nep-rmg New Economics Papers
on Risk Management
Issue of 2021‒08‒30
seventeen papers chosen by
Stan Miles
Thompson Rivers University

  1. Macroeconomic and Financial Risks: A Tale of Mean and Volatility By Dario Caldara; Chiara Scotti; Molin Zhong
  2. Foundations of system-wide financial stress testing with heterogeneous institutions By Farmer, J. Doyne; Kleinnijenhuis, Alissa; Nahai-Williamson, Paul; Wetzer, Thom
  3. Minimizing ruin probability under dependencies for insurance pricing By Ragnar Levy Gudmundarson; Manuel Guerra; Alexandra Bugalho de Moura
  4. What’s past is prologue? The effect of prior losses on agricultural risk management By Bryan, Calvin; Manning, Dale; Goemans, Christopher; Sloggy, Matthew R.
  5. Reaching for yield or resiliency? Explaining the shift in Canadian pension plan portfolios By Sébastien Betermier; Nicholas Byrne; Jean-Sébastien Fontaine; Hayden Ford; Jason Ho; Chelsea Mitchell
  6. From bid-ask credit default swap quotes to risk-neutral default probabilities using distorted expectations By Matteo Michielon; Asma Khedher; Peter Spreij
  7. How to Assess Country Risk: The Vulnerability Exercise Approach Using Machine Learning By International Monetary Fund
  8. Robust Risk-Aware Reinforcement Learning By Sebastian Jaimungal; Silvana Pesenti; Ye Sheng Wang; Hariom Tatsat
  9. The Pandemic's Impact on Credit Risk: Averted or Delayed? By SungJe Byun; Aaron L. Game; Alexander Jiron; Pavel Kapinos; Kelly Klemme; Bert Loudis
  10. Sharing Asymmetric Tail Risk: Smoothing, Asset Prices and Terms of Trade By Giancarlo Corsetti; Anna Lipinska; Giovanni Lombardo
  11. Do bankruptcy protection levels affect households’ demand for stocks? By Dal Borgo, Mariela
  12. Use of the bayesmh command in Stata to calculate excess relative and excess absolute risk for radiation health risk estimates By Lori Chappell
  13. The RQE-CAPM : New insights about the pricing of idiosyncratic risk By Benoît Carmichael; Gilles Boevi Koumou; Kevin Moran
  14. Public Debt Bubbles in Heterogeneous Agent Models with Tail Risk By Narayana R. Kocherlakota
  15. The Risk Premia of Energy Futures By Adrian Fernandez-Perez; Ana-Maria Fuertes; Joelle Miffre
  16. dstat: A new command for the analysis of distributions By Ben Jann
  17. Adaptive Gradient Descent Methods for Computing Implied Volatility By Yixiao Lu; Yihong Wang; Tinggan Yang

  1. By: Dario Caldara; Chiara Scotti; Molin Zhong
    Abstract: We study the joint conditional distribution of GDP growth and corporate credit spreads using a stochastic volatility VAR. Our estimates display significant cyclical co-movement in uncertainty (the volatility implied by the conditional distributions), and risk (the probability of tail events) between the two variables. We also find that the interaction between two shocks--a main business cycle shock as in Angeletos et al. (2020) and a main financial shock--is crucial to account for the variation in uncertainty and risk, especially around crises. Our results highlight the importance of using multivariate nonlinear models to understand the determinants of uncertainty and risk.
    Keywords: Uncertainty; Tail risk; Joint conditional distributions; Main shocks
    JEL: C53 E23 E32 E44
    Date: 2021–08–19
  2. By: Farmer, J. Doyne; Kleinnijenhuis, Alissa; Nahai-Williamson, Paul; Wetzer, Thom
    Abstract: We propose a structural framework for the development of system-wide financial stress tests with multiple interacting contagion, amplification channels and heterogeneous financial institutions. This framework conceptualises financial systems through the lens of five building blocks: financial institutions, contracts, markets, constraints, and behaviour. Using this framework, we implement a system-wide stress test for the European financial system. We obtain three key findings. First, the financial system may be stable or unstable for a given microprudential stress test outcome, depending on the system's shock-amplifying tendency. Second, the 'usability' of banks' capital buffers (the willingness of banks to use buffers to absorb losses) is of great consequence to systemic resilience. Third, there is a risk that the size of capital buffers needed to limit systemic risk could be severely underestimated if calibrated in the absence of system-wide approaches.
