nep-rmg New Economics Papers
on Risk Management
Issue of 2019‒06‒10
nineteen papers chosen by

  1. Making the square-root formula compatible with capital allocation By Paulusch, Joachim; Schlütter, Sebastian
  2. Time-Series Momentum: A Monte-Carlo Approach By Enoch Cheng; Clemens C. Struck
  3. Study of currency risk and the hedging strategies. By Tiwari, Anuradha
  4. The Network Effect in Credit Concentration Risk By Davide Cellai; Trevor Fitzpatrick
  5. Asset Price Bubbles and Systemic Risk By Markus Brunnermeier; Simon Rother; Isabel Schnabel
  6. The Effect of Possible EU Diversification Requirements on the Risk of Banks’ Sovereign Bond Portfolios By Craig, Ben R.; Giuzio, Margherita; Paterlini, Sandra
  7. Firm-Level Political Risk: Measurement and Effects By Tarek A. Hassan; Stephan Hollander; Laurence van Lent; Ahmed Tahoun
  8. Mortality Options: the Point of View of an Insurer By Schmeck, Maren Diane; Schmidli, Hanspeter
  9. A new approach of coherent risk-measure pricing By Jun Zhao; Emmanuel Lépinette; Peibiao Zhao
  10. Credit Scoring by Incorporating Dynamic Network Information By Yibei Li; Ximei Wang; Boualem Djehiche; Xiaoming Hu
  11. Weather Index Insurance in Sub-Saharan Africa By Ernst Juerg Weber
  12. Shipping Inspections, Detentions, and Accidents: An Empirical Analysis of Risk Dimensions By Heij, C.; Knapp, S.
  13. Cross-sectional Learning of Extremal Dependence among Financial Assets By Xing Yan; Qi Wu; Wen Zhang
  14. An assets-liabilities dynamical model of banking system and systemic risk governance By Lorella Fatone; Francesca Mariani
  15. Forecasting Realized Gold Volatility: Is there a Role of Geopolitical Risks? By Konstantinos Gkillas; Rangan Gupta; Christian Pierdzioch
  16. Preferences Over Rich Sets of Random Variables: Semicontinuity in Measure versus Convexity By Alexander Zimper; Hirbod Assa
  17. Bailouts, Bail-ins and Banking Crises By Todd Keister; Yuliyan Mitkov
  18. Financial Characteristics of Cost of Funds Indexed Loans By Greenfield, Patrick; Hall, Arden
  19. Risk allocation and management in PPP and PFI: Systematic Literature Review By Mouhcine Tallaki; Enrico Bracci; Federico Stefani

  1. By: Paulusch, Joachim; Schlütter, Sebastian
    Abstract: Modern regulatory capital standards, such as the Solvency II standard formula, employ a correlation based approach for risk aggregation. The so-called "square-root formula" uses correlation parameters between, for example, market risk, non-life insurance risk and default risk to determine the company's aggregate capital requirement. To support decision-making, companies will allocate the required capital back to business segments and risk drivers. We demonstrate that capital allocations based on the square-root formula can substantially differ from those based on the true risk distribution if correlations are viewed as Pearson or tail correlations. An EVA-maximizing insurer receives misleading steering signals which can induce mispricing of risk and a default probability substantially above the desired level. To make the square-root formula feasible for business steering, we propose partial-derivative-implied correlations which reflect how marginal exposure changes impact the aggregate capital requirement. We show that the square-root formula in combination with partial-derivative-implied correlations provides capital allocations in line with the true risk distribution.
    Keywords: Solvency II,Tail correlation,Risk aggregation,Capital allocation
    JEL: G22 G28 G32
    Date: 2019
  2. By: Enoch Cheng; Clemens C. Struck
    Abstract: This paper develops a Monte-Carlo backtesting procedure for risk premia strategies and employs it to study Time-Series Momentum (TSM). Relying on time-series models, empirical residual distributions and copulas we overcome two key drawbacks of conventional backtesting procedures. We create 10,000 paths of different TSM strategies based on the S&P 500 and a cross-asset class futures portfolio. The simulations reveal a probability distribution which shows that strategies that outperform Buy-and-Hold in-sample using historical backtests may out-of-sample i) exhibit sizeable tail risks ii) underperform or outperform. Our results are robust to using different time-series models, time periods, asset classes, and risk measures.
