The Sky Falls? The Sky Falls?

From Wolfram Blog rain in England around Swithun's day .

St. Swithun’s day if thou dost rain
For forty days it will remain
St. Swithun’s day if thou be fair
For forty days ’twill rain no more

Jon Mac Loone from Wolfram Reasearch, International Strategic Development tested, whether this is "true".

If you would bet on reverse rain floaters? A portfolio built of locations?

Inspired by an article of Aaron Brown in Wilmott magazine, Jul-09:

In financial risk management you might calculate VaR that, simplified, tells you, that there is a 1% chance your trading position would lose more than VaR (the days you get really wet in double sense).
But this is not enough. Risk managers should perform backtests like

• the actual fraction of VaR break days is 1% within statistical tolerance?
• the VaR breaks are randomly distributed (avoid Swithun situations)?
• the VaR breaks are independent of the level of VaR?

If you have the VaR, which calculation can become nasty with the most sophisticated deal types (you can do it in UnRisk), back testing is as simple as in Jon’s example. In Mathematica..

2010, Year of Dekonstruction and Reconstruction?

Ferran Adria the celebrated chef of "El Bulli", deconstructs and reconstructs, say, fish, fungi, ..., fragmented photography does and TRIZ innovation principles suggest a kind-of for re-inventing products.

In Asymptotic Mathematics I introduced an example in which mathematical solvers do. Decomposing domains as fine as exact solutions can be obtained and aggregate results.

In reconstruction you might want to use your exact solvers as base for simulations along a wide working-space and produce i/o samples that you can analyze by adequate machine learning methods. Extracting ultrafast Surrogate Models .

In finance, climate, biology, .. we need to model complex behavior knowing that more parameters and complexer models might lack the robustness required (you might get lost in the numerical jungle, stuck in local minima, inverse problems, ..).

Mathematica and mlf enable us to make comprehensive but low-effort experiments with deconstruction and reconstruction in quant finance.

This motivated me to playfully look back at the past from a future perspective.

Me talking to Myself in the Future

Geologists Love Beer

Why? explained a Wired article today (with winking eyes).

It has to do with the amount of time spent outside doing fieldwork; with the many places where they do not have drinkable water. Or - my favorite: when it is hot, and you've been hiking all day carrying 50 pounds of rocks, do you want a Merlot?

But: science does not work, when people keep secrets and don't share their data (and what could better help with free flow of information).

This seems to be in a little conflict with How to Pick a Good Fight . And free flowing beer for free flowing information seems to be ineffective for a good future-facing fight?

Mathematica's declarative environment and document centered approach helps with free flow of information. But it is also a great platform for good fights. Mine innovative solvers by attacking problems with different approaches.

And you get clean Mathematica in most of the places.

Silo but deadly?

The title of an article in The Economist (subtitle: messy IT systems are neglecting aspects of the financial crisis) suggests that many banks have huge problems with data quality and the fragmented IT landscape made it exceedingly difficult to track a bank’s overall risk exposure before and during the crisis. But also concluding answering such questions as ‘What is my exposure to this counterparty?’ should take minutes. But it often took hours, if not days.

The core question in difficult times: shall we emphasize on the technological support of our core business, or optimize the work flows? People often think, there is a trade off between supporting quickly emerging business ideas (in finance: new deal types, tradig strategies, ..) or the organisational aspects (including risk management).

It is assumed that mapping the quickly-emerging lead to quick-and-dirty prototyping that leads to quick-and-dirty sub systems.

But THERE ARE evolutionary prototyping platforms.

The compute-develop-deploy paradigm of Mathematica is a leading example, for all developments in quantitative fields, from the user-programmed desk top application to the largest scale enterprize-wide risk management system. With its link technologies Mathematica can integrate even legacy-system fragments, and its data base link allows for high data quality and consistency. Intelligent data aggregation and scalable built-in high-performance-computing enables in-time-decision support.

Again, it is not OR, it is AND.

Hopenhagen

Some thoughts on the big climate conference in Copenhagen. I am not a climate expert, not in social and economic sciences and not a politician. But interested in complex-systems theories, I have reservations about the linearity of the discussion. We will have deadly global warming and we can (only) avoid it by CO_2 avoidance (entering the anti-Carbon age immediately)? Or, we have nothing of that?

Assuming predictive modelling has produced correct results; how can we exactly know, where to put our concrete efforts and money? In the extreme: put them into hectically reducing CO_2 or measures to avoid negative impacts on people, social entities, the community, if "it" happens? Wouldn't our civilisation change in an atmosphere of hysterie? Do we know the social impact and cost?

The co-evolution of greed and fear has no equilibriums.

However, something will happen, consequently, something must happen. Crazy? Not at all, IMO.

It is always a reasonable objective to make our environment cleaner and save resources.

And probably a radical innovation was to exploit, say, weather and climate drifts and volatilities for energy and process optimization? This might lead to new systems of "technical" co-evolution (work with the knowledge about the partner system, to optimize the own)?

Future-Prize to Fraunhofer ISE

The 2009 Future-Price of the German Federal President (Horst Koehler) went to Fraunhofer ISE (Institute for Solar Energy) and BASF. Small spheres against climate change - Energy efficiency and comfort thanks to intelligent building materials. This was celebrated yesterday in a show at a major German TV station (ZDF).

Congratulations!

Fraunhofer uses Mathematica since 1992.

Fraunhofer ISE has the largest user group within Fraunhofer and hosts one of the yearly Fraunhofer Mathematica Seminar.

Huginn and Muninn

the pair of ravens that flew all over the world, Midgard, and brought Odin, head of the Aesir, information (attested in the Edda, written nordic mythology). Some interprete them as ear-whisperers, some as the personification of the god's intellectual power (Huginn - thought; Muninn - mind).

However Odin worries about the return of them each day and whether he can transform information into wisdom. He also worried whether this was enough and gave one eye to get a drink from Mimsbrunn (Mimir's well), to know yet more.

We don't need to give one eye and also ravens are replaced by massive information available online. But still we need to decide how we combine modeling and data-driven methods for decision support.

We have integrated our multi-method machine learning methods into Mathematica to create computational knowledge from modeling and data mining. All implemented in machine learning framework (now on version 2), for better decisions. In business and industry. We want customers that want to turn information into values. Unlike Odin, who wanted to become all-knowing and all-mighty and finally led Asgard into Ragnarök (end of ruling powers).