Modern risk management problems
The modern risk management is currently going through an ideological crisis showing the following symptoms:
- failure to understand the nature of the majority of risks, eclecticism of methods and concepts, in both technologies and standards of risk management,
- disregard of the interaction between operational risk, credit risk and market risk, lack of continuity in management processes, lack of common rating scales for the assessment of various risks,
- inadequate tools for operational risk assessment,
- the virtual absence of portfolio approach to operational risk management,
- difficulties with forecasting stress and crisis scenarios generation, difficulties with explaining the nature of chaotic market processes,
- the problem of the recently increased relevance of some previously uncommon factors, of which the following ones are thought by the author to be most important : cyber-terrorism and industrial terrorism, influence of social networks, High Frequency Trading (HFT), threat of antibiotic resistance.
Future risk management
The author believes that the next decades will see the development of the following branches of risk management: human error, transfer of operational risks including hedging and portfolio diversification, prediction markets, new concepts of key risk indicator (KRI), risk management of small and medium enterprises (SMEs) and households, crowdsourcing, including platforms like Ushahidi, Wiki, new generations of publicly available risk indices, emergence of new asset classes.
Global risk factor theory
The basis for the development of the global risk factor theory Herschel (1804), Jevons (1870), Chizhevsky (1920),the advent of modern heliobiology and its findings, findings of the sciences of human factors, human errors, findings of the sciences of risk management and financial mathematics, accumulation of statistical data (statistics of disasters, volatility, defaults, other events and indices).
The following postulates can be confirmed or refuted by explaining the causal relationships and by statistical analysis:
Risks are interrelated: there are relationships between financial risks of all types (market, credit, operational ones).
Risk interactions have an important role because of the existence of close economic, organizational and technological ties between risk owners: the occurrence of risks (operational, credit, market ones) for some persons implies the emergence of other risks for their counterparties and the subsequent chain reaction of credit and market risks propagating through exchange within the economy. In recent decades, these relations have been developing more intensively than ever before because of market globalization and technological progress. This causal relationship can be illustrated by a typical example of the domino effect in business environment: discontent of the local population (a political risk, part of operational risks) in Nigeria led to the explosion of a pipeline operated by Royal Dutch Shell on December 21, 2005. As a result, the output was cut by 180,000 barrels per day (operational risk of business interruption); the company declared ―force majeure,‖ which meant its failure to perform contract obligations (credit risks for the counterparties), and the oil price went up by 48 cents per barrel (commodity market risk). The mechanism of risk factor influence on the emergence of credit and market risks can be illustrated using the well-known Merton approach, the basis of the Expected Default Frequency (EDF) methodology: distance to default of a firm (i.e. credit risks of its counterparties) is determined by risks associated with the firm’s operations and expressed by the volatility of the market value of the firm’s assets exposed to various types of risk: operational, market, credit ones. The assets volatility determines the volatility of the market capitalization (market risks of investors). Statistical analysis of relationships
Correlation and cointegration of market and credit risks are well known and can be explained by changes of risk premium; however, relationships of these risks with various operational risks cannot be adequately explained without identifying a common factor.
Let us define the global risk factor as a global-scale correlator of risk factor volatilities.
Risks are anthropic: human error is the global risk factor.
Human error is not the only risk factor, but it has acquired a global nature. The principal cause of the global influence of the human factor is that it often and strongly affects the sensitivity of assets performance to the majority of other risk factors, no matter what their own nature. In the past decades, the influence of the human factor has been growing due to the increasing operator’s role in business processes and globalization. This is reflected by the increasing correlation of different types of risks.
Investigations of the occurrences of technological operational risk in almost all sectors and regions show that most of such events in the last half-century were initially caused by human error rather than technical failure. And moreover, when caused by technical failure, risk events were mostly the result of accumulated hidden defects due to accumulated maintenance errors caused by organizational errors and again the human factor. This can be confirmed by many examples, some of which are given below. The human factor is the main trigger behind the vast majority of transport accidents and disasters. Human errors are responsible for 90 percent of all motor vehicle accidents. National statistics of individual countries do not differ much from the world average figures. The human factor accounts for 70 to 80 percent of accidents in air and water transport, and for about 50 percent of accidents in railway transport. The human factor is also the dominant cause of industrial accidents and injuries. For instance, about 85 percent of lifting crane accidents are associated with violations of labor or technical discipline. There are about 200 best-known techniques for human factors analysis and assessment. For example, the Human Factors Analysis and Classification System (HFACS) is based on ― the Swiss Cheese model (J. Reason, 2000). The model illustrates errors passing through ―holes‖ (weaknesses) in business processes. According to this theory, there are unsafe acts (errors), preconditions for unsafe acts, including the operator’s psychic factors, unsafe supervision and organizational influences.