    Keywords: Monte-Carlo; Extreme Value Theory; Backtesting; Risk premia; Time-Series Momentum
    JEL: C12 C52 G12 F37
    Date: 2019–03
  3. By: Tiwari, Anuradha
    Abstract: The globalization of financial markets achieved by dynamic technological advancements, financial market liberalisation and the departure of capital controls have urged all MNC with foreign money streams the need to manage foreign exchange exposure risks introduced by a volatile exchange system. Today, multinational firms are striving to create methods and methodologies for an efficient and effective exchange risk management. The foreign exchange strategy embraced is essential to an MNC in the present-day condition because of the great inconstancy in transaction rates and needs to advance with the dynamic structure of the organisation. Further, given the way that organisations are continually signing commercial and business contracts titled in foreign currencies, precise estimation and supervision of exposure and economic risks have turned out to be vital to the success of an MNC. This paper review the traditional types of exchange rate risks faced by the firms due to the surge of global quest for trade across borders. The paper further explain the importance of risk management strategies with special reference to hedging and outline the various hedging strategies both external and internal used by Multinational companies (MNC’s).
    Keywords: Keywords: Exposure, currency risk ,hedging ,exchange rate, translation ,transaction, operating .
    JEL: F3 F31 G01 G2 G23
    Date: 2019–05–10
  4. By: Davide Cellai; Trevor Fitzpatrick
    Abstract: Measurement and management of credit concentration risk is critical for banks and relevant for micro-prudential requirements. While several methods exist for measuring credit concentration risk within institutions, the systemic effect of different institutions' exposures to the same counterparties has been less explored so far. In this paper, we propose a measure of the systemic credit concentration risk that arises because of common exposures between different institutions within a financial system. This approach is based on a network model that describes the effect of overlapping portfolios. We calculate this measure of systemic network concentration on a few data sets reporting exposures of financial institutions and show that typically the effect of common exposures is not fully contained by information at the level of single portfolio concentration. As a result, we show that an optimal solution that minimizes systemic risk is to be found in a balance between these two, typically different and rather divergent, effects. Using this network measure, we calculate the additional capital corresponding to the systemic risk arising from credit concentration interconnectedness. This adjustment is additional to both the original capital requirement from Basel II and the granularity adjustment of each portfolio. We also develop an approximated methodology to avoid double counting between the granularity adjustment and the common exposure adjustment. Although approximated, our common exposure adjustment is able to capture, with only two parameters, an aspect of systemic risk that goes beyond a view over single portfolios and analyzes the complexity of the interplay among (risk-adjusted) exposures.
    Date: 2019–05
  5. By: Markus Brunnermeier; Simon Rother; Isabel Schnabel
    Abstract: We analyze the relationship between asset price bubbles and systemic risk, using bank-level data covering almost thirty years. Systemic risk of banks rises already during a bubble’s build-up phase, and even more so during its bust. The increase differs strongly across banks and bubble episodes. It depends on bank characteristics (especially bank size) and bubble characteristics, and it can become very large: In a median real estate bust, systemic risk increases by almost 70 percent of the median for banks with unfavorable characteristics. These results emphasize the importance of bank-level factors for the build-up of financial fragility during bubble episodes.
    Keywords: Asset price bubbles, systemic risk, financial crises, credit booms, CoVaR, MES
    JEL: E32 G01 G12 G20 G32
    Date: 2019–05
  6. By: Craig, Ben R. (Federal Reserve Bank of Cleveland); Giuzio, Margherita (European Central Bank); Paterlini, Sandra (University of Trento)
    Abstract: Recent policy discussion includes the introduction of diversification requirements for sovereign bond portfolios of European banks. In this paper, we evaluate the possible effects of these constraints on risk and diversification in the sovereign bond portfolios of the major European banks. First, we capture the dependence structure of European countries’ sovereign risks and identify the common factors driving European sovereign CDS spreads by means of an independent component analysis. We then analyze the risk and diversification in the sovereign bond portfolios of the largest European banks and discuss the role of “home bias,” i.e., the tendency of banks to concentrate their sovereign bond holdings in their domicile country. Finally, we evaluate the effect of diversification requirements on the tail risk of sovereign bond portfolios and quantify the system-wide losses in the presence of fire-sales. Under our assumptions about how banks respond to the new requirements, demanding that banks modify their holdings to increase their portfolio diversification may mitigate fire-sale externalities, but it may be ineffective in reducing portfolio risk, including tail risk.
