It's Now A Year...

that I've given my uni software plus in younger hands - Michael Aichinger - and launched my new business.

A little review:

Exploit the wu-wei paradox

I am still passionate about transforming future technologies into margins. I planned to work less, and do more - hoping the wu-wei principle will help me: let the complex stream work for me.

When you start your own business, it's just you and your ideas. But I had already featured partners…continuing work with them made it easy.

Building technology stacks first

Technology trends influenced my entire business life. I adopted technologies in their infancies, including computer graphics, symbolic computation, machine learning…always testing new platforms like the massive parallel computing muscles…

For over 25 years now I deal with  Wolfram Language - the language to program everything. First in client-, then in partner- (UnRisk…) now in advisory-projects.

I'm wondering that it's still not a big climber in ratings of programming languages. To me it's confirming that "great" doesn't always mean "popular"

From its many advantages I pick two: the internal value of building technology stacks easily…and the external value of its declarative nature that let innovators build functions, tasks and workflows like "stories".

What always struck me when developing technology businesses...and still does:

The fear of regret

When I made my first tumbling steps into computing, in the mid 70s, nearly everybody agreed: "No one ever has got fired for buying IBM".

A wonderful example of understanding "defensive decision making". This is not "in search of the optimal risk" - it is loss aversion. Choose those, being good in not being bad?!

To remove this kind of fear is one of the big challenges in innovation marketing. Innovators need to know that at first they make things for somebody, not everybody.

Yes, loss aversion can make sales figures disappointing:

The eager sellers and stony buyers principle

I've written about this principles in past posts...

It tells us that sellers overrate their innovation's benefit threefold and that buyers overrate threefold what they have…the mismatch is one to nine…

We should buy that green electric car but their refueling isn't that easy, right?

What to do? Make innovations thats gains outweigh the losses by far? 10times improvements are rare.

The advice is to help actors managing the behavior changes required by the product changes…I've developed rules that help reducing the mismatch.

Rational markets?

Markets seem to be adaptive, but do we really have an idea why business works as it does?

We know from financial markets that the market efficiency hypothesis doesn't hold. Market behavior is, partially, predictable on the long run.

Rational buyers would ask for ugly cars, right?

Innovators that understand that some behavior is predictably irrational will have a competitive advantage…when, say, finding the right position on the value / cost map.

To understand markets, we've big data?

Big data is a big joke

The major concern is not about the access to such data and how to slice and dice them, but the nature of the problem. It is all about high-dimension-low-number-of-samples and that in those sets large deviations are more attributable to noise than to insight…as well, as the fact that data need to be "uncooked".

Life in the market data salt mines is often too hard...

The trust vs attention dance

Both are scarce elements in our businesses. Trust is fragile and attention is limited. If clients want constant attention to trust us, we might become a problem.

And in fact we find trusted brands that are not at top of an attention list. A misunderstood brand promise can kill businesses.

There are tactics to avoid falling in his kind of traps. One, I always recommended using, might be seen as arrogant: "No, this innovation is not for you!"

Did I stand still...

just exploiting my experiences dealing with innovation for 40 years?

I've developed The Innovation Mesh that adds emotional factors...when assessing an innovation.

More general, I've worked on principles that help optimizing market risk…atop my understanding of the essence of financial risk management…(value at) risk of the jungle.

Innovation means new. New means uncertain…
Antifragile systems are immune to prediction errors. Antifragility gains from volatilities and uncertainty…ways to the antifragile include  stressors, redundancy, tinkering…and optionality.

Real options help "buying" antifragility. I've put significant efforts in segmenting markets...and intensified partnerships with real options valuation tool makers and application experts.

It will be an exciting next year.

Working less and do more I'll need to sharpen the methodologies and tools and rely even more on featured partnerships.

A Big Controlling Idea

Here I wrote what a thrilling innovation must have (for UnRisk CM). It assumes that the innovations manages the obligatory rules, conventions, tasks well and apply innovative methodologies and technologies. Conventions often lead to obligatory tasks. Think of risk management in UnRisk…combine valuation and data management, multi-model and method approaches…lead to tasks like instrument construction, market data import, model calibration, model validation…

Only if this works well the system can manage portfolio across scenario analytics, VaR treatment, tail risk analytics…

A Big Controlling Idea

Today, I want to emphasize on the Big Controlling Idea. The incident is a meeting last week that opened an exciting opportunity. Two partners decided to integrate their key technologies to make something new for the financial market (too early to disclose details). The technologies are working very well and have been sold successfully.

