Please visit Numerix Events & Webinars for more information.

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