nep-rmg New Economics Papers
on Risk Management
Issue of 2017‒03‒12
ten papers chosen by



  1. Evaluation of total risk exposure and insurance premiums in the maritime industry By Knapp, S.; Heij, C.
  2. Modelling Conditional Volatility and Downside Risk for Istanbul Stock Exchange By Amira Akl Ahmed; Doaa Akl Ahmed
  3. Risk-sharing benefits and the capital structure of insurance companies By Degryse, Hans; Smedts, Kristien; Van Hulle, Cynthia
  4. "Taking Diversity into Account": the Diversity of Financial Institutions and Accounting Regulation By Gaëtan Le Quang
  5. Optimal Bank Capital Requirements: An Asymmetric Information Perspective By Berardi, Simone; Marcelletti, Alessandra
  6. Are Larger Banks Valued More Highly? By Bernadette A. Minton; René M. Stulz; Alvaro G. Taboada
  7. Are Basel's Capital Surcharges for Global Systemically Important Banks Too Small? By Wayne Passmore; Alexander H. von Hafften
  8. Risk aversion and wealth: evidence from person-to-person lending portfolios By Daniel Paravisini; Veronica Rappoport; Enrichetta Ravina
  9. Impact of capital regulation on SMEs credit By Jose Felix Izquierdo; Santiago Muñoz; Ana Rubio; Camilo Ulloa
  10. Stress-Testing of liquidity risk in TARGET2 By Group on TARGET2 Stress Testing of the Market Infrastructure Board; Papsdorf, Patrick; Arciero, Luca; Frutos de Andres, Juan Carlos; Hellqvist, Matti; Heyvaert, Patrick; Kaliontzoglou, Alexandros; König, Ronald; Korpinen, Kasperi; Martin, Clement; Müller, Alexander; Perez Garcia de Mirasierra, Miguel; Ponsart, Maxime; Rainone, Edoardo; Rosenkranz, Peter; Testi, Sara; Market Infrastructure and Payments Committee

  1. By: Knapp, S.; Heij, C.
    Abstract: This study provides an empirical evaluation of maritime risk exposure expressed as the monetary value at risk (MVR), which incorporates life of crew and passengers, vessel value of hull and machinery, carried cargo value, third party liabilities, and potential external damages like pollution. MVR is based on individual safety quality data of about 130,000 vessels, on insurable values related to various potential damages, and on proxies for fractions of values lost at incidents. MVR provides a tool to enhance strategic planning of maritime administrations and insurance providers, which is illustrated by a high level comparison of annual risk exposure with insurance premiums for 2010 to 2014. The analysis reveals a global annual insurable value of 30.6 trillion USD with associated annual MVR of 38.8 billion USD for very serious and serious incidents. Although oil tankers show the highest risk exposure (1.75 million USD per tanker per year), safety qualities are found to be best for this ship type (1.4% annual incident risk) and worst for container vessels (2.8%). Annual growth rates in total risk exposure are mostly positive with highest value for dry bulk carriers (27.8%), whereas risk exposure tends to decline for pollution of oil tankers (-2.0%) and passenger vessels (-11.3%), and for loss of life of oil tankers (-1.9%) and dry bulk carriers (-1.4%) but not of passenger vessels (6.9%). A comparison across administrative dimensions reveals that most risk exposure lies with old open registries and with beneficial owners and DoC companies located in high income countries. Comparison with global insurance premiums suggests reasonably adequate coverage of maritime risks (excluding cargo). Our analysis indicates under-insurance of risk by around 5%, corresponding to about 1 billion USD per year, with some uncertainties remaining for the actual loss fractions of the various involved damages.
    Keywords: shipping incident, monetary value at risk, risk exposure, insurance, pollution, loss of life
    Date: 2016–01–01
    URL: http://d.repec.org/n?u=RePEc:ems:eureir:98036&r=rmg
  2. By: Amira Akl Ahmed (University of Benha, Egypt); Doaa Akl Ahmed
    Abstract: We investigated the impact of alternative variance equation specifications and different densities on the forecasting of one-day-ahead value-at-risk for the Istanbul stock market. The three employed models are symmetric GARCH(1,1) of Bollerslev (1986), symmetric GARCH(1,1) of Taylor (1986) and APGARCH(1,1) of Ding et al. (1996) models, under three distributions. The comparison focuses on two different aspects: the difference between symmetric and asymmetric GARCH (i.e., GARCH versus APGARCH) and the difference between normal-tailed and fat-tailed distributions (i.e., Normal, Student-t, and GED). The GARCH(1,1) of Taylor was found to be unjustified since convergence could not be achieved. Also, we examined if the estimated coefficients are time-varying. We executed a fixed size rolling sample estimation to provide the one-step-ahead variance forecasts required to generate the one-step-ahead VaR. Our results indicate that the APGARCH(1,1) with t-distribution model outperform its competitors regarding out-of-sample forecasting ability. Moreover, we found that the power transformation parameter of APGARCH model was time-variant. In contrast, degrees of freedom of t-distribution and thickness parameter of GED distribution are time-invariant indicating that fat-tailedness of innovation does not change over time. Thus, these findings suggest that the student-t APGARCH(1,1) model could be used by conservative investors to evaluate their investment risk. Also, both exchanges and regulators may benefit from using that model when the market faces turmoil and becomes more volatile.