Risks are heliogeotropic: human errors and failures (the human factor) depend substantially on preconditions such as the effects of heliogeophysical factors (geomagnetic disturbances, etc.).
Geomagnetic activity depends on solar activity. According to the Svalgaard–Mansurov effect, the variations of the Earth’s magnetic field are influenced by the sector structure of the interplanetary magnetic field (IMF). These two major factors can disturb the heart rate and cause human errors, which in their turn, trigger chain reactions resulting in the occurrence of all types of financial risks (market, credit, operational ones) all over the world, depending on the assets sensitivity to the risk factors. Besides, human intuition and emotions enhance in the periods of geomagnetic disturbances, and this enhancement influences market expectations. As concerns operational risks caused by risk factors non-correlating with heliogeophysical conditions, their impact depends on the asset sensitivity to these risk factors, while the asset sensitivity itself is heliogeotropic due to the human factor influence. For a considerable part of risks, the dynamics of risk events can be explained by that of human errors under changing space weather that has a planetary effect. This risk source was termed ―the global risk factor. Astrophysicists have shown the chaotic nature of solar and geomagnetic activity, and this can explain (based on the global risk factor theory) the nature of the observed widely discussed chaotic processes in the markets.
Global risk factor indices
There are a lot of indices of solar and geomagnetic activity, and the objective was to choose the best indicator for adequate description of the global risk factor or to develop a new one. In the author’s opinion, the best global risk factor index should meet the following requirements: most fully explain the behavior of market, credit and operational risks, allow for possible regularities discovered in heliobiology (the Mansurov effect), be based on uniquely determinable or measurable values (heliogeophysical data), allow real-time updating. The indices of solar activity are not suitable for describing the global risk factor. This is the very reason of the skepticism of modern science towards the ideas of prominent scholars of the past, particularly (Jevons, 1878) and (Chizhevsky, 1936). The failure to find correlations with solar activity (the Wolf number, also known as the sunspot number) has led to the substitution of this idea in modern science with the general idea of accounting for random factors in economics. Economists rebranded the term ―sunspots‖ by completely stripping it of the implication of Sun-Earth relationships and using it to denote an external non-fundamental variable that influences human behavior. The RogovIndex© family of indices was developed for adequate description of the global risk factor; these indices satisfy the above requirements and are based on the widely accepted index of geomagnetic field variation averaged over several stations (storm-time variation Dst). The conclusion that the effect of heliogeophysical factors on risk is best described by storm-time variation than by any other of the great variety of indices is consistent by the findings of heliobiological research. The author is planning to create a market of space weather index derivatives.
Industry and geographical specifics of global risk factor exposure.
The industry specifics of preconditions for error proliferation includes, among other things, the scope of error impact on business processes (with a higher labor productivity, an error of one operator would affect more performance indicators and, generally, more business processes), the scope of business process regulation (including operator qualification requirements and other industry-specific barriers), relative attractiveness of the industry pay rate against the average pay in the region’s economy, the conflict intensity in the industry (the number of strikes). Industry specifics result in different global risk factor exposures that should be taken into account by risk managers. For instance, diversified portfolios may be created using the correlation matrix or cointegrating vector approaches that take account of the global risk factor exposures of various assets and consider credit risks in accordance with the industry specifics. A detector of those risks that cannot be explained by the global risk factor behavior allows planning most topical areas of risk audit for identification of operational risks. The geographical specifics of global risk factor exposure is related to the distance of the region, where the main business process or asset (if appropriate) is located, from the Magnetic Poles constantly drifting relative to fixed geographic coordinates.
The proposed global risk factor theory (Rogov 2002-2013) describes the frequently observed interaction of different types of risks (market, credit, operational) at different assets and in different business processes. The theory opens prospects for risk benchmarking, analysis, detection of anomalies and hidden risks, classification of risks, particularly based on hierarchical clustering of time series. This allows creating new proactive risk indicators for monitoring, as well as applying the market mechanisms of operational risk optimization through diversification and hedging with the use of index derivatives.