nep-rmg New Economics Papers
on Risk Management
Issue of 2012‒09‒09
seventeen papers chosen by
Stan Miles
Thompson Rivers University

  1. Financial Network Systemic Risk Contributions By Nikolaus Hautsch; Julia Schaumburg; Melanie Schienle;
  2. Systemic Risk and the European Banking Sector By Nicola Borri; Marianna Caccavaio; Giorgio Di Giorgio; Alberto Maria Sorrentino
  3. Measuring financial risk and portfolio optimization with a non-Gaussian multivariate model By Kim, Young Shin; Giacometti, Rosella; Rachev, Svetlozar T.; Fabozzi, Frank J.; Mignacca, Domenico
  4. Diversity among banks may increase systemic risk By Teruyoshi Kobayashi
  5. An Empirical Study of the Mexican Banking System's Network and its Implications for Systemic Risk By Serafín Martínez-Jaramillo; Biliana Alexandrova-Kabadjova; Bernardo Bravo-Benítez; Juan Pablo Solórzano-Margain
  6. An Early-warning and Dynamic Forecasting Framework of Default Probabilities for the Macroprudential Policy Indicators Arsenal By Xisong Jin; Francisco Nadal De Simone
  7. Scenarios and their Aggregation in the Regulatory Risk Measurement Environment By Andreas Haier; Thorsten Pfeiffer
  8. Optimal Hedging when the Underlying Asset Follows a Regime-switching Markov Process By Pascal François; Geneviève Gauthier; Frédéric Godin
  9. Statistical analysis of the Lognormal-Pareto distribution using Probability Weighted Moments and Maximum Likelihood By Marco Bee
  10. Bank Leverage Shocks and the Macroeconomy: a New Look in a Data-Rich Environment By Jean-Stéphane Mésonnier; Dalibor Stevanovic
  11. How big is too big? Critical Shocks for Systemic Failure Cascades By Claudio J. Tessone; Antonios Garas; Beniamino Guerra; Frank Schweitzer
  12. Algorithm for identifying systemically important banks in payment systems By Soramäki, Kimmo; Cook, Samantha
  13. Central Banking for Financial Stability in Asia By Kawai, Masahiro; Morgan, Peter J.
  14. The CAPM Risk Adjustment Needed for Exact Aggregation over Financial Assets By William Barnett; Yi Liu; Haiyang Xu; Mark Jensen
  15. Carry Trade and Liquidity Risk: Evidence from Forward and Cross-Currency Swap Markets By Erik Schlogl; Yang Chang
  16. Quantifying the impact of higher capital requirements on the Swiss economy By Georg Junge; Peter Kugler
  17. Finding communities in credit networks By Bargigli, Leonardo; Gallegati, Mauro

  1. By: Nikolaus Hautsch; Julia Schaumburg; Melanie Schienle;
    Abstract: We propose the realized systemic risk beta as a measure for financial companies’ contribution to systemic risk given network interdependence between firms’ tail risk exposures. Conditional on statistically pre-identified network spillover effects and market and balance sheet information, we define the realized systemic risk beta as the total time-varying marginal effect of a firm’s Value-at-risk (VaR) on the system’s VaR. Suitable statistical inference reveals a multitude of relevant risk spillover channels and determines companies’ systemic importance in the U.S. financial system. Our approach can be used to monitor companies’ systemic importance allowing for a transparent macroprudential regulation.