    Date: 2016–07
    URL: http://d.repec.org/n?u=RePEc:erg:wpaper:1028&r=rmg
  3. By: Degryse, Hans; Smedts, Kristien; Van Hulle, Cynthia
    Abstract: Providing risk-sharing benefits to risk-averse policy holders is a primary function of insurance companies. We model that policy holders are paying a fee over the present value of indemnifications (i.e., technical provisions) to enjoy these risk-sharing benefits. This fee implies that a capital structure largely consisting of technical provisions is optimal for insurance firms, making the traditional Modigliani-Miller logic inappropriate for them. To support the issuance of technical provisions with socially desirable properties, insurance firms choose a solvency risk target vis-à-vis policy holders and maintain a minimal surplus consistent with this risk choice to absorb losses. We show that the Modigliani-Miller logic applies to the composition of this loss-absorption capacity. This explains why insurance companies may use, next to equity and technical provisions, financial debt in supporting their activities.
    JEL: G22 G32
    Date: 2017–02
    URL: http://d.repec.org/n?u=RePEc:cpr:ceprdp:11838&r=rmg
  4. By: Gaëtan Le Quang
    Abstract: The global financial crisis and what followed point out at least two major failures of the financial system: its inability to contain liquidity risk and its inability to fund long term investments. We think that these two problems come from the setting up of rules and practices that tend to homogenize market participants’ incentives and behaviors. Fair value accounting is one element of this set of practices and rules. If the rationale behind fair value accounting – that is enhancing transparency in order to limit unreported losses and manipulations – can justify its use in the case of short-term financial institutions (meaning institutions whose time horizon is short because of the maturity of their liabilities) that constantly face the risk of a sudden liquidity need, it seems totally irrelevant when it comes to long-term financial institutions that will not face liquidity needs before ten or twenty years. In this perspective, we develop a model that shows that an accounting regulation that takes the diversity of financial institutions into account offers better results both in terms of liquidity and in terms of efficiency than a regulation that ignores this diversity.
    Keywords: Fair value; Banks; Insurers; Diversity.
    JEL: G21 G22 M41
    Date: 2017
    URL: http://d.repec.org/n?u=RePEc:drm:wpaper:2017-10&r=rmg
  5. By: Berardi, Simone (LUISS School of European Political Economy); Marcelletti, Alessandra (LUISS School of European Political Economy)
    Abstract: The issue on the amount of capital banks should hold has pushed back the debate on top of policymakers' agenda. Literature on this field mainly focuses on how to prevent banks from gaming risk-weighted capital requirements. The analysis has provided different types of solutions, such as the introduction of penalties and complementary use of risk-sensitive capital requirements and leverage ratio. Although the majority of theoretical papers rely on an asymmetric information framework, only one source of asymmetry is taken into account. The paper fills this gap by studying how to implement a socially optimal regulation scheme that simultaneously faces moral hazard and adverse selection problems. Including both sources of asymmetry is crucial because of the supervisor's inability to distinguish between risk profiles and misconduct (risk-shifting behavior) of banks.
    Keywords: bank capital requirements; bank regulation; moral hazard; adverse selection
    JEL: D81 G21 G28
    Date: 2017–03–07
    URL: http://d.repec.org/n?u=RePEc:ris:sepewp:2017_002&r=rmg
  6. By: Bernadette A. Minton; René M. Stulz; Alvaro G. Taboada
    Abstract: We investigate whether the value of large banks, defined as banks with assets in excess of the Dodd-Frank threshold for enhanced supervision, increases with the size of their assets using Tobin’s q and market-to-book as our valuation measures. Many argue that large banks receive subsidies from the regulatory safety net, so they should be worth more and their valuation should increase with size. Instead, using a variety of approaches, we find (1) no evidence that large banks are valued more highly, (2) strong cross-sectional evidence that the valuation of large banks falls with size, and (3) strong evidence of a within-bank negative relation between valuation and size for large banks from 1987 to 2006 but not when the post-Dodd-Frank period is included in the sample. The negative relation between bank value and bank size for large banks cannot be systematically explained by differences in ROA or ROE, equity volatility, tail risk, distress risk, and equity discount rates. However, we find that banks with more trading assets are worth less. A 1% increase in trading assets is associated with a Tobin’s q lower by 0.2% in regressions with year and bank fixed effects. This relation between bank value and trading assets helps explain the cross-sectional negative relation between large bank valuation and size. Our results hold when we use instrumental variables for bank size.