    Keywords: Bank regulation; sovereign-bank nexus; sovereign risk; home bias; diversification;
    JEL: G01 G11 G21 G28
    Date: 2019–05–28
  7. By: Tarek A. Hassan (Boston University, NBER, and CEPR); Stephan Hollander (Tilburg University); Laurence van Lent (Frankfurt School of Finance and Management); Ahmed Tahoun (London Business School)
    Abstract: We adapt simple tools from computational linguistics to construct a new measure of political risk faced by individual US firms: the share of their quarterly earnings conference calls that they devote to political risks. We validate our measure by showing it correctly identifies calls containing extensive conversations on risks that are political in nature, that it varies intuitively over time and across sectors, and that it correlates with the firm’s actions and stock market volatility in a manner that is highly indicative of political risk. Firms exposed to political risk retrench hiring and investment and actively lobby and donate to politicians. These results continue to hold after controlling for news about the mean (as opposed to the variance) of political shocks. Interestingly, the vast majority of the variation in our measure is at the firm level rather than at the aggregate or sector level, in the sense that it is neither captured by the interaction of sector and time fixed effects, nor by heterogeneous exposure of individual firms to aggregate political risk. The dispersion of this firm-level political risk increases significantly at times with high aggregate political risk. Decomposing our measure of political risk by topic, we find that firms that devote more time to discussing risks associated with a given political topic tend to increase lobbying on that topic, but not on other topics, in the following quarter.
    Keywords: Political uncertainty, quantification, firm-level, lobbying
    JEL: D8 E22 E24 E32 E6 G18 G32 G38 H32
    Date: 2019–04
  8. By: Schmeck, Maren Diane (Center for Mathematical Economics, Bielefeld University); Schmidli, Hanspeter (Center for Mathematical Economics, Bielefeld University)
    Abstract: We consider the surplus process of a life insurer who is able to buy a securitisation product to hedge mortality in a discrete time framework. Two cohorts are considered: one underlying the securitisation product and one for the portfolio of the insurer. In our main result we show that there exists a unique strategy that maximises the expected utility of the insurer. Our findings are illustrated by a tractable model for mortality catastrophe risk.
    Keywords: mortality option, optimal strategy, maximal utility, ex- ponential utility
    Date: 2019–05–28
  9. By: Jun Zhao; Emmanuel Lépinette (CEREMADE - CEntre de REcherches en MAthématiques de la DEcision - Université Paris-Dauphine - CNRS - Centre National de la Recherche Scientifique); Peibiao Zhao
    Abstract: In this paper, we revisit the discrete-time partial hedging problem of contingent claims with respect to a dynamic risk-measure defined by its acceptance sets. A natural and sufficient weak no-arbitrage condition is studied to characterize the minimal risk-hedging prices. The method relies only on conditional optimization techniques. In particular, we do not need robust representation of the risk-measure and we do not suppose the existence of a risk-neutral probability measure. Numerical experiments illustrate the efficiency of the method.
    Keywords: Risk-hedging prices,Dynamic risk-measures,Absence of immediate profit,Random sets,Conditional essential infimum
    Date: 2019–05–21
  10. By: Yibei Li; Ximei Wang; Boualem Djehiche; Xiaoming Hu
    Abstract: In this paper, the credit scoring problem is studied by incorporating network information, where the advantages of such incorporation are investigated in two scenarios. Firstly, a Bayesian optimal filter is proposed to provide a prediction for lenders assuming that published credit scores are estimated merely from structured individual data. Such prediction is used as a monitoring indicator for the risk warning in lenders' future financial decisions. Secondly, we further propose a recursive Bayes estimator to improve the accuracy of credit scoring estimation by incorporating the dynamic interaction topology of clients as well. It is shown that under the proposed evolution framework, the designed estimator has a higher precision than any efficient estimator, and the mean square errors are strictly smaller than the Cram\'er-Rao lower bound for clients within a certain range of scores. Finally, simulation results for a specific case illustrate the effectiveness and feasibility of the proposed methods.
