nep-rmg New Economics Papers
on Risk Management
Issue of 2016‒11‒27
sixteen papers chosen by
Stan Miles
Thompson Rivers University

  1. The Lila distribution and its applications in risk modelling By Bertrand K. Hassani; Wei Yang
  2. Portfolio analysis in jump-diffusion model with power-law tails By Paweł Kliber
  3. Regulation and Rational Banking Bubbles in Infinite Horizon By Claire Océane Chevallier; Sarah El Joueidi
  4. The Persistence of Financial Distress By Juan Sanchez; Jose Mustre-del-Rio; Kartik Athreya
  5. Assessing Liquidity Buffers in the Panamanian Banking Sector By Andras Komaromi; Metodij Hadzi-Vaskov; Torsten Wezel
  6. Age-Specific Adjustment of Graduated Mortality By Yahia Salhi; Pierre-Emmanuel Thérond
  7. Measuring Systemic Stress in European Banking Systems* By Heather D. Gibson; Stephen G. Hall; George S. Tavlas
  8. The Impact of Bunker Risk Management on CO2 Emissions in Maritime Transportation Under ECA Regulation By Gu, Yewen; Wallace, Stein W.; Wang, Xin
  9. Value-at-Risk Prediction in R with the GAS Package By David Ardia; Kris Boudt; Leopoldo Catania
  10. The Impact of Capital-Based Regulation on Bank Risk-Taking: A Dynamic Model By Paul S. Calem; Rafael Rob
  11. Financial Regulation in a Quantitative Model of the Modern Banking System By Tim Landvoigt; Juliane Begenau
  12. Prepayment Risk and Expected MBS Returns By Peter Diep; Andrea L. Eisfeldt; Scott Richardson
  13. "Honey, the Bank Might Go Bust": The Response of Finance Professionals to a Banking System Shock By Glenn Boyle; Roger Stover; Amrit Tiwana; Oleksandr Zhylyevskyy
  14. What was fair in actuarial fairness? By Antonio Heras Martínez; David Teira; Pierre-Charles Pradier
  15. The determinants of CDS spreads: Evidence from the model space By Pelster, Matthias; Vilsmeier, Johannes
  16. Learning from History : Volatility and Financial Crises By Jon Danielsson; Marcela Valenzuela; Ilknur Zer

  1. By: Bertrand K. Hassani (Centre d'Economie de la Sorbonne, Grupo Santander); Wei Yang (Risk methodology - Santander UK plc)
    Abstract: Risk data sets tend to have heavy-tailed, sometimes bi-modal, empirical distributions, especially in operational risk, market risk and customers behaviour data sets. To capture these observed "unusual" features, we construct a new probability distribution and call it the lowered-inside-leveraged-aside (Lila) distribution as it transfers the embedded weight of data from the body to the tail. This newly constructed distribution can be viewed as a parametric distribution with two peaks. It is constructed through the composition of a Sigmoid-shaped continuous increasing differentiable function with cumulative distribution functions of random variables. Examples and some basic properties of the Lila distribution are illustrated. As an application, we fit a Lila distribution to a set of generated data by using the quantile distance minimisation method (alternative methodologies have been tested too, such as maximum likelihood estimation)
    Keywords: probability distribution, parametric distribution, multimodal distribution, operational risk; market risk; pseudo bi-modal distribution
    JEL: G21 C16 C13 G32
    Date: 2016–10
  2. By: Paweł Kliber (Poznan University of Economics)
    Abstract: The classic portfolio analysis given by Markowitz theory and Capital Asset Pricing Model is based on the assumption that the assets’ returns are normally distributed. In this situation one can use only two criteria: expected return and variance of return as the measures of possible gains and risk, respectively. However there is a growing evidence that the assets’ returns and in particular returns of shares in the stock markets fail to obey Gaussian distribution. Therefore different measures of risk should be considered.In the paper we analyze the portfolio problem in the situation when stock prices follows jump-diffusion model with the tails of jumps obeying power-law. We consider a portfolio problem with two risk criteria: risk in the situation of normal market circumstances and the risk of jumps. We propose a method for numerical computing the former risk using Fast Fourier Transform (FFT). Finally we present the examples of portfolio analysis with the new method for the shares from Warsaw Stock Market Exchange.
