nep-rmg New Economics Papers
on Risk Management
Issue of 2019‒09‒16
23 papers chosen by



  1. Value adjustments and dynamic hedging of reinsurance counterparty risk By Claudia Ceci; Katia Colaneri; R\"diger Frey; Verena K\"ock
  2. Machine Learning in Least-Squares Monte Carlo Proxy Modeling of Life Insurance Companies By Anne-Sophie Krah; Zoran Nikoli\'c; Ralf Korn
  3. Regulating the doom loop By Alogoskoufis, Spyros; Langfield, Sam
  4. Systemic Risk Clustering of China Internet Financial Based on t-SNE Machine Learning Algorithm By Mi Chuanmin; Xu Runjie; Lin Qingtong
  5. Virtual Historical Simulation for estimating the conditional VaR of large portfolios By Christian Francq; Jean-Michel Zakoian
  6. Moments-Based Spillovers across Gold and Oil Markets By Matteo Bonato; Rangan Gupta; Chi Keung Marco Lau; Shixuan Wang
  7. Nash Equilibria in Optimal Reinsurance Bargaining By Michail Anthropelos; Tim J. Boonen
  8. The effects of asset liquidity on dynamic bankruptcy decisions By Michi Nishihara; Takashi Shibata
  9. Behind every farmer: Women's off-farm income and risk management for US farms By Jodlowski, Margaret C.
  10. Gold, Platinum and the Predictability of Bond Risk Premia By Elie Bouri; Riza Demirer; Rangan Gupta; Mark E. Wohar
  11. Presidential Power and Stock Returns By Youngsoo Kim; Jung Chul Park
  12. Credit risk in commercial real estate bank loans: the role of idiosyncratic versus macro-economic factors By Dimitris Mokas; Rob Nijskens
  13. Conditional survival probabilities under partial information: a recursive quantization approach with applications By Cheikh Mbaye; Abass Sagna; Fr\'ed\'eric Vrins
  14. The Countercyclical Capital Buffer and the Composition of Bank Lending By Raphael A. Auer; Steven Ongena
  15. Bayesian Inference on Volatility in the Presence of Infinite Jump Activity and Microstructure Noise By Qi Wang; Jos\'e E. Figueroa-L\'opez; Todd Kuffner
  16. Detecting stock market bubbles based on the cross-sectional dispersion of stock prices By Takayuki Mizuno; Takaaki Ohnishi; Tsutomu Watanabe
  17. Underwriting factors in motor insurance. By Ilona Tomaszewska
  18. Household Decisionmaking Under Risk: Evidence from Samburu County, Kenya By Hobbs, Andrew
  19. Impact of the Basel III Bank Regulation on Agricultural Lending By Kim, Kevin N.
  20. Long Term Impacts of Cover Crops on Corn Yield Risk and Implied Changes to Crop Insurance Premiums By Connor, Lawson
  21. An arbitrage-free conic martingale model with application to credit risk By Cheikh Mbaye; Fr\'ed\'eric Vrins
  22. An Impact Assessment of Higher Capital Adequacy Requirements: Evidence From India By Noor Ulain Rizvi; Smita Kashiramka; Shveta Singh
  23. The risk elicitation puzzle revisited: Across-methods (in)consistency? By Felix Holzmeister; Matthias Stefan

  1. By: Claudia Ceci; Katia Colaneri; R\"diger Frey; Verena K\"ock
    Abstract: Reinsurance counterparty credit risk (RCCR) is the risk of a loss arising from the fact that a reinsurance company is unable to fulfill her contractual obligations towards the ceding insurer. RCCR is an important risk category for insurance companies which, so far, has been addressed mostly via qualitative approaches. In this paper we therefore study value adjustments and dynamic hedging for RCCR. We propose a novel model that accounts for contagion effects between the default of the reinsurer and the price of the reinsurance contract. We characterize the value adjustment in a reinsurance contract via a partial integro-differential equation (PIDE) and derive the hedging strategies using a quadratic method. The paper closes with a simulation study which shows that dynamic hedging strategies have the potential to significantly reduce RCCR.
