1. Monitoring Systemic Risk with V-LAB SYstemic Risk TOmography: Signals, Measurements, Transmission Channels, and Policy Interventions Robert Engle Director of Volatility Institute At NYU Stern Brescia, 25 June 2013

2. The Volatility Laboratory or V-LAB is a public website with a wide range of risk measures that are updated daily. The site is a laboratory to determine the accuracy and reliability of cutting edge statistical models of financial risk. The site is designed to bring new academic developments to practitioners and regulators in a timely way. The Volatility Institute is supported by generous funding from the Sloan Foundation, Banque de France, Armellino Foundation, Deutsche Bank, BlackRock, and our collaborators UNSW and Universite de Lausanne 3. Or Google vlab There are four main regions on V-LAB Volatility Correlation Systemic Risk Long Run Risk Lets take a look at each before turning to systemic risk. 4. VaR is the 1% quantile of returns for some asset one day in the future. It is a very widely used measure of risk but is clearly a short run measure of risk. What is the VaR one month or one year from now? How much can some asset decline in a year? Measuring the risk that the risk can change Use GARCH and options to forecast quantiles. 5. In the global financial crisis of 2007-2009, we learned that failure of the financial system could have massive effects on the real economy, potentially for years to come. The sovereign debt crisis in Europe is a reminder that even though the causes may appear different, financial failure has real effects. How can we forsee and prevent these events? 6. 6/26/2013 VOLATILITY INSTITUTE 18 7. We saw that the Lehman bankruptcy began the worst episode of the global financial crisis. But it coincided with deep distress at FANNY and FREDDIE, Citi, Bank of America, Merrill Lynch, Goldman Sachs, Morgan Stanley, AIG, WAMU, Wachovia, and many more. Lehman was not a domino this was a tsunami. Weakness of the financial sector as a whole is the most important determinant of a financial crisis. It is not enough that one bank is undercapitalized. 8. How much capital would a financial institution need to raise in order to function normally if we have another financial crisis? We measure this econometrically based on market data on equities and balance sheet data on liabilities. We update weekly on V-LAB for US and Global financial firms. We call this SRISK. Principle investigators: Viral Acharya, Matt Richardson and me at the Volatility Institute at NYUs Stern School. Collaboration with HEC Lausanne and the Institute for Global Finance at University of New South Wales. Contributions by Christian Brownlees, Rob Capellini, Diane Perriet, Emil Siriwardane. References: Acharya, Pedersen, Phillipon, Richardson Measuring Systemic Risk (2010); Acharya, Engle, Richardson Capital Shortfall, A New Approach to Ranking and Regulating Systemic Risks, AEAPP (2012), Brownlees and Engle, Volatilities, Correlations and Tails for Systemic Risk Measurement,2010 9. Regulators measure this based on supervisory data and stress scenarios. Many measures based on public data are being developed. See the surveys by Brunnermeier and Oehmke and by Bisias, Flood, Lo and Valvanis Some of these measures are firm specific such as CoVaR and SRISK. Others are financial industry quality measures such as volatility or liquidity. Some measures are based on a network model and others such as SRISK are based on a Tsunami model. 6/26/2013 VOLATILITY INSTITUTE 21 10. SRISK is computed from: Where k is a prudential level of equity relative to assets taken to be 8% (and 5.5% for IFRS firms) and LRMES is the decline in equity values to be expected if there is another financial crisis. SRISK depends upon size, leverage and risk. , , ,1 1 i t t i t t n t n t n t n t i t i t SRISK E Capital Shortfall Crisis E k Debt Equity Equity Crisis kDebt k LRMES Equity 11. Bank of America has a market cap of $141billion. Its accounting liabilities are $2.0 trillion for a leverage ratio of 14.9 If we have another financial crisis which is assumed to be a fall of 40% in broad US equities over six months, then we estimate shares in BAC will fall by 50%. This reflects a Dynamic Conditional Beta of 1.0 today that will move in the future due to mean reversion in volatilities and correlations and also will rise with downside returns. SRISK = $91 billion. It is undercapitalized somewhat today and this will be more severe under the stress of an equity decline. 12. Credit Agricole has a market cap of $23 billion It has liabilities of $2.2 trillion for a leverage ratio of 102. Any fluctuation in asset or liability valuations can easily move the firm into bankruptcy. Most of the capital shortfall is needed to bring the leverage down now. The risk is only a small part of the capital shortfall calculation. Most likely, Credit Agricole is no longer making loans except possibly the most secure. 