nep-rmg New Economics Papers
on Risk Management
Issue of 2019‒04‒08
twenty papers chosen by

  1. What They Did Not Tell You About Algebraic (Non-)Existence, Mathematical (IR-)Regularity and (Non-)Asymptotic Properties of the Dynamic Conditional Correlation (DCC) Model By Michael McAleer
  2. Risk Management in Financial Institutions By Adriano A. Rampini; S. Viswanathan; Guillaume Vuillemey
  3. Least Impulse Response Estimator for Stress Test Exercises By Christian Gourieroux; Yang Lu
  4. Risk Aversion and Bitcoin Returns in Normal, Bull, and Bear Markets By Elie Bouri; Rangan Gupta; Chi Keung Marco Lau; David Roubaud
  5. Quantile coherency networks of international stock markets By Baumöhl, Eduard; Shahzad, Syed Jawad Hussain
  6. The nexus between underlying dynamics of bank capital buffer and performance. By Mamatzakis, Emmanuel; Bagntasarian, Anna
  7. Optimal Reinsurance and Investment in a Diffusion Model By Matteo Brachetta; Hanspeter Schmidli
  8. Does banks’ systemic importance affect their capital structure and balance sheet adjustment processes? By Yassine Bakkar; Olivier De Jonghe; Amine Tarazi
  10. Policy News and Stock Market Volatility By Scott R. Baker; Nicholas Bloom; Steven J. Davis; Kyle J. Kost
  11. Incentive Pay and Systemic Risk By Rui Albuquerque; Luis Cabral; Jose Guedes
  12. Understanding International Financial Crises By Reyes, Danilo
  13. Interpreting the Oil Risk Premium: do Oil Price Shocks Matter? By Valenti, Daniele; Manera, Matteo; Sbuelz, Alessandro
  14. The Relation between Behavior under Risk and over Time By Anujit Chakraborty; Yoram Halevy; Kota Saito
  15. A Thermodynamic Picture of Financial Market and Model Risk By Yu Feng
  16. ANALYSIS OF RISK PROPAGATION SCENARIOS WITHIN A PROJECT ORGANIZATION By Franck Marle; Meriam Kilani; Catherine Pointurier; Laurent Dehouck
  17. The Impact of Jumps and Leverage in Forecasting the Co-Volatility of Oil and Gold Futures By Manabu Asai; Rangan Gupta; Michael McAleer
  18. On Conceptualizing Risk: A Comment on Hoffmann By Xavier Méra
  19. FLIGHTS TO SAFETY By Lieven Baele; Geert Bekaert; Koen Inghelbrecht; Min Wei
  20. APPROACH AND SYSTEMIC APPROACH FOR RISK MANAGEMENT By Yves Mérian; Guy Planchette; André Lannoy; Myriam Merad

  1. By: 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: In order to hedge efficiently, persistently high negative covariances or, equivalently, correlations, between risky assets and the hedging instruments are intended to mitigate against financial risk and subsequent losses. If there is more than one hedging instrument, multivariate covariances and correlations will have to be calculated. As optimal hedge ratios are unlikely to remain constant using high frequency data, it is essential to specify dynamic time-varying models of covariances and correlations. These values can either be determined analytically or numerically on the basis of highly advanced computer simulations. Analytical developments are occasionally promulgated for multivariate conditional volatility models. The primary purpose of the paper is to analyse purported analytical developments for the only multivariate dynamic conditional correlation model to have been developed to date, namely Engle’s (2002) widely-used Dynamic Conditional Correlation (DCC) model. Dynamic models are not straightforward (or even possible) to translate in terms of the algebraic existence, underlying stochastic processes, specification, mathematical regularity conditions, and asymptotic properties of consistency and asymptotic normality, or the lack thereof. The paper presents a critical analysis, discussion, evaluation and presentation of caveats relating to the DCC model, and an emphasis on the numerous dos and don’ts in implementing the DCC and related model in practice.
    Keywords: Hedging, Covariances, Correlations, Existence, Mathematical regularity, Invertibility, Likelihood function, Statistical asymptotic properties, Caveats, Practical implementation.
