nep-rmg New Economics Papers
on Risk Management
Issue of 2018‒02‒19
fifteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Pricing formulae for derivatives in insurance using the Malliavin calculus By Caroline Hillairet; Ying Jiao
  2. Shapes of implied volatility with positive mass at zero By Stefano De Marco; Caroline Hillairet; Antoine Jacquier
  3. Systemic-risk-efficient asset allocation: Minimization of systemic risk as a network optimization problem By Anton Pichler; Sebastian Poledna; Stefan Thurner
  4. Corporate Credit Risk Premia By Antje Berndt; Rohan Douglas; Darrell Duffie; Mark Ferguson
  5. Identifying systemically important companies in the entire liability network of a small open economy By Sebastian Poledna; Abraham Hinteregger; Stefan Thurner
  6. Quantification of systemic risk from overlapping portfolios in the financial system By Sebastian Poledna; Seraf\'in Mart\'inez-Jaramillo; Fabio Caccioli; Stefan Thurner
  7. Multi-factor approximation of rough volatility models By Eduardo Abi Jaber; Omar El Euch
  8. Risks in China’s Financial System By Zheng Michael Song; Wei Xiong
  9. Time Varying Heteroskedastic Realized GARCH models for tracking measurement error bias in volatility forecasting By Gerlach, Richard; Naimoli, Antonio; Storti, Giuseppe
  10. Investor Sentiment and Crash Risk in Safe Havens By Adnen Ben Nasr; Matteo Bonato; Riza Demirer; Rangan Gupta
  11. Compulsory insurance and voluntary self-insurance: substitutes or complements? A matter of risk attitudes By François Pannequin; Anne Corcos
  12. An approach to risk quantification based on pseudo-random failure rates By Vicente González-Prida; Jayakumar Shambhu; Antonio Jesus Guillen; Joel Adams; François Pérès; Khairy Kobbacy
  13. Measuring Geopolitical Risk By Dario Caldara; Matteo Iacoviello
  14. What is the Sharpe Ratio, and how can everyone get it wrong? By Igor Rivin
  15. Closed-form and numerical computations of actuarial indicators in ruin theory and claim reserving By Alexandre Brouste; Christophe Dutang

  1. By: Caroline Hillairet (ENSAE; Université Paris Saclay); Ying Jiao (Université Claude Bernard - Lyon 1; Institut de Science Financière et d’Assurances)
    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: 2017–07–13
  2. By: Stefano De Marco (CMAP; Ecole Polytechnique); Caroline Hillairet (CREST; Ensae; Université Paris Saclay); Antoine Jacquier (Imperial College London)
    Abstract: We study the shapes of the implied volatility when the underlying distribution has an atom at zero. We show that the behaviour at small strikes is uniquely determined by the mass of the atom at least up to the third asymptotic order, regardless of the properties of the remaining (absolutely continuous, or singular) distribution on the positive real line. We investigate the structural difference with the no-mass-at-zero case, showing how one can—a priori—distinguish between mass at the origin and a heavy-left-tailed distribution. An atom at zero is found in stochastic models with absorption at the boundary, such as the CEV process, and can be used to model default events, as in the class of jump-to-default structural models of credit risk. We numerically test our model-free result in such examples. Note that while Lee’s moment formula [21] tells that implied variance is at most asymptotically linear in log-strike, other celebrated results for exact smile asymptotics such as [2, 14] do not apply in this setting essentially due to the breakdown of Put-Call symmetry—and we rely here on an alternative treatment of the problem.
    Keywords: Atomic distribution, heavy-tailed distribution, Implied Volatility, smile asymptotics, absorption at zero, CEV model
    Date: 2017–10–03
  3. By: Anton Pichler; Sebastian Poledna; Stefan Thurner
    Abstract: Systemic risk arises as a multi-layer network phenomenon. Layers represent direct financial exposures of various types, including interbank liabilities, derivative- or foreign exchange exposures. Another network layer of systemic risk emerges through common asset holdings of financial institutions. Strongly overlapping portfolios lead to similar exposures that are caused by price movements of the underlying financial assets. Based on the knowledge of portfolio holdings of financial agents we quantify systemic risk of overlapping portfolios. We present an optimization procedure, where we minimize the systemic risk in a given financial market by optimally rearranging overlapping portfolio networks, under the constraints that the expected returns and risks of the individual portfolios are unchanged. We explicitly demonstrate the power of the method on the overlapping portfolio network of sovereign exposure between major European banks by using data from the European Banking Authority stress test of 2016. We show that systemic-risk-efficient allocations are accessible by the optimization. In the case of sovereign exposure, systemic risk can be reduced by more than a factor of two, with- out any detrimental effects for the individual banks. These results are confirmed by a simple simulation of fire sales in the government bond market. In particular we show that the contagion probability is reduced dramatically in the optimized network.