13. If any firms have high SRISK, they will recognize their vulnerability and will begin to delever and derisk by selling assets and making fewer loans. If many firms have high SRISK, this will impact the real economy. As the macro economy slows, stock prices will fall, volatility will rise, and SRISK will go up more. 14. Investors recognize financial institution weakness and lower valuations, increasing SRISK Forward looking investors could make this happen in one step. Bankruptcies and other failures will occur until eventually, the return to capital is high enough to bring new capital to the industry. 15. The spiral can be arrested before the bottom with taxpayer money. However, this will erode market discipline and may impose huge regulatory costs on the financial sector going forward. Thus regulation is needed in advance. Ideally it would be countercyclical. 16. 6/26/2013 VOLATILITY INSTITUTE 28 17. Externalities if only one firm has high SRISK, there is no spiral. Competition! Implicit and Explicit government guarantees such as deposit insurance or too big to fail assurances Regulatory incentives that encourage investments that might not be prudent. Miscalculation 18. 6/26/2013 VOLATILITY INSTITUTE 30 DYNAMIC CONDITIONAL BETA 19. DYNAMICCONDITIONALBETA 20. ARE BETAS CONSTANT? LEAST SQUARES MODELS ARE USED IN COUNTLESS EMPIRICAL STUDIES IN FINANCE AND ECONOMICS RARELY IS THE HYPOTHESIS THAT BETAS ARE CONSTANT GIVEN CAREFUL SCRUTINY WHAT TOOLS DO WE HAVE? 21. MODELLING TIME VARYING BETA ROLLING REGRESSION INTERACTING VARIABLES WITH TRENDS, SPLINES OR OTHER OBSERVABLES TIME VARYING PARAMETER MODELS BASED ON KALMAN FILTER STRUCTURAL BREAK AND REGIME SWITCHING MODELS EACH OF THESE SPECIFIES CLASSES OF PARAMETER EVOLUTION THAT MAY NOT BE CONSISTENT WITH ECONOMIC THINKING OR DATA. 22. THE BASIC IDEA IF is a collection of k+1 random variables that are distributed as Then Hence: , , 1,...,t ty x t T , ,, 1 , ,, ~ , , yy t yx ty tt t t t xy t xx tx tt H Hy N H N H Hx F 1 1 1 , , , , , , , ,, ~ ,t t t y t yx t xx t t x t yy t yx t xx t xy ty x N H H x H H H H F 1 , ,t xx t xy tH H 23. HOW TO ESTIMATE H Econometricians have developed a wide range of approaches to estimating large covariance matrices. These include Multivariate GARCH models such as VEC and BEKK Constant Conditional Correlation models Dynamic Conditional Correlation models Dynamic Equicorrelation models Multivariate Stochastic Volatility Models Many many more Exponential Smoothing with prespecified smoothing parameter. 24. IS BETA CONSTANT? For none of these methods will beta appear constant. In the one regressor case this requires the ratio of to be constant. This is a non-nested hypothesis (or more technically a partially nested hypothesis) , ,/yx t xx th h 25. ARTIFICIAL NESTING Consider the model where means element by element multiplication or Hadamard product: If lambda is zero, the parameters are constant If phi is zero, the parameters are time varying. If both are non-zero, the nested model may be entertained. ' 't t t t ty x x v o 26. A. CALDER 1973, LA PORTE DE LESPACE 27. Combining the constant beta and dynamic conditional beta into one regression: Where u will be an MA(1) GARCH Updated weekly for 1200 Global financial institutions Results on V-LAB , 1 1 , , 2 2 , , 1i t i t m t i t m t tR R R u 28. 6/26/2013 VOLATILITY INSTITUTE 42 29. 6/26/2013 VOLATILITY INSTITUTE 43 30. 6/26/2013 VOLATILITY INSTITUTE 44 31. 6/26/2013 VOLATILITY INSTITUTE 45 32. 6/26/2013 VOLATILITY INSTITUTE 46 33. 6/26/2013 VOLATILITY INSTITUTE 50 34. 6/26/2013 VOLATILITY INSTITUTE 51 35. 6/26/2013 VOLATILITY INSTITUTE 52 36. How can you validate a systemic risk model? Do we get advanced warning of systemic events? 6/26/2013 VOLATILITY INSTITUTE 55 37. A Look Back 38. 6/26/2013 VOLATILITY INSTITUTE 58 39. A small piece of evidence. Monthly SRISK, calculated recursively at the end of each month and summed over all US financial institutions. Tested with monthly industrial production and unemployment. All variables log differenced, 3 lags of all variables, OLS estimation 40. SRISK INDPRD URATE SRISK 4.31 0.02 INDPRD 20.65*** 8.99** URATE 0.01 7.39*** 41. November 4, 2011 BIS with FSB of the G-20 released its list of Global Systemically Important Financial Institutions GSIFIs. They listed 17 European Banks November, our list of the top 17 banks is identical with one exception: We have Intesa Sanpaolo instead of Dexia Furthermore, we have ranked these It took BIS two years and many meetings. We have now updated many times. 42. See Acharya, Engle, Pierret Testing Macroprudential Stress Tests: The Risk of Regulatory Risk Weights , To be presented at Carnegie Rochester Conference in October. Findings: both European and US FED stress tests have rankings of firms similar to VLAB when measured relative to total assets. When measured relative to risk weighted assets, they are not similar. VLAB has slightly better forecast performance. Risk weighted measures are negatively correlated with outcomes and risk. 43. 6/26/2013 VOLATILITY INSTITUTE 66 44. This project is funded by the European Union under the 7th Framework Programme (FP7-SSH/2007-2013) Grant Agreement n320270 ! ! ! ! ! ! ! www.syrtoproject.eu This document reflects only the authors views. The European Union is not liable for any use that may be made of the information contained therein.