What the hell is big controlling idea? Is it just the combination of the two…?

The controlling ideas describe how the innovation meets the desires, objectives, (quantitative) requirements…From the controlling ideas we derive our key messages. If we understand the general what-and-how we can put the big takeaway into a few words.

The controlling idea

  • cannot be longer than a one-sentence statement
  • it must describe the value of the whole innovation 
  • it must be specific enough to explain how the value is made possible.

Careful choosing the most advanced mathematics, mapping every practical detail…we built automated risk analytics solutions that are development systems in one

The controlling idea is big when the value is high in a high confidence interval…

An insightful risk management process is indispensable for a financial market participant. It has many enemies…some hide in the problem (market risk) the others in the operations…"Wealth or death" is the possible outcome.

A system supporting must run scheduled tasks and perform individual valuations, for faster time-to-insight it must run blazingly fast valuation and risk engines, have all practical details implemented and avoid every risk that is not problem-based…and difficult enough it shall be programmable atop...

About Trees Again

Whenever you build a quant innovation, I recommend to organize objects, models and methods orthogonally. Why? The right selection of  models and methods is vital, but not obvious.

Example: (binomial) trees are still used valuing "options". This can be a good or bad decision.

Trees may destroy delta-hedging

In To Tree or Not To Tree, Andreas Binder, CEO, of UnRisk has pointed out that binomial trees are good, because they are  insightful, but they have a really bad computational behavior. So bad, that they may destroy the heart of the option theory…delta hedging.

Are Trees good for real options?

Real options are referring to project size, life and timing, and operation. Those determine the option characteristics.

Real options are usually distinguished from financial options in that they, and their underlying, are typically not tradable. So, most real options have a value but not a price. At the other hand option holders can influence the underlying project.

Whilst financial options can help optimizing the risk of a portfolio, real options can help maximizing the value of a project by creating value through flexibility.

With this objective, insight is more important than computational quality.

To Tree!

You can model real options by PDEs, apply forward techniques with (Least Square) Monte Carlo methods, but, most of the practitioners use binomial trees as they allow for implementing rules (up and down probabilities under conditions, ..) at each node.

Real options help finding competitive game rules

One can see investment projects as cash conversion cycle - with many decision points. Real option analytics can be a kind of sparring partner, telling what if...

The return is characterized by the investment, time and the distribution of the cash flows. You need to know the cash drivers, volatilities, formulate possible actions (their options) and know their influences on the cash flows.

If your project is innovative you don't have a history. So, you might need to simulate the project to get insight into quantitative aspects of possible decisions. Trees are of good nature for this purpose.

You can buy antifragility.  In finance, antifragility needs fragility, because hedgers need speculators as counter party, who accept the fragile side of a contract. "Correct" and transparent pricing, valuation and risk analytics is vital to make the market a "fair" play.

Real options usually pertain to tangible assets such as capital equipment. They're not a derivative. They're actual options. Walking through trees of decisions under uncertainty by simulation help finding competitive game rules you want to establish.


the real economy could learn from the innovations of the financial systems. They could maybe adopt the "fiction" that the option and the underlying are tradable and can be replicated by hedge portfolios.

But this is another story. In such a regime. trees would be devalued as firewood again…

This is a compression of this post at UnRisk Insight


Risk is two-sided…it can be placed at a map of opportunities vs danger. And the maps are different if the object of desire is fun, insight, return…

Not every "risk" is a risk

The two sided nature make it optimizable. Although, a quantitative optimization is difficult. It's a pity that not so much people know what risk is. Market risk is a risk but operational risk is a danger (wrong models, methods, calculations will usually not suggest a good decision). I've pointed this out here.

Remember the

Five paradigms of market risk management

Duality - in your analysis, be aware that you have two parts: the known and the unexpected
Boundaries - try to find boundaries that distinguish situations where markets behave "normal" from the rest. Boundaries based on cost of risk should work.
Optimization - Risk optimization only works inside the boundaries.
Evolution - business is often co-evolution. Not surprisingly genetic programming is a general way to optimize
Game Theory - a mathematical study of uncertainty caused by actions of others

Market risk optimization is the key instrument when developing a business.

Risk is not uncertainty

You can bet on five possible outcomes of of a dice throw. It's still uncertain, but there's only low risk. A large portfolio of possible outcomes is very different from, a large risk.

Innovators, present something new…consequently they don't have much feed-back.  Apple didn't know what people will say about the iPod…before they rolled it tout.

