When Radical Experimentation Becomes Indispensable
NN Taleb calls trial end error insight gain: stochastic tinkering. FastCompany presented a few stories about how companies are using rogue R&D to tinker their way to the next big idea in this article.
But, radical experimentation and tinkering are not necessarily twins.
Let me add our story:
Taming the machine infernal
Nov-09 we installed a NVIDIA Tesla personal super computer - see details here. It was at a time when GPUs became ripe for advanced numerical computation. With double precision, programming models ….
Our radical experiment-objective: reduce the calibration of a Heston model in a least-square sense from market data of vanilla options on the FTSE100 index from hours to seconds. And it worked: the results were published in a joint transtec-UnRisk white paper.
Exploit new hardware and accelerate schemes on the "old" one
We made it quick but clean, even bank proof, knowing it doesn't make sense to provide it as a single, although stunning, solution into our comprehensive platform.
It was a radical experimentation project that provided deep insight into the specifics, benefits and limits of hybrid CPU/GPU programming - and we discovered new schemes that accelerate the calculations drastically, even on CPUs.
Make UnRisk inherently parallel
Our parallel multi-core implementations are so blazingly fast that they manage the comprehensive risk management tasks of our customers in time. On contemporary PCs.
But the xVA requirements will introduce a new complexity of the valuation space - hundreds of millions of single valuations. are rquired And this is what we do. With the experience of the 2009+ radical experimentation project we go far beyond. Making our engine inherently parallel and platform-agnostic, the same code will run on multi-core or on heterogeneous architectures.
Do it right when the timing is right
We could not have done it without the experiment - selecting one of the most difficult problems. And we might have done it too early without that experience. The right time's now.
The next big idea?
Solving the most complex risk management problems on personal super computers is one ground breaking achievement. Bringing unexpected complex quant finance solutions to tablet computers another.
We spent years in radical experimentation (this is only one example). Carefully choosing the maths and mapping every practical implementation detail. And then throw it away and make something really big.
Picture from sehfelder