    Date: 2019–09
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1909.04354&r=all
  2. By: Anne-Sophie Krah; Zoran Nikoli\'c; Ralf Korn
    Abstract: Under the Solvency II regime, life insurance companies are asked to derive their solvency capital requirements from the full loss distributions over the coming year. Since the industry is currently far from being endowed with sufficient computational capacities to fully simulate these distributions, the insurers have to rely on suitable approximation techniques such as the least-squares Monte Carlo (LSMC) method. The key idea of LSMC is to run only a few wisely selected simulations and to process their output further to obtain a risk-dependent proxy function of the loss. In this paper, we present and analyze various adaptive machine learning approaches that can take over the proxy modeling task. The studied approaches range from ordinary and generalized least-squares regression variants over GLM and GAM methods to MARS and kernel regression routines. We justify the combinability of their regression ingredients in a theoretical discourse. Further, we illustrate the approaches in slightly disguised real-world experiments and perform comprehensive out-of-sample tests.
    Date: 2019–09
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1909.02182&r=all
  3. By: Alogoskoufis, Spyros; Langfield, Sam
    Abstract: Euro area governments have committed to break the doom loop between banks and sovereigns.But policymakers disagree on how to treat sovereign exposures in bank regulation. Our contributionis to model endogenous sovereign portfolio reallocation by banks in response toregulatory reform. Simulations highlight a tension between concentration and credit risk inportfolio reallocation. Resolving this tension requires regulatory reform to be complementedby an expansion in the portfolio opportunity set to include an area-wide low-risk asset. Byreinvesting into such an asset, banks would reduce both their concentration and credit riskexposure. JEL Classification: G01, G11, G21, G28
    Keywords: Bank regulation, sovereign risk, systemic risk
    Date: 2019–09
    URL: http://d.repec.org/n?u=RePEc:ecb:ecbwps:20192313&r=all
  4. By: Mi Chuanmin; Xu Runjie; Lin Qingtong
    Abstract: With the rapid development of Internet finance, a large number of studies have shown that Internet financial platforms have different financial systemic risk characteristics when they are subject to macroeconomic shocks or fragile internal crisis. From the perspective of regional development of Internet finance, this paper uses t-SNE machine learning algorithm to obtain data mining of China's Internet finance development index involving 31 provinces and 335 cities and regions. The conclusion of the peak and thick tail characteristics, then proposed three classification risks of Internet financial systemic risk, providing more regionally targeted recommendations for the systematic risk of Internet finance.
    Date: 2019–08
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1909.03808&r=all
  5. By: Christian Francq; Jean-Michel Zakoian
    Abstract: In order to estimate the conditional risk of a portfolio's return, two strategies can be advocated. A multivariate strategy requires estimating a dynamic model for the vector of risk factors, which is often challenging, when at all possible, for large portfolios. A univariate approach based on a dynamic model for the portfolio's return seems more attractive. However, when the combination of the individual returns is time varying, the portfolio's return series is typically non stationary which may invalidate statistical inference. An alternative approach consists in reconstituting a "virtual portfolio", whose returns are built using the current composition of the portfolio and for which a stationary dynamic model can be estimated. This paper establishes the asymptotic properties of this method, that we call Virtual Historical Simulation. Numerical illustrations on simulated and real data are provided.