Innovators live in uncertainty for a while, but if they've built a technology stack their transformative innovation's placement will not be very risky...and real option valuation tools will help them to plan under uncertainty…


Market risk is two sided…but, as Daniel Kahneman, has demonstrated people show a tendency to strongly prefer to avoid losses to acquiring gains. A win doesn't feel as good, as a loss feels bad…five great assessments do not balance a bad one…?

This leads to risk aversion…and prevents market participants from finding the optimum.

There are many things that can be placed at a map of positive vs negative outcomes and consequently optimized (although. I name price as position at the value / cost (or external vs internal value) map…is there a socio-economic optimal pricing? This is even more difficult, when serving two-sided markets…actors and, say, system integrators…provide a process automation system to steel makers and steel plant engineers and contractors…

We've managed the problem for UnRisk by shipping solutions and development systems in one…under the same pricing and licensing scheme.

p.s. but there are objects of desire where you need to pick two of three things: "performance" (of systems) is three-sided if yo want high standards - high production - flexibility…you need to pick two. 

Don't Be Afraid To Be Rejected

Maybe, my mouth is against my money…but when I offer to walk your innovation through The Innovation Mesh…I have not in mind to prevent you from acting, suggesting you shall fear that your innovation will be rejected.


Act swift (but not blind). Acting shows up risk and brings responsibility and you must choose…but most important it creates opportunities. It's difficult to recognize, but uncertainty is good.


Profesional innovators, unlike amateurs, don't fear failure. They don't walk away when success doesn't occur. Innovators do things the first time…each time they're unprepared for the reaction to it. "UnFear" means don't dare to try.

It's been done before?

No one's asking innovators to be the originator of everything. We're asking them, to change behavior, fix systems that behave bad…Even rewriting can be innovative. The done-before may not be "real".

It's too early?

When is the timing right? Never…if you fear to be rejected. And it's always too early…innovations are new and nobody knows how to use them. After the (big) computer was introduced it was predicted that a hand full will be needed world-wide…

Do things the first time may be the last time?

This was…when information and tools were so expensive. Now, with affordable tools, better communication channels, skill sharing…it has never been so easy to innovate…but entrepreneurship is in decline? Does this mean innovation went industrial?

What will the market say?

We call this the external value of innovations and we like to listen to focus groups (what's required). It's what we do to influence what the market will tell us…success (not criticism or rejection). But there's this other value, the internal, the one that enables antifragility…by tinkering and optionality (among other ways)...the most important value, IMO. 

By sharing my ideas (methodologies), I hope to help professional innovators leverage their businesses…My goal is to make the work practical and compelling…and accelerate time to release.

This post has been inspired by Seth Godin's great magazine style book It's Your Turn

End, Begin, Build

Marketers shall ask themselves constantly what to end, what to begin and what to continue building.

When thinking about this myself, I do this by observing the internal and external factors that both seem to develop in cycles. Both are rather fluctuations than cycles…the internal movements are quite often like pulses…expressing enthusiasm, depression or stability…

Business Cycles

The explanation of fluctuations in aggregate economic activity is one of the major concerns of macroeconomics. There are a number of heterodox economic theories of business cycles, associated with particular schools or theories…according to Real Business Cycle theory, business cycles are even real and not failure of markets…they are seen as efficient responses to exogenous changes…

Theories are passionately "discussed" and an outsider, like myself, may get the opinion the battles are influenced by ideologic positions…but heavy disagreements go beyond: pro and con equilibrium theories…neo-classical economy vs complexity economy…and who are the better economists, macro economists or the physicists?…I wrote about this in…Fit the Battle  of Econo. Econo. Econo

Market Fluctuations

My simple observation over many years…there are market behavior fluctuations that do not go in pairs with economic fluctuations. Especially in innovation marketing.

Periods where markets behave enthusiastic, stable or depressive may be counter intuitive to the economic development of this period.

i've no theory about this, but it reminds me on Innovation - Revolution of Heroes or Heroes of Revolution. A coincidence of talented people at a time or talented people to join a revolution...share their bets work. Yes, I believe in the latter…technology revolutions make heroes.

"Bebopers" wanted to counter the  swing style with non-dancable music by fast tempo, instrumental virtuosity and improvisation…later, "Freejazzers" wanted to free music from the controlling (limiting) ideas and conventions of bebop…

Uncertainty and Optionality

It's about (erratic) depression-enthusiasm-stability fluctuations…we should understand them perfectly when deciding what to end, start and continue?

