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by Stephen Channell
This is a case study of a live F# application for real-time early warning indicators of Liquidity Risk.
EWI used an F# Excel expression parser and computational expressions to generate a Cell network in memory that triggered indicator calculations from market events, that percolated up to RAG status changes.
The EWI model demonstrates features of F# that enabled rapid development:
Ever wish you could code Excel with a Functional Programming Language (F#) instead of VBA?
Excel has over 400M users all over the world from many backgrounds including business, finance, and governments. On average large spreadsheets have over 12 substantial coding errors. A perfect example of this is the Reinhart-Rogoff paper (Growth in the time of Debt) where a trivial coding error helped them make the case for austerity around the world.
In this presentation I will demonstrate how to prevent such errors while taking advantage of the rest of the .Net ecosystem by bridging the worlds of Excel and .Net with F#.
I will give rapid fire demonstrations of
* Big Data;
* Data Science;
* Cloud Computing;
* GPGPU; and
* Compiling F# Excel UDFs.
All from within Excel.
24th–25th October 2013