nep-rmg New Economics Papers
on Risk Management
Issue of 2017‒09‒24
sixteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Extreme M-quantiles as risk measures: From L1 to Lp optimization By Daouia, Abdelaati; Girard, Stéphane; Stupfler, Gilles
  2. Bank Acquisitiveness and Financial Crisis Vulnerability By Saqib Aziz; Michael Dowling; Jean-Jacques Lilti
  3. Uncertainty Shocks as Second-Moment News Shocks By David Berger; Ian Dew-Becker; Stefano Giglio
  4. Optimal Dynamic Resource Allocation to Prevent Defaults By Urtzi Ayesta; M Erausquin; E Ferreira; P Jacko
  5. The Implied Volatility of Forward Starting Options: ATM Short-Time Level, Skew and Curvature By Elisa Alòs; Antoine Jacquier; Jorge A. León
  6. Optimal Liquidation Problems in a Randomly-Terminated Horizon By Qing-Qing Yang; Wai-Ki Ching; Jia-Wen Gu; Tak Kwong Wong
  7. A Counterfactual Valuation of the Stock Index as a Predictor of Crashes By Tom Roberts
  8. Stakeholders in pension finance By Boon, Ling-Ni
  9. Semi-Static Variance-Optimal Hedging in Stochastic Volatility Models with Fourier Representation By Paolo Di Tella; Martin Haubold; Martin Keller-Ressel
  10. Theoretical and Empirical Differences Between Diagonal and Full BEKK for Risk Management By David E. Allen; Michael McAleer
  11. Too complex to work: A critical assessment of the bail-in tool under the European bank recovery and resolution regime By Tröger, Tobias
  12. Explicit Solution for Constrained Stochastic Linear-Quadratic Control with Multiplicative Noise By Weipin Wu; Jianjun Gao; Duan Li; Yun Shi
  13. Reading Between the Lines: Prediction of Political Violence Using Newspaper Text By Hannes Mueller; Christopher Rauh
  14. Semi-Static and Sparse Variance-Optimal Hedging By Paolo Di Tella; Martin Haubold; Martin Keller-Ressel
  15. Potentielle Risikofaktoren für die Erhöhung der Betriebsprüfungswahrscheinlichkeit - Eine analytische und empirische Untersuchung auf Basis der E-Bilanz-Taxonomie 6.0 - By Henselmann, Klaus; Haller, Stefanie
  16. The best of two worlds: Balancing model strength and comprehensibility in business failure prediction using spline-rule ensembles By Koen De Bock

  1. By: Daouia, Abdelaati; Girard, Stéphane; Stupfler, Gilles
    Abstract: The class of quantiles lies at the heart of extreme-value theory and is one of the basic tools in risk management. The alternative family of expectiles is based on squared rather than absolute error loss minimization. It has recently been receiving a lot of attention in actuarial science, econometrics and statistical finance. Both quantiles and expectiles can be embedded in a more general class of M-quantiles by means of Lp optimization. These generalized Lp-quantiles steer an advantageous middle course between ordinary quantiles and expectiles without sacrificing their virtues too much for 1 p 2. In this paper, we investigate their estimation from the perspective of extreme values in the class of heavy-tailed distributions. We construct estimators of the intermediate Lp-quantiles and establish their asymptotic normality in a dependence framework motivated by financial and actuarial applications, before extrapolating these estimates to the very far tails. We also investigate the potential of extreme Lp-quantiles as a tool for estimating the usual quantiles and expectiles themselves. We show the usefulness of extreme Lp-quantiles and elaborate the choice of p through applications to some simulated and financial real data.
    Keywords: Asymptotic normality; Dependent observations; Expectiles; Extrapolation; Extreme values; Heavy tails; Lp optimization; Mixing; Quantiles; Tail risk
    Date: 2017–09
  2. By: Saqib Aziz (ESC Rennes School of Business - ESC Rennes School of Business); Michael Dowling (ESC Rennes School of Business - ESC Rennes School of Business); Jean-Jacques Lilti (CREM - Centre de Recherche en Economie et Management - UNICAEN - Université Caen Normandie - UR1 - Université de Rennes 1 - CNRS - Centre National de la Recherche Scientifique)
    Abstract: We investigate the relation between European bank acquisitiveness during the period 1990-2006 and the vulnerability of banks to the financial crisis. Our main tests use distance to default and Z-score ratios to estimate banks impact from the financial crisis in terms of bankruptcy risk and solvency. The findings shed new light on whether bank acquisitions really did contribute towards weakness; and suggest that only acquisitions of investment banking assets increased risk, while acquisition of retail banking assets actually lowered solvency risk.