    Keywords: portfolio analysis, jump-diffusion models, power-law, risk of extremes, Fast Fourier Transform
    JEL: G11 C61 C58
  3. By: Claire Océane Chevallier (CREA, Université du Luxembourg); Sarah El Joueidi (CREA, Université du Luxembourg)
    Abstract: This paper develops a dynamic stochastic general equilibrium model in infinite horizon with a regulated banking sector where stochastic banking bubbles may arise endogenously. We analyze the conditions under which stochastic bubbles exist and their impact on macroeconomic key variables. We show that when banks face capital requirements based on Value-at- Risk, two different equilibria emerge and can coexist: the bubbleless and the bubbly equilibria. Alternatively, under a regulatory framework where capital requirements are based on credit risk only, as in Basel I, bubbles are explosive and, as a consequence, cannot exist. The stochastic bubbly equilibrium is characterized by positive or negative bubbles depending on the tightness of capital requirements based on Value-at-Risk. We find a maximum value of capital requirements under which bubbles are positive. Below this threshold, the stochastic bubbly equilibrium provides larger wel- fare than the bubbleless equilibrium. In particular, our results suggest that a change in banking policies might lead to a crisis without external shocks.
    Keywords: Banking bubbles; banking regulation; DSGE; infinitely lived agents; multiple equilibria; Value-at-Risk
    JEL: E2 E44 G01 G20
    Date: 2016
  4. By: Juan Sanchez (Federal Reserve Bank of St. Louis); Jose Mustre-del-Rio (Federal Reserve Bank of Kansas City); Kartik Athreya (Federal Reserve Bank of Richmond)
    Abstract: How persistent is financial distress? We answer this question using data on the proximity to debt limits, household debt-income ratios, and the probability that given a past default, a household experiences repayment difficulties. We show that all of these measures indicate that household financial distress is an extremely persistent phenomenon. To what extent can standard theory, as represented by a basic incomplete-markets model in which consumers face state contingent borrowing limits, arising from default risk capture this observed persistence of financial distress? We show that the answer is “not well†: None of a wide array of model variants is capable of capturing this aspect of consumer credit use. This is important, as these baseline models have informed policy discussions on how best to provide debt relief to mitigate consumer financial distress. We then show that a plausible extension of standard approach yields a better account for the persistence of financial distress.
    Date: 2016
  5. By: Andras Komaromi; Metodij Hadzi-Vaskov; Torsten Wezel
    Abstract: This paper assesses the resilience of Panamanian banks to (i) a very severe short-term, and (ii) a significant long-lasting liquidity shock scenario. Short-term liquidity buffers are evaluated by approximating the Liquidity Coverage Ratio (LCR) defined in the Basel III accord. The risk of losing a substantial part of foreign funding is analyzed through a conventional liquidity stress test scrutinizing several layers of liquidity across maturity buckets. The results of this study point to some vulnerabilities. First, our approximations indicate that about half of Panamanian banks would need to adjust their liquid asset portfolios to meet current LCR standards. Second, while most banks would be able to meet funding outflows in the stress-test scenario, a number of banks would have to use up all of their liquidity buffers, and a few even face a final shortfall. Nonetheless, most banks displaying sizable liquidity shortfalls have robust solvency positions.
    Keywords: Banking sector;Panama;Liquidity;External shocks;Stress testing;Bank liquidity, LCR, Liquidity stress tests
    Date: 2016–10–14
  6. By: Yahia Salhi (SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1); Pierre-Emmanuel Thérond (Galea & Associés, SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1)
    Abstract: Recently, there has been an increasing interest of life insurers to assess their portfolios own mortality risk. The new European prudential regulation, namely Solvency II, emphasized the need to use mortality and life tables that best capture and reflect the experienced mortality, and thus policyholders' proper risk profile, in order to adequately quantify the underlying risk. Therefore, building a mortality table based on the experience from the portfolio is highly recommended and, for this purpose, various approaches have been introduced in the literature. Although, such approaches succeed in capturing the main feature, it remains difficult to assess the mortality when the underlying portfolio lacks of sufficient exposure. In this paper, we propose to graduate the mortality curve using an adaptive procedure based on the local likelihood, which has the ability to model the mortality patterns even in presence of complex structures and avoid to rely on experts opinion. However, such a technique fails at proposing a consistent yet regular structure when for portfolios with limited deaths. Although the technique borrows the information from the adjacent ages, it is sometimes not sufficient to produce a robust life tables. In presence of such a bias, we propose to adjust the corresponding curve, at the age level, based on a credibility approach. This consists on reviewing, as new observations arrive, the assumption on the mortality curve. We derive the updating procedure and investigate the benefits of using the latter instead of a sole graduation based on real datasets. Moreover, we look at the divergences in the mortality forecasts generated by the classical credibility approaches including Hardy-Panjer, the Poisson-Gamma model and Makeham framework on portfolios originating from various French insurance companies.
