nep-rmg New Economics Papers
on Risk Management
Issue of 2022‒10‒10
fifteen papers chosen by
Stan Miles
Thompson Rivers University

  1. Systemic Risk of Optioned Portfolios: Controllability and Optimization By Xiaochuan Pang; Shushang Zhu; Xueting Cui; Jiali Ma
  2. Implementation of risk management in small construction companies in Czechia By Vladislav ?ehá?ek
  3. Convex Risk Measures for the Aggregation of Multiple Information Sources and Applications in Insurance By Georgios I. Papayiannis; Athanasios N. Yannacopoulos
  4. A risk measurement approach from risk-averse stochastic optimization of score functions By Marcelo Brutti Righi; Fernanda Maria M\"uller; Marlon Ruoso Moresco
  5. Bayesian Mixed-Frequency Quantile Vector Autoregression: Eliciting tail risks of Monthly US GDP By Matteo Iacopini; Aubrey Poon; Luca Rossini; Dan Zhu
  6. Do Climate Risks Predict US Housing Returns and Volatility? Evidence from a Quantiles-Based Approach By Elie Bouri; Rangan Gupta; Hardik A. Marfatia; Jacobus Nel
  7. Downside Risk Aversion vs Decreasing Absolute Risk Aversion: An Intuitive Exposition By Hammitt, James K.
  8. Evaluating market risk from leveraged derivative exposures By Jukonis, Audrius
  9. How QE changes the nature of sovereign risk By Dirk Broeders; Leo de Haan; Jan Willem van den End
  10. An assessment of physicians’ risk attitudes using laboratory and field data By Castro, M.F.;; Guccio, C.;; Romeo, D.;
  11. How to release capital requirements during a pandemic? Evidence from euro area banks By Couaillier, Cyril; Reghezza, Alessio; Rodriguez d’Acri, Costanza; Scopelliti, Alessandro
  12. The integration of life and non-life insurance in financial inclusion index By Shen Yap; Hui-Shan Lee; Ping-Xin Liew
  13. Rethinking Generalized Beta Family of Distributions By Jiong Liu; R. A. Serota
  14. Measuring Price Risk Aversion through Indirect Utility Functions: A Laboratory Experiment By Ali Zeytoon-Nejad
  15. The economic costs of financial distress By Claudia Custodio; Miguel A. Ferreira; Emilia Garcia-Appendini

  1. By: Xiaochuan Pang; Shushang Zhu; Xueting Cui; Jiali Ma
    Abstract: We investigate the portfolio selection problem against the systemic risk which is measured by CoVaR. We first demonstrate that the systemic risk of pure stock portfolios is essentially uncontrollable due to the contagion effect and the seesaw effect. Next, we prove that it is necessary and sufficient to introduce options to make the systemic risk controllable by the correlation hedging and the extreme loss hedging. In addition to systemic risk control, we show that using options can also enhance return-risk performance. Then, with a reasonable approximation of the conditional distribution of optioned portfolios, we show that the portfolio optimization problem can be formulated as a second-order cone program (SOCP) that allows for efficient computation. Finally, we carry out comprehensive simulations and empirical tests to illustrate the theoretical findings and the performance of our method.
    Date: 2022–09
  2. By: Vladislav ?ehá?ek (Czech Technical University in Prague)
    Abstract: No matter the field, projects are always accompanied by many risks. It is necessaryto manage them in order to prevent complications. The paper deals with the implementation of risk management in Czechia, especially focusing on small to medium size companies. The paper is divided into 3 parts: In the first part we define what risk management and risks are and why it is important to manage them. This part also includes various methods of risk analysis and their advantages/disadvantages. In the second part we define risks in the field of construction, separate the risks into several categories and name a few examples. In the third part we talk about the construction field in Czechia, the specifics, and the implementation of risk management and other management systems. The paper ends with a conclusion, where examples of what could improve the situation are provided.