    JEL: G02 G21 G28 G3
    Date: 2017–03
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:23212&r=rmg
  7. By: Wayne Passmore; Alexander H. von Hafften
    Abstract: The Basel Committee on Banking Supervision (BCBS, the Basel Committee, or Basel) has developed a methodology for identifying global systemically important banks (G-SIBs) and standards for requiring G-SIBs to hold more common equity.
    Date: 2017–02–27
    URL: http://d.repec.org/n?u=RePEc:fip:fedgfn:2017-02-27-1&r=rmg
  8. By: Daniel Paravisini; Veronica Rappoport; Enrichetta Ravina
    Abstract: We estimate risk aversion from the actual financial decisions of 2,168 investors in Lending Club (LC), a person-to-person lending platform. We develop a methodology that allows us to estimate risk aversion parameters from each portfolio choice. Since the same individual makes repeated investments, we are able to construct a panel of risk aversion parameters that we use to disentangle heterogeneity in attitudes towards risk from the elasticity of investor-specific risk aversion to changes in wealth. In the cross section, we find that wealthier investors are more risk averse. Using changes in house prices as a source of variation, we find that investors become more risk averse after a negative wealth shock. These preferences consistently extrapolate to other investor decisions within LC.
    Keywords: risk aversion; portfolio choice; crowdfunding
    JEL: D12 D14 E21 G11
    Date: 2016–02–29
    URL: http://d.repec.org/n?u=RePEc:ehl:lserod:62137&r=rmg
  9. By: Jose Felix Izquierdo; Santiago Muñoz; Ana Rubio; Camilo Ulloa
    Abstract: The Supporting Factor was introduced in Basel III with the aim of avoiding a reduction in the flow of new credit to SMEs, and the CRR revision published in November 2016 even proposes enlarging its scope to exposures above €1.5bn (but with a lower parameter).
    Keywords: Financial regulation , Spain , Working Paper
    JEL: G20 G21
    Date: 2017–01
    URL: http://d.repec.org/n?u=RePEc:bbv:wpaper:1701&r=rmg
  10. By: Group on TARGET2 Stress Testing of the Market Infrastructure Board; Papsdorf, Patrick; Arciero, Luca; Frutos de Andres, Juan Carlos; Hellqvist, Matti; Heyvaert, Patrick; Kaliontzoglou, Alexandros; König, Ronald; Korpinen, Kasperi; Martin, Clement; Müller, Alexander; Perez Garcia de Mirasierra, Miguel; Ponsart, Maxime; Rainone, Edoardo; Rosenkranz, Peter; Testi, Sara; Market Infrastructure and Payments Committee
    Abstract: The paper reports the outcome of the stress-testing of liquidity risk in the TARGET2 payment system, with the study having been conducted by an ad-hoc group composed of operators and overseers of TARGET2. The study aims to assess the resilience of the system, defined as the network of its participants, and the appropriateness of liquidity levels under tightened liquidity conditions. The scenarios analysed are based on extreme shocks to the value of collateral of different levels and types that lead to a decrease in the intraday credit lines available in TARGET2 and, as a result, the payment capacity of TARGET2 participants. The tool used to perform these stress tests is the TARGET2 simulator, which provides access to real transaction level data and allows simulations to be run by changing parameters, in this case the credit lines. The period under analysis is one maintenance period for the years 2008 to 2013. In general, the stress-testing indicates that the system is resilient under the stress scenarios; liquidity levels seem to be appropriate and supported by the efficient liquidity management features of TARGET2. Even in the worst simulated event of a 70% drop in all collateral value, 80-90% of TARGET2 turnover would have been settled. The scenario results take also into account that the period under analysis was characterised by unconventional monetary policy measures. JEL Classification: C63, E42, E58, G01
    Keywords: liquidity risk, principles for FMIs, simulation, stress testing, TARGET2
    Date: 2017–02
    URL: http://d.repec.org/n?u=RePEc:ecb:ecbops:2017183&r=rmg

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