    Keywords: Smoothing,Graduation,Life Insurance,Credibility,Mortality,Local Likelihood,Prediction
    Date: 2016–10–20
  7. By: Heather D. Gibson; Stephen G. Hall; George S. Tavlas
    Abstract: We construct a measure of systemic risk in selected EU banking systems using an indirect measure of the system covariance which is also time-varying. We proceed to examine to what extent the resulting measures of systemic stress provide a convincing narrative of events during the period January 2000 to March 2016. The results provide evidence of: (i) rising stress prior to the outbreak of the international financial crisis in 2007/08 in countries with banks exposed to toxic assets; (ii) stress associated with the euro area sovereign debt crisis from 2009/10; and (iii) continued concerns from 2013 out the need for euro area banks to clean up their balance sheets and raise new capital at a time of sluggish profitability.
    Keywords: euro area financial crisis, systemic stress, financial instability, European banks
  8. By: Gu, Yewen (Dept. of Business and Management Science, Norwegian School of Economics); Wallace, Stein W. (Dept. of Business and Management Science, Norwegian School of Economics); Wang, Xin (Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology)
    Abstract: The shipping industry carries over 90 percent of the world’s trade, and is hence a major contributor to CO2 and other airborne emissions. As a global effort to reduce air pollution from ships, the implementation of the ECA (Emission Control Areas) regulations has given rise to the wide usage of cleaner fuels. This has led to an increased emphasis on the management and risk control of maritime bunker costs for many shipping companies. In this paper, we provide a novel view on the relationship between bunker risk management and CO2 emissions. In particular, we investigate how different actions taken in bunker risk management, based on different risk aversions and fuel hedging strategies, impact a shipping company’s CO2 emissions. We use a stochastic programming model and perform various comparison tests in a case study based on a major liner company. Our results show that a shipping company’s risk attitude on bunker costs have impacts on its CO2 emissions. We also demonstrate that, by properly designing its hedging strategies, a shipping company can sometimes achieve noticeable CO2 reduction with little financial sacrifice.
    Keywords: Bunker risk management; Maritime bunker management; CO2 emissions; Stochastic programming; ECA; Fuel hedging; Sailing behavior
    JEL: C44 C60
    Date: 2016–11–16
  9. By: David Ardia; Kris Boudt; Leopoldo Catania
    Abstract: GAS models have been recently proposed in time-series econometrics as valuable tools for signal extraction and prediction. This paper details how financial risk managers can use GAS models for Value-at-Risk (VaR) prediction using the novel GAS package for R. Details and code snippets for prediction, comparison and backtesting with GAS models are presented. An empirical application considering Dow Jones Index constituents investigates the VaR forecasting performance of GAS models.
    Date: 2016–11
  10. By: Paul S. Calem; Rafael Rob
    Abstract: In this paper, we model the dynamic portfolio choice problem facing banks, calibrate the model using empirical data from the banking industry for 1984-1993, and assess quantitatively the impact of recent regulatory developments related to bank capital. The model suggests that two aspects of the new regulatory environment may have unintended effects: higher capital requirements may lead to increased portfolio risk, and capital-based premia do not deter risk-taking by well-capitalized banks. On the other hand, risk-based capital standards may have favorable effects provided the requirements are stringent enough.Full paper (249 KB Postscript)
  11. By: Tim Landvoigt (University of Texas Austin); Juliane Begenau (Harvard Business School)
    Abstract: This paper builds a quantitative general equilibrium model with commercial banks and shadow banks to study the unintended consequences of capital requirements. In particular, we investigate how the shadow banking system responds to capital regulation changes for traditional banks. A key feature of our model are defaultable bank liabilities that provide liquidity services to households. In case of default, commercial bank debt is fully insured and thus provides full liquidity services. In contrast, shadow banks are only randomly bailed out. Thus, shadow banks' liquidity services also depend on their default rate. Commercial banks are subject to a capital requirement. Tightening the requirement from the status quo, leads households to substitute shadow bank liquidity for commercial bank liquidity and therefore to more shadow banking activity in the economy. But this relationship is non-monotonic due to an endogenous leverage constraint on shadow banks that limits their ability to deliver liquidity services. The basic trade-off of a higher requirement is between bank liquidity provision and stability. Calibrating the model to data from the Financial Accounts of the U.S., the optimal capital requirement is around 20\%.