    JEL: C22 C32 C51 C52 C58 C62 G32
  2. By: Adriano A. Rampini; S. Viswanathan; Guillaume Vuillemey
    Abstract: We study risk management in financial institutions using data on hedging of interest rate and foreign exchange risk. We find strong evidence that better capitalized institutions hedge more, controlling for risk exposures, both across institutions and within institutions over time. For identification, we exploit net worth shocks resulting from loan losses due to drops in house prices. Institutions that sustain such shocks reduce hedging significantly relative to otherwise similar institutions. The reduction in hedging is differentially larger among institutions with high real estate exposure. The evidence is consistent with the theory that financial constraints impede both financing and hedging.
    JEL: D92 E44 G21 G32
    Date: 2019–03
  3. By: Christian Gourieroux (University of Toronto and Toulouse School of Economics); Yang Lu (Centre d'Economie de l'Université de Paris Nord (CEPN))
    Abstract: We introduce new semi-parametric models for the analysis of rates and proportions, such as proportions of default, (expected) loss-given-default and credit conversion factor encountered in credit risk analysis. These models are especially convenient for the stress test exercises demanded in the current prudential regulation. We show that the Least Impulse Response Estimator, which minimizes the estimated effect of a stress, leads to consistent parameter estimates. The new models with their associated estimation method are compared with the other approaches currently proposed in the literature such as the beta and logistic regressions. The approach is illustrated by both simulation experiments and the case study of a retail P2P lending portfolio.
    Keywords: Basel Regulation, Stress Test, (Expected) Loss-Given-Default,Impulse Response, Credit Scoring, Pseudo-Maximum Likelihood, LIR Estimation, Beta Regression, Moebius Transformation.
    JEL: C51 G21
    Date: 2019–03
  4. By: Elie Bouri (USEK Business School, Holy Spirit University of Kaslik, Jounieh, Lebanon); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa); Chi Keung Marco Lau (Department of Accountancy, Finance and Economics, Huddersfield Business School, University of Huddersfield, Queensgate, Huddersfield, HD1 3DH, UK); David Roubaud (Montpellier Business School, Montpellier, France)
    Abstract: We study whether level of risk aversion can be used to predict Bitcoin returns. Using a copula-quantile approach, we find evidence of predictability for the lower and upper quantiles of the conditional distribution of returns (i.e., in bull and bear markets). To reveal the sign of the predictability, we apply the cross-quantilogram approach and find that the cross-quantilogram is similar when risk aversion is at the low or medium level for various quantiles of Bitcoin returns. In particular, we find positive predictability when the risk aversion is very low and at the medium level. However, the predictability becomes negative when both the risk aversion and Bitcoin returns are very high, suggesting that very high levels of risk aversion are likely to drive down Bitcoin returns in a bull market.
    Keywords: Risk-aversion, Bitcoin returns, price predictability, copulas, quantiles
    JEL: C22 G10
    Date: 2019–03
  5. By: Baumöhl, Eduard; Shahzad, Syed Jawad Hussain
    Abstract: This paper uses the novel quantile coherency approach to examine the tail dependence network of 49 international stock markets in the frequency domain. We find that geographical proximity and state of market development are important factors in stock markets networks. Both the short- and long-run connectedness significantly increased after the global financial crisis and spillover is higher during bearish market states, highlighting the possibility of contagion effect mainly among developed markets. Frontier and emerging markets are relatively less connected. These findings have implications for international equity market diversification and risk management.
    Keywords: quantile coherency,networks,stock markets,extreme negative returns,financial crisis
    JEL: C32 C40 G01 G15
    Date: 2019
  6. By: Mamatzakis, Emmanuel; Bagntasarian, Anna
    Abstract: This paper reveals the underlying dynamics between the capital buffer and bank performance in EU-27 countries. A dynamic panel analysis shows that capital buffer is significantly affected by bank performance and risk exposure. Remarkably, a threshold analysis identifies regime changes for the underlying relationships during the financial crisis of 2008. We find a positive relationship between the capital buffer and performance for banks that fall in the low performance regime, while a negative relationship is reported for the banks that belong to the high regime. Threshold results also show that buffer exerts a positive impact on bank performance. Although regulation reforms that aim to raise the capital requirements could improve bank performance and stability, these improvements are not homogeneous across banks.
