nep-rmg New Economics Papers
on Risk Management
Issue of 2018‒03‒26
eleven papers chosen by

  1. Systematic Risk, Bank Moral Hazard, and Bailouts By Marcella Lucchetta; Michele Moretto; Bruno Maria Parigi
  2. Global Evidence on Economic Preferences By Armin Falk; Thomas Dohmen; David Huffman; Uwe Sunde
  3. Risk management from the information security perspective By Ionuț, Riza
  4. Sensitivity of credit risk stress test results: Modelling issues with an application to Belgium By Patrick Van Roy; Stijn Ferrari; Cristina Vespro
  5. RACORN-K: Risk-Aversion Pattern Matching-based Portfolio Selection By Yang Wang; Dong Wang; Yaodong Wang; You Zhang
  6. A risk dashboard for the Italian economy By Fabrizio Venditti; Francesco Columba; Alberto Maria Sorrentino
  7. An elusive panacea? The impact of the regulatory valuation regime on insurers' investment behaviour By Lepore, Caterina; Tanaka, Misa; Humphry, David; Sen, Kallol
  8. Synthetic Control Methods and Big Data By Daniel Kinn
  9. Market power and the risk-taking of banks: Some semiparametric evidence from emerging economies By Jeon, Bang Nam; Wu, Ji; Guo, Mengmeng; Chen, Minghua
  10. Options: From Conventional and Islamic perspectives Analyses on the Islamic solutions By Bengana, Mohamed; Khouildi, Mohamed Yassine
  11. Mortality data reliability in an internal model By Fabrice Balland; Alexandre Boumezoued; Laurent Devineau; Marine Habart; Tom Popa

  1. By: Marcella Lucchetta; Michele Moretto; Bruno Maria Parigi
    Abstract: We show that the impact of government bailouts (liquidity injections) on a representative bank’s risk taking depends on the level of systematic risk of its loans portfolio. In a model where bank’s output follows a geometric Brownian motion and the government guarantees bank’s liabilities, we show first that more generous bailouts may or may not induce banks to take on more risk depending on the level of systematic risk; if systematic risk is high (low), a more generous bailout decreases (increases) bank’s risk taking. Second, the optimal liquidity policy itself depends on systematic risk. Third, the relationship between bailouts and bank’s risk taking is not monotonic. When systematic risk is low, the optimal liquidity policy is loose and more generous bailouts induce banks to take on more risk. If systematic risk is high and the optimal liquidity policy is tight, less generous bailouts induce banks to take on less risk. However, when high systematic risk makes a very tight liquidity policy optimal, a less generous bailout could increase bank’s risk taking. While in this model there is only one representative bank, in an economy with many banks, a higher level of systematic risk could also be a source of systemic risk if a tighter liquidity policy induces correlated risk taking choices by banks.
    Keywords: bailout, bank closure, real option, systematic risk
    JEL: G00 G20 G21
    Date: 2018
  2. By: Armin Falk; Thomas Dohmen; David Huffman; Uwe Sunde
    Abstract: This paper discusses the recent literature on the relationship between cognitive ability and decision making under risk and uncertainty. After clarifying some important distinctions between concepts and measurement of risk preference and cognitive ability, we take stock of what is known empirically on the connections between cognitive ability and measured risk preferences. We conclude by discussing perspectives for future research.
    JEL: D81 D91 D89
    Date: 2018–03
  3. By: Ionuț, Riza
    Abstract: Risk management has emerged ever since the appearance of human communities and it has developed at a slow rate. Over time, a significant improvement was made, from accepting hazards to the identification, evaluation and control of unwanted events, threat prevention and exploitation of opportunities through scientific risk management actions. The fundamental role of research in cyber security is to concentrate the efforts on those contexts and conditions which determine the way in which key players reach a common understanding of the way to conceive and eventually answer to certain challenges in cyber security. In order to build a clear perception of these effects, this work presents the main elements which define cyber space, to come to the aid of turning the management process into an efficient one, especially when talking about cyber space as a space for conflicts, both economic and political.
    Keywords: cyber space; risk management; cyber security; information technology; risk evaluation
    JEL: M15
    Date: 2017–10
  4. By: Patrick Van Roy (National Bank of Belgium and Université Libre de Bruxelles, Boulevard de Berlaimont 14, 1000 Brussels, Belgium); Stijn Ferrari (National Bank of Belgium, Boulevard de Berlaimont 14, 1000 Brussels, Belgium); Cristina Vespro (National Bank of Belgium, Boulevard de Berlaimont 14, 1000 Brussels, Belgium - Present address: European Commission, Rue de Spa 2, 1000 Brussels, Belgium.)
