nep-rmg New Economics Papers
on Risk Management
Issue of 2016‒02‒23
ten papers chosen by

  1. Credit risk stress testing and copulas: Is the Gaussian copula better than its reputation? By Koziol, Philipp; Schell, Carmen; Eckhardt, Meik
  2. CoRisk: measuring systemic risk through default probability contagion By Paolo Giudici; Laura Parisi
  3. The Lehman Brothers Bankruptcy B: Risk Limits and Stress Tests By Rosalind Z. Wiggins; Andrew Metrick
  4. Credit risk spillovers, systemic importance and vulnerability in financial networks By Inna Grinis
  5. Can we prove a bank guilty of creating systemic risk?: a minority report By Jon Danielsson; Kevin R. James; Marcela Valenzuela; Ilknur Zer
  6. Value-at-Risk and backtesting with the APARCH model and the standardized Pearson type IV distribution By Stavros Stavroyiannis
  7. Corporate policies with permanent and temporary shocks By Décamps, Jean Paul; Gryglewicz, Sebastian; Morellec, Erwan; Villeneuve, Stéphane
  8. Hawkes processes in finance By Emmanuel Bacry; Iacopo Mastromatteo; Jean-Fran\c{c}ois Muzy
  9. Systemic risk spillovers in the European banking and sovereign network By Betz, Frank; Hautsch, Nikolaus; Peltonen, Tuomas A.; Schienle, Melanie
  10. Modeling and forecasting exchange rate volatility in time-frequency domain By Barunik, Jozef; Krehlik, Tomas; Vacha, Lukas