    Date: 2016
  12. By: Peter Diep; Andrea L. Eisfeldt; Scott Richardson
    Abstract: We present a simple, linear asset pricing model of the cross section of Mortgage-Backed Security (MBS) returns. We measure prepayment risk and estimate security risk loadings using real data on prepayment forecasts vs. realizations. Estimated loadings are monotonic in securities' coupons relative to the par coupon, as predicted by the model. Prepayment risks appear to be priced by specialized MBS investors. In particular, we find convincing evidence that prepayment risk prices change sign over time with the sign of a representative MBS investor's exposure to prepayment risk.
    JEL: E02 G12 G2
    Date: 2016–11
  13. By: Glenn Boyle (University of Canterbury); Roger Stover; Amrit Tiwana; Oleksandr Zhylyevskyy
    Abstract: How do informed depositors respond to a banking crisis? To shed light on this question, we apply conjoint analysis to a sample of 417 finance professionals from six countries. For a range of bank accounts that differ in the type and level of depositor protection that they offer, we ask each participant to indicate how they would respond to a banking system shock that could potentially affect their own bank. We find that intended withdrawal rates depend only on account profile attributes and are independent of respondent characteristics and respondent expectations about deposit interest rate changes. The most important account attributes are the existence of a formal deposit insurance fund and the fraction of the deposit at risk (particularly for under-capitalized banks).
    Keywords: finance professionals; banking crisis; conjoint analysis, deposit insurance
    JEL: G21 G28
    Date: 2016–11–14
  14. By: Antonio Heras Martínez (Departamento de Economía Financiera y Contabilidad 1 - Universidad Complutense de Madrid); David Teira (Departamento de Lógica, Historia y Filosofia de la Ciencia - Universidad Nacional de Educatión a Distancia (UNED)); Pierre-Charles Pradier (Centre d'Economie de la Sorbonne & LabEx RéFi)
    Abstract: The concept of acturial fairness stems from an Aristotelian tradition in which fairness requires equality between the goods exchanged. When dealing with aleatory contracts, this principle evolved, among medieval scholars, into equality in risk: benefits and losses should be proportional to the risks undertaken. The formalization of this principle gave rise to the concept of mathematical expectation, first implemented in the calculation of the fair price of gambles. The concept of an actuarial fair price was first theoretically articulated in the 17th century as an implementation of this same Aristotelian principle in the field of life insurance. For a practical estimation of fair actuarial prices it was necessary to build mortality tables, assuming that the major risk factor was age. Yet, in the 18th and 19th centuries, we find no agreement among proto-actuaries about the proper construction of these tables. Among the obstacles they found, we want to highlight their early awareness of the possibility of adverse selection: buyers and sellers could manipulate the risk assessment for their own private interests, in a way that would either make fair companies collapse or fair customers be cheated. The paradox in the concept of actuarial fairness is that as soon as it was formally articulated, markets made clear it could never be implemented in actual pricing
    Keywords: actuarial fairness; mathematical expectation; life insurance; annuity; risk
    JEL: G22 G28 G01
    Date: 2016–10
  15. By: Pelster, Matthias; Vilsmeier, Johannes
    Abstract: We apply Bayesian Model Averaging and a frequentistic model space analysis to assess the pricing-determinants of credit default swaps (CDS). Our study focuses on the complete model space of plausible models covering most of the variables and specifications used elsewhere in the literature, including different copula models. The approach followed supports ultimate transparency and robustness for the empirical study at hand. Using a large data-set of CDS contracts we find that CDS price dynamics can be mainly explained by factors describing firms' sensitivity to extreme market movements. More precisely, our results suggest that dynamic copula based measures of tail dependence incorporate almost all essential pricing information making other potential determinants such as Merton-type factors or variables measuring the systematic market evolution - based on simple means or principal component analysis - negligible.
    Keywords: CDS,bayesian model averaging,crash aversion,tail risk,tail dependence,time-varying copulas
    JEL: G12 C11 G01
    Date: 2016
  16. By: Jon Danielsson; Marcela Valenzuela; Ilknur Zer
    Abstract: We study the effects of volatility on financial crises by constructing a cross-country database spanning over 200 years. Volatility is not a significant predictor of crises whereas unusually high and low volatilities are. Low volatility is followed by credit build-ups, indicating that agents take more risk in periods of low financial risk consistent with Minsky hypothesis, and increasing the likelihood of a banking crisis. The impact is stronger when financial markets are more prominent and less regulated. Finally, both high and low volatilities make stock market crises more likely, while volatility in any form has no impact on currency crises.
    Keywords: Stock market volatility ; Financial crises predictability ; Volatility paradox ; Minsky hypothesis ; Financial instability ; Risk-taking
    JEL: F30 F44 G01 G10 G18 N10 N20
    Date: 2016–10

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