    Date: 2019–05
  11. By: Ernst Juerg Weber (Economics Discipline, Business School, The University of Western Australia)
    Abstract: Food insecurity is a leading cause of poverty in sub-Saharan Africa. Overcoming food insecurity would improve the health and education of rural populations, increase labour productivity and promote rural economic development. Governments and numerous aid agencies dispense food aid during famines. The recent emergence of weather index insurance offers a promising new risk management tool that enhances economic opportunities and welfare in rural sub-Saharan Africa. In 2004 MicroEnsure launched Africa’s first weather index-based insurance product.1 In 2008 the International Fund for Agricultural Development (IFAD) and the World Food Programme (WFP) established the Weather Risk Management Facility (WRMF), which supported pilot projects for weather index insurance. In 2009 Kenya Seed, the Syngenta Foundation, UAP Group, Swiss Re and the World Bank’s Global Index Insurance Facility (GIIF) joined forces to establish Kilimo Salama, which offered index-based microinsurance to Kenyan maize and wheat farmers, with more crops and livestock being added later. In 2011 WFP and Oxfam America founded the R4 Rural Resilience Initiative, building on the Horn of Africa Risk Transfer for Adaptation (HARITA). In 2013 the AXA Group launched index-based agricultural insurance; in 2014 AXA and the South African Sanlam participated in MicroEnsure; and in 2015 AXA entered into partnership with the World Bank’s GIIF. In 2014 Kilimo Salama was succeeded by the Agriculture and Climate Risk Enterprise (ACRE), which assists local insurers in Kenya, Tanzania and Rwanda. After a decade of keen experimentation, the focus has now shifted from pilot projects to scaling up index-based insurance as a risk management tool for smallholder farmers.
    Date: 2019
  12. By: Heij, C.; Knapp, S.
    Abstract: Inspections play a key role in keeping vessels safe. Inspection authorities employ different policies to decide which vessels to inspect, including type of vessel, age, and flag. Attention for vessel history is usually restricted only to past detentions. This paper shows that it helps to combine past detention with past accident information to target risky vessels for inspection and to prevent serious and very serious accidents. Five methods are presented to classify risk of vessels based on these two risk dimensions, i.e., detention risk and accident risk, each of which involves an extensive set of risk factors. It is shown that these classification methods have predictive power for future serious and very serious accidents. Compared to using only detention information, incorporation of accident risk improves inspection hit rates for vessels with future accidents by 30-50%, depending on the applied inspection rate. It is recommended to focus on vessels where both risks are relatively high. A practical example shows management implications for inspection authorities how to prevent missing risky ships and how to prioritize inspection areas defined in terms of eight risk domains that include collisions, groundings, engine and hull failures, loss of life, fire, and pollution.
    Keywords: Maritime safety, inspection policy, vessel-specific risk, detention risk, accident risk, risk domains
    Date: 2018–04–01
  13. By: Xing Yan; Qi Wu; Wen Zhang
    Abstract: We propose a novel probabilistic model to facilitate the learning of multivariate tail dependence of multiple financial assets. Our method allows one to construct from known random vectors, e.g., standard normal, sophisticated joint heavy-tailed random vectors featuring not only distinct marginal tail heaviness, but also flexible tail dependence structure. The novelty lies in that pairwise tail dependence between any two dimensions is modeled separately from their correlation, and can vary respectively according to its own parameter rather than the correlation parameter, which is an essential advantage over many commonly used methods such as multivariate $t$ or elliptical distribution. It is also intuitive to interpret, easy to track, and simple to sample comparing to the copula approach. We show its flexible tail dependence structure through simulation. Coupled with a GARCH model to eliminate serial dependence of each individual asset return series, we use this novel method to model and forecast multivariate conditional distribution of stock returns, and obtain notable performance improvements in multi-dimensional coverage tests. Besides, our empirical finding about the asymmetry of tails of the idiosyncratic component as well as the whole market is interesting and worth to be well studied in the future.
