nep-rmg New Economics Papers
on Risk Management
Issue of 2018‒05‒07
fourteen papers chosen by

  1. Idiosyncratic Risk and the Cross-Section of European Insurance Equity Returns By Hassen Raîs
  2. Toward a Systematic Approach to the Economic Effects of Risk: Characterizing Utility Functions" By Gollier, Christian; Kimball, Miles S.
  3. Comparative empirical analysis on the effect of mortgage loan on capital adequacy ratio By Dinc, Yusuf
  4. Strategic Selection of Risk Models and Bank Capital Regulation By Colliard, Jean-Edouard
  5. Nonlinearity in stock networks By David Hartman; Jaroslav Hlinka
  6. The Interplay between Regulations and Financial Stability By Allen, Franklin; Gu, Xian
  7. Predictive power of inspection outcomes for future shipping accidents – an empirical appraisal with special attention for human factor aspects By Heij, C.; Knapp, S.
  8. Ruin probabilities for two collaborating insurance companies By Zbigniew Michna
  9. Interpreting Quantile Independence By Matthew A. Masten; Alexandre Poirier
  10. The Impact of the Exchange Rate Volatilities on Stock Market Returns Dynamic By Nesrine Mechri; Ben Hamad; Christian Peretti; Sahar Charfi
  11. Robust Log-Optimal Strategy with Reinforcement Learning By Yifeng Guo; Xingyu Fu; Yuyan Shi; Mingwen Liu
  12. The determinants of bank loan recovery rates in good times and bad - new evidence By Hong Wang; Catherine S. Forbes; Jean-Pierre Fenech; John Vaz
  13. Appraisal Accuracy, Automated Valuation Models, And Credit Modeling in Rural Areas By Alexander N. Bogin; Jessica Shui
  14. Financing Insurance By Rampini, Adriano A.; Viswanathan, S.

  1. By: Hassen Raîs (ESSCA - Ecole Supérieure des Sciences Commerciales d'Angers - ESSCA)
    Abstract: —Based on a survey of 203 Insurance equities from European capital markets over the 2001-2014 period, this article analyses the role of idiosyncratic risk in the pricing of European insurance equities. The capital asset pricing model predicts that in equilibrium, investors should hold the market portfolio. As a result, investors should only be rewarded for carrying undiversifiable systematic risk and not for diversifiable idiosyncratic risk. The framework of Fama and MacBeth is employed. Regressions of the cross-section of expected equity excess returns on idiosyncratic risk and other firm characteristics such as beta, size, book-to-market equity (BE/ME), momentum, liquidity and co-skewness are performed. The empirical models reveal that the largest part of total volatility is idiosyncratic and therefore firm specific in nature. Simple cross-correlations indicate that high beta, small size, high BE/ME, low momentum, low liquidity and high co-skewness equities have higher idiosyncratic risk.
    Keywords: EGARCH,Insurance equities,cross-section,idiosyncratic risk,idiosyncratic volatility
    Date: 2016–12
  2. By: Gollier, Christian; Kimball, Miles S.
    Abstract: The Diffidence Theorem, together with complementary tools, can aid in illuminating a broad set of questions about how to mathematically characterize the set of utility functions with specified economic properties. This paper establishes the technique and illustrates its application to many questions, old and new. For example, among many other older and other technically more difficult results, it is shown that (1) several implications of globally greater risk aversion depend on distinct mathematical properties when the initial wealth level is known, (2) whether opening up a new asset market increases or decreases saving depends on whether the reciprocal of marginal utility is concave or convex, and (3) whether opening up a new asset market raises or lowers risk aversion towards small independent risks depends on whether absolute risk aversion is convex or concave.
    Date: 2018–04
  3. By: Dinc, Yusuf
    Abstract: Capital adequacy ratio is the main indicator for banks to proceed with their operations. Standards for the calculation of the ratio are based on Basel Accord. Key factor for the calculation is credit risk. Credit risk is a function of credit and collateral type. In this case, mortgage has lower risk weight based on its collateral structure on credit risk. This research evaluates the effects of mortgages on capital adequacy ratio to understand the effects of collateral based credits. The findings show positive results between capital adequacy ratio and mortgages of participation banks. However, mortgages have negative impact on capital adequacy ratio of conventional banks. Participation and conventional banks of Turkey are compared on linear regression to analyse the effects of mortgages on capital adequacy ratio. Results are important for further research and professionals.
    Keywords: Capital adequacy ratio Mortgage Islamic banking Retail credit
    JEL: G21 G29
    Date: 2017–05–07
  4. By: Colliard, Jean-Edouard
    Abstract: The regulatory use of banks' internal models makes capital requirements more risk-sensitive but invites regulatory arbitrage. I develop a framework to study bank regulation with strategic selection of risk models. A bank supervisor can discourage arbitrage by auditing risk models, and implements capital ratios less risk-sensitive than in the first-best to reduce auditing costs. The optimal capital ratios of a national supervisor can be different from those set by supranational authorities, in which case the supervisor optimally tolerates biased models. I discuss the empirical implications of this "hidden model" problem, and policy answers such as leverage ratios and more reliance on backtesting mechanisms.