    Date: 2019–09
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1909.04661&r=all
  6. By: Matteo Bonato (Department of Economics and Econometrics, University of Johannesburg, Auckland Park, South Africa; IPAG Business School, 184 Boulevard Saint-Germain, 75006 Paris, France); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa; IPAG Business School, 184 Boulevard Saint-Germain, 75006 Paris, France); Chi Keung Marco Lau (Huddersfield Business School, University of Huddersfield, Huddersfield, HD1 3DH, United Kingdom); Shixuan Wang (Department of Economics, University of Reading, Reading, RG6 6AA, United Kingdom)
    Abstract: In this paper, we use intraday futures market data on gold and oil to compute returns, realized volatility, volatility jumps, realized skewness and realized kurtosis. Using these daily metrics associated with two markets over the period of December 2, 1997 to May 26, 2017, we conduct linear, nonparametric, and time-varying (rolling) tests of causality, with the latter two approaches motivated due to the existence of nonlinearity and structural breaks. While, there is hardly any evidence of spillovers between the returns of these two markets, strong evidence of bidirectional causality is detected for realized volatility, which seems to be resulting from volatility jumps. Evidence of spillovers are also detected for the crash risk variables, i.e., realized skewness, and for realized kurtosis as well, with the effect on the latter being relatively stronger. Moreover, based on a moments-based test of causality, evidence of co-volatility is deduced, whereby we find that extreme positive and negative returns of gold and oil tend to drive the volatilities in these markets. Our results have important implications for not only investors, but also policymakers.
    Keywords: Gold and Oil Markets, Linear, Nonparametric and Time-Varying Causality Tests, Moments-Based Spillovers
    JEL: C32 Q02
    Date: 2019–08
    URL: http://d.repec.org/n?u=RePEc:pre:wpaper:201966&r=all
  7. By: Michail Anthropelos; Tim J. Boonen
    Abstract: We introduce a strategic behavior in reinsurance bilateral transactions, where agents choose the risk preferences they will appear to have in the transaction. Within a wide class of risk measures, we identify agents' strategic choices to a range of risk aversion coefficients. It is shown that at the strictly beneficial Nash equilibria, agents appear homogeneous with respect to their risk preferences. While the game does not cause any loss of total welfare gain, its allocation between agents is heavily affected by the agents' strategic behavior. This allocation is reflected in the reinsurance premium, while the insurance indemnity remains the same in all strictly beneficial Nash equilibria. Furthermore, the effect of agents' bargaining power vanishes through the game procedure and the agent who gets more welfare gain is the one who has an advantage in choosing the common risk aversion at the equilibrium.
    Date: 2019–09
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1909.01739&r=all
  8. By: Michi Nishihara (Graduate School of Economics, Osaka University); Takashi Shibata (Graduate School of Management, Tokyo Metropolitan University)
    Abstract: We develop a dynamic bankruptcy model with asset illiquidity. In the model, a distressed firm chooses between sell-out and default, as well as its timing under the assumption that sell-out is feasible only at Poisson jump times, where the arrival rate of acquirers stands for asset liquidity. With lower asset liquidity, the firm increases the sell-out region to mitigate the risk of not finding an acquirer until bankruptcy. Despite the larger sell-out region, lower asset liquidity increases the default probability and decreases the equity, debt, and firm values. In the optimal capital structure, with lower asset liquidity, the firm reduces leverage, but the cautious capital structure does not fully offset the increased default risk. The stock price reaction caused by sell-out depends on the sell-out timing. When the firm's asset value is not sufficiently high, the stock price jump size is an inverted U-shape with the economic state variable. Lower asset liquidity increases the jump size due to greater surprise. These results fit empirical observations.
    Keywords: liquidation; illiquidity; real option; M&A
    JEL: G13 G32 G33
    Date: 2019–09
    URL: http://d.repec.org/n?u=RePEc:osk:wpaper:1912&r=all
  9. By: Jodlowski, Margaret C.
    Keywords: Labor and Human Capital
    Date: 2019–06–25
    URL: http://d.repec.org/n?u=RePEc:ags:aaea19:290975&r=all
  10. By: Elie Bouri (USEK Business School, Holy Spirit University of Kaslik, Jounieh, Lebanon); Riza Demirer (Department of Economics and Finance, Southern Illinois University Edwardsville, Edwardsville, IL 62026-1102, USA); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa); Mark E. Wohar (College of Business Administration, University of Nebraska at Omaha, 6708 Pine Street, Omaha, NE 68182, USA, and School of Business and Economics, Loughborough University, Leicestershire, LE11 3TU, UK)
    Abstract: We show that the ratio of gold to platinum prices (GP) contains significant predictive information for excess U.S. government bond returns, even after controlling for a large number of financial and macro factors. Including GP in the model improves the predictive accuracy, over and above the standard macroeconomic and financial predictors, at all forecasting horizons for the shortest maturity bonds and at longer forecasting horizons for bonds with longer maturities beyond 2 years. The findings highlight the predictive information captured by commodity prices on bond market excess returns with significant investment and policy making implications.