    Keywords: Capital buffer; Dynamic threshold; Performance; Bank default risk.
    JEL: G0 G1 G2
    Date: 2019–03–14
  7. By: Matteo Brachetta; Hanspeter Schmidli
    Abstract: We consider a diffusion approximation to an insurance risk model where an external driver models a stochastic environment. The insurer can buy reinsurance. Moreover, investment in a financial market is possible. The financial market is also driven by the environmental process. Our goal is to maximise terminal expected utility. In particular, we consider the case of SAHARA utility functions. In the case of proportional and excess-of-loss reinsurance, we obtain explicit results.
    Date: 2019–03
  8. By: Yassine Bakkar (Université de Limoges, LAPE); Olivier De Jonghe (Economics and Research Department, NBB and European Banking Center, Tilburg University); Amine Tarazi (Université de Limoges, LAPE and Institut Universitaire de France (IUF))
    Abstract: Frictions prevent banks to immediately adjust their capital ratio towards their desired and/or imposed level. This paper analyzes (i) whether or not these frictions are larger for regulatory capital ratios vis-à-vis a plain leverage ratio; (ii) which adjustment channels banks use to adjust their capital ratio; and (iii) how the speed of adjustment and adjustment channels differ between large, systemic and complex banks versus small banks. Our results, obtained using a sample of listed banks across OECD countries for the 2001-2012 period, bear critical policy implications for the implementation of new (systemic risk-based) capital requirements and their impact on banks’ balance sheets, specifically lending, and hence the real economy.
    Keywords: , capital structure, speed of adjustment, systemic risk, systemic size, bank regulation, lending, balance sheet composition
    JEL: G20 G21 G28
    Date: 2019–03
  9. By: Michel Giraudeau (Institut pour la Maîtrise des Risques - Institut pour la Maîtrise des Risques); Yves Mérian (Institut pour la Maîtrise des Risques - Institut pour la Maîtrise des Risques); Alioune Cisse (AFNOR)
    Date: 2018–10–16
  10. By: Scott R. Baker; Nicholas Bloom; Steven J. Davis; Kyle J. Kost
    Abstract: We create a newspaper-based Equity Market Volatility (EMV) tracker that moves with the VIX and with the realized volatility of returns on the S&P 500. Parsing the underlying text, we find that 72 percent of EMV articles discuss the Macroeconomic Outlook, and 44 percent discuss Commodity Markets. Policy news is another major source of volatility: 35 percent of EMV articles refer to Fiscal Policy (mostly Tax Policy), 30 percent discuss Monetary Policy, 25 percent refer to one or more forms of Regulation, and 13 percent mention National Security matters. The contribution of particular policy areas fluctuates greatly over time. Trade Policy news, for example, went from a virtual nonfactor in equity market volatility to a leading source after Donald Trump’s election and especially after the intensification of U.S-China trade tensions. The share of EMV articles with attention to government policy rises over time, reaching its peak in 2017-18. We validate our measurement approach in various ways. For example, tailoring our EMV tracker to news about petroleum markets yields a measure that rises and falls with the implied and realized volatility of oil prices.
    JEL: E44 G12 G18
    Date: 2019–03
  11. By: Rui Albuquerque; Luis Cabral; Jose Guedes
    Date: 2018
  12. By: Reyes, Danilo
    Abstract: This review article presents an overview of the themes developed in the theoretical literature on international financial crises before the Global Financial Crisis in 2008. The directions that future research might take are discussed in conclusion.
