They'll help optimizing market risk. Market risk management is the management of returns of positions arising from changes of market behaviors…under risk consideration. This is not completely independent of the approach and realization of the innovation.
Insight 1 - Understand Innovation Risk
Provocatively speaking, a more-complete but more-complicated innovation may carry greater risk than a cruder one. Risk becomes a danger, if the actors using the innovation are not qualified for the job.
Talking about quant innovation, I recommend the following rules
- Recognize that models are needed
- Acknowledge their limitations
- Expect the unexpected
- Understand use and user
- Check the infrastructure (source of operational risk)
Models can be formal or intuitive, but in quant innovations, computational knowledge help transforming objects is indispensable. Users want to check possible transformations in scenarios, what-if analysis…
If the models for the core processes are already intrinsically flawed, too complex, not robust…their use models in interplay are consequently wrong. But if core models are right, the use models can still be wrong because of new complexity, wrong operation or interpretation.
Insight 2 - Understand the UTOPE Risk
Unfortunate cosT Of Pattern rEcognition (from the cover story of Wilmott Magazine, Jul.12). Apophenia is the technical name for a problem with human nature: seeing meaningful patterns, when they do not exist.
But this is not only restricted to human nature…it's systemic.
There's an intrinsic trap in all inverse problems…it's much more difficult to extract insight, knowledge, models…from data than the other way orotund, data from...models. Solving inverse problems of a mathematical nature mathematically, you need tricks, like regularizytion...
Apophenia is not uncommon in marketing. It's said, innovation marketers of tomorrow need to have experience in understanding big data. But, because the nature of innovation is dealing with the "new", big data have usually high dimensions but a comparatively low number of samples and in such sets large deviations are more attribute to noise than to information.
If you just naively apply statistical methods you will most probably find significant correlations that are spurious.
The disadvantage of big data: the more variables the more spurious dependencies...the possible misinterpretation grows nonlinear with respect to the dimension.
Big data may become a big joke.
So, ill-posedness of inverse problems may become a danger internally and externally.
Insight 3 - Understand the Tightly-Coupled-Complex-System Risk
A complex system can have untended consequences and tightly coupled means there is not enough time to react to them. What is true for the process is true for the system controlling it.
In a tightly coupled process there's no plan for possibilities and options. A tightly coupled complex system, usually result of such a process, does not increase the number of choices and the emergence of an unexpected event can become horrible.
So, diversify and decentralize your system, make it agile by increasing its adaptability and optionality. Make intelligent independent system components that are accurate and robust, but flexible. Let them co-exist and co-evolute.
This may raise the eyebrows of the system centralizers, integrators, top-downers … but it is correct.
There is no such horrible operating risk than a tightly coupled organization, serving tightly coupled complex processes by tightly coupled complex systems.
Insight 4 - Play the 80% Low Risk Game
Optimize risk in the regimes where you know the conditions with a tendency to lower risk in, say, 80 percent of the cases (a safe game with very low probability to ruin the the solution, the process…the investment, the business). You can then play a higher risk game.
This also refers to Five Paradigms of Market Risk Management.
In financial business planning, this would be a kind of playing the cash cow game.
Insight 5 - Choose the Right Kind of Luck
There are unexpected events that can help you a lot or harm you a little and others that can help you a little or harm you a lot. Distinguish between risk with a lower and higher upside. This kind of asymmetry is usually not easy to see...
If you price your innovation at 100, but your client had paid 102, you've lost 2, if the client was only willing to pay 98, you've lost 98…
Apophenia is not uncommon in marketing. It's said, innovation marketers of tomorrow need to have experience in understanding big data. But, because the nature of innovation is dealing with the "new", big data have usually high dimensions but a comparatively low number of samples and in such sets large deviations are more attribute to noise than to information.
If you just naively apply statistical methods you will most probably find significant correlations that are spurious.
The disadvantage of big data: the more variables the more spurious dependencies...the possible misinterpretation grows nonlinear with respect to the dimension.
Big data may become a big joke.
So, ill-posedness of inverse problems may become a danger internally and externally.
Insight 3 - Understand the Tightly-Coupled-Complex-System Risk
A complex system can have untended consequences and tightly coupled means there is not enough time to react to them. What is true for the process is true for the system controlling it.
In a tightly coupled process there's no plan for possibilities and options. A tightly coupled complex system, usually result of such a process, does not increase the number of choices and the emergence of an unexpected event can become horrible.
So, diversify and decentralize your system, make it agile by increasing its adaptability and optionality. Make intelligent independent system components that are accurate and robust, but flexible. Let them co-exist and co-evolute.
This may raise the eyebrows of the system centralizers, integrators, top-downers … but it is correct.
There is no such horrible operating risk than a tightly coupled organization, serving tightly coupled complex processes by tightly coupled complex systems.
Insight 4 - Play the 80% Low Risk Game
Optimize risk in the regimes where you know the conditions with a tendency to lower risk in, say, 80 percent of the cases (a safe game with very low probability to ruin the the solution, the process…the investment, the business). You can then play a higher risk game.
This also refers to Five Paradigms of Market Risk Management.
In financial business planning, this would be a kind of playing the cash cow game.
Insight 5 - Choose the Right Kind of Luck
There are unexpected events that can help you a lot or harm you a little and others that can help you a little or harm you a lot. Distinguish between risk with a lower and higher upside. This kind of asymmetry is usually not easy to see...
If you price your innovation at 100, but your client had paid 102, you've lost 2, if the client was only willing to pay 98, you've lost 98…
Not surprisingly the innovation type influences its risk profile and consequently marketing success factors.