    Keywords: Bond Premia, Predictability, Gold-Platinum Price Ratio, Out-of-Sample Forecasts
    JEL: C22 C53 G12 G17 Q02
    Date: 2019–08
    URL: http://d.repec.org/n?u=RePEc:pre:wpaper:201967&r=all
  11. By: Youngsoo Kim (University of Regina); Jung Chul Park (University of South Florida)
    Abstract: Recent studies highlight positive effect of political connections on firm performance and stock returns. This paper shows that the positive effect of political connections on the cross-sectional stock returns disappears in the weak presidency period, defined as the last two years before the presidential party change, or period of low job approval ratings. The extent of the presidential party?s control over the Congress does not affect our main result. The result is driven by small firms, who typically do not have financial resources to hedge away political risks, and by the firms located in the states where residents more strongly support the president. Additional test suggests that the industries that rely on heavy government expenditure use a variety of political strategies to maintain the value of their political capital even during the weak presidency period.
    Keywords: Political geography; political connections; policy risk; returns; performance; Presidential Power; Presidential job approval rating
    JEL: G10 G11 G14
    Date: 2019–07
    URL: http://d.repec.org/n?u=RePEc:sek:iacpro:8710820&r=all
  12. By: Dimitris Mokas; Rob Nijskens
    Abstract: The commercial real estate market is pro-cyclical. This feature, together with the relative size of the industry and the large capital inflows, has made this sector relevant for financial stability. Using a novel loan level data set covering the commercial real estate portfolios of Dutch banks we aim to uncover potential drivers of distress in commercial real estate loans. Furthermore, we estimate the relative importance of idiosyncratic and systematic factors and emphasize the importance of bank behavior for distinguishing between good and bad credit growth. We find that loans originated near the peak of the cycle are riskier, confirming the pro-cyclical nature of the market. As opposed to loans originated during busts, the risk of boom loans does not decrease when economic conditions improve. Idiosyncratic factors correlated with higher credit risk are loan-to-value ratios and interest rates, especially when coupled with variable rate contracts. Moreover, we find that collateral type plays a role, as loans for non-residential (office, retail, industrial) real estate with higher vacancy rates are riskier. These results have implications for both macroprudential and microprudential supervision, as they demonstrate the pro-cyclicality of the market and show that indicators like loan-to-value, interest rate structure and vacancy rates must be monitored more carefully in boom times.
    Keywords: macroprudential policy; risk monitoring; commercial real estate; procyclicality of credit
    JEL: E32 E44 E58 G21 G3 G33
    Date: 2019–08
    URL: http://d.repec.org/n?u=RePEc:dnb:dnbwpp:653&r=all
  13. By: Cheikh Mbaye; Abass Sagna; Fr\'ed\'eric Vrins
    Abstract: We consider a structural model where the survival/default state is observed together with a noisy version of the firm value process. This assumption makes the model more realistic than most of the existing alternatives, but triggers important challenges related to the computation of conditional default probabilities. In order to deal with general diffusions as firm value process, we derive a numerical procedure based on the recursive quantization method to approximate it. Then, we investigate the error approximation induced by our procedure. Eventually, numerical tests are performed to evaluate the performance of the method, and an application is proposed to the pricing of CDS options.
    Date: 2019–09
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1909.01970&r=all
  14. By: Raphael A. Auer; Steven Ongena
    Abstract: Do macroprudential regulations on residential lending influence commercial lending behavior too? To answer this question, we identify the compositional changes in banks’ supply of credit using the variation in their holdings of residential mortgages on which extra capital requirements were uniformly imposed by the countercyclical capital buffer (CCyB) introduced in Switzerland in 2012. We find that the CCyB’s introduction led to higher growth in commercial lending although this was unrelated to conditions in regional housing markets. Interest rates and fees charged to the firms concurrently increased. We rationalize these findings in a model featuring both private and firm-specific collateral.