    Keywords: Systemic risk contribution, systemic risk network, Value at Risk, network topology, two-step quantile regression, time-varying parameters
    JEL: G01 G18 G32 G38 C21 C51 C63
    Date: 2012–08
  2. By: Nicola Borri (LUISS Guido Carli University, Department of Economics and Finance and CASMEF); Marianna Caccavaio (LUISS Guido Carli University, Department of Economics and Finance and CASMEF); Giorgio Di Giorgio (LUISS Guido Carli University, Department of Economics and Finance and CASMEF); Alberto Maria Sorrentino (University of Rome Tor Vergata and CASMEF)
    Abstract: Systemic risk is the risk of a collapse of the entire financial system, typically triggered by the default of one, or more, large and interconnected financial institutions. In this paper we estimate the systemic risk contribution of each financial institution in a large sample of European banks. We follow a recent methodology first proposed by Adrian and Brunnermeier (2011) based on the CoVaR and find that size is a predictor of a bank contribution to systemic risk, but it is not the only one. Leverage is important as well. Also, banks that have their headquarters in countries with a more concentrated banking system tend to contribute more to European wide systemic risk, even after controlling for their size. Therefore, any financial regulation designed only to curb banksÕ size would not completely eliminate systemic risk. On average, balance sheet variables are very weak predictors of banksÕ contribution to systemic risk, if compared to market based variables. Accounting rules provide enough degrees of freedom to make balance sheet less informative than market prices. As a result, measures of risk based on higher frequency market prices are more likely to anticipate systemic risk.
    Keywords: Systemic Risk, SIFIs, European Banking System, CoVaR.
    JEL: G01 G18 G21 G32
    Date: 2012
  3. By: Kim, Young Shin; Giacometti, Rosella; Rachev, Svetlozar T.; Fabozzi, Frank J.; Mignacca, Domenico
    Abstract: In this paper, we propose a multivariate market model with returns assumed to follow a multivariate normal tempered stable distribution. This distribution, defined by a mixture of the multivariate normal distribution and the tempered stable subordinator, is consistent with two stylized facts that have been observed for asset distributions: fat-tails and an asymmetric dependence structure. Assuming infinitely divisible distributions, we derive closed-form solutions for two important measures used by portfolio managers in portfolio construction: the marginal VaR and the marginal AVaR. We illustrate the proposed model using stocks comprising the Dow Jones Industrial Average, first statistically validating the model based on goodness-of-fit tests and then demonstrating how the marginal VaR and marginal AVaR can be used for portfolio optimization using the model. Based on the empirical evidence presented in this paper, our framework offers more realistic portfolio risk measures and a more tractable method for portfolio optimization. --
    Keywords: portfolio risk,portfolio optimization,portfolio budgeting,marginal contribution,fat-tailed distribution,multivariate normal tempered stable distribution
    JEL: C58 C61 G11 G32
    Date: 2012
  4. By: Teruyoshi Kobayashi (Graduate School of Economics, Kobe University)
    Abstract: The problem of how to stabilize the financial system has attracted considerable attention since the global financial crisis of 2007-2009. Recently, Beal et al. (2011, gIndividual versus systemic risk and the regulatorfs dilemmah, Proc Natl Acad Sci USA 108: 12647-12652) demonstrated that higher portfolio diversity among banks would reduce systemic risk by decreasing the likelihood of simultaneous defaults. Here, I show that this result is overturned once a financial network comes into play. In a networked financial system, the failure of one bank can bring about a contagion of failure. The optimality of individual risk diversification, as opposed to economy-wide risk diversification, is thus restored. I also present a new method to quantify how the diversity of bank size affects the stability of a financial system. It is shown that a higher diversity of bank size itself makes the financial system more fragile even if external risk exposure is controlled for. The main reason for this is that larger banks are more likely to become a gsuper spreaderh of infectious defaults. In this situation the social cost of letting a bank fail is not uniform and depends on the size of the failing bank. This strongly implies that larger banks are systemically more important than smaller banks, and preventing large banks from being exposed to high external risks would therefore be the most effective vaccine against financial crisis.
    Keywords: Systemic risk, financial crisis, financial network
    JEL: C63 D85 G01
    Date: 2012–08
  5. By: Serafín Martínez-Jaramillo; Biliana Alexandrova-Kabadjova; Bernardo Bravo-Benítez; Juan Pablo Solórzano-Margain
    Abstract: With the purpose of measuring and monitoring systemic risk, some topological properties of the interbank exposures and the payments system networks are studied. We propose non-topological measures which are useful to describe the individual behavior of banks in both networks. The evolution of such networks is also studied and some important conclusions from the systemic risks perspective are drawn. A unified measure of interconnectedness is also created. The main findings of this study are: the payments system network is strongly connected in contrast to the interbank exposures network; the type of exposures and payment size reveal different roles played by banks; behavior of banks in the exposures network changed considerably after Lehmans failure; interconnectedness of a bank, estimated by the unified measure, is not necessarily related with its assets size.
