A team of researches was able to estimate the systemic risk of another financial crisis due to the increased interconnectivity of the banking system by taking into account derivatives, securities and foreign exchange exposure on top of interbank loans. The study showed the risk to be 4 times higher than before the 2008 crisis and 90% higher than other studies that take into account only interbank loans, which is what the market bases its measures on. It goes on to say that the real systemic risk is likely to be even higher when including other measures such as overlapping portfolios and funding liquidity.
What it basically means is that when the next financial crisis hits the markets, the losses due to increased interconnectivity between financial institutions will be much bigger compared to the past, so be prepared for a recession that is going to be much worse than the last one and consider the possibility of not being able to retrieve your savings when planning for the future.
http://phys.org/news/2015-09-financial-crisis-higher-previously.html
Abstract of paper analysing data from the Mexican banking system between 2007-2013 to estimate systemic risk.
http://www.sciencedirect.com/science/article/pii/S1572308915000856
What it basically means is that when the next financial crisis hits the markets, the losses due to increased interconnectivity between financial institutions will be much bigger compared to the past, so be prepared for a recession that is going to be much worse than the last one and consider the possibility of not being able to retrieve your savings when planning for the future.
http://phys.org/news/2015-09-financial-crisis-higher-previously.html
The study, published in the journal Financial Stability, introduces a new method that allows researchers to estimate the systemic risk that emerge from multiple layers of connectivity.
"Systemic risk is the risk that a significant part of the financial system stops working—that it cannot perform its function," says IIASA Advanced Systems Analysis program researcher Sebastian Poledna, who led the study. For example if a major bank fails, it could trigger the failure of other financial institutions that are linked to it through loans, derivatives, securities, and foreign exchange exposure. The fear of such contagion is what drives governments to bail out banks.
"Previous studies of systemic risk had just examined one layer of this system, the interbank loans," says Poledna. The new study expands this to include three other layers of connectivity: derivatives, securities, and foreign exchange. By including the other layers, Poledna and colleagues found that the actual risk was 90% higher than the risk just from interbank loans.
Currently, financial regulators tend to use market-based measures to estimate systemic risk. The researchers find that these measures also underestimate the actual risk. In Mexico, which the researchers used as a case study, they found that systemic risk levels are about four times higher today than before the financial crisis—yet these risks are not reflected in market-based measures.
"Banks today are far more connected than they were before the financial crisis," explains Poledna. "This means that in a new crisis, the public costs for Mexico could be four times higher than those experienced in the last crisis,"
The new method would make it possible to create systemic risk profiles for markets and individual institutions, which could prove useful for financial regulators aiming to prevent future crises.
In addition, the methodology provides a way to estimate the cost and repercussions of a bank failure, which could help financial policymakers determine whether a bailout would be worth the cost. Bank bailouts come at a huge cost to taxpayers, yet until now, there has been no clear method of determining the cost to the system of not bailing out a failing bank.
Poledna points out that the new method may still underestimate systemic risk, as it leaves out two additional potential sources of risk - overlapping investment portfolios, and funding liquidity. The researchers are now working in collaboration with the IIASA Risk, Policy and Vulnerability program on a new study that brings in these additional layers.
The study relied on data from the Mexican banking system but the researchers say that the method could be used for any country, as long as the data were available.
Abstract of paper analysing data from the Mexican banking system between 2007-2013 to estimate systemic risk.
http://www.sciencedirect.com/science/article/pii/S1572308915000856
Abstract
The inability to see and quantify systemic financial risk comes at an immense social cost. Systemic risk in the financial system arises to a large extent as a consequence of the interconnectedness of its institutions, which are linked through networks of different types of financial contracts, such as credit, derivatives, foreign exchange, and securities. The interplay of the various exposure networks can be represented as layers in a financial multi-layer network. In this work we quantify the daily contributions to systemic risk from four layers of the Mexican banking system from 2007 to 2013. We show that focusing on a single layer underestimates the total systemic risk by up to 90%. By assigning systemic risk levels to individual banks we study the systemic risk profile of the Mexican banking system on all market layers. This profile can be used to quantify systemic risk on a national level in terms of nation-wide expected systemic losses. We show that market-based systemic risk indicators systematically underestimate expected systemic losses. We find that expected systemic losses are up to a factor of four higher now than before the financial crisis of 2007–2008. We find that systemic risk contributions of individual transactions can be up to a factor of one thousand higher than the corresponding credit risk, which creates huge risks for the public. We find an intriguing non-linear effect whereby the sum of systemic risk of all layers underestimates the total risk. The method presented here is the first objective data-driven quantification of systemic risk on national scales that reveal its true levels.