    Date: 2019–05
  14. By: Lorella Fatone; Francesca Mariani
    Abstract: We consider the problem of governing systemic risk in an assets-liabilities dynamical model of banking system. In the model considered each bank is represented by its assets and its liabilities.The capital reserves of a bank are the difference between assets and liabilities of the bank. A bank is solvent when its capital reserves are greater or equal to zero otherwise the bank is failed.The banking system dynamics is defined by an initial value problem for a system of stochastic differential equations whose independent variable is time and whose dependent variables are the assets and the liabilities of the banks.The banking system model presented generalizes those discussed in [4],[3] and describes a homogeneous population of banks. The main features of the model are a cooperation mechanism among banks and the possibility of the (direct) intervention of the monetary authority in the banking system dynamics. We call systemic risk or systemic event in a bounded time interval the fact that in that time interval at least a given fraction of the banks fails. The probability of systemic risk in a bounded time interval is evaluated using statistical simulation. The systemic risk governance pursues the goal of keeping the probability of systemic risk in a bounded time interval between two given thresholds.The monetary authority is responsible for the systemic risk governance.The governance consists in the choice of the assets and of the liabilities of a kind of "ideal bank" as functions of time and in the choice of the rules that regulate the cooperation mechanism among banks.These rules are obtained solving an optimal control problem for the pseudo mean field approximation of the banking system model. The governance induces the banks of the system to behave like the "ideal bank". Shocks acting on the assets or on the liabilities of the banks are simulated.
    Date: 2019–05
  15. By: Konstantinos Gkillas (Department of Business Administration, University of Patras-University Campus, Rio, P.O. Box 1391, 26500 Patras, Greece); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa); Christian Pierdzioch (Department of Economics, Helmut Schmidt University, Holstenhofweg 85, P.O.B. 700822, 22008 Hamburg, Germany)
    Abstract: We use a quantile-regression heterogeneous autoregressive realized volatility (QR-HARRV) model to study whether geopolitical risks have predictive value in sample and out-of-sample for realized gold-returns volatility estimated from intradaily data. We consider overall geopolitical risks along with a decomposition into actual risks (i.e., acts) and threats, and we control for overall the impact of economic policy uncertainty (EPU). We find that, after controlling for EPU, the components of geopolitical risks have predictive power for realized volatility mainly at a longer forecast horizon when we account for the potential asymmetry of the loss function a forecaster uses to evaluate forecasts.
    Keywords: Gold-price returns, Realized volatility, Geopolitical risks, Forecasting
    Date: 2019–05
  16. By: Alexander Zimper (Department of Economics; University of Pretoria; postal address: Private Bag X20; Hat.eld 0028; South Africa); Hirbod Assa (Institute for Financial and Actuarial Mathematics and Institute for Risk and Uncertainty, University of Liverpool, Center for Doctoral Training, Chadwick Building, G62, Liverpool UK.)
    Abstract: The choice of a continuity concept in decision theoretic models has behavioral meaning because it pins down how the decision maker perceives the similarity of random variables. This paper analyzes the preferences of a decision maker who perceives similarity in accordance with the topology of convergence in measure. As our main insight we show that this decision maker cannot be globally risk or ambiguity averse whenever her preferences are lower-semicontinuous and complete on a rich set of random variables. Real life decision makers who perceive the similarity of random variables in accordance with convergence in measure might thus account for violations of global convexity as observed in empirical studies. Similarly, the non-convex risk measure value-at-risk might be popular among decision makers because it represents preferences that are lower-semicontinuous in measure.