    Keywords: Systemic risk, financial networks, payment systems.
    JEL: C01 C02 C44 C63 G21
    Date: 2012–08
  6. By: Xisong Jin; Francisco Nadal De Simone
    Abstract: The estimation of banks? marginal probabilities of default using structural credit risk models can be enriched incorporating macro-financial variables readily available to economic agents. By combining Delianedis and Geske?s model with a Generalized Dynamic Factor Model into a dynamic t-copula as a mechanism for obtaining banks? dependence, this paper develops a framework that generates an early warning indicator and robust out-of-sample forecasts of banks? probabilities of default. The database comprises both a set of Luxembourg banks and the European banking groups to which they belong. The main results of this study are, first, that the common component of the forward probability of banks? defaulting on their long-term debt, conditional on not defaulting on their short-term debt, contains a significant early warning feature of interest for an operational macroprudential framework driven by economic activity, credit and interbank activity. Second, incorporating the common and the idiosyncratic components of macro-financial variables improves the analytical features and the out-of-sample forecasting performance of the framework proposed.
    Keywords: financial stability, macroprudential policy, credit risk, early warning indicators, default probability, Generalized Dynamic Factor Model, dynamic copulas, GARCH
    JEL: C30 E44 G1
    Date: 2012–07
  7. By: Andreas Haier; Thorsten Pfeiffer
    Abstract: We define scenarios, propose different methods of aggregating them, discuss their properties and benchmark them against quadrant requirements.
    Date: 2012–09
  8. By: Pascal François; Geneviève Gauthier; Frédéric Godin
    Abstract: We develop a flexible discrete-time hedging methodology that minimizes the expected value of any desired penalty function of the hedging error within a general regime-switching framework. A numerical algorithm based on backward recursion allows for the sequential construction of an optimal hedging strategy. Numerical experiments comparing this and other methodologies show a relative expected penalty reduction ranging between 0.9% and 12.6% with respect to the best benchmark.
    Keywords: Dynamic programming, hedging, risk management, regime switching
    JEL: G32 C61
    Date: 2012
  9. By: Marco Bee
    Abstract: This paper deals with the estimation of the lognormal-Pareto and the lognormal-Generalized Pareto mixture distributions. The log-likelihood function is discontinuous, so that Maximum Likelihood Estimation is not asymptotically optimal. For this reason, we develop an alternative method based on Probability Weighted Moments. We show that the standard version of the method can be applied to the first distribution, but not to the latter. Thus, in the lognormal- Generalized Pareto case, we work out the details of a mixed approach combining Maximum Likelihood Estimation and Probability Weighted Moments. Extensive simulations give precise indications about the relative efficiencies of the methods in various setups. Finally, we apply the techniques to two real datasets in the actuarial and operational risk management fields.
