Ruckusmaker Day

Yesterday, we celebrated, what Seth Godin calls Ruckusmaker Day - in honor of the 60th birthday of Steve Jobs. I agree, more should speak more about their ideas.

We should talk about them, but we should not only be storytellers, but what Navi Modri  (and others?) call "storydoers".

This is why I wrote one day before the Ruckusmaker day: You're a Genius. We all have creative minds.  It's exciting to share...

You're A Genius

says WIRED in its Mar-15 issue of the UK Edition.
There's no magic behind creative thinking. You're born to do it. Keep asking: "why doesn't it work"…"what should I change to make it work"…Normal thinking is rich and complex - so rich and complex that it can yield extraordinary results
writes Kevin Ashton, spanning over evolution, philosophy, psychology, neuroscience…Two pages are about Steve Job's "secrets" (be never satisfied?)

Innovation makes our species different

Behavioral neurologists may say: yes, there are talents, but the neurological principles of creative behavior are the same among us - we all have creative minds. I agree. Creativity is a special class of problem-solving…characterized by difficulty, unconventionality, novelty…but it needs (some) competency and I ask: can you buy competency? Yes you can.

Wheels aren't hard to invent, are they? 

Original thinkers often look for adventure and start thinking not reading (eschewing algorithmic and technological fruits available). This is great for explorative learning, but it may reduce the value of the innovation - in quality or delivery time?

The innovative spiral drives faster if you push new, validated theorems...into the knowledge base and use them in a next turn. This white box - black box principle is very general, but especially powerful in quantitative fields.

What makes quant innovations work?

What are the units of quant innovations and what are their generic building blocks? IMO, the basic units are functions, the most important units are tasks. Functions create tasks…tasks create workflows and workflows create subsystems and subsystems create the system - the quant innovatio. The structure may be more sequential or nested. In quant finance it's quite nested.

It is my strong belief that a quant innovation does only work, if it is developed the bottom up fashion and that each unit has building blocks that are constructors, management of progressive problems (with critical moments), solutions and their interpretation.

Functions tune the mechanics of tasks, workflows, subsystems, the system and they are the "media" of actors. They define the coverage and the depth of the system. Their programming style shall be symbolic, functional…but their implementations shall combine symbolic and numerical computation.

Tasks have usually a time dimension and they move objects and actors. Tasks shall offer a clear shift (change) throughout its flow. Comprehensive tasks may be: financial market data selection, curation and import...model validation…instrument pricing with xVA...portfolio across scenario valuation... VaR calculations, stress tests…risk data analysis and aggregation…a task is a subject of event modeling…a task oriented language as well as the data  representation need to know events…again a symbolic language serves this requirement…

Workflows are responsible for the management of progressive problems. They may deal with the analysis, prediction or control of processes…in workflows we may use generic tasks like, "Create", "Select", "Apply"…Data, Instruments, Models, Parameters, Valuation Methods, Portfolios, Scenarios, Risk Factors

Subsystems and the system are created by workflows…sub systems are add-ons if they're built atop another subsystem (a platform).

This are the ideas behind UnRisk Quants. Develop a cascade of innovations that work and empower us unfolding creativity based on growing bank-proof systems, technologies…and make the same stack available to the most busy people in quant finance - quants.  Help them making their deadlines. Offer new kinds of insight partnerships.

Negative Interest Rates Are Here To Stay

wrote Frances Coppola at Piera a few days ago. In short, QE (and interest rate cuts) of major economic players force smaller countries to cut deposit rates into further negative territories. What I find convincing in the article:
I don’t buy the argument that households in the US, UK and European countries such as Spain and Italy have low saving ratios. They have low levels of liquid savings, yes – but they invest hugely in illiquid assets, particularly property, usually as a leveraged investment.
and finally
If the elderly actually spent their savings, rather than living frugally to preserve capital, the release of that money into the economy would be a demand stimulus that would both raise inflation and arrest falling interest rates. And if those saving for retirement risked their money in young, growing enterprises rather than seeking low-risk passive investments in mature industries, property and government debt, it might dampen the cycle of asset price booms and busts and reverse the long-term trend of interest rates. 
As business owners we know about financing a project: it does not matter where it comes from (equity or debt - Modigliani-Miller - you always sell parts of your future business) it matters where it goes to. This should be obvious for everybody, when interest rates are low.

And it's true for an economy as a whole. It may be the lack of innovative ideas, but if an economy is unable to find a more productive use of savings (or debt) than blowing up asset bubbles…interest rates will continue to fall.

It's turning the price logic: if, at the green market, carrots become too expensive, we buy other vegetables. If houses get expensive they become objects of speculation and prices rise until the bubble bursts…the economy as a whole does not optimize risk.

As I have pointed out on previous posts...I doubt that the regulatory regime of risk minimization by centralization will be the right contribution of the financial system, but it happens and we will get used to it.