    Keywords: Financial Crises
    JEL: G01
    Date: 2019–01
  13. By: Valenti, Daniele; Manera, Matteo; Sbuelz, Alessandro
    Abstract: This paper provides an analysis of the link between the global market for crude oil and oil futures risk premium at the aggregate level. It offers empirical evidence on whether the compensation for risk required by the speculators depends on the type of the structural shock of interest. Understanding the response of the risk premium to unexpected changes in the price of oil can be useful to address some research questions, among which: what is the relationship between crude oil risk premium and unexpected rise in the price of oil? On average, what should speculators expect to receive as a compensation for the risk they are taking on? This work is based on a Structural Vector Autoregressive (SVAR) model of the crude oil market. Two main results emerge. First, the impulse response analysis provides evidence of a negative relationship between the risk premium and the changes in the price of oil triggered by shocks to economic fundamentals. Second, this analysis shows that the historical decline of the risk premium can be modelled as a part of endogenous effect of the oil market driven shocks.
    Keywords: Research Methods/ Statistical Methods
    Date: 2018–02–26
  14. By: Anujit Chakraborty; Yoram Halevy; Kota Saito
    Abstract: The paper establishes a tight relation between non-standard behaviors in the domains of risk and time, by considering a decision maker with non-expected utility preferences who believes that only present consumption is certain while any future consumption is uncertain. We provide the first complete characterizations of the two-way relations between the certainty effect and present biased temporal behavior, and between the common ratio effect and temporal reversals related to the common difference effect.
    Keywords: time consistency, hyperbolic discounting, non-expected utility, present bias, implicit risk.
    JEL: D01 D81 D91
    Date: 2019–03–31
  15. By: Yu Feng
    Abstract: By treating the financial market as a thermodynamic system, we establish a one-to-one correspondence between thermodynamic variables and economic quantities. Measured by the expected loss under the worst-case scenario, financial risk caused by model uncertainty is regarded as a result of the interaction between financial market and external information sources. This forms a thermodynamic picture in which a closed system interacts with an external reservoir, reaching its equilibrium at the worst-case scenario. The severity of the worst-case scenario depends on the rate of heat dissipation, caused by information sources reducing the entropy of the system. This thermodynamic picture leads to simple and natural derivation of the characterization rules of the worst-case risk, and gives its Lagrangian and Hamiltonian forms. With its help financial practitioners may evaluate risks utilizing both equilibrium and non-equilibrium thermodynamics.
    Date: 2019–03
  16. By: Franck Marle (LGI - Laboratoire Génie Industriel - EA 2606 - CentraleSupélec); Meriam Kilani (LGI - Laboratoire Génie Industriel - EA 2606 - CentraleSupélec); Catherine Pointurier (CEA - Commissariat à l'énergie atomique et aux énergies alternatives); Laurent Dehouck (ENS Rennes - École normale supérieure - Rennes)
    Abstract: Les projets complexes se caractérisent par un certain nombre de phénomènes, comme des réactions non-linéaires ou chaotiques, des chaînes de propagation et des boucles/cycles. Cela entraîne pour la maîtrise des risques de tels projets un double enjeu, qui est d'une part, de mieux comprendre et anticiper dans la complexité, d'autre part de décider en connaissant du mieux possible toutes les conséquences indirectes des alternatives de décisions. Le projet étudié est un grand projet de construction, pour lequel une analyse de risques a été faite en 2014 et une autre en 2017. La problématique est la grande complexité du réseau de risques qui peut conduire le projet vers des phénomènes surprenants alors que l'analyse basique n'en tient pas du tout compte. L'approche consiste en premier lieu à étudier de façon basique les risques projets, puis les scénarios de propagation à partir de la matrice d'interactions entre risques. A chaque fois, ces valeurs sont comparées aux valeurs 2017, pour essayer d'en tirer des réponses à deux questions : • L'analyse avancée 2014 permet-elle de mieux anticiper ce qui va se passer en 2017 ? et si oui, est-ce général ou certaines zones particulières du projet, certains types de risques ? • L'analyse avancée permet-elle de mieux choisir des actions à incorporer spécifiquement dans le Plan de Maîtrise des Risques ? Certains développements sont encore en cours de réalisation, mais les premiers résultats montrent une amélioration significative de la capacité de prédiction dans les cas complexes, là où le réseau est le plus dense. De même, la correction du Plan de Maîtrise des Risques est significative par rapport à celui obtenu avec l'analyse basique.