    Keywords: Probability Weighted Moments; Mixed Estimation Method; Lognormal-Pareto Distri- bution; Loss Models
    Date: 2012
  10. By: Jean-Stéphane Mésonnier; Dalibor Stevanovic
    Abstract: The recent crisis has revealed the potentially dramatic consequences of allowing the build-up of an overstretched leverage of the financial system, and prompted proposals by bank supervisors to significantly tighten bank capital requirements as part of the new Basel 3 regulations. Although these proposals have been fiercely debated ever since, the empirical question of the macroeconomic consequences of shocks to banks’ leverage, be they policy induced or not, remains still largely unsettled. In this paper, we aim to overcome some longstanding identification issues hampering such assessments and propose a new approach based on a data-rich environment at both the micro (bank) level and the macro level, using a combination of bank panel regressions and macroeconomic factor models. We first identify bank leverage shocks at the micro level and aggregate them to an economy-wide measure. We then compute impulse responses of a large array of macroeconomic indicators to our aggregate bank leverage shock, using the new methodology developed by Ng and Stevanovic (2012). We find significant and robust evidence of a contractionary impact of an unexpected shock reducing the leverage of large banks. <P>
    Keywords: bank capital ratios, macroeconomic fluctuations, panel, dynamic factor models,
    JEL: C23 C38 E32 E51 G21 G32
    Date: 2012–09–01
  11. By: Claudio J. Tessone; Antonios Garas; Beniamino Guerra; Frank Schweitzer
    Abstract: External or internal shocks may lead to the collapse of a system consisting of many agents. If the shock hits only one agent initially and causes it to fail, this can induce a cascade of failures among neighoring agents. Several critical constellations determine whether this cascade remains finite or reaches the size of the system, i.e. leads to systemic risk. We investigate the critical parameters for such cascades in a simple model, where agents are characterized by an individual threshold \theta_i determining their capacity to handle a load \alpha\theta_i with 1-\alpha being their safety margin. If agents fail, they redistribute their load equally to K neighboring agents in a regular network. For three different threshold distributions P(\theta), we derive analytical results for the size of the cascade, X(t), which is regarded as a measure of systemic risk, and the time when it stops. We focus on two different regimes, (i) EEE, an external extreme event where the size of the shock is of the order of the total capacity of the network, and (ii) RIE, a random internal event where the size of the shock is of the order of the capacity of an agent. We find that even for large extreme events that exceed the capacity of the network finite cascades are still possible, if a power-law threshold distribution is assumed. On the other hand, even small random fluctuations may lead to full cascades if critical conditions are met. Most importantly, we demonstrate that the size of the "big" shock is not the problem, as the systemic risk only varies slightly for changes of 10 to 50 percent of the external shock. Systemic risk depends much more on ingredients such as the network topology, the safety margin and the threshold distribution, which gives hints on how to reduce systemic risk.
    Date: 2012–09
  12. By: Soramäki, Kimmo; Cook, Samantha
    Abstract: The ability to accurately estimate the extent to which the failure of a bank disrupts the financial system is very valuable for regulators of the financial system. One important part of the financial system is the interbank payment system. This paper develops a robust measure, SinkRank, that accurately predicts the magnitude of disruption caused by the failure of a bank in a payment system and identifies banks most affected by the failure. SinkRank is based on absorbing Markov chains, which are well-suited to model liquidity dynamics in payment systems. Because actual bank failures are rare and the data is not generally publicly available, the authors test the metric by simulating payment networks and inducing failures in them. The authors use two metrics to evaluate the magnitude of the disruption: the duration of delays in the system (Congestion) aggregated over all banks and the average reduction in available funds of the other banks due to the failing bank (Liquidity dislocation). The authors test SinkRank on Barabasi-Albert types of scale-free networks modeled on the Fedwire system and find that the failing bank's SinkRank is highly correlated with the resulting disruption in the system overall; moreover, the SinkRank technology can identify which individual banks would be most disrupted by a given failure. --
    Keywords: Systemic risk,interbank payment system,liquidity,Markov chains,simulation
    JEL: C63 E58 G28
    Date: 2012
  13. By: Kawai, Masahiro (Asian Development Bank Institute); Morgan, Peter J. (Asian Development Bank Institute)
    Abstract: A key lesson of the 2007–2009 global financial crisis was the importance of containing systemic financial risk and the need for a “macroprudential” approach to surveillance and regulation that can identify system-wide risks and take appropriate actions to maintain financial stability. By virtue of their overview of the economy and the financial system and their responsibility for payments and settlement systems, there is a broad consensus that central banks should play a key role in monitoring and regulating financial stability. Emerging economies face additional challenges because of their underdeveloped financial systems and vulnerability to volatile international capital flows, especially “sudden stops” or reversals of capital inflows. This paper reviews the recent literature on this topic and identifies relevant lessons for central banks, especially those in Asia’s emerging economies.