    Keywords: Financial Crisis, Mergers and Acquisitions, Probability of Default, Solvency, Investment Banking
    Date: 2016–07
  3. By: David Berger; Ian Dew-Becker; Stefano Giglio
    Abstract: We provide evidence on the relationship between aggregate uncertainty and the macroeconomy. Identifying uncertainty shocks using methods from the news shocks literature, the analysis finds that innovations in realized stock market volatility are robustly followed by contractions, while shocks to forward-looking uncertainty have no significant effect on the economy. Moreover, investors have historically paid large premia to hedge shocks to realized but not implied volatility. A model in which fundamental shocks are skewed left can match those facts. Aggregate volatility matters, but it is the realization of volatility, rather than uncertainty about the future, that has been associated with declines.
    JEL: E00 E32 G12
    Date: 2017–09
  4. By: Urtzi Ayesta (LAAS-SARA - Équipe Services et Architectures pour Réseaux Avancés - LAAS - Laboratoire d'analyse et d'architecture des systèmes [Toulouse] - INP - Institut National Polytechnique [Toulouse] - INSA Toulouse - Institut National des Sciences Appliquées - Toulouse - INSA - Institut National des Sciences Appliquées - UPS - Université Paul Sabatier - Toulouse 3 - CNRS - Centre National de la Recherche Scientifique); M Erausquin; E Ferreira; P Jacko (Lancaster University)
    Abstract: We consider a resource allocation problem, where a rational agent has to decide how to share a limited amount of resources among different companies that might be facing financial difficulties. The objective is to minimize the total long term cost incurred by the economy due to default events. Using the framework of multi-armed restless bandits and, assuming a two-state evolution of the default risk, the optimal dynamic resource sharing policy is determined. This policy assigns an index value to each company, which orders its priority to be funded. We obtain an analytical expression for this index, which generalizes the return-on-investment (ROI) index under the static setting, and we analyse the influence of the future events on the optimal dynamic policy. A discussion about the structure of the optimal dynamic policy is provided, as well as some extensions of the model.
    Keywords: Dynamic Resource Allocation Policies,Markov Decision Processes,Multi-Armed Bandit Problem,Default Risk Management
    Date: 2016–07–01
  5. By: Elisa Alòs; Antoine Jacquier; Jorge A. León
    Abstract: For stochastic volatility models, we study the short-time behaviour of the at-the-money implied volatility level, skew and curvature for forward-starting options. Our analysis is based on Malliavin Calculus techniques
    Keywords: Forward starting options, implied volatility, Malliavin calculus, stochastic volatility models
    JEL: C02
    Date: 2017–09
  6. By: Qing-Qing Yang; Wai-Ki Ching; Jia-Wen Gu; Tak Kwong Wong
    Abstract: In this paper, we study optimal liquidation problems in a randomly-terminated horizon. We consider the liquidation of a large single-asset portfolio with the aim of minimizing a combination of volatility risk and transaction costs arising from permanent and temporary market impact. Three different scenarios are analyzed under Almgren-Chriss's market impact model to explore the relation between optimal liquidation strategies and potential inventory risk arising from the uncertainty of the liquidation horizon. For cases where no closed-form solutions can be obtained, we verify comparison principles for viscosity solutions and characterize the value function as the unique viscosity solution of the associated Hamilton-Jacobi-Bellman (HJB) equation.
    Date: 2017–09
  7. By: Tom Roberts
    Abstract: Stock market fundamentals would not seem to meaningfully predict returns over a shorter-term horizon—instead, I shift focus to severe downside risk (i.e., crashes). I use the cointegrating relationship between the log S&P Composite Index and log earnings over 1871 to 2015, combined with smoothed earnings, to first construct a counterfactual valuation benchmark. The price-versus-benchmark residual shows an improved, and economically meaningful, logit estimation of the likelihood of a crash over alternatives such as the dividend yield and price momentum. Rolling out-of-sample estimates highlight the challenges in this task. Nevertheless, the overall results support the common popular belief that a higher stock market valuation in relation to fundamentals entails a higher risk of a crash.
    Keywords: Asset Pricing, Financial stability
    JEL: C50 C58 G0 G01 G12 G17 G19
    Date: 2017
  8. By: Boon, Ling-Ni (Tilburg University, School of Economics and Management)
    Abstract: This dissertation examines three stakeholders in pension finance: the individual, the policymaker, and the pension provider (e.g., an insurer or a pension fund). In a setting beset by unforeseen financial market circumstances and demographic changes that disfavor financial security in retirement, a re-evaluation of these stakeholders' role is necessary. We explore the regulation and design of retirement plans by incorporating features that characterize the future retirement landscape, such as the increasing burden of risk borne by the individual, and the potential involvement of market investors in the provision of retirement contracts. The implications of our findings encompass guidance for individuals in managing longevity risk, evaluation of the appeal of longevity risk exposure to investors, insights on contract design for the pension provider, and proposals to the policymaker on regulatory measures that foster a sustainable retirement environment.