    Keywords: risk, risk management, risk analysis, construction, Czechia, small and medium companies
    JEL: L74 D24
    Date: 2022–07
  3. By: Georgios I. Papayiannis; Athanasios N. Yannacopoulos
    Abstract: We propose a novel class of convex risk measures, based on the concept of the Fr\'echet mean, designed in order to handle uncertainty which arises from multiple information sources regarding the risk factors of interest. The proposed risk measures robustly characterize the exposure of the firm, by filtering out appropriately the partial information available in individual sources into an aggregate model for the risk factors of interest. Importantly, the proposed risks can be expressed in closed analytic forms allowing for interesting qualitative interpretations as well as comparative statics and thus facilitate their use in the everyday risk management process of the insurance firms. The potential use of the proposed risk measures in insurance is illustrated by two concrete applications, capital risk allocation and premia calculation under uncertainty.
    Date: 2022–09
  4. By: Marcelo Brutti Righi; Fernanda Maria M\"uller; Marlon Ruoso Moresco
    Abstract: We propose a risk measurement approach for a risk-averse stochastic problem. We provide results that guarantee that our problem has a solution. We characterize and explore the properties of the argmin as a risk measure and the minimum as a deviation measure. We provide a connection between linear regression models and our framework. Based on this conception, we consider conditional risk and provide a connection between the minimum deviation portfolio and linear regression. Moreover, we also link the optimal replication hedging to our framework. An empirical illustration is carried out to demonstrate the practical utility of our proposal.
    Date: 2022–08
  5. By: Matteo Iacopini; Aubrey Poon; Luca Rossini; Dan Zhu
    Abstract: Timely characterizations of risks in economic and financial systems play an essential role in both economic policy and private sector decisions. However, the informational content of low-frequency variables and the results from conditional mean models provide only limited evidence to investigate this problem. We propose a novel mixed-frequency quantile vector autoregression (MF-QVAR) model to address this issue. Inspired by the univariate Bayesian quantile regression literature, the multivariate asymmetric Laplace distribution is exploited under the Bayesian framework to form the likelihood. A data augmentation approach coupled with a precision sampler efficiently estimates the missing low-frequency variables at higher frequencies under the state-space representation. The proposed methods allow us to nowcast conditional quantiles for multiple variables of interest and to derive quantile-related risk measures at high frequency, thus enabling timely policy interventions. The main application of the model is to nowcast conditional quantiles of the US GDP, which is strictly related to the quantification of Value-at-Risk and the Expected Shortfall.
    Date: 2022–09
  6. By: Elie Bouri (School of Business, Lebanese American University, Beirut, Lebanon); Rangan Gupta (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa); Hardik A. Marfatia (Department of Economics, Northeastern Illinois University, BBH 344G, 5500 N. St. Louis Avenue, Chicago, IL 60625, USA); Jacobus Nel (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa)
    Abstract: We analyse the ability of textual-analysis-based daily proxies of physical (natural disasters and global warming) and transition (US climate policy and international summits) climate risks to predict daily movements in the US housing market over the period 2nd August, 2007 to 29th November, 2019. To this end, we apply a nonparametric causality-in-quantiles test not only to uncover potential predictability in the entire conditional distribution of housing returns and volatility but also to account for nonlinearity and structural breaks which exist between housing returns and climate risk factors. We find that climate risk factors (and the associated uncertainty) do predict housing returns and volatility across the conditional distribution. These results are robust to alternative daily data of aggregate housing prices for the US and ten major metropolitan statistical areas (MSAs). Insights from our findings can benefit academics, investors, and policymakers in their decision-making.
    Keywords: Physical and transitional climate risks, US housing returns and volatility, higher-order nonparametric causality-in-quantiles test, natural disasters and global warming, US climate policy and international summits
    JEL: C22 C32 Q54 R30
    Date: 2022–09
  7. By: Hammitt, James K.
    Abstract: Downside risk aversion (downside RA) and decreasing absolute risk aversion (DARA) are different concepts that describe preferences for which the harm from bearing risk is lessened by an increase in wealth. This note presents some intuitive explanations of the difference between the two concepts using simple lotteries and graphical analysis. All risk-averse utility functions exhibit downside risk aversion, except those that exhibit sufficiently strong increasing absolute risk aversion (IARA). In a sense, downside RA is to be expected: adding downside risk to a baseline lottery is analogous to increasing risk while adding upside risk is analogous to decreasing risk. The difference between the two concepts can be attributed to the use of different measures of the harm from risk bearing: downside RA measures harm using the utility premium and DARA measures harm using the risk premium. The two premia can change at different rates and even in different directions as wealth increases.
