In a world dominated by turbulence and interdependency, fragility and complexity are the main new factors which are impacting the global economy and driving financial performance. While the unprecedented challenges affecting the global economy are a source of both opportunities and threats, traditional analytics technology is insufficient when it comes to capturing new drivers of value creation. The ´New Normal´ of a more uncertain world requires a different kind of approach and a new set of analytical tools.
In order to address these challenges and to provide guidance to financial markets we adopt a recently-developed Quantitative Complexity Theory (QCT) as a reflection of the interplay between these drivers. In particular, the focus of our analysis is on the impact of these drivers on portfolio management and asset allocation.
The availability of massive computing power allows us to improve the reliability of financial analysis and provides new guidance in terms of anticipating the shaping of the world economy. In particular, we address the systemic aspects and the dynamics of stock markets, market sectors, systems of corporations or national economies.
Systemic risks are not well-defined and are a generally poorly understood concept. This leaves the door open to regulatory discretion, which can compound these risks further. The idea, therefore, is to approach the problem from a totally different angle. Instead of trying to measure risks the idea is to measure the resilience of the system. Resilience measures the ability of a system to absorb shocks and destabilizing events, such as financial contagion, shocks, conflicts, extreme events, sudden loss of major suppliers or customers, etc.
A systemic resilience analysis allows us to answer the following questions:
- What is the overall state of health of the system?
- How resilient/fragile is the system?
- What is its degree of interdependency?
- Which components of the system make is fragile and vulnerable?
- Which are the dominant components of the system and what is their footprint?
- How far is the system from potentially critical states?
- How much market uncertainty can the system absorb while remaining stable?
- What are the most like modes of failure and failure propagation?
- How can the resilience of a given system be improved?
- How do any of the above properties evolve in time?
A fundamental issue one encounters when analysing systems is that its behaviour cannot be deduced from that of its components. Conventional analytics technology and ´linear thinking´ can lead to extremely misleading results and conclusions. Moreover, as the number of system components increases, the number of the so-called ´modes of behaviour´ also increases. This means that as the turbulence and uncertainty of markets grow, more complex systems can develop the capacity to suddenly produce surprising behaviour. This is precisely what fragility is and this why it is so important to actually get the big picture.
What systemic analyses reveal is that the state of health of a system can differ significantly from that of its components. A system of apparently healthy components may conceal far from obvious concentrations of fragility. The whole can be greater than the sum of the parts but is can also be less.
In our analyses we integrate numerous and heterogeneous data types and sources to provide a truly holistic and broad-scale picture:
- Corporate financials (Balance Sheet, Cash Flow, Income Statement, Ratios)
- Stock market performance
- Macroeconomic data (unemployment, interest rates, raw materials and energy prices etc.)
Systemic Risk and Resilience Analysis offers numerous benefits:
- Better understanding of the system as a whole
- New information of strategic nature
- Quantitative and objective measures of system resilience and interdependency
- Early-warnings of increased fragility and/or instability
A simple example of systemic risk analysis may be found here.