Volatility, financial crises and Minsky's hypothesis, by Jon Danielsson, Marcela Valenzuela, Ilknur Zer, Vox EU: Received wisdom maintains that financial market volatility has a direct impact on the likelihood of financial crisis.
Perhaps the best expression of this is Minsky's (1982) hypothesis that economic agents observing low financial risk are induced to increase risk-taking, which in turn may lead to a crisis. This is the foundation of his famous statement, "stability is destabilizing".
More recently, this sentiment has found support amongst policymakers:
“Volatility in markets is at low levels, both actual and expected... to the extent that low levels of volatility may induce risk-taking behavior is a concern to me and to the Committee” -- Federal Reserve Chair Janet Yellen, 18 June 2014.
Such views find support in the recent theoretical literature, where economic agents react to volatility deviating from what they become to expect it to be.
Low volatility induces economic agents to take more risk, endogenously increasing the likelihood of future shocks. If the economic conditions deteriorate and the resulting bad investment decisions start to sour, volatility then increases, signaling a pending crisis.
However, we could not find any empirical literature documenting such a relationship between financial market volatility, risk taking, the real economy and crises. Perhaps we have made little empirical progress since Paul Samuelson's famous quip in 1966 that “Wall Street indexes predicted nine out of the last five recessions”!
The decomposition of volatility
This lack of empirical clarity has motivates us to take a new approach to verify the volatility-crisis relationship, focusing on unexpectedly high and unexpectedly low volatility.
Crises are rare events – recent history notwithstanding, an OECD member country suffers a banking crisis only once every 35 years, on average. Consequently, in order to obtain a meaningful statistical relationship between volatility and crises, it is helpful to take the long-term historical view.
Since no comprehensive data on historical volatilities is available, we constructed such a database from primary sources, one that spans 1800 to 2010 and covers 60 countries.
We make use of Reinhart and Rogoff’s (2009) banking and stock market dataset as our crisis indicator and use GDP per capita, inflation, change in government debt to GDP ratio, institution quality and fixed effects as controls.
We then ran a binomial regression model on the incidence of financial crises with lagged averages of volatility and controls as explanatory variables, finding little significance.
We surmise that this is due in part to the theoretical literature emphasizing volatility expectations and deviations therefrom, not the contemporaneous level of volatility.
Furthermore, volatility has a trend that evolves slowly over time, where one can identify regimes of high or low volatiles that last for many years and decades. Consequently, the expected level of volatility can be quite different across countries and time, weakening any empirical analysis focused solely on volatility levels.
We address this by decomposing volatility into unexpectedly low and high volatilities and using these as explanatory variables in the regression model.
In particular, borrowing terminology from the literature on output gap, we interpret the slow running volatility trend, calculated by a one-sided Hodrick-Prescott filter, as long-term expected volatility. Unexpectedly high and low volatility is then the deviation of volatility from above and below its trend, respectively.
We find a strong and significant relationship between unexpected volatilities and the likelihood of financial crises.
Unexpectedly low volatility increases the probability of both banking and stock market crises. This holds especially strongly if low volatility persists half a decade or longer.
We further investigate this by using the credit-to-GDP gap as a proxy for risk-taking, finding that unexpectedly low volatility significantly increases risk-taking. This result complements that of Taylor and Schularick (2009), where credit booms are destabilizing, leading to a banking crisis.
For stock market crises, but not banking crises, high volatility also increases the likelihood of a crisis, but only with much shorter lags, up to two or three years.
This is very much in line with what theory predicts and provides strong evidence for Minsky’s instability hypothesis. Low volatility induces risk-taking that leads to riskier investments. When those turn sour, the resulting high volatility signals a pending crisis.
These results are robust to a number of alternative specifications, for example on the definition of volatility, filtering, lag lengths, sample selections and model specifications.
We find that the relationship between unexpected volatility and the likelihood of a future crisis becomes stronger over time. This is not surprising since the importance of stock markets and the prevalence of limited liability corporations have steadily been increasing.
The main exception to this is the Bretton Woods era when financial markets were tightly regulated and capital flows controlled, causing the volatility-crisis relationship to weaken significantly.
While the common view maintains that volatility directly affects the probability of a crisis, this has been proven difficult to verify empirically.
In what we believe is the first study to do so, we find direct empirical evidence that the level of volatility is not a good indicator of crisis, but that unexpectedly high and low volatilities are.
This is directly in line with what is predicted by theory and provides a validation of Minsky's hypothesis – stability is destabilizing.
Market volatility is of clear interest to policymakers, with the quote of chairwoman Yellen above just one example.
By documenting how volatility can affect the risk-taking behavior of economic agents and hence, the incidence of financial crises, policymakers and market participants alike would gain a valuable tool in understanding crises, tail events and systemic risk.
Author's note: Jon Danielsson thanks the Economic and Social Research Council (UK). Marcela Valenzuela thanks Fondecyt and Instituto Milenio.
Disclaimer: The views in this column are solely those of the authors and should not be interpreted as reflecting the views of the Board of Governors of the Federal Reserve System or of any other person associated with the Federal Reserve System.
Danielsson, J, M Valenzuela, and I Zer (2015), “Learning from History: Volatility and Financial Crises”, SSRN.
Minsky, H (1992), “The financial instability hypothesis”, Working Paper.
Reinhart, C M and K S Rogoff (2009), “This Time is Different: Eight Centuries of Financial Folly”, Princeton University Press.
Samuelson, P (1966), “Science and stocks”, Newsweek.
Taylor, S (2009), “Credit booms go wrong”, VoxEU, 8 December.
Yellen, J (2014), press conference, Federal Reserve Board, 18 June.