A Resilience Test of US and EU banks. A Systems Perspective.

There is much discussion today about systemic risks. In particular, the notion of “systemic” banks or corporations has become popular, which indicates entities that have the capability of causing considerable damage to the economy in case of default. Such entities are often termed as “Too Big To Fail” and their footprint on the national and global economies is, clearly, substantial. It is therefore of great interest to monitor closely systemic banks and corporations and to keep an eye on their resilience.

Resilience is a new quantity in finance. It represents the capacity of a business to withstand shocks and extreme events. Because our global economy is characterized by fluctuations, turbulence and is highly interconnected, business resilience is surely a good-to-have property.

Assetdyne has developed a tool which measures the resilience of a corporation based on the evolution of its stock price. It is therefore a simplified approach which, evidently, is based on the assumption that a healthy company will have an equally “healthy” evolution of its stock price. The huge advantage of this approach is that analysis can be performed on a daily basis. This is of immense value. Conventional ratings are published on a yearly basis when a Consolidated Balance Sheet is issued. Even quarterly financials are unable to capture the intricacy and speed of our complex economy. Stock markets, on the other hand, provide a real-time reflection of the situation.

We have investigated the resilience of the systems (portfolios) of the largest US and EU banks based on the evolution of their respective stock prices. The so-called Complexity Maps, which illustrate the interconnections between the various entities, are illustrated below and have been synthesized on March 7-th, 2014.

US banks Resilience = 69,9%

UE banks Resilience = 81,7%

The size of each node in the Complexity Maps corresponds to the footprint (weight) of each bank on the system. Large nodes, therefore, point to banks which, at the time of the analysis, have the largest impact on the systems in terms of its resilience and stability. Complexity Maps are interactive and may be navigated by clicking on the following links:

US banks:
http://www.assetdynex.com/?function=ReadObf&obf=rab_rating_spreadsheet_6lVIpF_m&id=19

EU banks:
http://www.assetdynex.com/?function=ReadObf&obf=rab_rating_spreadsheet_x5idlL_m&id=88

As far the resilience, complexity and Resilience Rating of each bank, those of the largest banks are indicated in the table below.

Bank	Resilience (%)	Complexity	Resilience Rating
Bank of America	79,59	9,96
JP Morgan	77,73	42,83
Citigroup	93,64	5,41
Wells Fargo	76,37	14,18
Morgan Stanley	87,82	11,65
Goldman Sachs	77,07	25,59

Deutsche Bank	67,52	11,41
BNP Paribas	90,65	19,17
Barclays	86,81	24,76
ING	84,46	33,01
Unicredit	81,36	37,59
BBVA	81,89	52,98
Credit Suisse	89,54	7,83

It is clear how the EU banks are considerably more resilient than the US banks. While EU banks, with the exception of Deutsche Bank, enjoy a Resilience Rating of 4 or more stars, most US banks have a 3-star rating. This is in accordance with the fact that the US system of banks has a Resilience of 69.9% (a 3-star rating) while that of EU banks boasts a Resilience of 81.7% and a 4-star rating. Basically what this means is that at the time of the analysis the EU bank system appears better prepared to absorb shocks than the US one. Clearly, it is important to take into account that since our economy is extremely fast and turbulent, the situation may quickly change. For this reason such analyses should be performed with a high frequency (e.g. montlhy).

The above analysis is interesting to those who study the dynamics of systems of banks or corporations but can also be immensely useful to investors. Complexity reflects the intricacy of stock dynamics – high values point to potentially chaotic behavior, hence difficult to predict. Resilience, on the other hand, reflects the “stability” of stock dynamics – values close to 0% point to extreme volatility while values in the proximity of 100% correspond to more stable situations.

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