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Timetable (SYRW02)

Monitoring Systemic Risk: Data, Models and Metrics

Monday 22nd September 2014 to Friday 26th September 2014

Monday 22nd September 2014
10:30 to 11:15 Registration
11:15 to 11:30 Welcome from Christie Marr (INI Deputy Director) and Introduction from Rama Cont (Imperial College) INI 1
11:30 to 12:15 P Hartmann (European Central Bank)
Systemic Risk, Macroprudential Supervision and Regulation
The presentation will give a general overview of systemic risk, macroprudential supervision and regulation. It draws on more than 15 years of relevant experience in research and policy, including the results of the European System of Central Banks' Macroprudential Research Network (MaRs). The first part lays out some basic concepts needed for the analysis of systemic risk. The second part describes analytical tools for identifying the different forms of systemic risk and systemic financial instability. The third part reviews regulatory policy instruments that are discussed in the macroprudential policy debate. The various parts contain illustrations through research examples, in particular from the MaRs Network. The talk concludes with a discussion of research directions, which are particularly valuable from the angle of central banks and other macroprudential policy authorities.
INI 1
12:15 to 12:30 Discussion INI 1
12:30 to 13:30 Lunch at Wolfson Court
14:00 to 14:45 When Micro Prudence increases Macro Risk: The Destabilizing Effects of Financial Innovation, Leverage, and Diversification
Session: Network Models
We propose a simple analytically tractable model showing how basic common practices of accounting and risk management are able to destabilize the financial market, when feedback effects and illiquidity are taken into account. Specifically our model considers financial institutions having capital requirements in the form of VaR constraint and following standard mark-to-market and risk management rules. They also face a diversification cost that prevent them to fully diversify their portfolio. We provide a full analytical quantification of the multivariate feedback effects between investment prices and bank behavior induced by portfolio rebalancing in presence of asset illiquidity and show how changes in the constraints of the bank portfolio optimization endogenously drive the dynamics of the balance sheet aggregate of financial institutions and creates systemic risk. The model shows that when financial innovation reduces the cost of diversification below a given threshold, the strength (due to higher leverage) and coordination (due to similarity of bank portfolios) of feedback effects increase. Under fairly general assumptions on the institution's expectations on future asset volatility and correlation, we observe that when the diversification cost is decreased or the VaR constraint is loosened, the dynamics of the system develops cycles and eventually display a chaotic behavior. Further decrease triggers a transition to a non stationary dynamics characterized by steep growths (bubbles) and plunges (bursts) of market prices. (in collaboration with F. Corsi, S. Marmi, P. Mazzarisi)
INI 1
14:45 to 15:00 Discussion
Session: Network Models
INI 1
15:00 to 15:30 Afternoon Tea
Session: Network Models
15:30 to 16:15 C Brownlees (Universitat Pompeu Fabra)
Bank Credit Risk Networks: Evidence from the Eurozone Crisis
Session: Network Models
Co-authors: Christina Hans (Universitat Pompeu Fabra), Eulalia Nualarte (Universitat Pompeu Fabra)

The European financial crisis has shown that the credit risk of large financial institutions is highly interconnected as a results of a number of linkages between entities like exposure to common assets and interbank lending. In this work we propose a novel methodology to study credit risk interdependence in large panels of financial institutions. We introduce a credit risk model in which bank defaults can be triggered both by systematic economy wide and idiosyncratic bank specific shocks. The idiosyncratic shocks are assumed to have a sparse conditional dependence structure that we call the bank credit risk network. An estimation strategy based on CDS data and Lasso-type regression allows to estimate the parameters of the model and to recover the bank credit risk network structure. We apply this technique to analyse the interdependence of large European financial institutions between 2006 and 2013. Results show that the credit risk network captures a substantial amount of de pendence on top of what can be explained by systematic factors.

