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SkillsCast

Simulation in a Big Data World: Convergence of financial modelling in QuantLib and big-data technologies - Intermediate

6th July 2017 in London at CodeNode

There are 43 other SkillsCasts available from Infiniteconf 2017 - the conference on Big Data and Fast Data

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Quantlib is a long-lived open-source library for pricing for financial derivative contracts. It is in production use in a number commercial organisations for both pricing and risk analysis and management purposes. This type of computing is best classified as <<simulation>> but as I will show in this talk, with QuantLib as an example, there is an increasing convergence between <<simulation>> computing and <<big data>> computing. The reasons for this convergence include:

1) Desire to reuse scale-out and on-demand-scaling technologies developed for big-data analysis

2) Very high data volume output from the simulations which is costly to reproduce, meaning that the outputs are saved and mined subsequently for multiple scenarios and analyses.

3) <>, where rapid analysis of initial results is used to adjust the pricing parameters and the space of market conditions which is simulated

A similar convergence pattern can be seen in a number of other fields in science and engineering, e.g., climate modelling simulation, which will make this talk of interest to a wide audience.

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Simulation in a Big Data World: Convergence of financial modelling in QuantLib and big-data technologies - Intermediate