    Keywords: central banking; central banks; financial stability; asia; surveillance and regulation; global financial crisis
    JEL: E52 F31 G28
    Date: 2012–08–31
  14. By: William Barnett (Department of Economics, The University of Kansas); Yi Liu (Washington University in St.Louis); Haiyang Xu (Washington University in St.Louis); Mark Jensen (Southern Illinois University at Carbondale)
    Date: 2012–09
  15. By: Erik Schlogl (Finance Discipline Group, UTS Business School, University of Technology, Sydney); Yang Chang (Finance Discipline Group, UTS Business School, University of Technology, Sydney)
    Abstract: This study empirically examines the effect of foreign exchange (FX) market liquidity risk and volatility on the excess returns of currency carry trades. In contrast to the existent literature, we construct an alternative proxy of liquidity risk - violations of no arbitrage bounds in the forward and currency swap markets. We also use volatility smile data to capture FX-market specific volatility. The sample data cover periods both before and after the Global Financial Crisis (GFC). Both proxies are significant in explaining the abnormal returns of carry trades, particularly after the GFC. Our findings provide substantial evidence that uncovered interest parity (UIP) puzzle can be resolved after controlling for liquidity risk and market volatility.
    Keywords: uncovered interest rate parity; carry trade; liquidity risk; no-arbitrage bound; volatility
    JEL: F31 G15
    Date: 2012–08–01
  16. By: Georg Junge; Peter Kugler (University of Basel)
    Abstract: <span lang="EN-US">So far the discussion in Switzerland about the social costs and benefits of higher capital requirements resulting from the new Basel III Accord and the Swiss Too Big To Fail legislation has been heavily qualitative. This paper provides a quantitative view and estimates the long-run costs and benefits of substantially higher capital requirements using empirical evidence on Swiss banks to assess both benefits and costs. The analysis yields two main conclusions. The long-run economic benefits of higher capital requirements are substantial for the Swiss economy leading to a significantly lower probability of banking crises and associated expected losses. In contrast the costs of higher capital requirements as reflected in increased lending spreads and potential output reductions are literally non-existent. As an aside we note that the cyclical component of leverage is a major driver of leverage in the banking sector. This suggests that macro-prudential measures such as the countercyclical buffer could be an important tool against the build-up of systemic banking crises. </span>
    Keywords: Capital regulation, banks, cost of equity, banking crisis, economic growth, Modigliani-Miller
    JEL: G21 G28
    Date: 2012
  17. By: Bargigli, Leonardo; Gallegati, Mauro
    Abstract: In this paper the authors focus on credit connections as a potential source of systemic risk. In particular, they seek to answer the following question: how do we find densely connected subsets of nodes within a credit network? The question is relevant for policy, since these subsets are likely to channel any shock affecting the network. As it turns out, a reliable answer can be obtained with the aid of complex network theory. In particular, the authors show how it is possible to take advantage of the community detection network literature. The proposed answer entails two subsequent steps. Firstly, the authors need to verify the hypothesis that the network under study truly has communities. Secondly, they need to devise a reliable algorithm to find those communities. In order to be sure that a given algorithm works, they need to test it over a sample of random benchmark networks with known communities. To overcome the limitation of existing benchmarks, the authors introduce a new model and test alternative algorithms, obtaining very good results with an adapted spectral decomposition method. To illustrate this method they provide a community description of the Japanese bank-firm credit network, getting evidence of a strengthening of communities over time and finding support for the well-known Japanese main bank system. Thus, the authors find comfort both from simulations and from real data on the possibility to apply community detection methods to credit markets. They believe that this method can fruitfully complement the study of contagious defaults, since the likelihood of intracommunity default contagion is expected to be high. --
    Keywords: Credit networks,communities,contagion,systemic risk
    JEL: C49 C63 D85 E51 G21
    Date: 2012

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