  1. By: Koziol, Philipp; Schell, Carmen; Eckhardt, Meik
    Abstract: In the last decade, stress tests have become indispensable in bank risk management which has led to significantly increased requirements for stress tests for banks and regulators. Although the complexity of stress testing frameworks has been enhanced considerably over the course of the last few years, the majority of credit risk models (e.g. Merton (1974), CreditMetrics, KMV) still rely on Gaussian copulas. This paper complements the finance literature providing new insights into the impact of different copulas in stress test applications using supervisory data of 17 large German banks. Our findings imply that the use of a Gaussian copula in credit risk stress testing should not by default be dismissed in favor of a heavy-tailed copula which is widely recommended in the finance literature. Gaussian copula would be the appropriate choice for estimating high stress effects under extreme scenarios. Heavy-tailed copulas like the Clayton or the t copula are recommended in the case of less severe scenarios. Furthermore, the paper provides clear advice for designing a credit risk stress test.
    Keywords: credit risk,top-down stress tests,copulas,macroeconomic scenario
    JEL: G21 G33 C13 C15
    Date: 2015
  2. By: Paolo Giudici (Department of Economics and Management, University of Pavia); Laura Parisi (Department of Economics and Management, University of Pavia)
    Abstract: We propose a novel systemic risk measurement model, based on stochastic processes, correlation networks and conditional probabilities of default.For each country we consider three different spread measures, one for each sector of the economy (sovereigns, corporates, banks), and we model each of them as a linear combination of two stochastic processes: a country-specific idiosyncratic component and a common systematic factor. We then build a partial correlation network model, and by combining it with the spread measures we derive the conditional default probabilities of each sector. Comparing them with the unconditional ones, we obtain the CoRisk, which measures the variation in the probability of default due to contagion effects. Our measurement model is applied to understand the time evolution of systemic risk in the economies of the European monetary union, in the recent period. The results show that, overall, the sovereign crisis has increased systemic risks more than the financial crisis. In addition, peripheral countries turn out to be exporters, rather than importers of systemic risk, and, conversely, core countries.
    Keywords: correlation networks, default probabilities, systemic risk, stochastic processes
    Date: 2016–02
  3. By: Rosalind Z. Wiggins; Andrew Metrick
    Abstract: Investment banks are in the business of taking calculated risks. Risk management infrastructure facilitates the safe pursuit of profits and the balancing of associated risks. By 2006, Lehman Brothers was thought to have a very respectable risk management system, and even its regulator, the Securities and Exchange Commission, viewed its risk framework as being fully compliant with regulatory requirements. In its public disclosures, Lehman characterized its risk controls as “meaningful constraints on its risk taking” and evidence of its continued financial stability. Beginning in late 2006, however, Lehman began dismantling its carefully crafted risk management framework as it pursued a new high-leverage growth strategy. During the next two years, it exceeded many risk limits, aggressively increased a number of risk metrics, disregarded its risk procedures, and excluded risk management personnel from key decisions. In October 2007, it replaced its well-regarded chief risk officer with a seasoned deal maker who lacked professional risk management experience. This case considers the value of a risk management system and how it functioned (and then did not) to constrain risk taking at Lehman. It also considers the role of its regulator.
    Keywords: Systemic Risk, Financial Crises, Financial Regulation
    JEL: G01 G28
    Date: 2014–10
  4. By: Inna Grinis
    Abstract: How does the change in the creditworthiness of a financial institution or sovereign impact its creditors’ solvency? I address this question in the context of the recent European sovereign debt crisis. Considering the network of Eurozone member states, interlinked through investment cross-holdings, I model default as a multi-stage disease with each credit-rating corresponding to a new infection phase, then derive systemic importance and vulnerability indicators in the presence of financial contagion, triggered by the change in the creditworthiness of a network member. I further extend the model to analyse not only negative, but also positive credit risk spillovers.
    Keywords: Sovereign Default; Debt Crises; Political Survival; Networks; Voter Behavior.
    JEL: R21
    Date: 2015–01–06
  5. By: Jon Danielsson; Kevin R. James; Marcela Valenzuela; Ilknur Zer
    Abstract: Since increasing a bank's capital requirement to improve the stability of the financial system imposes costs upon the bank, a regulator should ideally be able to prove beyond a reasonable doubt that banks classified as systemically risky really do create systemic risk before subjecting them to this capital punishment. Evaluating the performance of two leading systemic risk models, we show that estimation error alone prevents the reliable identification of the most systemically risky banks. We conclude that it will be a considerable challenge to develop a riskometer that is both sound and reliable enough to provide an adequate foundation for macroprudential policy.
    Keywords: Systemic risk; macroprudential policy; financial stability; risk management
    JEL: G32 F3 G3
    Date: 2015–09
  6. By: Stavros Stavroyiannis
    Abstract: We examine the efficiency of the Asymmetric Power ARCH (APARCH) model in the case where the residuals follow the standardized Pearson type IV distribution. The model is tested with a variety of loss functions and the efficiency is examined via application of several statistical tests and risk measures. The results indicate that the APARCH model with the standardized Pearson type IV distribution is accurate, within the general financial risk modeling perspective, providing the financial analyst with an additional skewed distribution for incorporation in the risk management tools.
    Date: 2016–02
  7. By: Décamps, Jean Paul; Gryglewicz, Sebastian; Morellec, Erwan; Villeneuve, Stéphane
    Abstract: We develop a dynamic model of investment, cash holdings, financing, and risk management policies in which firms face financing frictions and are subject to permanent and temporary cash flow shocks. In this model, target cash holdings depend on the long-term prospects of the firm, implying that the payout policy of the firm, its financing policy, and its cash-flow sensitivity of cash display a more realistic behavior than in prior models with financing frictions. In addition, risk management policies are richer and depend on the nature of cash flow shocks and potential collateral constraints. Lastly, the timing of investment and the firm’s initial asset mix both reflect financing frictions and the joint effects of permanent and temporary shocks.
    Keywords: corporate policies; financing frictions; permanent vs. temporary shocks; risk management
    JEL: G31 G32 G35
    Date: 2015–02
  8. By: Emmanuel Bacry; Iacopo Mastromatteo; Jean-Fran\c{c}ois Muzy
    Abstract: In this paper we propose an overview of the recent academic literature devoted to the applications of Hawkes processes in finance. Hawkes processes constitute a particular class of multivariate point processes that has become very popular in empirical high frequency finance this last decade. After a reminder of the main definitions and properties that characterize Hawkes processes, we review their main empirical applications to address many different problems in high frequency finance. Because of their great flexibility and versatility, we show that they have been successfully involved in issues as diverse as estimating the volatility at the level of transaction data, estimating the market stability, accounting for systemic risk contagion, devising optimal execution strategies or capturing the dynamics of the full order book.
    Date: 2015–02
  9. By: Betz, Frank; Hautsch, Nikolaus; Peltonen, Tuomas A.; Schienle, Melanie
    Abstract: We propose a framework for estimating time-varying systemic risk contributions that is applicable to a high-dimensional and interconnected financial system. Tail risk dependencies and systemic risk contributions are estimated using a penalized two-stage fixed-effects quantile approach, which explicitly links time-varying interconnectedness to systemic risk contributions. For the purposes of surveillance and regulation of financial systems, network dependencies in extreme risks are more relevant than simple (mean) correlations. Thus, the framework provides a tool for supervisors, reflecting the market's view of tail dependences and systemic risk contributions. The model is applied to a system of 51 large European banks and 17 sovereigns during the period from 2006 through 2013, utilizing both equity and CDS prices. We provide new evidence on how banking sector fragmentation and sovereign-bank linkages evolved over the European sovereign debt crisis, and how they are reflected in estimated network statistics and systemic risk measures. Finally, our evidence provides an indication that the fragmentation of the European financial system has peaked.
    Keywords: systemic risk contribution,tail dependence,network topology,sovereignbank linkages,Value-at-Risk
    JEL: G01 G18 G32 G38 C21 C51 C63
    Date: 2016
  10. By: Barunik, Jozef; Krehlik, Tomas; Vacha, Lukas
    Abstract: This paper proposes an enhanced approach to modeling and forecasting volatility using high frequency data. Using a forecasting model based on Realized GARCH with multiple time-frequency decomposed realized volatility measures, we study the influence of different timescales on volatility forecasts. The decomposition of volatility into several timescales approximates the behaviour of traders at corresponding investment horizons. The proposed methodology is moreover able to account for impact of jumps due to a recently proposed jump wavelet two scale realized volatility estimator. We propose a realized Jump-GARCH models estimated in two versions using maximum likelihood as well as observation-driven estimation framework of generalized autoregressive score. We compare forecasts using several popular realized volatility measures on foreign exchange rate futures data covering the recent financial crisis. Our results indicate that disentangling jump variation from the integrated variation is important for forecasting performance. An interesting insight into the volatility process is also provided by its multiscale decomposition. We find that most of the information for future volatility comes from high frequency part of the spectra representing very short investment horizons. Our newly proposed models outperform statistically the popular as well conventional models in both one-day and multi-period-ahead forecasting.
    Keywords: realized GARCH,wavelet decomposition,jumps,multi-period-ahead volatility forecasting
    Date: 2016

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