Systemic risk

Overview

In finance, systemic risk is the risk of collapse of an entire financial system or entire market, as opposed to the risk associated with any one individual entity, group or component of a system, that can be contained therein without harming the entire system. It can be defined as "financial system instability, potentially catastrophic, caused or exacerbated by idiosyncratic events or conditions in financial intermediaries". It refers to the risks imposed by interlinkages and interdependencies in a system or market, where the failure of a single entity or cluster of entities can cause a cascading failure, which could potentially bankrupt or bring down the entire system or market. It is also sometimes erroneously referred to as "systematic risk".

Explanation

Systemic risk has been associated with a bank run which has a cascading effect on other banks which are owed money by the first bank in trouble, causing a cascading failure. As depositors sense the ripple effects of default, and liquidity concerns cascade through money markets, a panic can spread through a market, with a sudden flight to quality, creating many sellers but few buyers for illiquid assets. These interlinkages and the potential "clustering" of bank runs are the issues which policy makers consider when addressing the issue of protecting a system against systemic risk. Governments and market monitoring institutions (such as the U.S. Securities and Exchange Commission (SEC), and central banks) often try to put policies and rules in place with the justification of safeguarding the interests of the market as a whole, claiming that the trading participants in financial markets are entangled in a web of dependencies arising from their interlinkage. In simple English, this means that some companies are viewed as too big and too interconnected to fail. Policy makers frequently claim that they are concerned about protecting the resiliency of the system, rather than any one individual in that system. Systemic risk arises because of the interaction of market participants, and therefore can be seen as a form of endogenous risk. The risk management literature offers an alternative perspective to notions from economics and finance by distinguishing between the nature of systemic failure, its causes and effects, and the risk of its occurrence. It takes an "operational behaviour" approach to defining systemic risk of failure as: "A measure of the overall probability at a current time of the system entering an operational state of systemic failure by a specified time in the future, in which the supply of financial services no longer satisfies demand according to regulatory criteria, qualified by a measure of uncertainty about the system's future behaviour, in the absence of new mitigation efforts." This definition lends itself to practical risk mitigation applications, as demonstrated in recent research by a simulation of the collapse of the Icelandic financial system in circa 2008. Systemic risk should not be confused with market or price risk as the latter is specific to the item being bought or sold and the effects of market risk are isolated to the entities dealing in that specific item. This kind of risk can be mitigated by hedging an investment by entering into a mirror trade. Insurance is often easy to obtain against "systemic risks" because a party issuing that insurance can pocket the premiums, issue dividends to shareholders, enter insolvency proceedings if a catastrophic event ever takes place, and hide behind limited liability. Such insurance, however, is not effective for the insured entity. One argument that was used by financial institutions to obtain special advantages in bankruptcy for derivative contracts was a claim that the market is both critical and fragile. Systemic risk can also be defined as the likelihood and degree of negative consequences to the larger body. With respect to federal financial regulation, the systemic risk of a financial institution is the likelihood and the degree that the institution's activities will negatively affect the larger economy such that unusual and extreme federal intervention would be required to ameliorate the effects. A general definition of systemic risk which is not limited by its mathematical approaches, model assumptions or focus on one institution, and which is also the first operationalizable definition of systemic risk encompassing the systemic character of financial, political, environmental, and many other risks, was put forth in 2010. The Systemic Risk Centre at the London School of Economics is focused on the study of systemic risk. It finds that systemic risk is a form of endogenous risk, hence frustrating empirical measurements of systemic risk.

TBTF/TCTF

According to the Property Casualty Insurers Association of America, there are two key assessments for measuring systemic risk, the "too big to fail" (TBTF) and the "too (inter)connected to fail" (TCTF or TICTF) tests. First, the TBTF test is the traditional analysis for assessing the risk of required government intervention. TBTF can be measured in terms of an institution's size relative to the national and international marketplace, market share concentration, and competitive barriers to entry or how easily a product can be substituted. Second, the TCTF test is a measure of the likelihood and amount of medium-term net negative impact to the larger economy of an institution's failure to be able to conduct its ongoing business. The impact is measure beyond the institution's products and activities to include the economic multiplier of all other commercial activities dependent specifically on that institution. The impact is also dependent on how correlated an institution's business is with other systemic risks.

Too big to fail

The traditional analysis for assessing the risk of required government intervention is the "too big to fail" test (TBTF). TBTF can be measured in terms of an institution's size relative to the national and international marketplace, market share concentration (using the Herfindahl-Hirschman Index for example), and competitive barriers to entry or how easily a product can be substituted. While there are large companies in most financial marketplace segments, the national insurance marketplace is spread among thousands of companies, and the barriers to entry in a business where capital is the primary input are relatively minor. The policies of one homeowners insurer can be relatively easily substituted for another or picked up by a state residual market provider, with limits on the underwriting fluidity primarily stemming from state-by-state regulatory impediments, such as limits on pricing and capital mobility. During the 2008 financial crisis, the collapse of American International Group (AIG) posed a significant systemic risk to the financial system. There are arguably either no or extremely few insurers that are TBTF in the U.S. marketplace.

