nep-rmg New Economics Papers
on Risk Management
Issue of 2019‒02‒25
eighteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Risk Management with Tail Conditional Certainty Equivalents By Nicole B\"auerle; Tomer Shushi
  2. The anatomy of the euro area interest rate swap market By Dalla Fontana, Silvia; Holz auf der Heide, Marco; Pelizzon, Loriana; Scheicher, Martin
  3. Locally Constant Model Uncertainty Risk Measure By Obradovic, Lazar
  4. Anticipating the bust: a new cyclical systemic risk indicator to assess the likelihood and severity of financial crises By Lang, Jan Hannes; Izzo, Cosimo; Fahr, Stephan; Ruzicka, Josef
  5. Pricing formulae for derivatives in insurance using the Malliavin calculus * By Caroline Hillairet; Ying Jiao; Anthony Réveillac
  6. Global Price of Risk and Stabilization Policies By Adrian, Tobias; Stackman, Daniel; Vogt, Erik
  7. Mean and median-based nonparametric estimation of returns in mean-downside risk portfolio frontier By Hanene Ben Salah; Mohamed Chaouch; Ali Gannoun; Christian De Peretti; Abdelwahed Trabelsi
  8. What drives the short-term fluctuations of banks' exposure to interest rate risk? By Memmel, Christoph
  9. Constrained Risk Budgeting Portfolios: Theory, Algorithms, Applications & Puzzles By Jean-Charles Richard; Thierry Roncalli
  10. Model risk in mean-variance portfolio selection: an analytic solution to the worst-case approach By Roberto Baviera; Giulia Bianchi
  11. Macroprudential Policy with Capital Buffers By Josef Schroth
  12. Dynamics of multivariate default system in random environment By Nicole El Karoui; Monique Jeanblanc; Ying Jiao
  13. The Risk Spiral: The Effects of Bank Capital and Diversification on Risk Taking By Peleg Lazar, Sharon; Raviv, Alon
  14. Fraud phenomenon seen from Luhmann's systemic perspective By Emmanuel Laffort; Nicolas Dufour
  15. Quantile relationship between oil and stock returns: Evidence from emerging and frontier stock markets By Mehmet Balcilar; Riza Demirer; Shawkat Hammoudeh
  16. New testing approaches for mean-variance predictability By Fiorentini, Gabriele; Sentana, Enrique
  17. Dividends from Unrealized Earnings and Default Risk By Ester Chen; Ilanit Gavious; Nadav Steinberg

  1. By: Nicole B\"auerle; Tomer Shushi
    Abstract: Certainty Equivalent is a utility-based measure that performs as a measure in which investors are indifferent between this measure and investment that holds some uncertainty. Therefore, it plays an essential role in utility-based decision making. One of the most extensively used risk measures is the Value at Risk, which is investigated and used by both researchers and practitioners as a powerful tool that measures the risk under some quantile level which allows focusing on the extreme amount of losses. In this paper, we propose a natural generalization of the Certainty Equivalent measure that, similar to the Value at Risk measure, is focusing on the tail distribution of the risk, and thus, focusing on extreme financial and insurance risk events. We then investigate the fundamental properties of the proposed measure and show its unique features and implications in the risk measurement process. Furthermore, we derive formulas for truncated elliptical models of losses and provide formulas for selected members of such models.
