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Showing posts from October, 2017

Alechinsky and Margin

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Today I visited an exposition on Pierre Alechinsky , a Belgian artist. Some of his works are visible at the MoMA . Among the frames, there was the poster of a previous artist exposition in New York titled   Margin and Center. Margins are following me everywhere now, even in art shows!

Algorithmic Differentiation training

I will present a training session on AD in December. Location: Warsaw, Poland Date: 13 December 2017 (full day) Organizer: CEETA - Tomasz Dendura Algorithmic Differentiation in Finance Algorithmic Differentiation (AD) has been used in engineering and computer science for a long time. The term Algorithmic Differentiation can be explained as the art of calculating the differentiation of functions with a computer . AD is now also a standard tool in quantitative finance. The workshop presents AD from a practical point of view and targets quantitative analyst, risk manager and developers working in finance. The focus is on the foundation of the method and the idiosyncrasies of the applications in finance. Different implementation alternatives are presented, allowing each participant to adapt the general method to his needs. Introduction AD is magic (or not)! Exact derivatives Finite difference Development time v running time The Principles of Algorithmic Differentiation

Game of Benchmarks: Season 1 - Episode 4: Transition and transition team.

Transition to a different world is difficult, more difficult than inventing a better world from scratch. In this episode, I’m looking at the transition. There are probably more questions than answers. But, as you know, In mathematics, the art of posing a question is more important than the art of solving one. Georg Cantor, 1867. Is transition important? Valuation of flow derivatives, and in particular Libor linked derivatives, and the associated collateral discounting framework are vanilla in name but certainly not simple if you have to implement them from first principles. The impact of features that were considered before the Great Financial Crisis (GFC) as “details” are nowadays very significant. You can not simply replace one benchmark by another and hope for the best. There are numerous items to take care of, like valuation framework, non linear effects, convexity adjustment, risk management strategies, liquidity, regulatory impacts, etc. I don’t know if, from a purel