As quant supporting technology providers we know that some widely used models bear operational risk in a regime of negative values. And we offer better approaches and insight:

The Theory of Speculation
Black vs Bachelier revisited
When Variance Is Negative
Negative Eigenvalues in Practical Finance
Libor and the Negative Eigenvalue Trap

whilst following the regulatory requirement of central clearing and counterpart as well as margin rules empowered by the xVA Engine.

It's all embraced in our brand-new UnRisk Quant

Consider looking into it…ask the authors of A Workout in Computational Finance directly:

Andreas Binder
Michael Aichinger

Negative interest rates are here to stay?!

Multiple Choice Buying?

This is the post at RBS Insight that surprised me: How retail technologies will help corporate treasurers.

It suggests that banks shall/will adopt a kind of "collaborative filtering algorithms"...successfully used by the online retail sector…to pitch new products to clients.

What is a collaborative filtering algorithm?

It's a method of making automated predictions about the interests of a user by collecting preferences from many users. If one shares a taste with others its more likely that she shares another taste too…is the basic idea behind.

If you listen too much to main stream, you create mainstream?

Collaborative filtering needs enough samples (user-item matrixes may become large and sparse), it looks into the past…so, although collaborate filtering can claim to achieve good diversity and independence, it may work the other way around in unpredictable cases - if you listen too much to mainstream, you create mainstream.

Is good for gadget buyers also good for corporate treasurers?

The traditional role of a corporate treasury embraces core functions…corporate finance, cash management, liquidity planning and control, procurement of financial investments…and increasingly important: management of interest, currency and commodity risk…and marginal functions that are extremely company specific.

IMO, senior management and board seek greater visibility to liquidity and risk exposures and better monitoring financial metrics on critical projects…this requires finding new ways to leverage treasury skills and technologies…maybe use things that are not in stock.

Yes, Steve Job said once: "...people don't always know what they want before you show it to them…" But how do we show complex system behavior and something that has not been described before?

Quant finance

Without using algorithms, you can't understand values and risk and engineer new financial instruments, but the success of treasury departments may need also quantitative methods to validate the major instruments they need…beyond collaborative filtering...

A treasurer's role may need to shift from being an asset guardian to a value creator…set the stage for successful investment and risk management, leverage technology and build quant finance skills.

We'll be pleased to help.

Banks pay for loans ?



It seems that not only borrowers speculated with their Swiss Franc loans. Banks did not include floors into their rate calculation for the loans. As the Swiss Franc reference rates go down banks have to pay interest to the borrowers. In Austria banks try to change the contracts but it is a legal dispute whether they are allowed to do so. If not these are some positive news for the borrowers who have been hit hard by the EUR-SFR exchange rate.

Superquant 2015

Beyond the Barricades is the title of the cover story of the Jan-15 issue of the Wilmott Magazine…it's about the recruitment outlook for quants in 2015…advocating for the ability to work and communicate well across disciplines.

In October 2014 I posted about the Antidisciplinary

In Beyond the Barricades Wilmott asked major recruiters a few questions….about increasing and decreasing opportunities, drivers, specifics of market segments, skill requirements…

Superquant by compliance or innovation?

The word that has been placed several times across the interviewees: "quant risk teams"…that, IMO, means that emphasis will shift from quant traders to risk quants…especially market risk modelers, operational risk modelers, (risk) model validation specialists…were mentioned.

From the many answers, I select two from London
The best-remunerated quant jobs will be the ones closed linked to regulatory coordination or model audit/governance (Anna Purves from Robert Walters)
The ability to combine programming with business-oriented responsibilities, creating new products working with clients…will be part of the big boom for 2015 (James Martin from Phaidon International)
Be compliant or innovative? The market within the space of quant finance seems to change very much and, pointedly speaking, I understand the above positions as two extremes: work along constrained tasks that are defined by somebody else or figure out what the new opportunities are? In short do the industrial or the lab work?

Gold Rush or modern mining?

As the Wilmott article states in its beginning hook
The days of the quant savant as the secret weapon of the front desk and proprietary operations are now long gone. The difference between pioneering days of the first rocked scientists arriving on Wall Street and the current situation is akin that between the first prospectors of the California Gold Rush and the modern mining industry
That happens with many businesses. Pioneers take the arrows and the settlers take the land…But in many industries quant skills are still seen as drivers for better outcomes.

Can the finance industry be defined as one that develops on the basis of retreating innovation? Meeting regulatory requirements alone?

Is it surprising that the Wall Street has got strong competitors when recruiting talents? Google...or even tech startups?

Our offer beyond productivity

Productivity? It's a measure of output over time.

You get more productivity by working harder or with more skill. Then you might find people who cost less for doing the assigned task. You may manage cooperate and build clever teams...

Then you may invest in technologies that boost the output of your teams…And then?

Then you may invent a new technology…it finally may empower you to define your own tasks. Those that make the change to the better in principle…those that make you a "hybrid quant"…combining programming with business-oriented responsibilities.

The final step may separate the extraordinary careers from the normal ones.
But it often requires a short downturn of your productivity.