But there will be still uncertainty…if innovation marketers want to fully understand the financial consequences of the decisions…real option valuation (across scenarios) will help quantifying them and find the game-changing rules they want to set in their market segments in a certain period…

Good innovation marketers do not decide on average expectations.

What A Thrilling Innovation Must Have

After the Big Picture post, I've walked another innovation through The Innovation Mesh…Opexar from Advexo…triggered by a workshop with live presentations by the makers (and their partner here: my friend Hermann Fuchs).

It's a compelling innovation, a quantitative tool-enhanced methodology, helping make decisions under uncertainty, leveraging business and financial planning...I've continued reading Shawn Coyne's blog…and was inspired to extract some must-haves after having classified the global type, and done the detailed diagnosis…

for UnRisk CM

A Big Idea

telling the actors what to expect. Explorative Investment and Risk Intelligence 

Key Actor / Danger / Decision Support

Risk manger / excessive losses, violation of the regulatory framework / VaR and tail risk analytics, stress tests, risk data evaluation

Objective / Promise

Help optimizing market risk / Transparency, explanation and exploration to help avoiding technology risk

Path / Methodology

Valuation and data management, portfolio across scenario simulation, risk data aggregation / Multi model - multi method approaches

Side Benefits

Detect toxic instruments and structures

An Clear Statement of the Controlling Idea

We've spent 120 years developing, careful choosing the mathematical methods, mapping every practical detail…building automated  solutions that are development systems in one

Ethic / Logic / Emotion

Apply models to expose (not hide) risk / validate models, check data plausibility… / use simulation to explore individual game rules for risk management 

Ironic Payoff

Arming David - systems that seem to be devoted to the large market participants...made affordable and manageable

For me it's just a summarizing check that does not substitute the detail diagnosis…but it may motivate for another iteration...

Not Fooled By Randomness - Videos

can be found here. Edit: this seems to have been removed, Sorry.

They really have a beginning hook, describe progressive conflicts and the resolution (the evidence and the bet). Yes, Paul's a great researcher, quant, teacher, storyteller…but most important storydoer.


There's no such thing as "raw" data.

About 25 years ago, I sought a benchmark project for our machine learning methods…and luckily we were asked by the quality assurance department of a continuous casting plant unit of a steel maker to analyze the dependencies of surface cracks at the slabs on a vast variety of process parameters (recipes, temperatures, speeds, cooling…). Fortunately they've collected a large sample set (across about 50 parameters) for supervised learning. To avoid "knowledge bias" they named the parameters just p_i (not telling us the meaning).

Data  are cooked 

Using various techniques including decision tree methods we found important dependencies that most became understandable after discovering the parameter meaning…Carbon, casting speed…some contributed just as pink noise..

One, p_28 showed a dominant influence…drumroll…the date?! Discussing this we found that they did periodically change the whole casting bow (secondary cooling zone)…and clearly this influences geometrical properties, like the alignment between the mold (primary cooling) and the bow and the bow and the straightening section…

Dates are perfectly cooked data (they contain, but hide, all interesting informations)…

Its like in the kitchen: chefs do not only use "raw" ingredients, but semi-finished things like stocks, sauces…But even the raw ingredients are result of natural processes that influence the final product...the dish.

Again…working in the data salt mines is difficult

To understand "raw" data you need to look deeper and need insight that you at the other hand want to extract from data.

I've worked with machine learning for 25 years now…and this made me quite modest with my objects of desire. To extract knowledge from data needs a lot of data uncooking…and this means modeling.

This is one reason why I'm advocating intelligent mixes of modeling and machine learning. Remember, machine learning does hardly generalize…in combination with modeling you get deep learning…by adaptive re-calibration.

Related to this I wrote are you a consequentialist?

Not Fooled By Randomness

Paul Wilmott, the renowned researcher, quant, quantitative finance has successfully forecast  the results of the UK General Election 2015.

I'm looking forward to read the whole paper…I'm sure it will fully explain how to overcome the traps of traditional predictive modeling…lacking the right treatment of randomness. Comparisons are made between elections and derivative valuation…about stochastic (mathematical) modeling complexity, the model calibration traps…

It's quant innovation. I'm senior member at that serves the quant finance community and I enjoyed meeting Paul in person several times. He influenced my view of quant innovation and inspired me to think beyond what it does…(we) innovators must recognize that our work has enormous effects on our life and time many of them beyond our comprehension. The world doesn't follow our equations, but our innovation can explain, inspire, forecast, control…

The successful forecast of the election results is thrilling…it disrupted beliefs, use different points of view, changes controlling ideas, methodology…validating approaches from another field.