    Keywords: Similarity Perceptions, Continuous Preferences, Uncertainty, Ambiguity, Utility Representations, Risk Measures
    JEL: D81
    Date: 2019–05
  17. By: Todd Keister; Yuliyan Mitkov
    Abstract: We study the interaction between a government’s bailout policy during a bank- ing crisis and individual banks’ willingness to impose losses on (or “bail in†) their investors. Banks in our model hold risky assets and are able to write complete, state-contingent contracts with investors. In the constrained efficient allocation, banks experiencing a loss immediately bail in their investors and this bail-in removes any incentive for investors to run on the bank. In a competitive equi- librium, however, banks may not enact a bail-in if they anticipate being bailed out. In some cases, the decision not to bail in investors provokes a bank run, creating further distortions and leading to even larger bailouts. We ask what macroprudential policies are useful when bailouts crowd out bail-ins.
    Keywords: Financial Fragility, Bailouts, Bail-ins, Limited Commitment
    JEL: E61 G21 G28
    Date: 2019–05
  18. By: Greenfield, Patrick (yFederal Reserve Bank of San Francisco); Hall, Arden (Federal Reserve Bank of Philadelphia)
    Abstract: Two recent articles by Hancock and Passmore (2016) and Passmore and von Hafften (2017) make several suggestions for improving the home mortgage contract to make homeownership more achievable for creditworthy borrowers. Though the proposals in the two papers differ in some aspects, one common feature is an adjustable rate indexed to a cost of funds (COF) measure. Such indices are based on the interest expense as a fraction of liability balance for one or a group of depository institutions. One of these, the 11th District Cost of Funds (COF) Index, was in wide use in the 1980s and '90s, but use has fallen off since then. COF indices have the advantage that they are less volatile than market-based indices such as the 1-year U.S. Treasury rate, so that borrowers are not exposed to rapid increases in payments in a rising rate environment. We analyze COF-indexed ARMs from the point of view of the lender. First we develop a methodology for constructing a liability portfolio that closely tracks the specific COF index proposed by Hancock and Passmore (2016) and Passmore and von Hafften (2017). We then explore the financial characteristics of this liability portfolio. We show that the liability portfolio, and by implication, the mortgages it would fund, s are a characteristic of fixed-rate mortgages: Values can vary significantly from par if rates change. This creates two problems for lenders: Pricing of COF-indexed ARMs is difficult because it depends not only on current interest rates but also on interest rates when principal is r paid, either through amortization or prepayment. Second, deviations from par make mortgage prepayment options valuable, so that lenders offering the product must manage option risk as well as interest rate risk. We conclude that while mortgages using a COF index have clear benefits for borrowers, they also are more difficult for lenders to price accurately. Further, once they are in lenders' portfolios, they increase the complexity of interest rate risk management. While these issues do not imply that COF indices cannot be part of innovative new mortgage designs, understanding their financial characteristics may contribute to the search for a better mortgage.
    Keywords: Mortgages; cost of funds; interest rate risk; funds transfer pricing
    JEL: G12 G28
    Date: 2019–05–28
  19. By: Mouhcine Tallaki; Enrico Bracci; Federico Stefani
    Abstract: Public private partnerships (PPP) and Public Finance initiative (PFI) have been widely used to finance infrastructures and public services. PPP and PFI are an effective way to achieve value for money (VFM) (Broadbent et al. 2008) as they guarantee efficiency levels and transfer risk away from the public sector. Scholars analysed “risk†from different angles, i.e. risk identification and controlling (Broadbent et al. 2008), diffusion of risks (Demirag et al. 2012), demand risk (Burke and Demirag 2013) and risk management (Chung and Hensher 2015). Despite the importance of the risk the topic has not yet been deepened. This research aims at understanding the state of the art of risk consideration under PPP and PFI studies. We conducted a systematic literature review (SLR), we defined five constitutive areas, namely: value for Money, risk determination and allocation, financial risk transfer, contractualization of risk and risk management in post construction phase. Risk in PPP and PFF is still in its infancy. Further research are required. In particular, regarding operational and post-operational risk studies, risk management and the role of trust between partners in operational phase, and more in general issues related to PPP/PFIs within developing countries.
    Keywords: Risk; Project Financing; PFI; PPP
    JEL: H83 M40
    Date: 2019–05–28

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