    Date: 2019–02
  2. By: Dalla Fontana, Silvia; Holz auf der Heide, Marco; Pelizzon, Loriana; Scheicher, Martin
    Abstract: Using a novel regulatory dataset of fully identified derivatives transactions, this paper provides the first comprehensive analysis of the structure of the euro area interest rate swap (IRS) market after the start of the mandatory clearing obligation. Our dataset contains 1.7 million bilateral IRS transactions of banks and non-banks. Our key results are as follows: 1) The euro area IRS market is highly standardised and concentrated around the group of the G16 Dealers but also around a significant group of core ”intermediaries" (and major CCPs). 2) Banks are active in all segments of the IRS euro market, whereas non-banks are often specialised. 3) When using relative net exposures as a proxy for the “flow of risk" in the IRS market, we find that risk absorption takes place in the core as well as the periphery of the network. 4) Among the Basel III capital and liquidity ratios, the leverage ratio plays a key role in determining a bank's IRS trading activity. 5) Also, after mandatory central clearing, there is still a large dispersion in IRS transaction prices, which is partly determined by bank characteristics, such as the leverage ratio. JEL Classification: G21, E43, E44
    Keywords: banking, hedging, interest rate risk, network analysis, OTC derivatives, risk management
    Date: 2019–02
  3. By: Obradovic, Lazar (Center for Mathematical Economics, Bielefeld University)
    Abstract: This paper introduces a (coherent) risk measure that describes the uncertainty of the model (represented by a probability measure $P_0$) by a set $P_\lambda$ of probability measures each of which has a Radon-Nikodym's derivative (with respect to $P_0$) that lies within the interval $[\lambda,\frac{1}{\lambda}]$ for some constant $\lambda\in(0,1]$. Economic considerations are discussed and an explicit representation is obtained that gives a connection to both the expected loss of the financial position and its *average value-at-risk*. Optimal portfolio analysis is performed -- different optimization criteria lead to Merton portfolio. Comparison with related problems reveals examples of extreme sensitivity of optimal portfolios to model parameters and the choice of risk measure.
    Keywords: Risk measure, Model uncertainty, Value at risk, Average value at risk, Optimal portfolio, Merton portfolio.
    Date: 2019–02–13
  4. By: Lang, Jan Hannes; Izzo, Cosimo; Fahr, Stephan; Ruzicka, Josef
    Abstract: This paper presents a tractable, transparent and broad-based domestic cyclical systemic risk indicator (d-SRI) that captures risks stemming from domestic credit, real estate markets, asset prices, and external imbalances. The d-SRI increases on average several years before the onset of systemic financial crises, and its early warning properties for euro area countries are superior to those of the total credit-to-GDP gap. In addition, the level of the d-SRI around the start of financial crises is highly correlated with measures of subsequent crisis severity, such as GDP declines. Model estimates suggest that the d-SRI has significant predictive power for large declines in real GDP growth three to four years down the line, as it precedes shifts in the entire distribution of future real GDP growth and especially of its left tail. The d-SRI therefore provides useful information about both the probability and the likely cost of systemic financial crises many years in advance. Given its timely signals, the d-SRI is a useful analytical tool for macroprudential policymakers. JEL Classification: G01, G17, C22, C54
    Keywords: early warning models, financial crises, GDP at risk, local projections, quantile regressions, systemic risk
    Date: 2019–02
  5. By: Caroline Hillairet (ENSAE ParisTech - École Nationale de la Statistique et de l'Administration Économique); Ying Jiao (SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon); Anthony Réveillac (INSA Toulouse - Institut National des Sciences Appliquées - Toulouse - INSA - Institut National des Sciences Appliquées, IMT - Institut de Mathématiques de Toulouse UMR5219 - UT1 - Université Toulouse 1 Capitole - UT2J - Université Toulouse - Jean Jaurès - UPS - Université Toulouse III - Paul Sabatier - Université Fédérale Toulouse Midi-Pyrénées - PRES Université de Toulouse - INSA Toulouse - Institut National des Sciences Appliquées - Toulouse - INSA - Institut National des Sciences Appliquées - CNRS - Centre National de la Recherche Scientifique)
    Abstract: In this paper we provide a valuation formula for different classes of actuarial and financial contracts which depend on a general loss process, by using the Malliavin calculus. In analogy with the celebrated Black-Scholes formula, we aim at expressing the expected cash flow in terms of a building block. The former is related to the loss process which is a cumulated sum indexed by a doubly stochastic Poisson process of claims allowed to be dependent on the intensity and the jump times of the counting process. For example, in the context of Stop-Loss contracts the building block is given by the distribution function of the terminal cumulated loss, taken at the Value at Risk when computing the Expected Shortfall risk measure.