INI 1
16:15 to 16:30 Discussion
Session: Network Models
INI 1
16:30 to 17:15 Filling in the Blanks: Network Structure and Interbank Contagion
Session: Network Models
Co-authors : Kartik Anand (Bank of Canada), Ben Craig (Federal Reserve)

The network pattern of financial linkages is important in many areas of banking and finance. Yet bilateral linkages are often unobserved, and maximum entropy serves as the leading method for estimating counterparty exposures. This paper proposes an efficient alternative that combines information-theoretic arguments with economic incentives to produce more realistic interbank networks that preserve important characteristics of the original interbank market. The method loads the most probable links with the largest exposures consistent with the total lending and borrowing of each bank, yielding networks with minimum density. When used in a stress-testing context, the minimum density solution overestimates contagion, whereas maximum entropy underestimates it. Using the two benchmarks side by side defines a useful range that bounds the cost of systemic stress present in the true interbank network when counterparty exposures are unknown.

INI 1
17:15 to 17:30 Discussion
Session: Network Models
INI 1
17:30 to 18:30 Welcome Wine Reception
Tuesday 23rd September 2014
09:00 to 09:45 Systemic risk in derivatives markets: a pilot study using CDS data
Session: Counterparty Networks
Co-authors: Robleh Ali, Bank of England, Nick Vause, Bank of England and Filip Zikes, Bank of England

In this paper, we draw on network analysis and a sample of OTC derivatives data from a trade repository to demonstrate how the systemic importance of market participants in the derivatives markets may be measured. This is with a view to the trade repository data available to regulators becoming more comprehensive. We consider the importance of institutions both to the smooth functioning of OTC derivatives markets as well as their scope to spread financial distress, suggesting metrics from network analysis that effectively capture these two concepts. For some of these metrics, we find that direct counterparty positions or exposures serve as a good proxy for more comprehensive measures of systemic importance or risk that additionally take into account positions or exposures beyond those of immediate counterparties. This may be of interest to regulators who may only access counterparty data for firms that they regulate and may not collect data relating to the counterparties of those counterparties.

INI 1
09:45 to 10:00 Discussion
Session: Counterparty Networks
INI 1
10:00 to 10:45 Systemic Risk and Centralized Clearing of OTC Derivatives: A Network Approach
Session: Counterparty Networks
We analyze the effect of central clearing of OTC derivatives on the financial system stability by means of network simulation approach. We build simple but realistic networks of financial firms, connected by bilateral links and via a single CCP. We simulate balance sheets of firms and introduce shocks to the system to simulate defaults. The default mechanism and shock absorption in presence of the CCP is modeled in the way that maximally reflects the reality. We run Monte Carlo simulations of the networks' evolution and obtain their default and contagion characteristics. We analyze the likelihood of the CCP's default and compare the stability of the financial network with and without the CCP for various network configurations and market scenarios.

We find that, for a homogeneous financial system, the presence of the CCP increases the network's stability and the probability of the CCP's failure is virtually zero. However, for non-homogeneous financial networks, we find the opposite effects: the presence of the CCP leads in this case to a disproportionately large probability of contagion defaults, especially for smaller financial firms. Furthermore, we find that the probability of the CCP failure is substantial in this case, regardless of the capitalization requirements. In all, we find that non-homogeneous networks exhibit greater instability and contagion in the presence of the CCP: a worrying fact, given that any real financial system is highly inhomogeneous in terms of size and concentration.

INI 1
10:45 to 11:00 Discussion
Session: Counterparty Networks
INI 1
11:00 to 11:30 Morning Coffee
Session: Counterparty Networks
11:30 to 12:15 Margining with Multiple Central Counterparties
Session: Counterparty Networks
Co-authors: Paul Glasserman (Columbia University), Kai Yuan (Columbia University)

Spurred by regulatory efforts to mitigate systemic risk, many financial markets are shifting from a bilateral model of settlement towards central clearing. This is facilitated by a number of central counterparties (CCPs) that have recently emerged. We consider the issues that arise from the presence of multiple CCPs clearing a common set of financial products. In particular, we highlight a number of downstream consequences when such CCPs differ with respect to their margining policies.