    Date: 2017
  9. By: Paolo Di Tella; Martin Haubold; Martin Keller-Ressel
    Abstract: In a financial market model, we consider the variance-optimal semi-static hedging of a given contingent claim, a generalization of the classic variance-optimal hedging. To obtain a tractable formula for the expected squared hedging error and the optimal hedging strategy, we use a Fourier approach in a general multidimensional semimartingale factor model. As a special case, we recover existing results for variance-optimal hedging in affine stochastic volatility models. We apply the theory to set up a variance-optimal semi-static hedging strategy for a variance swap in both the Heston and the 3/2-model, the latter of which is a non-affine stochastic volatility model.
    Date: 2017–09
  10. By: David E. Allen (School of Mathematics and Statistics, University of Sydney, Centre for Applied Finance, University of South Australia, and School of Business and Law, Edith Cowan University.); Michael McAleer (Department of Quantitative Finance National Tsing Hua University, Taiwan and Econometric Institute Erasmus School of Economics Erasmus University Rotterdam, The Netherlands and Department of Quantitative Economics Complutense University of Madrid, Spain And Institute of Advanced Sciences Yokohama National University, Japan.)
    Abstract: The purpose of the paper is to explore the relative biases in the estimation of the Full BEKK model as compared with the Diagonal BEKK model, which is used as a theoretical and empirical benchmark. Chang and McAleer [4] show that univariate GARCH is not a special case of multivariate GARCH, specifically, the Full BEKK model, and demonstrate that Full BEKK which, in practice, is estimated almost exclusively, has no underlying stochastic process, regularity conditions, or asymptotic properties. Diagonal BEKK (DBEKK) does not suffer from these limitations, and hence provides a suitable benchmark. We use simulated financial returns series to contrast estimates of the conditional variances and covariances from DBEKK and BEKK. The results of non-parametric tests suggest evidence of considerable bias in the Full BEKK estimates. The results of quantile regression analysis show there is a systematic relationship between the two sets of estimates as we move across the quantiles. Estimates of conditional variances from Full BEKK, relative to those from DBEKK, are lower in the left tail and higher in the right tail.
    Keywords: DBEKK, BEKK, Regularity Conditions, Asymptotic Properties, Non-Parametric, Bias, Qantile regression.
    JEL: C13 C21 C58
    Date: 2017–07
  11. By: Tröger, Tobias
    Abstract: This paper analyzes the bail-in tool under the Bank Recovery and Resolution Directive (BRRD) and predicts that it will not reach its policy objective. To make this argument, this paper first describes the policy rationale that calls for mandatory private sector involvement (PSI). From this analysis, the key features for an effective bail-in tool can be derived. These insights serve as the background to make the case that the European resolution framework is likely ineffective in establishing adequate market discipline through risk-reflecting prices for bank capital. The main reason for this lies in the avoidable embeddedness of the BRRD's bail-in tool in the much broader resolution process, which entails ample discretion of the authorities also in forcing private sector involvement. Moreover, the idea that nearly all positions on the liability side of a bank's balance sheet should be subjected to bail-in is misguided. Instead, a concentration of PSI in instruments that fall under the minimum requirements for own funds and eligible liabilities (MREL) is preferable. Finally, this paper synthesized the prior analysis by putting forward an alternative regulatory approach that seeks to disentangle private sector involvement as a precondition for effective bank-resolution as much as possible form the resolution process as such.
    Keywords: bail-in,private sector involvement,precautionary recapitalization,cross-border insolvency,market discipline
    JEL: G01 G18 G21 G28 K22 K23
    Date: 2017
  12. By: Weipin Wu; Jianjun Gao; Duan Li; Yun Shi
    Abstract: We study in this paper a class of constrained linear-quadratic (LQ) optimal control problem formulations for the scalar-state stochastic system with multiplicative noise, which has various applications, especially in the financial risk management. The linear constraint on both the control and state variables considered in our model destroys the elegant structure of the conventional LQ formulation and has blocked the derivation of an explicit control policy so far in the literature. We successfully derive in this paper the analytical control policy for such a class of problems by utilizing the state separation property induced from its structure. We reveal that the optimal control policy is a piece-wise affine function of the state and can be computed off-line efficiently by solving two coupled Riccati equations. Under some mild conditions, we also obtain the stationary control policy for infinite time horizon. We demonstrate the implementation of our method via some illustrative examples and show how to calibrate our model to solve dynamic constrained portfolio optimization problems.