    Date: 2018–06–05
  6. By: Adrian, Tobias; Stackman, Daniel; Vogt, Erik
    Abstract: We estimate a highly significant price of risk that forecasts global stock and bond returns as a nonlinear function of the VIX. We show that countries' exposure to the global price of risk is related to macroeconomic risks as measured by output, credit, and inflation volatility, the magnitude of financial crises, and stock and bond market downside risk. Higher exposure to the global price of risk corresponds to both higher output volatility and higher output growth. We document that the transmission of the global price of risk to macroeconomic outcomes is mitigated by the magnitude of stabilization in the Taylor rule, the degree of countercyclicality of fiscal policy, and countries' tendencies to employ prudential regulations. The estimated magnitudes are quantitatively important and significant, with large cross sectional explanatory power. Our findings suggest that macroeconomic and financial stability policies should be considered jointly.
    Keywords: Financial Stability; Fiscal policy; monetary policy; regulatory policy
    JEL: G01 G12 G17
    Date: 2019–01
  7. By: Hanene Ben Salah (IMAG - Institut Montpelliérain Alexander Grothendieck - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique, BESTMOD - Business and Economic Statistics MODeling - ISG - Institut Supérieur de Gestion de Tunis [Tunis] - Université de Tunis [Tunis], SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon); Mohamed Chaouch (UAEU - United Arab Emirates University); Ali Gannoun (IMAG - Institut Montpelliérain Alexander Grothendieck - UM - Université de Montpellier - CNRS - Centre National de la Recherche Scientifique); Christian De Peretti (SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon); Abdelwahed Trabelsi (BESTMOD - Business and Economic Statistics MODeling - ISG - Institut Supérieur de Gestion de Tunis [Tunis] - Université de Tunis [Tunis])
    Abstract: The DownSide Risk (DSR) model for portfolio optimisation allows to overcome the drawbacks of the classical Mean-Variance model concerning the asymmetry of returns and the risk perception of investors. This model optimization deals with a positive definite matrix that is endogenous with respect to portfolio weights. This aspect makes the problem far more difficult to handle. For this purpose, Athayde (2001) developed a new recursive minimization procedure that ensures the convergence to the solution. However, when a finite number of observations is available, the portfolio frontier presents some discontinuity and is not very smooth. In order to overcome that, Athayde (2003) proposed a Mean Kernel estimation of the returns, so as to create a smoother portfolio frontier. This technique provides an effect similar to the case in which continuous observations are available. In this paper, Athayde model is reformulated and clarified. Then, taking advantage on the robustness of the median, another nonparametric approach based on Median Kernel returns estimation is proposed in order to construct a portfolio frontier. A new version of Athayde's algorithm will be exhibited. Finally, the properties of this improved portfolio frontier are studied and analysed on the French Stock Market. Keywords DownSide Risk · Kernel Method · Mean Nonparametric Estimation · Median Nonparametric Estimation · Portefolio Efficient Frontier · Semi-Variance.
    Keywords: Downside risk,Kernel method,Mean nonparametric estimation,Median nonparametric estimation,Portefolio efficient frontier,Semi-variance
    Date: 2018–03
  8. By: Memmel, Christoph
    Abstract: We investigate whether banks actively manage their exposure to interest rate risk in the short run. Using bank-level data of German banks for the period 2011Q4- 2017Q2, we find evidence that banks actively manage their interest rate risk exposure in their banking books: They take account of their regulatory situation and adjust their exposure to the earning opportunities of this risk. We also find that the customers' preferences predominantly determine the fixed-interest period of housing loans and that the fixed-interest period of these loans has an impact on the banks' overall exposure to interest rate risk. This last finding is not in line with active interest rate risk management.
    Keywords: interest rate risk in the banking book,fixed-interest period of housing loans,interest swaps,regulation of interest rate risk
    JEL: G21
    Date: 2019
  9. By: Jean-Charles Richard; Thierry Roncalli
    Abstract: This article develops the theory of risk budgeting portfolios, when we would like to impose weight constraints. It appears that the mathematical problem is more complex than the traditional risk budgeting problem. The formulation of the optimization program is particularly critical in order to determine the right risk budgeting portfolio. We also show that numerical solutions can be found using methods that are used in large-scale machine learning problems. Indeed, we develop an algorithm that mixes the method of cyclical coordinate descent (CCD), alternating direction method of multipliers (ADMM), proximal operators and Dykstra's algorithm. This theoretical body is then applied to some investment problems. In particular, we show how to dynamically control the turnover of a risk parity portfolio and how to build smart beta portfolios based on the ERC approach by improving the liquidity of the portfolio or reducing the small cap bias. Finally, we highlight the importance of the homogeneity property of risk measures and discuss the related scaling puzzle.