INI 1
12:15 to 12:30 Discussion
Session: Counterparty Networks
INI 1
12:30 to 13:30 Lunch at Wolfson Court
14:00 to 14:45 Market diversity under Central Clearing
Co-authors: Allen Cheng (Johns Hopkins University), Sriram Rajan (Office of Financial Research)

We quantify the level of market concentration in a financial system where dealers hedge their operations by trading through a Central Counterparty (CCP). We partition individual dealer total assets into hedging and operating portfolios and model interactions of clearing entities with the CCP using Wright-Fisher diffusion dynamics.

We derive the unique Nash equilibrium attained when each dealer optimizes its hedge ratio. More specifically, we identify a relationship between the effectiveness of the clearing member's hedging portfolio transacted over the CCP and the volatility it experiences. As a consequence of this outcome and under optimal hedging, we show that market concentration tends to increase over time hence presenting systemic risk. We propose a self-financing tax and subsidy system that can effectively control market concentration. Using the margin model of Duffie, Scheicher and Vuillemey (2014), we calibrate our framework via an extensive dataset consisting of CDS bilateral exposures cleared through a US-based CCP. We analyze the calibrated model parameters and discuss implications for policy makers.

INI 1
14:45 to 15:00 Discussion INI 1
15:00 to 15:30 Afternoon Tea
15:30 to 16:15 Capital Adequacy, Pro-cyclicality and Systemic Risk
VaR-based capital adequacy as specified by Basel II accords is subject to procyclical effects, potentially aggravating systemic risk, when it is supposed to mitigate it, as observed during 2008 crisis. Supposed improvements in Basel III, not only don’t resolve the problem, but introduce new sources of systemic risk. The method proposed here for computing the regulatory capital of financial institutions avoids the pitfalls of the Value-at-Risk. The computation is based on a generalized stress testing method, with the following principles: (i) market scenarios are defined by the regulator; (ii) institutions compute the impact of scenarios defined by the regulator and report them; (iii) the regulator not only counts the number of violations of the risk reporting but also their size; (iv) the regulatory capital is a multiple of the worst stress test, where the multiplier depends on the size and the frequency of the violations. By letting the institutions estimate their sensitivities to extreme market shifts, the regulator not only avoids a costly burden, but also keeps institutions responsible for their reporting. On the other hand, by keeping control on the list of stress tests involved in the computation of the capital, the regulator offers itself a very strong lever to prevent speculative bubbles, by making them costly in terms of capital requirements.
INI 1
16:15 to 16:30 Discussion INI 1
16:30 to 17:15 Assessing Measures of Order Flow Toxicity and Early Warning Signals for Market Turbulence
Co-authors: Oleg Bondarenko (University of Illinois at Chicago), Maria Gonzalez-Perez (CUNEF, Madrid)

Following the much publicized "flash crash" in the U.S. financial markets on May 6, 2010, much work has been done in terms of developing reliable warning signals for impending market stress. However, this has met with limited success, except for one measure. The VPIN, or Volume-synchronized Probability of INformed trading, metric is introduced by Easley, Lopez de Prado and O'Hara (ELO) as a real-time indicator of order flow toxicity. They find the measure useful in predicting return volatility and conclude it, indeed, may help signal impending market turmoil. The VPIN metric involves decomposing volume into active buys and sells. We use the best-bid-offer (BBO) files from the CME Group to construct highly accurate trade classification measures for the E-mini S&P 500 futures contract. Against this benchmark, the ELO Bulk Volume Classification (BVC) scheme is inferior to a standard tick rule based on individual transactions. Moreover, when VPIN is constructed from an accurate classification, it behaves in a diametrically opposite way to BVC-VPIN. We also find the latter to have forecast power for volatility solely because it generates systematic classification errors that are correlated with trading volume and return volatility. Controlling for trading intensity and volatility, the BVC-VPIN measure has no incremental predictive power for future volatility. We conclude that VPIN is not suitable for capturing order flow toxicity or signaling ensuing market turbulence. In an extension, we also explore high-frequency VIX measures as real-time indicators of market stress. We find it critical to control for confounding effects in the computation of the index. In particular, during stressful periods, when a "fear gauge" is most needed, VIX is least reliable. As an alternative, we construct a real-time "corridor" VIX measure. We document that this index performs vastly better during stressful episodes like the financial crisis and the flash crash.