    Keywords: macroprudential policy, spillovers, credit, bank capital, systemic risk
    JEL: E51 E58 E60 G01 G21 G28
    Date: 2019
    URL: http://d.repec.org/n?u=RePEc:ces:ceswps:_7815&r=all
  15. By: Qi Wang; Jos\'e E. Figueroa-L\'opez; Todd Kuffner
    Abstract: Volatility estimation based on high-frequency data is key to accurately measure and control the risk of financial assets. A L\'{e}vy process with infinite jump activity and microstructure noise is considered one of the simplest, yet accurate enough, models for financial data at high-frequency. Utilizing this model, we propose a "purposely misspecified" posterior of the volatility obtained by ignoring the jump-component of the process. The misspecified posterior is further corrected by a simple estimate of the location shift and re-scaling of the log likelihood. Our main result establishes a Bernstein-von Mises (BvM) theorem, which states that the proposed adjusted posterior is asymptotically Gaussian, centered at a consistent estimator, and with variance equal to the inverse of the Fisher information. In the absence of microstructure noise, our approach can be extended to inferences of the integrated variance of a general It\^o semimartingale. Simulations are provided to demonstrate the accuracy of the resulting credible intervals, and the frequentist properties of the approximate Bayesian inference based on the adjusted posterior.
    Date: 2019–09
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1909.04853&r=all
  16. By: Takayuki Mizuno (National Institute of Informatics); Takaaki Ohnishi (Graduate School of Information Science and Technology, The University of Tokyo); Tsutomu Watanabe (Graduate School of Economics, The University of Tokyo)
    Abstract: A statistical method is proposed for detecting stock market bubbles that occur when speculative funds concentrate on a small set of stocks. The bubble is defined by stock price diverging from the fundamentals. A firm’s financial standing is certainly a key fundamental attribute of that firm. The law of one price would dictate that firms of similar financial standing share similar fundamentals.We investigate the variation in market capitalization normalized by fundamentals that is estimated by Lasso regression of a firm’s financial standing. The market capitalization distribution has a substantially heavier upper tail during bubble periods, namely, the market capitalization gap opens up in a small subset of firms with similar fundamentals. This phenomenon suggests that speculative funds concentrate in this subset. We demonstrated that this phenomenon could have been used to detect the dot-com bubble of 1998-2000 in different stock exchanges.
    Date: 2019–09
    URL: http://d.repec.org/n?u=RePEc:cfi:fseres:cf463&r=all
  17. By: Ilona Tomaszewska (Warsaw School of Economics, Poland)
    Abstract: Underwriting is an important element of the assessment and valuation process of insurance risk. The aim of this process is the proper construction of the insurance portfolio by defining criteria indicating the risk appetite by the insurer, at the same time having a real impact on the technical result. Each insurance company specifies its own guidelines on risk tolerance, both regarding the entity and the subject of insurance. What variables are taken into account when determining the risk parity depends on the strategy adopted by the management of the company, guidelines defined within the capital group or simply by the risk appetite. Less restrictive or even other set of parameters is determined if the purpose of the insurance company is to achieve the highest possible gross written premium, understood as collecting the highest value of premium and volume of customers. Other parameters will be considered when the insurance company focuses on achieving a certain profitability index. Still others, when the purpose of the company is to diversify the vehicle portfolio and, for example, to open up to more expensive vehicles.The aim of the study is to show how important for motor insurance is underwriting process conducted by the insurer, what are its elements for MTPL as for casco, and how underwriting process affects the quality of the insurance company's portfolio.
