Saturday 28 September 2013

Crowdrating Systems of Banks Using Stockmarkets

Crowdrating Systems of Banks Using Stockmarkets: Assetdyne , the London-based company which has introduced for the first time the concepts of complexity and resilience to stock and stoc...

Crowdrating Systems of Banks Using Stockmarkets


Assetdyne, the London-based company which has introduced for the first time the concepts of complexity and resilience to stock and stock portfolio analysis and design, has analyzed recently systems of banks, namely those of Brazil, Singapore, Israel, as well top European banks. The way this is done is to assemble portfolios of the said banks and to treat them as system (which, in reality, they are!). The results are provided with comments.

Brazil



Singapore



Australia



Israel


 European banks


Similar analysis may be run free of charge at Assetdyne's website. As the analyses are performed on daily Close value of the corresponding stocks, the above indicated values of complexity and resilience may also change on a daily basis.


www.assetdyne.com



Monday 23 September 2013

Ontonix S.r.l.: Is Risk Management a Source of Risk

Ontonix S.r.l.: Is Risk Management a Source of Risk: The deployment of risk management within a business can be a source of false assurance. Over recent years, businesses have becom...

Is Risk Management a Source of Risk





The deployment of risk management within a business can be a source of false assurance.

Over recent years, businesses have become more and more reliant on increasingly complex modelling processes to predict outcomes, to the point that in many cases, businesses have lost sight of what risk management is all about - and at the same time, risk management lost sight of what the business was all about. Increasingly, I have seen risk management services being deployed in large institutions by the 'big four' consultancy firms, and to keep their huge costs down, they end up with the newly qualified consultants - mid twenties, bright young things, but I'm sorry, they often don't have the faintest idea what your business does. They have insufficient real world experience to permit effective dissemination of risk knowledge.

I worked with one lovely young lady recently in a banking environment. Very intelligent - but she did not have the first clue of what the business was about. She made assumptions, and those assumptions lead the business down some long, dark alleys.

If you have risk function, however, that fully understands the business model, the deployment of its operational strategy, the sector the business operates in and the macro-economic and socio-political environment in which it operates, then they will be able to provide risk information that is relevant to the business, and can be understood by the business.

My hope going into this recession was that businesses would learn from this period in time, and take a more realistic, holistic view of the world. Worryingly, what I see is "more of the same".

I see financial institutions that have - on the face of it - bolstered their risk functions, but in doing so have allowed them to become ever more 'siloed' and fractured in their approach. This can only lead to disaster, in my view. The left hand will not know what the right hand is doing - no one owns anything, no one is responsible, no one is accountable.

So, I think the deployment of risk management has been a source of risk, but I don't think the dramas are over yet. There is a second wave of failure yet to hit, unless businesses can swallow the pill and take the right approach.

Posted by Andrew Bird, Managing Director at Nile Blue and freelance business consultant.




Saturday 21 September 2013

Ontonix S.r.l.: Measuring the magnitdue of a crisis

Ontonix S.r.l.: Measuring the magnitdue of a crisis: How can you measure the magnitude of an economic crisis? By the number of lost jobs, foreclosures, GDP drop, number of defaulti...

Measuring the magnitdue of a crisis




How can you measure the magnitude of an economic crisis? By the number of lost jobs, foreclosures, GDP drop, number of defaulting banks and corporations, deflation? Or by the drop in stock-market indices? All these parameters do indeed reflect the severity of a crisis. But how about a single holistic index which takes them all into account? This index is complexity and in particular its variation. Let us examine, for example, the US sub-prime crisis. The complexity of the US housing market in the period 2004-2009 is illustrated in the above plot. A total of fifty market-specific parameters have been used to perform the analysis in addition to fifteen macroeconomic indicators such as the ones mentioned above. The "bursting bubble" manifests itself via a complexity increase from a value of approximately 19 to around 32. With respect to the initial value this means an increase of 40%. The arrow in the above plot indicates this jump in complexity and this number represents a systemic measure of how profound the US housing market crisis is.

In summary, the magnitude of a crisis can be measured as follows:

M = | C_i - C_f | / C_i

where C_i is the value of complexity before the crisis and C_f the value during crisis. The intensity of a crisis can be measured as the rate of change of complexity

Serious science starts when you begin to measure.




Friday 20 September 2013

Complexity: The Fifth Dimension





When complexity is defined as a function of structure, entropy and granularity, examining its dynamics reveals its fantastic depth and phenomenal properties. The process of complexity computation materializes in a particular mapping of a state vector onto a scalar. What is surprising is how a simple process can enshroud such an astonishingly rich spectrum of features and characteristics. Complexity does not possess the properties of an energy and yet it expresses the "life potential" of a system in terms of the modes of behaviour it can deploy. In a sense, complexity, the way we measure it, reflects the amount of fitness of an autonomous dynamical system that operates in a given Fitness Landscape. This statement by no means implies that higher complexity leads to higher fitness. In fact, our research shows the existence of an upper bound on the complexity a given system may attain. We call this limit critical complexity. We know that in proximity of this limit, the system in question becomes delicate and fragile and operation close to this limit is dangerous. There surely exists a "good value" of complexity - which corresponds to a fraction, ß, of the upper limit - that maximizes fitness:

Cmax fitness = ß Ccritical

We don't know what the value of ß is for a given system and we are not sure on how it may be computed. However, we think that the fittest systems are able to operate around a good value of ß. Fit systems can potentially deploy a sufficient  variety of modes of behaviour so as to respond better to a non-stationary environment (ecosystem). The dimension of the modal space of a system ultimately equates to its degree of adaptability. Close to critical complexity the number of modes, as we observe, increases rapidly but, at the same time, the probability of spontaneous (and unwanted) mode transitions also increases quickly. This means the system can suddenly undertake unexpected and potentially self-compromising actions (just like adolescent humans).