INI 1
17:15 to 17:30 Discussion INI 1
Wednesday 24th September 2014
09:00 to 09:45 K Yuan (London School of Economics)
Network Risk and Key Players: A Structural Analysis of Interbank Liquidity
Session: Funding Liquidity and Systemic Risk
Co-authors: Edward Denbee, Christian Julliard and Ye Li

We model banks' liquidity holding decision as a simultaneous game on an interbank borrowing network. We show that at the Nash equilibrium, the contributions of each bank to the network liquidity level and liquidity risk are distinct functions of its indegree and outdegree Katz-Bonacich centrality measures. A wedge between the planner and the market equilibria arises because individual banks do not internalize the effect of their liquidity choice on other banks' liquidity benefit and risk exposure. The network can act as an absorbent or a multiplier of individual banks' shocks. Using a sterling interbank network database from January 2006 to September 2010, we estimate the model in a spatial error framework, and find evidence for a substantial, and time-varying, network risk: in the period before the Lehman crisis, the network is cohesive and liquidity holding decisions are complementary and there is a large network liquidity multiplier; during the 2007-08 crisis, the network becomes less clustered and liquidity holding less dependent on the network; after the crisis, during Quantitative Easing, the network liquidity multiplier becomes negative, implying a lower network potential for generating liquidity. The network impulse-response functions indicate that the risk key players during these periods vary, and are not necessarily the largest borrowers.

INI 1
09:45 to 10:00 Discussion
Session: Funding Liquidity and Systemic Risk
INI 1
10:00 to 10:45 The Euro interbank repo market
Session: Funding Liquidity and Systemic Risk
Co-authors: Angelo Ranaldo (University of St. Gallen), Jan Wrampelmeyer (University of St. Gallen)

In the aftermath of the recent financial crisis, policy makers and regulators have initiated enormous efforts to reform financial markets in general and to stabilize banks' funding in particular. Is there a market design for short-term funding that ensures that banks can satisfy their liquidity needs even during severe crisis periods like the 2007-2009 financial crisis or the European sovereign debt crisis? Can a well-designed private market encourage lending even when aggregate risk is large and overall funding conditions tighten? This paper shows that such a private funding market already exists, namely the central counterparty (CCP)-based euro interbank repo market. Using a unique and comprehensive dataset, we provide the first systematic study of this important funding market and show that it is resilient during crisis episodes. If the CCP-based infrastructure is combined with very safe collateral, the market even acts as a shock absorber, in the sense that repo volume increases with risk, while spreads, maturities, and haircuts remain stable. Our results are consistent with banks trusting the CCP-based repo market to be a safe venue to hoard liquidity.

INI 1
10:45 to 11:00 Discussion
Session: Funding Liquidity and Systemic Risk
INI 1
11:00 to 11:30 Morning Coffee
Session: Funding Liquidity and Systemic Risk
11:30 to 12:15 J-C Heam (Autorité de Contrôle Prudentiel (ACPR))
Funding liquidity from a regulatory perspective
Session: Funding Liquidity and Systemic Risk
Co-author: Christian Gourieroux (CREST and University of Toronto)

In the Basel regulation, only the uncertainty on the asset price or on the default of borrowers is considered while the uncertainty about depositors’ or investors’ behaviors on the liability side is neglected. In contrast, we consider risks on both the asset and liability sides. We adapt usual risk measures, such as Value-at-Risk or Probability of Default, to disentangle the losses due to liquidity shortage from the losses due to a lack of solvency. Applied to US data, these additional terms are significant when shocks on prices and volumes are correlated. Consequently, the regulatory reserves for solvency risk cannot be set independently of the reserves for liquidity risk. We show how to set and manage jointly two reserve accounts to control the different risks.