    Date: 2018–01
  4. By: Antje Berndt; Rohan Douglas; Darrell Duffie; Mark Ferguson
    Abstract: We measure credit risk premia - prices for bearing corporate default risk in excess of expected default losses - using Markit CDS and Moody’s Analytics EDF data. We find dramatic variation over time in credit risk premia, with peaks in 2002, during the global financial crisis of 2008-09, and in the second half of 2011. Even after normalizing these premia by expected default losses, median credit risk premia fluctuate over time by more than a factor of ten. Credit risk premia comove with macroeconomic indicators, even after controlling for variation in expected default losses, with higher premia per unit of expected loss during times of market-wide distress. Countercyclical variation of premia-to-expected-loss ratios is more pronounced for investment-grade issuers than for high-yield issuers.
    JEL: G12 G13 G22 G24
    Date: 2018–01
  5. By: Sebastian Poledna; Abraham Hinteregger; Stefan Thurner
    Abstract: To a large extent, the systemic importance of financial institutions is related to the topology of financial liability networks. In this work we reconstruct and analyze the - to our knowledge - largest financial network that has been studied up to now. This financial liability network consists of 51,980 firms and 796 banks. It represents 80.2% of total liabilities towards banks by firms and all interbank liabilities from the entire Austrian banking system. We find that firms contribute to systemic risk in similar ways as banks do. In particular, we identify several medium-sized banks and firms with total assets below 1 bln. EUR that are systemically important in the entire financial network. We show that the notion of systemically important financial institutions (SIFIs) or global and domestic systemically important banks (G-SIBs or D-SIBs) can be straightforwardly extended to firms. We find that firms introduce slightly more systemic risk than banks. In Austria in 2008, the total systemic risk of the interbank network amounts to only 29% of the total systemic risk of the entire financial network, consisting of firms and banks.
    Date: 2018–01
  6. By: Sebastian Poledna; Seraf\'in Mart\'inez-Jaramillo; Fabio Caccioli; Stefan Thurner
    Abstract: Financial markets are exposed to systemic risk, the risk that a substantial fraction of the system ceases to function and collapses. Systemic risk can propagate through different mechanisms and channels of contagion. One important form of financial contagion arises from indirect interconnections between financial institutions mediated by financial markets. This indirect interconnection occurs when financial institutions invest in common assets and is referred to as overlapping portfolios. In this work we quantify systemic risk from indirect interconnections between financial institutions. Having complete information of security holdings of major Mexican financial intermediaries and the ability to uniquely identify securities in their portfolios, allows us to represent the Mexican financial system as a bipartite network of securities and financial institutions. This makes it possible to quantify systemic risk arising from overlapping portfolios. We show that focusing only on direct exposures underestimates total systemic risk levels by up to 50%. By representing the financial system as a multi-layer network of direct exposures (default contagion) and indirect exposures (overlapping portfolios) we estimate the mutual influence of different channels of contagion. The method presented here is the first objective data-driven quantification of systemic risk on national scales that includes overlapping portfolios.
    Date: 2018–01
  7. By: Eduardo Abi Jaber (CEREMADE); Omar El Euch
    Abstract: Rough volatility models are very appealing because of their remarkable fit of both historical and implied volatilities. However, due to the non-Markovian and non-semimartingale nature of the volatility process, there is no simple way to simulate efficiently such models, which makes risk management of derivatives an intricate task. In this paper, we design tractable multi-factor stochastic volatility models approximating rough volatility models and enjoying a Markovian structure. Furthermore, we apply our procedure to the specific case of the rough Heston model. This in turn enables us to derive a numerical method for solving fractional Riccati equations appearing in the characteristic function of the log-price in this setting.