It's about modeling under uncertainty.

Edit: the videos on Paul's talk are here

Be a Game Changer

I took a few days off and went to Friuli…in concrete the Collio wine region (as many years before). To do nothing else than hiking, reading, wine and dine…How I like the wine region you can read here.  In the p.s. I've mentioned Ronchi Ro…and convinced of their great wines, I stayed there (the first time) during my whole visit.

They offer 5 rooms and 3 wines...They've only about 2.5 ha vineyards and cultivate them for individual  and high quality without compromises (oh yes, they're terroirists). They offer spacious rooms, a breakfast with a selection of local ingredients…their meadow and shadow (under the linden) is yours...

They do not strive for getting picked, they choose themselves…They do things that matter for those, who care...and I've no doubt, they grow healthy.

It's innovation…and it's a great metaphor for innovator's work. It's a better way to move forward. It makes change happen. If you choose yourself, instead of trying to get picked, you create an environment where you can grow with confidence.

Make "wines, rooms, environments…" not profits (would Steve Jobs have said).

Is this the best we can do?

There's this trap of striving for the perfect competence...leading to industrial work…inevitably, you forget to disrupt yourself and you miss possibilities.

Work to get picked, is reactive...if you choose yourself, you set the pace.

A game changer, changes the underlying systems that are causing major problems of our lives and time…in the small or in the large. It's hard work, because a game changer needs to overcome shock, denial, even depression, before the change becomes accepted and finally integrated.

Be A Terroirist

I borrow from wine making: terroir is how a particular vineyard's climate, soil, terrain…affects the taste of a wine. In my definition a terroirist does not cover this influence by artificial ingredients like designed yeast or industrialized cellar techniques (temperature control, reverse osmosis, wood chips…). Terroirists like spontaneous fermentation.

You can taste it. Does it taste like everywhere (or nowhere)? Or, like a "clear mountain spring water with a subtle grape and terroir replication"?

We can extend the idea to our work…the things we are creating and building.

Good innovation is not only about balancing product and behavior changes…its purpose, functions, tasks and flows, the front-ends, the methodologies and technologies, interaction patterns…the client services, the education, the business game rules…shall be a package that's difficult to copy.

The pressure to fit in, to industrialize…is huge…but it removes the essence of our innovations.

Your clients can taste the difference…and feel: "it's not for everybody…it's for us".

Why Your Great Innovations May Not Sell

You're bursting of ideas and apply clever processes and tools to turn them into innovations swiftly. But your sales figures are so disappointing?

The Eager Sellers Stony Buyers Principle tells us that sellers overrate their innovation's benefit threefold and the buyers overrate threefold what they have…the mismatch is one to nine


Loss aversion

Clients view products they own as part of their foundation..and they assess innovations in gains and losses related to what they have…Remember, what Nobel Prize winner Daniel Kahneman told us: we are loss averse.

We should buy that green electric car but their refueling isn't that easy, right?

What to do? Make innovations thats gains outweigh the losses by far? 10times improvements are rare.

Balance product and behavior changes

Innovators understand the internal approaches, conventions, methods an tools very well…but it's much more important to understand its relation to the outside world...the objects of desire, progressive problems, conflicts…resolutions.

Innovators innovate through product changes but they demand behavior change

To get actors hooked to your innovation make things that matter, but don't forget to
  • support routine
  • identify underlying emotions
  • let them add things that matter
  • strengthen their role
  • educate regular users
"Long Lasting Hits" balance product and behavior changes and LLH innovators help actors to manage the change.

Overcoming the Eager Sellers Stony Buyers trap, innovators need to act as analysts, newists, communicators, connectors and risk managers.  

Will Someone Else Capitalize on Your Brilliance?

This is the first of a series of short posts concerning a few experiences about traps when innovating. I've already posted a few, starting with my own failures.

A good innovator is able to imagine a product or service that clients need before they know that they need it. This implies uncertainties, because you don't have a history to rely on. It's all new.

But let us assume that the product is developed, it works and will sell…you have identified the market segment for leadership, there are no known product deficiencies, the pricing and licensing seems right, you know the position in the competitive arena, you have the right marketing resources, the sales force is fit…you even know your dream client and dream partners…

Look into the numbers

But don't forget looking into the numbers…the financing, the expected returns…to manage them you need partners…banks may work in a new regulatory scheme, want to pass on additional costs to you…in short, keep your books clean, take care what term sheets you sign…and most important know your options…or someone else may capitalize on your brilliance.