INI 1
12:15 to 12:30 Discussion
Session: Funding Liquidity and Systemic Risk
INI 1
12:30 to 13:30 Lunch at Wolfson Court
14:00 to 14:45 Liquidity spillovers in the German banking system
Session: Funding Liquidity and Systemic Risk
Co-author: Frank Heid (Deutsche Bundesbank)

This paper estimates spillover or contagion effects in bank liquidity for a panel of German banks. To estimate liquidity spillover effects, a spatial econometric approach is adopted, in which an economic distance is introduced that describes the connectedness between each pair of banks. This distance is constructed using interbank lending operations. Given this distance measure, the set of banks form a network, and spillover effects can be estimated in this network by employing the spatial autoregressive model. The results from the instrumental variable estimation indicate that there is a positive and significant liquidity spillover effect for the period of 2008 to 2013. Furthermore, spatial impulse response functions are estimated suggesting that shocks liquidity in this network are not very persistent over time since they do not diffuse over a horizon longer than one week.

INI 1
14:45 to 15:00 Discussion
Session: Funding Liquidity and Systemic Risk
INI 1
15:00 to 15:30 Afternoon Tea
Session: Funding Liquidity and Systemic Risk
15:30 to 16:15 T Ota (Bank of England)
Measuring Systemic Illiquidity and Optimal Policy Options: A Dynamic Approach
Session: Funding Liquidity and Systemic Risk
Co-authors: Gerardo Ferrara (University of Turin), Sam Langfield (ECB), Zijun Liu (Bank of England)

This paper studies systemic liquidity risk in UK interbank system in a dynamic context. We estimate the daily network structures of banks’ short-term funding (up to 30 days) with various confidential datasets, and identify (1) banks that fall short of liquidity by themselves (individually illiquid banks); (2) banks that fall short of liquidity because the counterparties fail to repay their debts to the banks (systemically illiquid banks); and (3) the timing of these banks falling short of liquidity. In order to consider the timing of defaults, not only the number of defaults which normal contagion models focus on, we test a dynamic financial contagion model for the first time in the literature. This dynamic feature is important particularly when we discuss liquidity regulations such as LCR.

We obtain outcomes by the numerical simulations of the dynamic contagion model, with assumptions consistent with PRA’s micro-prudential liquidity monitoring schemes. The outcomes so far show the existence of significant systemic liquidity risk when banks do not have sufficient liquidity buffers. To the authors’ knowledge, this is the first paper in the literature studying interbank systemic liquidity risk with real datasets.

Based on the estimated systemic liquidity risk, we will consider the optimal liquidity provision policies to minimise the systemic liquidity risk, by solving a dynamic programming model.

INI 1
16:15 to 16:30 Discussion
Session: Funding Liquidity and Systemic Risk
INI 1
16:30 to 17:15 Quantifying contagion in funding markets: An application to stress-testing
Session: Funding Liquidity and Systemic Risk
In the aftermath of the financial crisis, stress-testing has become mandatory for banks. We propose a tractable model at the frontier of systemic risk stress-testing. Our theoretically-based stress-testing framework integrates credit risk, liquidity risk and contagion risk. We contribute to the literature in different ways. We first generalize the theoretical contagion results of Manz (2010) to an N-banks world, show the uniqueness and existence of an equilibrium in that context, and characterize the contagion dynamics. We then quantify the potential important contribution of information contagion to systemic risk and illustrates why ensuring that each bank is liquid when considered in isolation is not enough. Each bank must also be sufficiently liquid to resist to contagion effects. Finally, we illustrates how crucial are market participants' beliefs about an eventual central bank intervention in the unfolding of events when the financial system is in a fragile state.
INI 1
17:15 to 17:30 Discussion
Session: Funding Liquidity and Systemic Risk
INI 1
19:30 to 22:00 Conference Dinner at Cambridge Union Society hosted by Cambridge Dining Co.
Thursday 25th September 2014
09:00 to 09:45 Vulnerable Banks
Session: Fire Sales and Price-Mediated Contagion
Based on joint work with David THESMAR (HEC) and Robin Greenwood (NBER).

When a bank experiences a negative shock to its equity, one way to return to target leverage is to sell assets. If asset sales occur at depressed prices, then one bank's sales may impact other banks with common exposures, resulting in contagion. We propose a simple framework that accounts for how this effect adds up across the banking sector. Our framework explains how the distribution of bank leverage and risk exposures contributes to a form of systemic risk. We compute bank exposures to system-wide deleveraging, as well as the spillover of a single bank's deleveraging onto other banks. We show how our model can be used to evaluate a variety of crisis interventions, such as mergers of good and bad banks and equity injections. We apply the framework to European banks vulnerable to sovereign risk in 2010 and 2011.