    Date: 2018–01
  8. By: Zheng Michael Song; Wei Xiong
    Abstract: Motivated by growing concerns about the risks and instability of China’s financial system, this article reviews several commonly perceived financial risks and discusses their roots in China’s politico-economic institutions. We emphasize the need to evaluate these risks within China’s unique economic and financial systems, in which the state and non-state sectors coexist and the financial system serves as a key tool of the government to fund its economic policies. Overall, we argue that: (1) financial crisis is unlikely to happen in the near future, and (2) the ultimate risk lies with China’s economic growth, as a vicious circle of distortions in the financial system lowers the efficiency of capital allocation and economic growth and will eventually exacerbate financial risks in the long run.
    JEL: E00 E02 G00 G01
    Date: 2018–01
  9. By: Gerlach, Richard; Naimoli, Antonio; Storti, Giuseppe
    Abstract: This paper proposes generalisations of the Realized GARCH model by Hansen et al. (2012), in three different directions. First, heteroskedasticity in the noise term in the measurement equation is allowed, since this is generally assumed to be time-varying as a function of an estimator of the Integrated Quarticity for intra-daily returns. Second, in order to account for attenuation bias effects, the volatility dynamics are allowed to depend on the accuracy of the realized measure. This is achieved by letting the response coefficient of the lagged realized measure depend on the time-varying variance of the volatility measurement error, thus giving more weight to lagged volatilities when they are more accurately measured. Finally, a further extension is proposed by introducing an additional explanatory variable into the measurement equation, aiming to quantify the bias due to effect of jumps and measurement errors.
    Keywords: Realized Volatility, Realized GARCH, Measurement Error, Realized Quarticity
    JEL: C22 C53 C58
    Date: 2018–01–08
  10. By: Adnen Ben Nasr (BESTMOD, Institut Supérieur de Gestion de Tunis, Université de Tunis, Tunisia); Matteo Bonato (Department of Economics and Econometrics, University of Johannesburg, Auckland Park, South Africa); Riza Demirer (Department of Economics and Finance, Southern Illinois University Edwardsville, Edwardsville, USA); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa)
    Abstract: This study examines the relationship between investor sentiment and intraday return dynamics for safe haven assets, with particular focus on crash risk in these assets. Examining intraday returns for a wide range of safe havens proposed in the literature, we find that shocks to investor sentiment have a significant effect on most safe havens, while the sentiment is heterogeneous both in terms of its size and direction. While the strongest effects of sentiment shocks are observed in the case of Gold, Swiss Francs and Japanese Yen, interestingly, we find that oil stands out from the rest of the pack, responding negatively to sentiment shocks, suggesting that positive shocks to sentiment (i.e. high fear) increase crash risk for this asset. Our findings also point to intra-safe haven spillover effects, with oil exhibiting a markedly different pattern. Investment and hedging implications are discussed next.
    Keywords: Investor sentiment, Safe haven assets, Intraday returns, Crash risk
    JEL: C32 Q02
    Date: 2018–01
  11. By: François Pannequin (CREST; Ecole Normale Supérieure Paris-Saclay); Anne Corcos (CURAPP; Université de Picardie Jules Verne,)
    Abstract: Based on Ehrlich and Becker’s model (1972) on insurance and self-insurance substitutability, we study the effects of a compulsory partial insurance on self-insurance decisions of both risk-averters and (mixed) risk-lovers. We show that when insurance is compulsory, risk-averters adjust (by substituting) their self-insurance behavior to compensate for the level (too high or too low) of the compulsory coverage level. By contrast, even though they would refuse to invest in any voluntarily hedging scheme, (mixed) risk-lovers freely invest in self-insurance to complete a compulsory partial insurance coverage. Moreover, we prove that for a (mixed) risk-lover, an increase in the partial compulsory insurance coverage induces simultaneously a rise of the self-insurance marginal benefit and a decrease of its marginal cost. Therefore, while compulsory insurance and self-insurance are substitutes for risk-averters, they are complements for (mixed) risk-lovers. This last result brings an unexpected justification for compulsory insurance policies.