    Keywords: risk aversion; prudence; risk apportionment; utility premium
    Date: 2022–09–14
  8. By: Jukonis, Audrius
    Abstract: Market participants use leveraged derivatives to gain access to equity market exposure through broker banks. Leverage and interconnectedness via overlapping portfolios of dealer banks can amplify adverse market movements, potentially causing sizeable losses. I propose a model, based on granular data, to simulate losses from a banks’ trading book in case of an adverse market scenario. Following a move in asset prices, banks mark their positions and issue margin calls; some (leveraged) counterparties fail to pay their margins, forcing banks to liquidate their positions causing a pressure on asset prices due to market impact. The impact is amplified because of the leverage and when counterparties are exposed to multiple banks over the same underlying. I employ the model to assess current capital and margin rules in covering risks from broker’s exposure to highly leveraged clients. JEL Classification: C60, G23, G13, G17
    Keywords: EMIR, Initial margin, leverage, market risk, Variation margin
    Date: 2022–09
  9. By: Dirk Broeders; Leo de Haan; Jan Willem van den End
    Abstract: We examine the effect of Quantitative Easing (QE) by the ECB on the sovereign bond risks of Italy, Ireland, Spain and Portugal. First, outcomes of panel regression models suggest that QE lowered the effect of volatility on sovereign bond spreads by 1 to 2 percentage points. Compared to asset purchases aimed at easing the monetary stance, purchase programmes supporting monetary transmission by countering financial market stress most clearly reduced the effect of volatility on spreads. Second, using a contingent claims model (CCM), the values of the implicit put options provided by QE as a backstop to investors are calculated to be substantial. Our results guide policymakers on the use of backstop facilities for sovereign bond markets.
    Keywords: Quantitative Easing, Sovereign risk, Sovereign spreads, Contingent Claims Model
    JEL: E52 E58 G12
    Date: 2022–02
  10. By: Castro, M.F.;; Guccio, C.;; Romeo, D.;
    Abstract: By employing a large sample of both laboratory and field data, we investigate whether attitudes towards risk significantly vary between physicians, medical students and non-medical students. Also, we look for differences in risk propensity between laboratory and artefactual field experimental sessions and control for individuals’ characteristics that may affect risk attitude. Results show significant variation in risk attitude, regardless of the estimation technique employed (linear regression, interval regression and maximum likelihood estimation), suggesting constant relative risk aversion (CRRA) as a supported representation of risk preferences. Finally, data consistently show that physicians are more risk-seeking in the monetary domain than other subject groups.
    Keywords: risk aversion; field experiments; laboratory experiment; physicians’ behaviour;
    JEL: I1 C81 C93 D81
    Date: 2022–09
  11. By: Couaillier, Cyril; Reghezza, Alessio; Rodriguez d’Acri, Costanza; Scopelliti, Alessandro
    Abstract: This paper investigates the impact of the capital relief package adopted to support euro area banks at the outbreak of the COVID-19 pandemic. By leveraging confidential supervisory and credit register data, we uncover two main findings. First, capital relief measures support banks' capacity to supply credit to firms. Second, not all measures are equally successful. Banks adjust their credit supply only if the capital relief is permanent or implemented through established processes that foresee long release periods. By contrast, discretionary relief measures are met with limited success, possibly owing to the uncertainty surrounding their capital replenishment path. Moreover, requirement releases are more effective for banks with a low capital headroom over requirements and do not trigger additional risk-taking. These findings provide key insights on how to design effective bank capital requirement releases in crisis time. JEL Classification: E61, G01, G18, G21
    Keywords: bank capital requirements, coronavirus, countercyclical policy, credit register, macroprudential policy
    Date: 2022–09
  12. By: Shen Yap (Universiti Tunku Abdul Rahman); Hui-Shan Lee (Universiti Tunku Abdul Rahman); Ping-Xin Liew (Universiti Tunku Abdul Rahman)
    Abstract: Motivated by the lack of a harmonised financial inclusion measure in the existing literature which accounts for the role of insurance, this paper constructs a multidimensional financial inclusion index which incorporates life and non-life insurance indicators for 79 countries for the year 2019. The computed financial inclusion indices reveal higher financial inclusion in high-income countries in Europe region vis-à-vis that of medium-income countries from the Asian and African regions. When only life insurance indicators are considered, some countries leapfrogged in their financial inclusion level whereas most of the developed and developing countries see a decline in their financial inclusion. On the other hand, non-life insurance appears to have only marginal positive impact on overall financial inclusiveness in the sample countries. The findings of this study indicate the lack of contribution of the insurance spectrum of financial services to financial inclusion.
