Systemic risk

In finance, systemic risk means the danger that the whole financial system or market could collapse. This is different from risks that only affect one company or a small part of the system. Systemic risk happens when problems in one place spread to many others because everything is connected.

When one bank or financial group gets into trouble, it can cause other banks and markets to fail too. This spreading of problems is called a cascading failure. If this happens, it could bring down the entire financial system, which would be very harmful to everyone.

People sometimes confuse systemic risk with "systematic risk". But they are not the same. Systemic risk is about the whole system failing, while systematic risk is about risks that affect nearly all investments at the same time. Understanding systemic risk helps leaders try to prevent big financial problems that could affect many people.

Explanation

Systemic risk is when a problem in one part of the financial system can spread and cause trouble for the whole system. For example, if one bank has trouble and cannot pay back money it owes, other banks that are connected to it may also get into trouble. This can make people worried, and they might try to take their money out of banks quickly. This can cause panic and make it hard to buy or sell certain assets.

Governments and special groups, like the U.S. Securities and Exchange Commission and central banks, work to create rules to help protect the financial system. They worry about keeping the whole system strong, not just one part of it. Systemic risk happens because many parts of the financial system depend on each other, and this connection can sometimes lead to bigger problems.

Measurement

TBTF/TCTF

There are two ways to measure big risks in finance: "too big to fail" (TBTF) and "too (inter)connected to fail" (TCTF or TICTF). The TBTF test looks at how big a company is compared to the whole market and how hard it would be for another company to take its place. The TCTF test looks at how much harm a company's failure could cause to the larger economy, including other businesses that depend on it.

Too big to fail

The "too big to fail" test checks if a company is so large that its failure might need government help. This is measured by looking at the company's size, how much of the market it controls, and how easy it is for other companies to step in. During the 2008 financial crisis, the collapse of American International Group (AIG) showed how one big company could risk the whole financial system.

Too connected to fail

The "too connected to fail" test looks at how likely a company's failure is to cause big problems for the economy. This includes not just the company's own business, but also how other businesses depend on it.

Network models have been suggested as a way to measure how connections between companies can increase big risks.

Criticisms of systemic risk measurements

Some experts worry that measurements of big risks, like SRISK and CoVaR, might not match the real chance of a big crisis. Financial crises happen about once every 43 years in a typical country, so measurements should aim for that level of risk.

SRISK

A financial institution can cause big risks if it runs out of money when the whole financial system is also struggling. SRISK is a way to measure this risk. It shows how much money a company needs to meet basic rules. SRISK is easy to understand because it uses money amounts and can be added up for groups of companies or whole countries.

SRISK uses things like the size of the company, how much it owes, and how its performance changes with the market. There are models for both the US and Europe, which look at how changes in one part of the world can affect others.

SRISK is calculated every week and can be found on websites like the Volatility Lab of NYU Stern School and the Center of Risk Management (CRML) at HEC Lausanne.

Pair/vine copulas

A vine copula can help model big risks for groups of financial assets. One way to use this is with the Clayton Canonical Vine Copula, which looks at how assets depend on each other. By adding up certain values from this method, we can see when big risks are more likely. This has helped spot big market problems over the past few decades, like energy crises, wars, and financial crashes.

Valuation of assets and derivatives under systemic risk

Inadequacy of classic valuation models

When trying to figure out the value of things like loans or stocks in a big, connected financial system, it gets really tricky. This is because companies often own pieces of each other. For example, one company might own part of another, which in turn owns part of a third, and so on. This means the value of one company can affect the values of all the others, making it hard to predict what will happen if one fails.

One old way to value companies, called the Merton model, works well for single companies but struggles when companies are connected. It simply looks at a company's own assets and debts to decide its value. But when companies own each other’s debts or stocks, things get more complicated. The value of each company depends on the others, creating a web of connections that makes valuation much harder.

Structural models under financial interconnectedness

To better understand these connected systems, some experts have created models that show how risks move between companies. These models help us see how the failure of one company might affect others. Some researchers found that a certain level of connection can actually make the financial system more stable. But if connections get too dense, risks can spread quickly, making the whole system more vulnerable.

Risk-neutral valuation: price indeterminacy and open problems

When trying to set prices in these connected systems, it’s hard to know what the right price should be. Some models work well for simple connections of debts and stocks, but things get much harder when complex financial products called derivatives are involved. Right now, it’s still not clear what the best ways are to set prices in these situations, and this remains an important area of research.

Factors

Some things can make big problems in money and banking harder to avoid. One reason is that we don’t fully understand how different money models work together with the real world. Even if each model looks good on its own, using the same ideas can make things worse if something goes wrong.

Another reason is that some models don’t think about what happens when money is hard to use or trade. When this happens, everyone using these models can face big risks together.

Diversification

Risks can be lowered in several ways, such as avoiding them, spreading them out, protecting against them, or sharing them with others. However, some risks, called systematic risk or market risk, cannot be reduced by spreading them out. Even big market players like hedge funds can sometimes make these risks worse.

For a long time, many financial models suggested that spreading out risks in a busy financial system helps keep things stable. But newer research shows that this isn't always true. When connections between financial systems are just right, they can help absorb shocks and share risks. But if there are too many connections, they can actually make things more fragile and spread risks further.

Regulation

One big reason we have rules in the marketplace is to keep the whole financial system safe. But sometimes, people find ways around these rules by moving their business to areas with fewer rules. This can bring back the danger to the whole system. For example, rules were put in place for banks to keep them safe. But because banks were careful about risky deals, other areas like insurance started taking on those risks instead. This shows that having rules for just one part isn't enough to protect the whole system.

Project risks

In project management and cost engineering, systemic risks are dangers that affect many projects and cannot be easily controlled by a single project team. These risks come from inside the project, like unsure plans or the way a company handles projects. They can also come from how new or complicated a project is.

For example, the collapse of Lehman Brothers in 2008 caused big problems for the whole financial system. On the other hand, risks that are special to just one project, like changes in the economy, are called overall project risks. These can affect a project in many ways, good or bad. The Great Recession in the late 2000s is an example of this kind of risk.

Systemic risk and insurance

In February 2010, a group of experts called The Geneva Association studied how insurance companies affect big money problems around the world. They found that normal insurance work usually doesn’t cause big problems for the whole financial system. This is because insurance companies get money upfront from customers, have long-term policies, and stayed stable even during the big money trouble in 2008.

But the report did find that some special activities by insurance companies, like trading complex financial products or managing short-term money poorly, could cause big problems if not watched carefully. They suggested better rules to watch these activities, improve how they manage money, and share information globally to keep everything safe. Later, another group also said that while insurance can feel effects from other parts of the financial world, it usually doesn’t start or make those big problems worse.

Discussion

Systemic risk looks at how likely and how bad things could get for the whole economy. People often talk about this when discussing big money problems, like the subprime mortgage crisis. The 2008 financial crisis showed how problems at some banks could hurt the whole economy.

Some studies from the 1990s and 2000s found that when there are too many banks competing, they might take bigger risks to make more money. This can lead to big problems. Banks hold many financial items, and if these items are hard to value correctly, even small mistakes can affect the banks a lot. In Europe, banks had lots of these tricky financial items, which could make the whole financial system less stable.