    Keywords: basel risk-weights; internal risk models; leverage ratio; supervisory audits
    JEL: D82 D84 G21 G32 G38
    Date: 2017–09–01
  5. By: David Hartman; Jaroslav Hlinka
    Abstract: Stock networks constitute a well established tool for characterization of complex behavior in stock markets. The networks are constructed from time series of stock prices. Since Mantegna seminal paper the linear Pearson's correlation coefficient between pairs of stocks is used to determine network edges. Recently, possible effects of nonlinearity on graph characteristics have been demonstrated when using nonlinear measures such as mutual information instead of linear correlation. In this paper, we quantitatively characterize the nonlinearity in stock time series and the effect it has on stock network properties. It is achieved by a systematic multi-step approach, that allows 1. to quantify the nonlinearity of coupling, 2. to correct its effects wherever it is caused by simple univariate non-Gaussianity, 3. to potentially localize in space and time any remaining strong sources of this nonlinearity, and finally, 4. to study the effect the nonlinearity has on global network properties. By applying the presented approach to stocks included in three prominent indices (NYSE100, FTSE100 and SP500), we document that most of the apparent nonlinearity is due to univariate non-Gaussianity. Further, strong nonstationarity in a few specific stocks may play a role. In particular, the sharp decrease of some stocks during the global finance crisis in 2008 gives rise to apparent nonlinear dependences among stocks.
    Date: 2018–04
  6. By: Allen, Franklin; Gu, Xian
    Abstract: The crisis demonstrated that microprudential regulation focusing on the risks taken by individual banks is not sufficient to prevent crises. This is because it ignores systemic risk. Six types of systemic risk are identified, namely: (i) panics - banking crises due to multiple equilibria; (ii) banking crises due to asset price falls; (iii) contagion; (iv) financial architecture; (v) foreign exchange mismatches in the banking system; (vi) behavioral effects from Knightian uncertainty. We focus on the first three as they are arguably the main causes of the 2007-9 crisis and consider regulatory and other policies to counteract them.
    Keywords: Asset price bubbles; contagion; Financial crises; macroprudential
    JEL: G01 G21 G28
    Date: 2018–04
  7. By: Heij, C.; Knapp, S.
    Abstract: This paper investigates whether deficiencies detected during port state control (PSC) inspections have predictive power for future accident risk, in addition to other vessel-specific risk factors like ship type, age, size, flag, and owner. The empirical analysis links accidents to past inspection outcomes and is based on data from all around the globe of PSC regimes using harmonized deficiency codes. These codes are aggregated into eight groups related to human factor aspects like crew qualifications, working and living conditions, and fatigue and safety management. This information is integrated by principal components into a single overall deficiency index, which is related to future accident risk by means of logit models. The factor by which accident risk increases for vessels with above average compared to below average deficiency scores is about 6 for total loss, 2 for very serious, 1.5 for serious, and 1.3 for less-serious accidents. Relations between deficiency scores and accident risk are presented in graphical format. The results may be of interest to PSC authorities for targeting inspection areas, to maritime administrations for improving asset allocation based on prediction scenarios connected with vessel traffic data, and to maritime insurers for refining their premium strategies.
    Keywords: deficiencies, human factor, Maritime safety, port state control inspections, risk prediction, shipping accidents
    Date: 2018–02–26
  8. By: Zbigniew Michna
    Abstract: In this note we find a formula for the supremum distribution of spectrally positive or negative L\'evy processes with a broken linear drift. This gives formulas for ruin probabilities in the case when two insurance companies (or two branches of the same company) divide between them both claims and premia in some specified proportions. As an example we consider gamma L\'evy process, $\alpha$-stable L\'evy process and Brownian motion. Moreover we obtain identities for Laplace transform of the distribution for the supremum of L\'evy processes with randomly broken drift and on random intervals.
    Date: 2018–04
  9. By: Matthew A. Masten; Alexandre Poirier
    Abstract: How should one assess the credibility of assumptions weaker than statistical independence, like quantile independence? In the context of identifying causal effects of a treatment variable, we argue that such deviations should be chosen based on the form of selection on unobservables they allow. For quantile independence, we characterize this form of treatment selection. Specifically, we show that quantile independence is equivalent to a constraint on the average value of either a latent propensity score (for a binary treatment) or the cdf of treatment given the unobservables (for a continuous treatment). In both cases, this average value constraint requires a kind of non-monotonic treatment selection. Using these results, we show that several common treatment selection models are incompatible with quantile independence. We introduce a class of assumptions which weakens quantile independence by removing the average value constraint, and therefore allows for monotonic treatment selection. In a potential outcomes model with a binary treatment, we derive identified sets for the ATT and QTT under both classes of assumptions. In a numerical example we show that the average value constraint inherent in quantile independence has substantial identifying power. Our results suggest that researchers should carefully consider the credibility of this non-monotonicity property when using quantile independence to weaken full independence.