    Date: 2019–02
  10. By: Roberto Baviera; Giulia Bianchi
    Abstract: In this paper we consider the worst-case model risk approach described in Glasserman and Xu (2014). Portfolio selection with model risk can be a challenging operational research problem. In particular, it presents an additional optimisation compared to the classical one. We find the analytical solution for the optimal mean-variance portfolio selection in the worst-case scenario approach. In the minimum-variance case, we prove that the analytical solution is significantly different from the one found numerically by Glasserman and Xu (2014) and that model risk reduces to an estimation risk. A detailed numerical example is provided.
    Date: 2019–02
  11. By: Josef Schroth
    Abstract: This paper studies optimal bank capital requirements in a model of endogenous bank funding conditions. I find that requirements should be higher during good times such that a macroprudential “buffer” is provided. However, whether banks can use buffers to maintain lending during a financial crisis depends on the capital requirement during the subsequent recovery. The reason is that a high requirement during the recovery lowers bank shareholder value during the crisis and thus creates funding-market pressure to use buffers for deleveraging rather than for maintaining lending. Therefore, buffers are useful if banks are not required to rebuild them quickly.
    Keywords: Credit and credit aggregates; Financial stability; Financial system regulation and policies; Business fluctuations and cycles; Credit risk management; Lender of last resort
    JEL: E13 E32 E44
    Date: 2019
  12. By: Nicole El Karoui (LPMA - Laboratoire de Probabilités et Modèles Aléatoires - UPMC - Université Pierre et Marie Curie - Paris 6 - UPD7 - Université Paris Diderot - Paris 7 - CNRS - Centre National de la Recherche Scientifique); Monique Jeanblanc (LaMME - Laboratoire de Mathématiques et Modélisation d'Evry - INRA - Institut National de la Recherche Agronomique - UEVE - Université d'Évry-Val-d'Essonne - ENSIIE - CNRS - Centre National de la Recherche Scientifique); Ying Jiao (SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon)
    Abstract: We consider a multivariate default system where random environmental information is available. We study the dynamics of the system in a general setting and adopt the point of view of change of probability measures. We also make a link with the density approach in the credit risk modelling. In the particular case where no environmental information is concerned, we pay a special attention to the phenomenon of system weakened by failures as in the classical reliability system.
    Keywords: prediction process,Multiple defaults,density approach,change of probability measure
    Date: 2017–03–17
  13. By: Peleg Lazar, Sharon; Raviv, Alon
    Abstract: We present a model where bank assets are a portfolio of risky debt claims and analyze stockholders' risk-taking behavior while considering the strategic interaction between debtors and creditors. We find that: (1) as the leverage of a bank increases, risk shifting by borrowers increases, even if their leverage is unchanged (zombie lending). (2) While the literature demonstrates that an increase in the co-movement of a loan portfolio increases the bank's cost of default directly, we find that the increase in co-movement causes an increase in risk shifting that further increases the cost of default (3) Risk shifting decreases with the diversification of a loan portfolio.
    Keywords: Risk taking, Banks, Comovements, Deposit insurance, Zombie lending
    JEL: G21 G28 G32 G38
    Date: 2019–02
  14. By: Emmanuel Laffort (CREG - Centre de recherche et d'études en gestion - UPPA - Université de Pau et des Pays de l'Adour); Nicolas Dufour (BMGE - Biologie Moléculaire du Gène chez les Extrêmophiles - Institut Pasteur [Paris])
    Abstract: The paper aims at mobilizing Niklas Luhmann's sociology to fraud — the only perspective that is likely to account for the fraud phenomenon according to Luhmann —, both to try to apply a radical framework to a never-ending and fast-growing phenomenon and to criticize previous work related to the field. This research merges two empirical works that aim to encourage antifraud measures and applies Luhmann's sociology and notably its major distinction between risk and danger to assess their (in)validity. Luhmann's sociology helps understanding the distinction between these two notions of risk and danger; therefore, the analysis succeeds in explaining why fraud — be it external or internal — should be considered from this perspective. Thence, this research calls for a true long-term horizon when addressing the danger of fraud, but also and above all, calls for expanding the limited vision we have of the world we are contributing to.