    Keywords: Life Insurance, Non-Life Insurance, Financial Inclusion
    Date: 2022–07
  13. By: Jiong Liu; R. A. Serota
    Abstract: We approach the Generalized Beta (GB) family of distributions using a mean-reverting stochastic differential equation (SDE) for a power of the variable, whose steady-state (stationary) probability density function (PDF) is a modified GB (mGB) distribution. The SDE approach allows for a lucid explanation of Generalized Beta Prime (GB2) and Generalized Beta (GB1) limits of GB distribution and, further down, of Generalized Inverse Gamma (GIGa) and Generalized Gamma (GGa) limits, as well as describe the transition between the latter two. We provide an alternative form to the "traditional" GB PDF to underscore that a great deal of usefulness of GB distribution lies in its allowing a long-range power-law behavior to be ultimately terminated at a finite value. We derive the cumulative distribution function (CDF) of the "traditional" GB, which belongs to the family generated by the regularized beta function and is crucial for analysis of the tails of the distribution. We analyze fifty years of historical data on realized market volatility, specifically for S\&P500, as a case study of the use of GB/mGB distributions and show that its behavior is consistent with that of negative Dragon Kings.
    Date: 2022–09
  14. By: Ali Zeytoon-Nejad
    Abstract: The present paper introduces a theoretical framework through which the degree of risk aversion with respect to uncertain prices can be measured through the context of the indirect utility function (IUF) using a lab experiment. First, the paper introduces the main elements of the duality theory (DT) in economics. Next, it proposes the context of IUFs as a suitable framework for measuring price risk aversion through varying prices as opposed to varying payoffs, which has been common practice in the mainstream of experimental economics. Indeed, the DT in modern microeconomics indicates that the direct utility function (DUF) and the IUF are dual to each other, implicitly suggesting that the degree of risk aversion (or risk seeking) that a given rational subject exhibits in the context of the DUF must be equivalent to the degree of risk aversion (or risk seeking) elicited through the context of the IUF. This paper tests the accuracy of this theoretical prediction through a lab experiment using a series of relevant statistical tests. This study uses the multiple price list (MPL) method, which has been one of the most popular sets of elicitation procedures in experimental economics to study risk preferences in the experimental laboratory using non-interactive settings. The key findings of this study indicate that price risk aversion (PrRA) is statistically significantly greater than payoff risk aversion (PaRA). Additionally, it is shown that the risk preferences elicited under the expected utility theory (EUT) are somewhat subject to context. Other findings imply that the risk premium (RP), as a measure of willingness to pay for insuring an uncertain situation, is statistically significantly greater for stochastic prices compared to that for stochastic payoffs. These results are robust across different MPL designs and various statistical tests that are utilized.
    Date: 2022–09
  15. By: Claudia Custodio; Miguel A. Ferreira; Emilia Garcia-Appendini
    Abstract: We estimate the economic costs of financial distress due to lost sales, by exploiting cross-supplier variation in real estate assets and leverage and the timing of real estate shocks. We show that for the same client buying from different suppliers, its purchases from distressed suppliers decline by an additional 10% following a drop in real estate prices. The effect is more pronounced in more competitive industries, manufacturing, durable goods, less-specific goods, and when the costs of switching suppliers are low. Our results suggest that clients reduce their exposure to suppliers in financial distress.
    Keywords: Financial distress, Economic distress, Real estate prices, Supply chain
    JEL: G31 G32 G33 L11 L14
    Date: 2022

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