Challenges in Identifying and Measuring Systemic Risk

Hansen, Lars Peter, “Challenges in Identifying and Measuring Systemic Risk,” SSRN, February 14, 2014,

Purpose & Motivation:  The “great recession” sparked immense interest in “systemic risk,” but that phrase is at risk of becoming a buzzword used to justify policy based on vague notions.  This essay offers perspective on the difficulty of quantifying systemic risk, or the connections between financial markets and the broader economy.

The Problem:  Before something can be rigorously discussed, debated, and analyzed, it must be measured.  The danger in allowing “systemic risk” to remain a qualitative label is that related policy cannot be based on hard data and informed debate.  Such policy is potentially harmful, and always difficult to criticize.

Challenges:  A lot of people are trying to quickly produce measures of systemic risk, to guide policy responses to the 2007-2009 recession.  While the hunt for numbers can be helpful, numbers without theory are difficult to apply.  We need economic theories that tell us which risk measurement techniques are useful for which purposes.

  • Challenge #1: Distinguishing “systematic” from “systemic”
    • “Systematic” risk is an investor’s exposure to macroeconomic shocks. It cannot be eliminated through diversification, and so demands a premium.
      • Macroeconomists try to identify shocks and propose policy that will mitigate their effects.
      • Finance research asks what premium is demanded by each element of systematic risk.
    • “Systemic” risk refers to the markets breaking down altogether. It has multiple interpretations:
      • A bank run – this is a concern of central banks in their position as “lenders of last resort”
      • The susceptibility of a network of financial institutions to shocks that start in one place and spread throughout – understanding this requires knowing which networks are risky and which shocks could start a fire
      • The insolvency of a major financial sector or institution
    • Challenge #2: Quantifying risk and uncertainty
      • Even the best models are inaccurate. Economists face uncertainty when they select between competing models, and agents within those models also face uncertainty.

Current Approaches to Measuring Systemic Risk:

  • Tail Measures look at the relation between the tails of financial institutions’ equity returns. This approach is plagued by the paucity of historical data, and ignores non-public institutions that may be important.
  • Contingent Claims Analysis uses option pricing techniques to value the debt (as a put option) and equity (as a call option) of an entire sector of the financial system. Development of this analysis requires better understanding of the overall market’s risk appetite and of the shocks that demand large risk premia.
  • Network Models look at the degree of interconnectedness between institutions. Rampant endogeneity complicates these models.
  • Dynamic, Stochastic Macroeconomic Models seem promising, but applications to systemic risk are still new.
  • Problems with data collection and sharing – researchers deal with confidentiality issues, biases in data collection, and limitations in the scope of publicly-available data.

Conclusions:  Attempts to examine systemic risk in the financial system face difficulties determining how to model the system, which data to use, and how to measure the data.  However, the high public interest in this topic and the general lack of good research present an alluring challenge.