    Keywords: systemic sociology,fraud management,Niklas Luhmann,risk and danger distinction,appropriation
    Date: 2019–01–23
  15. By: Mehmet Balcilar (Department of Economics, Eastern Mediterranean University); Riza Demirer (Southern Illinois University Edwardsville); Shawkat Hammoudeh (Montpellier Business School, Montpellier, France)
    Abstract: This study extends the literature on the asymmetric effect of oil price fluctuations on emerging and frontier stock markets via a quantile-on-quantile approach that allows to capture normal and extreme states in each respective market. We find that oil risk exposures are heterogeneous across the emerging and frontier stock markets and indeed display quantile-specific characteristics. Observing uniform patterns of oil risk exposures within groups of countries that include both importers and exporters, we argue that oil price risk serves as a systematic risk proxy, capturing the market’s concerns regarding global growth expectations, rather than a simple import/export commodity. Our findings suggest that signals from the oil market, either via measures of trading activity in oil futures or changes in basis values, could be utilized by policy makers to improve models of stock market volatility.
    Keywords: Stock returns; Oil prices; Quantile regression; Emerging markets
    JEL: C22 G12 Q40
    Date: 2019
  16. By: Fiorentini, Gabriele; Sentana, Enrique
    Abstract: We propose tests for smooth but persistent serial correlation in risk premia and volatilities that exploit the non-normality of financial returns. Our parametric tests are robust to distributional misspecification, while our semiparametric tests are as powerful as if we knew the true return distribution. Local power analyses confirm their gains over existing methods, while Monte Carlo exercises assess their finite sample reliability. We apply our tests to quarterly returns on the five Fama-French factors for international stocks, whose distributions are mostly symmetric and fat-tailed. Our results highlight noticeable differences across regions and factors and confirm the fragility of Gaussian tests.
    Keywords: Financial forecasting; Misspecification; Moment tests; robustness; volatility
    JEL: C12 C22 G17
    Date: 2019–01
  17. By: Ester Chen (Peres Academic Center); Ilanit Gavious (Ben-Gurion University); Nadav Steinberg (Bank of Israel)
    Abstract: Using hand-collected data on Israeli firms’ unrealized earnings and debt restructurings following adoption of the IFRS, we investigate whether and how dividend payments based on unrealized revaluation earnings affect a firm’s default risk. Our results indicate that in the era of fair value accounting, the origin of the dividend payout—coming from unrealized versus realized earnings—has a significant effect on a firm’s default risk above and beyond the effect of the extent of the payment. Specifically, controlling for various determinants of financial risk, including the amount of the dividends paid (originating from either realized or unrealized earnings), companies are over three times more likely to subsequently require debt restructuring if they distribute dividends based on unrealized earnings. However, this enhanced risk seems to be mispriced by the market; firms that distribute dividends based on unrealized earnings exhibit an insignificantly different cost of debt than firms that never do so.
    Keywords: cost of debt, default risk, dividends, fair value accounting
    JEL: M21 M41 G35
    Date: 2017–06
  18. By: Hadrien De March (CMAP - Centre de Mathématiques Appliquées - Ecole Polytechnique - X - École polytechnique - CNRS - Centre National de la Recherche Scientifique); Pierre Henry-Labordere (SOCIETE GENERALE - Equity Derivatives Research Societe Generale - Société Générale)
    Abstract: We consider the classical problem of building an arbitrage-free implied volatility surface from bid-ask quotes. We design a fast numerical procedure, for which we prove the convergence, based on the Sinkhorn algorithm that has been recently used to solve efficiently (martingale) optimal transport problems.
    Date: 2019–02–08

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