    Keywords: underwriting, motor insurance, referrals, policy, risk
    JEL: G22
    Date: 2019–06
    URL: http://d.repec.org/n?u=RePEc:sek:iacpro:9011481&r=all
  18. By: Hobbs, Andrew
    Keywords: International Development
    Date: 2019–06–25
    URL: http://d.repec.org/n?u=RePEc:ags:aaea19:291024&r=all
  19. By: Kim, Kevin N.
    Keywords: Agricultural Finance
    Date: 2019–06–25
    URL: http://d.repec.org/n?u=RePEc:ags:aaea19:290747&r=all
  20. By: Connor, Lawson
    Keywords: Production Economics
    Date: 2019–06–25
    URL: http://d.repec.org/n?u=RePEc:ags:aaea19:291150&r=all
  21. By: Cheikh Mbaye; Fr\'ed\'eric Vrins
    Abstract: Conic martingales refer to Brownian martingales evolving between bounds. Among other potential applications, they have been suggested for the sake of modeling conditional survival probabilities under partial information, as usual in reduced-form models. Yet, conic martingale default models have a special feature; in contrast to the class of Cox models, they fail to satisfy the so-called \emph{immersion property}. Hence, it is not clear whether this setup is arbitrage-free or not. In this paper, we study the relevance of conic martingales-driven default models for practical applications in credit risk modeling. We first introduce an arbitrage-free conic martingale, namely the $\Phi$-martingale, by showing that it fits in the class of Dynamized Gaussian copula model of Cr\'epey et al., thereby providing an explicit construction scheme for the default time. In particular, the $\Phi$-martingale features interesting properties inherent on its construction easing the practical implementation. Eventually, we apply this model to CVA pricing under wrong-way risk and CDS options, and compare our results with the JCIR++ (a.k.a. SSRJD) and TC-JCIR recently introduced as an alternative.
    Date: 2019–09
    URL: http://d.repec.org/n?u=RePEc:arx:papers:1909.02474&r=all
  22. By: Noor Ulain Rizvi (Indian Institute of Technology Delhi); Smita Kashiramka (Indian Institute of Technology Delhi); Shveta Singh (Indian Institute of Technology Delhi)
    Abstract: Regulatory norms aim to ensure stability and resilience in the banking sector as episodes of crises may have a spill-over effect in the real economy. Literature based on studies of developed economies, suggests that higher capital norms improve the resilience of the banking sector, which in turn, reduces the probability of a financial crisis. An important benefit of which is on the size of the economic loss if the crisis does occur. On the other hand, higher capital requirements pose significant costs to banks, which are, in turn, passed on to the rest of society through reductions in lending volumes, credit rationing and increase in prices of credit that culminates into decreasing the output of the economy. This study aims to find the net impact of implementing Basel norms in a fast-growing economy, (yet under-researched) of Asia, i.e, India. The results prove that the implementation of Basel norms has significant benefits (using a step wise approach, multivariate logistic regression), along with costs (using vector auto regression). In sum, there are positive net benefits in terms of output saved.
    Keywords: Basel, Banking, Financial crisis, India, Comparative study
    JEL: G28 G01 O57
    Date: 2019–06
    URL: http://d.repec.org/n?u=RePEc:sek:iacpro:9011309&r=all
  23. By: Felix Holzmeister; Matthias Stefan
    Abstract: With the rise of experimental research in the social sciences, numerous methods to elicit and classify people's risk attitudes in the laboratory have evolved. However, evidence suggests that people's attitudes towards risk may change considerably when measured with different methods. Based on a with-subject experimental design using four widespread risk preference elicitation methods, we find that different procedures indeed give rise to considerably varying estimates of individual and aggregate level risk preferences. Conducting simulation exercises to obtain benchmarks for subjects' behavior, we find that the observed heterogeneity in risk preference estimates across methods looks qualitatively similar to the heterogeneity arising from independent random draws from choices in the experimental tasks, despite significantly positive correlations between tasks. Our study, however, provides evidence that subjects are surprisingly well aware of the variation in the riskiness of their choices. We argue that this calls into question the common interpretation of variation in revealed risk preferences as being inconsistent.
    Keywords: Risk preference elicitation, inconsistent behavior, risk attitudes
    JEL: C91 D81
    Date: 2019
    URL: http://d.repec.org/n?u=RePEc:inn:wpaper:2019-19&r=all

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