    Abstract: This paper assesses the sensitivity of solvency stress testing results to the choice of credit risk variable and level of data aggregation at which the stress test is conducted. In practice, both choices are often determined by technical considerations, such as data availability. Using data for the Belgian banking system, we find that the impact of a stress test on banks' Tier 1 ratios can differ substantially depending on the credit risk variable and the level of data aggregation considered. If solvency stress tests are going to be used as a supervisory tool or to set regulatory capital requirements, there is a need to further harmonise their execution across institutions and supervisors in order to enhance comparability. This is certainly relevant in the context of the EUwide stress tests, where institutions often use different credit risk variables and levels of data aggregation to estimate the impact of the common methodology and macroeconomic scenario on their capital level while supervisors rely on different models to quality assure and validate banks’results. More generally, there is also a need to improve the availability and quality of the data to be used for stress testing purposes.
    Keywords: stress tests, credit risk, sensitivity analysis, capital requirements, modelling choices.
    JEL: C52 G21
    Date: 2018–03
  5. By: Yang Wang; Dong Wang; Yaodong Wang; You Zhang
    Abstract: Portfolio selection is the central task for assets management, but it turns out to be very challenging. Methods based on pattern matching, particularly the CORN-K algorithm, have achieved promising performance on several stock markets. A key shortage of the existing pattern matching methods, however, is that the risk is largely ignored when optimizing portfolios, which may lead to unreliable profits, particularly in volatile markets. We present a risk-aversion CORN-K algorithm, RACORN-K, that penalizes risk when searching for optimal portfolios. Experiments on four datasets (DJIA, MSCI, SP500(N), HSI) demonstrate that the new algorithm can deliver notable and reliable improvements in terms of return, Sharp ratio and maximum drawdown, especially on volatile markets.
    Date: 2018–02
  6. By: Fabrizio Venditti (Bank of Italy); Francesco Columba (Bank of Italy); Alberto Maria Sorrentino (Bank of Italy)
    Abstract: In this paper we describe an analytical framework to assess financial stability risks in the Italian economy. We use a large number of indicators, selected to take into account the peculiarities of the Italian economy, to monitor risks in seven areas: interlinkages, the credit markets, the macroeconomic environment, funding conditions, the financial markets, and the banking and insurance sectors. Based on thresholds selected on the basis of either expert judgment or historical distributions, we construct risk heatmaps and derive aggregate scores for each of the above risk categories. By providing timely information on the buildup of risks, the proposed dashboard usefully complements other analytical tools currently used for developing and implementing macroprudential policy.
    Keywords: early warning indicators, financial stability risks, heatmaps, macroprudential policy
    JEL: G12 G21 G23 G28
    Date: 2018–02
  7. By: Lepore, Caterina (Bank of England); Tanaka, Misa (Bank of England); Humphry, David (Bank of England); Sen, Kallol (Bank of England)
    Abstract: This paper examines how the interactions between the valuation regime and solvency requirements influence investment behaviour of long-term investors with stable liabilities, such as life insurers. Under limited liability, solvency requirements based on historical cost valuation encourage risk-shifting to the detriment of policyholders, while those based on fair value regime can induce procyclical asset sales. A hybrid valuation regime, intended to address these unfavourable outcomes, does not strictly dominate the other two regimes. But both fair value and hybrid regimes outperform the historical cost regime if the regulators can set the penalty imposed on insurers based on supervisory information about their asset quality, even if this information is imperfect.
    Keywords: Valuation; historical cost accounting; mark-to-market; risk-shifting; fire sales; prudential regulation; insurance
    JEL: G22 G28 M41
    Date: 2018–02–09
  8. By: Daniel Kinn
    Abstract: Many macroeconomic policy questions may be assessed in a case study framework, where the time series of a treated unit is compared to a counterfactual constructed from a large pool of control units. I provide a general framework for this setting, tailored to predict the counterfactual by minimizing a tradeoff between underfitting (bias) and overfitting (variance). The framework nests recently proposed structural and reduced form machine learning approaches as special cases. Furthermore, difference-in-differences with matching and the original synthetic control are restrictive cases of the framework, in general not minimizing the bias-variance objective. Using simulation studies I find that machine learning methods outperform traditional methods when the number of potential controls is large or the treated unit is substantially different from the controls. Equipped with a toolbox of approaches, I revisit a study on the effect of economic liberalisation on economic growth. I find effects for several countries where no effect was found in the original study. Furthermore, I inspect how a systematically important bank respond to increasing capital requirements by using a large pool of banks to estimate the counterfactual. Finally, I assess the effect of a changing product price on product sales using a novel scanner dataset.