INI 1
09:45 to 10:00 Discussion
Session: Fire Sales and Price-Mediated Contagion
INI 1
10:00 to 10:45 Fire sales, endogenous risk and price-mediated contagion
Session: Fire Sales and Price-Mediated Contagion
Fire sales of assets during financial crises have been recognized as an important channel of contagion and amplification of losses We present a simple model of feedback and contagion through fire sales triggered by an initial macro-shock to a set of leveraged portfolios with common exposures and subject to leverage constraints. We show that the threshold nonlinearity inherent in the onset of fire sales plays a key role in the amplifying of shocks to portfolios, and investigate the role of portfolio constraints -leverage constraints and capital ratios- and the tradeoff between diversification and 'diversity' in determining the magnitude of contagion. The competition between contagion across portfolios and market impact of liquidation ('self-contagion') leads to a non-monotone dependence of the system-wide losses on parameters describing portfolio concentration, with different results depending on the severity of the stress scenarios considered. In particular, the model indicates that, for a given level of severity of the stress, the onset of contagion occurs when leverage is allowed to exceed a critical level, a criterion which can be used to calibrate regulatory constraints on leverage.
INI 1
10:45 to 11:00 Discussion
Session: Fire Sales and Price-Mediated Contagion
INI 1
11:00 to 11:30 Morning Coffee
Session: Fire Sales and Price-Mediated Contagion
11:30 to 12:15 Networks of Common Asset Holdings: Aggregation and Measures of Vulnerability
Session: Fire Sales and Price-Mediated Contagion
Co-author : Anton BRAVERMAN (Cornell)

This paper quantifies the interrelations induced by common asset holdings among financial institutions. A network representation emerges, where nodes represent portfolios and edge weights aggregate the common asset holdings and the liquidity of these holdings. As a building block, we introduce a simple model of order imbalance that estimates price impacts due to liquidity shocks. In our model, asset prices are set by a competitive risk-neutral market maker and the arrival rates for the buyers and sellers depend on the common asset holdings. We illustrate the relevance of our aggregation method and the resulting network representation using data on mutual fund asset holdings. We introduce three related measures of vulnerability in the network and demonstrate a strong dependence between mutual fund returns and these measures.

INI 1
12:15 to 12:30 Discussion
Session: Fire Sales and Price-Mediated Contagion
INI 1
12:30 to 13:30 Lunch at Wolfson Court
14:00 to 14:45 System-wide risk and systemic importance: an incomplete review of metrics and data
Session: Systemic Risk Monitoring
I. Two major competing types of systemic-risk metrics are: (i) quantiles, e.g. VaR; and (ii) tail expectations, e.g. expected shortfall (ES). I.a. The choice of a risk metric is often motivated with: (i) properties of the metric’s estimator; (ii) computational convenience. But different metrics correspond to different economic concepts and thus to different policy objectives (e.g. to reduce system-wide risk vs. to build a war chest for a systemic crisis). Similar tension between alternative metrics exists in an investment portfolio context.

I.b. Given a metric for system-wide risk, the Shapley value offers a convenient prism for comparing alternative measures of the systemic importance of individual institutions. It also allows for deriving important properties of these measures and for identifying the policy contexts in which they should be used.

I.c. There is a subtle difference between the impact of an institution on system-wide risk and the presence of an institution in systemic events. Ignoring this difference could lead to grossly misleading conclusions as regards systemic importance.

II. Data availability shapes existing approaches to measuring system-wide risk and systemic importance. One approach builds on a structural model of system-wide risk and relies on balance sheet data and commercial vendors’ estimates of individual riskiness. Another approach builds on reduced-form models and relies on market-price data.

II.a. The first approach has revealed a material impact of the system's network structure on system-wide risk and the systemic importance of individual institutions. The scarcity of real-world data on such structures is thus a major problem in practical applications. II.b. The second approach makes it possible to study tail interdependence across institutions. Tools based on extreme-value theory deliver estimates of such interdependence, which contributes materially to measures of systemic importance.