Too connected to fail

A more useful systemic risk measure than a traditional TBTF test is a "too connected to fail" (TCTF) assessment. An intuitive TCTF analysis has been at the heart of most recent federal financial emergency relief decisions TCTF is a measure of the likelihood and amount of medium-term net negative impact to the larger economy of an institution's failure to be able to conduct its ongoing business. Network models have been proposed as a method for quantifying the impact of interconnectedness on systemic risk. The impact is measured not just on the institution's products and activities, but also the economic multiplier of all other commercial activities dependent specifically on that institution. It is also dependent on how correlated an institution's business is with other systemic risk.

Criticisms of systemic risk measurements

Criticisms of systemic risk measurements: Danielsson et al. express concerns about systemic risk measurements, such as SRISK and CoVaR, because they are based on market outcomes that happen multiple times a year, so that the probability of systemic risk as measured does not correspond to the actual systemic risk in the financial system. Systemic financial crises happen once every 43 years for a typical OECD country and measurements of systemic risk should target that probability.

SRISK

A financial institution represents a systemic risk if it becomes undercapitalized when the financial system as a whole is undercapitalized. In a single risk factor model, Brownlees and Engle build a systemic risk measure named SRISK. SRISK can be interpreted as the amount of capital that needs to be injected into a financial firm as to restore a certain form of minimal capital requirement. SRISK has several nice properties: SRISK is expressed in monetary terms and is, therefore, easy to interpret. SRISK can be easily aggregated across firms to provide industry and even country specific aggregates. Last, the computation of SRISK involves variables which may be viewed on their own as risk measures. These are the size of the financial firm, the leverage (ratio of assets to market capitalization), and a measure of how the return of the firm evolves with the market (some sort of time varying conditional beta but with emphasis on the tail of the distribution). Whereas the initial Brownlees and Engle model is tailored to the US market, the extension by Engle, Jondeau, and Rockinger is more suitable for the European markets. One factor captures worldwide variations of financial markets, another one the variations of European markets. This extension allows for a country-specific factor. By accounting for different factors, one captures the notion that shocks to the US or Asian markets may affect Europe, but also that bad news within Europe (such as the news about a potential default of one of the countries) matters for Europe. Also, there may be country specific news that does not affect Europe or the US, but matters for a given country. Empirically the last factor is less relevant than the worldwide or European factor. Since SRISK is measured in terms of currency, the industry aggregates may also be related to Gross Domestic Product. As such one obtains a measure of domestic, systemically important banks. The SRISK Systemic Risk Indicator is computed automatically on a weekly basis and made available to the community. For the US model, SRISK and other statistics may be found under the Volatility Lab of NYU Stern School website and for the European model under the Center of Risk Management (CRML) website of HEC Lausanne.

Pair/vine copulas

A vine copula can be used to model systemic risk across a portfolio of financial assets. One methodology is to apply the Clayton Canonical Vine Copula to model asset pairs in the vine structure framework. As a Clayton copula is used, the greater the degree of asymmetric (i.e., left tail) dependence, the higher the Clayton copula parameter. Therefore, one can sum up all the Clayton Copula parameters, and the higher the sum of these parameters, the greater the impending likelihood of systemic risk. This methodology has been found to detect spikes in the US equities markets in the last four decades capturing the Oil Crisis and Energy Crisis of the 1970s, Black Monday and the Gulf War in the 1980s, the Russian Default/LTCM crisis of the 1990s, and the Technology Bubble and Lehman Default in the 2000s. Manzo and Picca introduce the t-Student Distress Insurance Premium (tDIP), a copula-based method that measures systemic risk as the expected tail loss on a credit portfolio of entities, in order to quantify sovereign as well as financial systemic risk in Europe.

Inadequacy of classic valuation models

One problem when it comes to the valuation of derivatives, debt, or equity under systemic risk is that financial interconnectedness has to be modelled. One particular problem is posed by closed valuations chains, as exemplified here for four firms A, B, C, and D:

B might hold shares of A, C holds some debt of B, D owns a derivative issued by C, and A owns some debt of D. For instance, the share price of A could influence all other asset values, including itself.

The Merton (1974) model

Situations as the one explained earlier, which are present in mature financial markets, cannot be modelled within the single-firm Merton model, but also not by its straightforward extensions to multiple firms with potentially correlated assets. To demonstrate this, consider two financial firms,

i = 1 , 2

{\displaystyle i=1,2}

, with limited liability, which both own system-exogenous assets of a value

a

i

≥ 0

{\displaystyle a_{i}\geq 0}

at a maturity

T ≥ 0

{\displaystyle T\geq 0}

, and which both owe a single amount of zero coupon debt

d

i

≥ 0

{\displaystyle d_{i}\geq 0}

, due at time

T

{\displaystyle T}

. "System-exogenous" here refers to the assumption, that the business asset

Non-trivial asset value equations

Consider now again two such firms, but assume that firm 1 owns 5% of firm two's equity and 20% of its debt. Similarly, assume that firm 2 owns 3% of firm one's equity and 10% of its debt. The equilibrium price equations, or liquidation value equations, at maturity are now given by

r

1

= min {

d

1

,

a

1

+ 0.05

s

2

+ 0.2

r

2

}

{\displaystyle r_{1}=\min\{d_{1},a_{1}+0.05s_{2}+0.2r_{2}\}}

r

2

= min {

Over- and underestimation of default probabilities

It is known that modelling credit risk while ignoring cross-holdings of debt or equity can lead to an under-, but also an over-estimation of default probabilities. The need for proper structural models of financial interconnectedness in quantitative risk management – be it in research or practice – is therefore obvious.