    Date: 2018–10–16
  17. By: Manabu Asai (Faculty of Economics, Soka University, Japan); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa); Michael McAleer (Department of Finance, Asia University, Taiwan, Discipline of Business Analytics, University of Sydney Business School, Australia, Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, The Netherlands, Department of Economic Analysis and ICAE, Complutense University of Madrid, Spain, and Institute of Advanced Sciences, Yokohama National University, Japan)
    Abstract: The paper investigates the impact of jumps in forecasting co-volatility in the presence of leverage effects. We modify the jump-robust covariance estimator of Koike (2016), such that the estimated matrix is positive definite. Using this approach, we can disentangle the estimates of the integrated co-volatility matrix and jump variations from the quadratic covariation matrix. Empirical results for daily crude oil and gold futures show that the co-jumps of the two futures have significant impacts on future co-volatility, but that the impact is negligible in forecasting weekly and monthly horizons.
    Keywords: Commodity Markets, Co-volatility, Forecasting, Jump, Leverage Effects, Realized Covariance, Threshold Estimation
    JEL: C32 C33 C58 Q02
    Date: 2019–03
  18. By: Xavier Méra (Granem - Groupe de Recherche ANgevin en Economie et Management - UA - Université d'Angers - AGROCAMPUS OUEST - Institut National de l'Horticulture et du Paysage)
    Abstract: Hoffmann (2018) attempts to reconstruct a typology of risks deemed more accurate and useful to both economists and risk managers than currently received views on the subject within mainstream economics/finance and Austrian economics. This comment argues that his criticisms of the Misesian approach and his case for an alternative are unconvincing. We explain weaknesses in his criticisms of the Misesian approach and outline some problems with his constructive task of building up the alternative.
    Keywords: probability,Austrian economics,risk,uncertainty,complexity
    Date: 2018–09–23
  19. By: Lieven Baele; Geert Bekaert; Koen Inghelbrecht; Min Wei (-)
    Abstract: We identify flight-to-safety (FTS) days for 23 countries using only stock and bond returns and a model averaging approach. FTS days comprise less than 2% of the sample, and are associated with a 2.7% average bond-equity return differential and significant flows out of equity funds and into government bond and money market funds. FTS represents flights to both quality and liquidity in international equity markets, but mainly a flight-to-quality in the US corporate bond market. Emerging markets, endowment funds, and hedge funds all perform poorly during FTS, while hedge funds appear to vary their systematic exposures prior to a FTS
    Keywords: Flight-to-Safety, Flight-to-Quality, Stock-Bond Return Correlation, Liquidity, Hedge Funds
    JEL: G11 G12 G14 E43 E44
    Date: 2019–03
  20. By: Yves Mérian (Institut pour la Maîtrise des Risques - Institut pour la Maîtrise des Risques); Guy Planchette (Institut pour la Maîtrise des Risques - Institut pour la Maîtrise des Risques); André Lannoy (Institut pour la Maîtrise des Risques); Myriam Merad (CNRS - Centre National de la Recherche Scientifique)
    Abstract: Summary All the efforts to manage risks have significant results, but several issues show the limits of the results: persistence of disasters, difficulties to reduce chronical risks, existence of latent risks. In order to push the boundaries, we propose to distinguish analytical approach, which is generally used, and systemic approach which should be added to better respond to the needs of complex systems. The concept of systemic approach is described, defined, and illustrated with concrete applications, which show its interest and that it works in complementarity with the analytic approach. Operational methodologies are necessary.
    Abstract: Les efforts consacrés à la maîtrise des risques ont dans l'ensemble donné des résultats significatifs, mais plusieurs phénomènes en montrent aussi les limites : persistance de catastrophes, difficultés à réduire les risques chroniques, présence de risques latents. Pour repousser ces limites, on propose de distinguer les approches analytiques, couramment pratiquées, et les approches systémiques pour mieux répondre aux besoins de nos systèmes complexes. Le concept d'approche systémique est décrit, défini et illustré d'applications concrètes qui en montrent la validité et la complémentarité avec l'approche analytique. Des méthodologies opérationnelles sont nécessaires.
    Date: 2018–10–16

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