    Keywords: self-insurance; compulsory insurance; risk attitudes; risk-lovers
    JEL: D11 D86 G22 K32 L51
    Date: 2017–08–01
  12. By: Vicente González-Prida (University of Seville Camino de los Descubrimientos S/N - University of Seville Camino de los Descubrimientos S/N); Jayakumar Shambhu (University of Stavanger - University of Stavanger); Antonio Jesus Guillen (University of Seville Camino de los Descubrimientos S/N - University of Seville Camino de los Descubrimientos S/N); Joel Adams (University of Cambrige (UNITED KINGDOM)); François Pérès (LGP - Laboratoire Génie de Production - Ecole Nationale d'Ingénieurs de Tarbes); Khairy Kobbacy (Taibah University - Taibah University)
    Abstract: The risk quantification is one of the most critical areas in asset management (AM). The relevant information from the traditional models can be shown in risk matrices that represent a static picture of the risk levels and are according to its frequency and its impact (consequences). These models are used in a wide spectrum of knowledge domains. In this paper, we describe a quantitative model using the reliability and failure probability (as frequency in our risk model), and the preventive and corrective costs (as consequences in our risk model). The challenge here will be the treatment of reliability based on failure rate values with different e random distributions (normal, triangular etc.) according to the available data. These possible values will enable the simulation of the behavior of the system in terms of reliability and, consequently, to use this information for making a risk based analysis. The traditional risk-cost-benefit models applied to maintenance usually provides an optimum for the time to apply a preventive task. But in this case, a time window is obtained showing minimum and maximum thresholds for the best time to apply the preventive maintenance task, together with other interesting statistics useful for the improvement of complex industrial asset management.
    Keywords: Reliability,Statistical approaches,Asset and maintenance management,Maintenance models,Engineering
    Date: 2016
  13. By: Dario Caldara; Matteo Iacoviello
    Abstract: We present a monthly indicator of geopolitical risk based on a tally of newspaper articles covering geopolitical tensions, and examine its evolution and effects since 1985. The geopolitical risk (GPR) index spikes around the Gulf War, after 9/11, during the 2003 Iraq invasion, during the 2014 Russia-Ukraine crisis, and after the Paris terrorist attacks. High geopolitical risk leads to a decline in real activity, lower stock returns, and movements in capital flows away from emerging economies and towards advanced economies. When we decompose the index into threats and acts components, the adverse effects of geopolitical risk are mostly driven by the threat of adverse geopolitical events. Extending our index back to 1900, geopolitical risk rose dramatically during the World War I and World War II, was elevated in the early 1980s, and has drifted upward since the beginning of the 21st century.
    Keywords: Geopolitical Risk ; Economic Uncertainty ; War ; Terrorism ; Business Cycles
    JEL: C1 D80 E32 H56
    Date: 2018–02–02
  14. By: Igor Rivin
    Abstract: The Sharpe ratio is the most widely used risk metric in the quantitative finance community - amazingly, essentially everyone gets it wrong. In this note, we will make a quixotic effort to rectify the situation.
    Date: 2018–02
  15. By: Alexandre Brouste (Laboratoire Manceau de Mathématiques, - Aucune); Christophe Dutang (LMM - Laboratoire Manceau de Mathématiques - UM - Le Mans Université)
    Abstract: Insurance reserving is a key topic for both actuaries and academics. In the present paper, we present an efficient way to compute all the key indicators in a unified approach of the ruin theory and claim reserving methods. The proposed framework allows to derive closed-form formulas for both ruin theory and claim reserves indicators. A numerical illustration of these indicators is carried out on a real dataset from a private insurer. Résumé Le provisionnement en assurance non-vie est un sujet clé pour les actuaires et les académiques. Dans le présent article, nous présentons une méthode efficace pour calculer les indicateurs par une approche unifiée de la théorie de la ruine et du provisionnement non-vie. Le cadre proposé permet de déduire des formules fermées pour les indicateurs de provisionnement et de ruine. Une illustration de ces indicateurs est réalisée sur un jeu de données réellles. Mots-clés : théorie de la ruine, provisionnement non-vie, processus de Poisson, assurance non vie.
    Keywords: ruin theory,claim reserving,Poisson process,non-life insurance
    Date: 2016–01

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