Related Links: http://www.sciencedirect.com/science/article/pii/S1042957313000326 - "Measuring the systemic importance of interconnected banks" http://www.bis.org/publ/work308.htm - "Attributing systemic risk to individual institutions" http://www.bis.org/publ/qtrpdf/r_qt1306g.htm - "Looking at the tail: price-based measures of systemic importance"

INI 1
14:45 to 15:00 Discussion
Session: Systemic Risk Monitoring
INI 1
15:00 to 15:30 Afternoon Tea
Session: Systemic Risk Monitoring
15:30 to 17:00 Monitoring systemic risk: indicators and data requirements
Session: Systemic Risk Monitoring
Laurent Clerc (Banque de France)

Robert Engle (NYU Stern)

Martin Summer (Austrian National Bank)

INI 1
Friday 26th September 2014
09:00 to 09:45 Measuring and allocating systemic risk
Session: Systemic Risk Indicators
Co-author: Markus Brunnermeier (Princeton)

This paper develops a framework for measuring, allocating and managing systemic risk. SystRisk, our measure of total systemic risk, captures the a priori cost to society for providing tail-risk insurance to the financial system. Our allocation principle distributes the total systemic risk among individual institutions according to their size-shifted marginal contributions. To describe economic shocks and systemic feedback effects we propose a reduced form stochastic model that can be calibrated to historical data. We also discuss systemic risk limits, systemic risk charges and a cap and trade system for systemic risk.

INI 1
09:45 to 10:00 Discussion
Session: Systemic Risk Indicators
INI 1
10:00 to 10:45 Conditional Quantiles and Tail Dependence
Session: Systemic Risk Indicators
Co-author: Claudia Czado

Conditional quantile estimation is a crucial step in many statistical problems. For example, the recent work on systemic risk relies on estimating risk conditional on an institution being in distress or conditional on being in a crisis (Adrian and Brunnermeier (2010), Brownlees and Engle (2011)). Specifically, the CoVaR systemic risk measure is based on a conditional quantile when one of the variable is in the tail of the distribution. In this paper, we study properties of conditional quantiles and how they relate to properties of the dependence. In particular, we provide a new graphical characterization of tail dependence and intermediate tail dependence from plots of conditional quantiles with normalized marginal distributions. A popular method to estimate conditional quantiles is the quantile regression (Koenker (2005), Koenker and Bassett (1978)). We discuss the properties and pitfalls of this estimation approach.

INI 1
10:45 to 11:00 Discussion
Session: Systemic Risk Indicators
INI 1
11:00 to 11:30 Morning Coffee
Session: Systemic Risk Indicators
11:30 to 12:15 R Engle (New York University)
The Prospects for Global Financial Stability
Session: Systemic Risk Indicators
Nobel Prize-winning economist Robert F. Engle will present his thoughts on The Prospects for Global Financial Stability during the final session of Monitoring Systemic Risk: Data, Models and Metrics, the second workshop on the INI programme Systemic Risk: Mathematical Modelling and Interdisciplinary Approaches.

Prof Engle is the Michael Armellino Professor of Finance at the New York University Stern School of Business. He was awarded the 2003 Nobel Prize in Economics, which he shared with Prof Clive W. J. Granger of the University of California, San Diego, for his work developing new statistical models of volatility that captured the tendency of stock prices and other financial variables to move between high volatility and low volatility periods.

Amongst other achievements, he is also co-founding president of the Society for Financial Econometrics, a nonprofit group based at New York University. Prof Engle earned his doctorate in Economics and a Master of Science in Physics from Cornell University following his Bachelor of Science which he earned at Williams College. He taught economics at MIT and the University of California, San Diego before joining New York University in 2000.

INI 1
12:15 to 12:30 Discussion
Session: Systemic Risk Indicators
INI 1
12:30 to 13:30 Lunch at Wolfson Court
University of Cambridge Research Councils UK
    Clay Mathematics Institute London Mathematical Society NM Rothschild and Sons