    Date: 2018–02
  9. By: Jeon, Bang Nam (Drexel University); Wu, Ji (Southwestern University of Finance and Economics); Guo, Mengmeng (Southwestern University of Finance and Economics); Chen, Minghua (Southwestern University of Finance and Economics)
    Abstract: We investigate the nexus between the market power of banks and their risk-taking, using bank-level data from 35 emerging economies during the period of 2000-2014. Under a Bayesian framework, we employ the semiparametric method, which allows for a nonlinear risk impact of banks' market power. Our results suggest a significant nonlinear relationship between the market power and the risk-taking of banks.
    Keywords: Market power; bank risk-taking; emerging economies
    JEL: D53 G15 G21
    Date: 2018–01–22
  10. By: Bengana, Mohamed; Khouildi, Mohamed Yassine
    Abstract: Purpose: As Islamic finance is growing there is a need for more innovative instruments to be used especially for risk management purposes. The main purpose of this paper is to analyze “option” as derivative instrument form conventional point of view, and to analyze it from Islamic perspective. Also the paper aims to replace the prohibited elements in option by alternative Islamic contracts. Design/Methodology: The methodology used in this paper is qualitative method in which it uses a combination of historical research and literature review based on some previously published articles and reports and library research. Findings: The study finds out the diverged shariah opinions about the impressibility of “option” as a derivative instrument, rather than this the paper found various permissible Islamic contracts that can be used as alternative. The first alternative is the usage of simple Waad (promise) with a fee, the second contract is a combination of Waad, Wakalah, and commodity Murabaha. The third alternative is the usage of Urbun (earnest money) as an Islamic alternative to call option as well as hamish al jediya. Furthermore the paper highlights the need of such instruments for hedging purposes rather than speculation. Originality/Value: The significance of this study is the way the topic was treated. A lot of previous research papers have identified the prohibited elements of options and the Islamic alternatives, but this paper tries to facilitate the understanding of options from Islamic perspective by using diagrams. Also this paper clarifies the main alternatives and compares the classical and the contemporary shariah scholars’ views.
    Keywords: Keywords: Options, Waad, Urbun, derivatives, hedging
    JEL: G23
    Date: 2018–02–12
  11. By: Fabrice Balland (AXA GRM - AXA Group Risk Management); Alexandre Boumezoued (R&D, Milliman, Paris - Milliman); Laurent Devineau (R&D, Milliman, Paris - Milliman); Marine Habart (AXA GRM - AXA Group Risk Management); Tom Popa (AXA GRM - AXA Group Risk Management)
    Abstract: In this paper, we discuss the impact of some mortality data anomalies on an internal model capturing longevity risk in the Solvency 2 framework. In particular, we are concerned with abnormal cohort effects such as those for generations 1919 and 1920, for which the period tables provided by the Human Mortality Database show particularly low and high mortality rates respectively. To provide corrected tables for the three countries of interest here (France, Italy and West Germany), we use the approach developed by Boumezoued (2016) for countries for which the method applies (France and Italy), and provide an extension of the method for West Germany as monthly fertility histories are not sufficient to cover the generations of interest. These mortality tables are crucial inputs to stochastic mortality models forecasting future scenarios, from which the extreme 0,5% longevity improvement can be extracted, allowing for the calculation of the Solvency Capital Requirement (SCR). More precisely, to assess the impact of such anomalies in the Solvency II framework, we use a simplified internal model based on three usual stochastic models to project mortality rates in the future combined with a closure table methodology for older ages. Correcting this bias obviously improves the data quality of the mortality inputs, which is of paramount importance today, and slightly decreases the capital requirement. Overall, the longevity risk assessment remains stable, as well as the selection of the stochastic mortality model. As a collateral gain of this data quality improvement, the more regular estimated parameters allow for new insights and a refined assessment regarding longevity risk.
    Date: 2018–02–28

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