Our offers are made to promote yourself by high level programming, regulation-compliant engines, multi-model approaches for new products…know how packages and transparency. Based on UnRisk Quant.

We wan to help pioneers to take the land and settlers to pay the rent.

About productivity, has been inspired by Seth Godin's blog post.

Electrons, Crystals and Attoseconds

How long does an electron need for its way through a crystal grid ? Austrian and German physicists now answered this question with an sophisticated experiment. For its way through one atomic layer of a solid state an electron needs 40 attoseconds. For this time measurement the team around Reinhard Kienberger targeted two succeeding laser pulses on a few atomic layers strong magnesium crystal an a Wolfram surface. Details of the experiment and the measurement can be found in the actual issue of the Nature magazine. Insights from this experiment can help to  further increase the speed and to further minimize electronic devices.

After 247.500 Hours Developing UnRisk...

we've announced UnRisk Quant. But it's not yet another announcement.

I recall the very beginning…the decision to make UnRisk PRICING ENGINE after some amazingly successful quant finance projects - 2001. Or 2008 when we launched our flagship platform the UnRisk FACTORY.

But things have changed drastically. The new regulatory regime of centralization and standardization may not only lead to revenue compression of derivatives businesses, but also change the roles of quants fundamentally. Instead of "structure me this" or "optimize me the market risk of that portfolio" they will need to manage massive data and valuations diving deep into the institutions information system?

The open workload of quants may become horrible and their race at the critical path of no avail?!

With UnRisk-Q we've unleashed the programming power behind UnRisk. It became an indispensable add-on for our clients that individually post-process the comprehensive risk data of the UnRisk FACTORY. It stretched our business. Consequently, we didn't push it hard,

Help quants leverage their work  

We believe hot creativity and not frozen standards will heel the feverish financial systems. Quants have it.  We decided therefore to offer them a fundamentally new partnership. The foundation is UnRisk Quant in a license form including free updates and application support by our key developers.

We'll also provide know how packages by the UnRisk Academy heads.

Savor or save?

We're too small to change the big decisions, but we decided to help quants suffering less from constraints…We're lucky to have only few constraints when making our decisions…do the important or the profitable is not the same.

This is what we've decided:
  • Help the most busy people in quant finance - quants
  • Move fast when making decisions - listen less to focus groups, but quants
  • Help quants making their deadlines - its developed for maximum quant productivity
  • Trade up on trust - by telling the truth, full transparency, unprecedented quick response...
With UnRisk Quant you program in a high level Financial Language implemented in high performance valuation and xVA engines, scenario simulators, a VaR Universe…

Mail now to Michael Aichinger…the response may surprise you...

What I think About Machines That Can Think

What Do You Think About Machines That Think? is the 2015 Edge question. (Maybe) in reply to Stephen Hawkins' warning: "The development of full AI could spell the end of the human race".

The first contributors and responses can be found here.

The following view is shaped by 15 years of practical project experience with AI tools:

I think, the real questions behind are

"…..About Machines That Think Like Us?"

"Is building a thinking machine possible?" and if yes "how far from thinking are machines we can build in the near future?".

"Should thinking machines be built at all?"

I have no doubt that thinking machines are possible (when a combinations of chemicals can do it, why not silicon...?)

When?

AI - the future that never happened by now.

The idea has a long tradition: computerized systems are people and there is a strong relation between algorithms and life,,,

First…the top down expert system thinking of AI..."died".

Then…"Artificial Life" promised to create intelligent creatures by genetic programming…it works well fur less ambitious objectives.

Now…because we have neurons intelligent machines need to have them too…our brain has an enormous capacity…to make AIs we only need to combine massive inherent parallelism, massive data management and deep neural nets…?

However, our objects of desire - universal machines that think like us - are, IMO, far away.

Summarizing, I'm in the camp of people who believe that machines that think can complement us doing things better for a better society. But it depends on what they are supposed to be thinking about.

What I fear: that we try to teach people to behave like machines - if we think like machines, it will be easier for machines to think like us?!

IMO, AI is a set of techniques of mathematics, engineering, science…not a post human species. Not only in finance, economy…behavior must be quantified and knowledge made computational...

The Age of Unicorns - But not in Austria

"The billion-dollar tech startup was supposed to be the stuff of myth. Now they seem to be … everywhere."

I read this sentence in an article about startups and their valuation in an article in Fortune . The article is about start ups worth one billion or more and they state, that today the technology industry is crowded with billion-dollar startups. Reason is the availability of venture capital. Many of these startups will vanish in a short period of time. But some of them will be the next Google, Amazons and Facebooks driving the technology further and doing a lot of fancy things.

The same day I have read an article in the Austrian newspaper Der Standard. The article claimed, that  Austria, although a rich country, is only on the 20th place in Europe when it comes to financing using risk capital. I ask myself how we can close the gap for high level technologies if neither the public nor the private sector is willing to take some risks in financing innovation. It is typical for Austrians to abhor risk, but this fact, combined with a year long deadlock in Austrian politics is driving us  downwards the innovation spiral.