    Date: 2018–04
  10. By: Nesrine Mechri (UCBL - Université Claude Bernard Lyon 1 - Université de Lyon, FSEG Sfax - Faculté des Sciences Economiques et de Gestion de Sfax - Faculté des Sciences Economiques et de Gestion de Sfax); Ben Hamad (IHEC de Sfax); Christian Peretti (University of Orleans - LEO); Sahar Charfi (FSEG Sfax - Faculté des Sciences Economiques et de Gestion de Sfax - Faculté des Sciences Economiques et de Gestion de Sfax)
    Abstract: The present research provides an overview of the interactions and links between exchange rate volatility and the dynamics of stock market returns in order to clarify the relationship between this variables for managers and investors who will be able to control better the portfolio risk level. This research aims to identify the impact of both exchange rate and relative prices uncertainty on the fluctuations of stock markets prices, considering two countries that belong to MENA zone. The GARCH model is applied to measure the volatility of our variables and implemented a multiple regression model to determine the impact of exchange rate and relative prices fluctuations as well as their volatilities on stock market volatility using Monthly data. In this work, several determinants of stock market indices are integrated in our empirical examination that have not been used simultaneously before, hence, the results show that in the case of Tunisia, exchange rate volatility have a significant effect on stock market fluctuations, as well as the volatility of the Gold and the oil prices, which are significant. Alternatively, in Turkey both the volatilities of the exchange rate and gold prices have an influence on the dynamics of the stock market returns and the fluctuation of the interest rate as well, while other prices are statistically non-significant. J.E.L. classification: F31, F62, F65, G15
    Keywords: Nominal exchange rate,MENA,Volatility,GARCH 2,Stock market return
    Date: 2018–04–14
  11. By: Yifeng Guo; Xingyu Fu; Yuyan Shi; Mingwen Liu
    Abstract: We proposed a new Portfolio Management method termed as Robust Log-Optimal Strategy (RLOS), which ameliorates the General Log-Optimal Strategy (GLOS) by approximating the traditional objective function with quadratic Taylor expansion. It avoids GLOS's complex CDF estimation process,hence resists the "Butterfly Effect" caused by estimation error. Besides,RLOS retains GLOS's profitability and the optimization problem involved in RLOS is computationally far more practical compared to GLOS. Further, we combine RLOS with Reinforcement Learning (RL) and propose the so-called Robust Log-Optimal Strategy with Reinforcement Learning (RLOSRL), where the RL agent receives the analyzed results from RLOS and observes the trading environment to make comprehensive investment decisions. The RLOSRL's performance is compared to some traditional strategies on several back tests, where we randomly choose a selection of constituent stocks of the CSI300 index as assets under management and the test results validate its profitability and stability.
    Date: 2018–05
  12. By: Hong Wang; Catherine S. Forbes; Jean-Pierre Fenech; John Vaz
    Abstract: We find that factors explaining bank loan recovery rates vary depending on the state of the economic cycle. Our modeling approach incorporates a two-state Markov switching mechanism as a proxy for the latent credit cycle, helping to explain differences in observed recovery rates over time. We are able to demonstrate how the probability of default and certain loan-specific and other variables hold different explanatory power with respect to recovery rates over `good' and `bad' times in the credit cycle. That is, the relationship between recovery rates and certain loan characteristics, firm characteristics and the probability of default differs depending on underlying credit market conditions. This holds important implications for modelling capital retention, particularly in terms of countercyclicality.
    Date: 2018–04
  13. By: Alexander N. Bogin (Federal Housing Finance Agency); Jessica Shui (Federal Housing Finance Agency)
    Abstract: Accurate and unbiased property value estimates are essential to credit risk management. Along with loan amount, they determine a mortgage’s loan-to-value ratio, which captures the degree of homeowner equity and is a key determinant of borrower credit risk. For home purchases, lenders generally require an independent appraisal, which, in addition to a home’s sales price, is used to calculate a value for the underlying collateral. A number of empirical studies have shown that property appraisals tend to be biased upwards, and over 90 percent of the time, either confirm or exceed the associated contract price. Our data suggest that appraisal bias is particularly pervasive in rural areas where over 25 percent of rural properties are appraised at more than five percent above contract price. Given this significant upward bias, we examine a host of alternate valuation techniques to more accurately estimate rural property values. We then include these alternate value estimates when modeling delinquencies and examine their explanatory power.
    Keywords: automated valuation models, appraisal, property value, credit risk, rural
    JEL: G21 L85 R3
    Date: 2018–04
  14. By: Rampini, Adriano A.; Viswanathan, S.
    Abstract: Insurance has an intertemporal aspect as insurance premia have to be paid upfront. We argue that the financing aspect of insurance is key to understanding basic insurance patterns. In a model with limited enforcement, we show that insurance is globally monotone increasing in household net worth and income, incomplete, and precautionary. These results hold in economies with income risk, durable goods and collateral constraints, and durable goods price risk that affects asset values, under quite general conditions. In equilibrium, insurers are financial intermediaries with collateralized loans as assets and diversified portfolios of insurance claims as liabilities. Collateral scarcity lowers the interest rate, reduces insurance, and increases inequality.
    Keywords: Collateral; Financial constraints; household finance; Insurance; Risk management
    JEL: D91 E21 G22
    Date: 2018–04

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