    Date: 2017–09
  13. By: Hannes Mueller; Christopher Rauh
    Abstract: This article provides a new methodology to predict armed conflict by using newspaper text. Through machine learning, vast quantities of newspaper text are reduced to interpretable topics. These topics are then used in panel regressions to predict the onset of conflict. We propose the use of the within-country variation of these topics to predict the timing of conflict. This allows us to avoid the tendency of predicting conflict only in countries where it occurred before. We show that the within-country variation of topics is a good predictor of conflict and becomes particularly useful when risk in previously peaceful countries arises. Two aspects seem to be responsible for these features. Topics provide depth because they consist of changing, long lists of terms which makes them able to capture the changing context of conflict. At the same time topics provide width because they are summaries of the full text, including stabilizing factors.
    Keywords: Civil War, conflict, early-warning, topic model, forecasting, machine learning, news, prediction, panel regression
    JEL: O11 O43
    Date: 2017–09
  14. By: Paolo Di Tella; Martin Haubold; Martin Keller-Ressel
    Abstract: We consider hedging of a contingent claim by a 'semi-static' strategy composed of a dynamic position in one asset and static (buy-and-hold) positions in other assets. We give general representations of the optimal strategy and the hedging error under the criterion of variance-optimality and provide tractable formulas using Fourier-integration in case of the Heston model. We also consider the problem of optimally selecting a sparse semi-static hedging strategy, i.e. a strategy which only uses a small subset of available hedging assets. The developed methods are illustrated in an extended numerical example where we compute a sparse semi-static hedge for a variance swap using European options as static hedging assets.
    Date: 2017–09
  15. By: Henselmann, Klaus; Haller, Stefanie
    Abstract: Das Gesetz zur Modernisierung des Besteuerungsverfahrens (StModernG) gestattet es der deutschen Finanzverwaltung die Daten der sog. E-Bilanz (§ 5b EStG) in ihrem fiskalischen Risikomanagement-System auszuwerten. Dies kann zur gezielten Auswahl von Unternehmen für eine spätere Betriebsprüfung genutzt werden. Details zur Ausgestaltung des Risikomanagement-Systems auf Basis der E-Bilanz-Datensätze sind bislang nicht bekannt. Der Beitrag identifiziert mögliche Risikofaktoren, deren Auftreten in einer vom Steuerpflichtigen einge¬reichten E-Bilanz dazu führen könnte, dass sein Unternehmen im Risikomanagement-System der Finanzverwaltung als risikoreich eingestuft wird. Als Risikofaktoren gelten dabei Sachverhalte oder Umstände, die Indizien für eine erhöhte Fehleranfälligkeit oder für aggressive Steuervermeidungsstrategien sind. Alle XBRL-Tags der E-Bilanz Taxonomie 6.0 werden in Hinblick auf solche Risiken analysiert und klassifiziert. Die Ergebnisse werden durch strukturierte Expertenbefragungen auf ihre Relevanz für die Praxis der Betriebsprüfung hin validiert.
    Keywords: Risk Management,Risk Factors,Tax Audit,Taxation,XBRL,Taxonomy,Risikomanagement,Besteuerung,Betriebsprüfung,E-Bilanz,Deutschland
    JEL: H25 H26 K34 M41 M42
    Date: 2017
  16. By: Koen De Bock (Audencia Recherche - Audencia Business School)
    Abstract: Numerous organizations and companies rely upon business failure prediction to assess and minimize the risk of initiating business relationships with partners, clients, debtors or suppliers. Advances in research on business failure prediction have been largely dominated by algorithmic development and comparisons led by a focus on improvements in model accuracy. In this context, ensemble learning has recently emerged as a class of particularly well-performing methods, albeit often at the expense of increased model complexity. However, in practice, model choice is rarely based on predictive performance alone. Models should be comprehensible and justifiable to assess their compliance with common sense and business logic, and guarantee their acceptance throughout the organization. A promising ensemble classification algorithm that has been shown to reconcile performance and comprehensibility are rule ensembles. In this study, an extension entitled spline-rule ensembles is introduced and validated in the domain of business failure prediction. Spline-rule ensemble complement rules and linear terms found in conventional rule ensembles with smooth functions with the aim of better accommodating nonlinear simple effects of individual features on business failure. Experiments on a large selection of 21 datasets of European companies in various sectors and countries (i) demonstrate superior predictive performance of spline-rule ensembles over a set of well-established yet powerful benchmark methods, (ii) show the superiority of spline-rule ensembles over conventional rule ensembles and thus demonstrate the value of the incorporation of smoothing splines, (iii) investigate the impact of alternative term regularization procedures and (iv) illustrate the comprehensibility of the resulting models through a case study. In particular, the ability of the technique to reveal the extent and the way in which predictors impact business failure, and if and how variables interact, are exemplified.
    Keywords: Bankruptcy prediction,business failure prediction,data mining,ensemble learning,model comprehensibility,penalized cubic regression splines,rule ensembles,spline-rule ensembles,risk management
    Date: 2017

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