    Keywords: Systemic risk, stress testing, financial contagion, financial institutions, capital requirements, macroprudential policy
    JEL: G17 G21 G23 G28 C63
    Date: 2020–05
  3. By: Ragnar Levy Gudmundarson; Manuel Guerra; Alexandra Bugalho de Moura
    Abstract: In this work the ruin probability of the Lundberg risk process is used as a criterion for determining the optimal security loading of premia in the presence of price-sensitive demand for insurance. Both single and aggregated claim processes are considered and the independent and the dependent cases are analyzed. For the single-risk case, we show that the optimal loading does not depend on the initial reserve. In the multiple risk case we account for arbitrary dependency structures between different risks and for dependencies between the probabilities of a client acquiring policies for different risks. In this case, the optimal loadings depend on the initial reserve. In all cases the loadings minimizing the ruin probability do not coincide with the loadings maximizing the expected profit.
    Date: 2021–08
  4. By: Bryan, Calvin; Manning, Dale; Goemans, Christopher; Sloggy, Matthew R.
    Keywords: Agricultural and Food Policy, Institutional and Behavioral Economics, Risk and Uncertainty
    Date: 2021–08
  5. By: Sébastien Betermier; Nicholas Byrne; Jean-Sébastien Fontaine; Hayden Ford; Jason Ho; Chelsea Mitchell
    Abstract: “Reach for yield”—This is the commonly heard explanation for why pension plans shift their portfolios toward alternative assets. But we show that the new portfolios also hold more bonds, offer lower average returns and produce smaller and less volatile solvency deficits. These shifts are part of a broader strategy to reduce solvency risk.
    Keywords: Financial institutions; Financial markets; Financial system regulation and policies
    JEL: G11
    Date: 2021–08
  6. By: Matteo Michielon; Asma Khedher; Peter Spreij
    Abstract: Risk-neutral default probabilities can be implied from credit default swap (CDS) market quotes. In practice, mid CDS quotes are used as inputs, as their risk-neutral counterparts are not observable. We show how to imply risk-neutral default probabilities from bid and ask quotes directly by means of formulating the CDS calibration problem to bid and ask market quotes within the conic finance framework. Assuming the risk-neutral distribution of the default time to be driven by a Poisson process we prove, under mild liquidity-related assumptions, that the calibration problem admits a unique solution that also allows to jointly calculate the implied liquidity of the market.
    Date: 2021–08
  7. By: International Monetary Fund
    Abstract: The IMF’s Vulnerability Exercise (VE) is a cross-country exercise that identifies country-specific near-term macroeconomic risks. As a key element of the Fund’s broader risk architecture, the VE is a bottom-up, multi-sectoral approach to risk assessments for all IMF member countries. The VE modeling toolkit is regularly updated in response to global economic developments and the latest modeling innovations. The new generation of VE models presented here leverages machine-learning algorithms. The models can better capture interactions between different parts of the economy and non-linear relationships that are not well measured in ”normal times.” The performance of machine-learning-based models is evaluated against more conventional models in a horse-race format. The paper also presents direct, transparent methods for communicating model results.
    Keywords: Risk Assessment, Supervised Machine Learning, Prediction, Sudden Stop, Exchange Market Pressure, Fiscal Crisis, Debt, Financial Crisis, Economic Crisis, Economic Growth
    Date: 2021–05–07
  8. By: Sebastian Jaimungal; Silvana Pesenti; Ye Sheng Wang; Hariom Tatsat
    Abstract: We present a reinforcement learning (RL) approach for robust optimisation of risk-aware performance criteria. To allow agents to express a wide variety of risk-reward profiles, we assess the value of a policy using rank dependent expected utility (RDEU). RDEU allows the agent to seek gains, while simultaneously protecting themselves against downside events. To robustify optimal policies against model uncertainty, we assess a policy not by its distribution, but rather, by the worst possible distribution that lies within a Wasserstein ball around it. Thus, our problem formulation may be viewed as an actor choosing a policy (the outer problem), and the adversary then acting to worsen the performance of that strategy (the inner problem). We develop explicit policy gradient formulae for the inner and outer problems, and show its efficacy on three prototypical financial problems: robust portfolio allocation, optimising a benchmark, and statistical arbitrage
    Date: 2021–08
  9. By: SungJe Byun; Aaron L. Game; Alexander Jiron; Pavel Kapinos; Kelly Klemme; Bert Loudis
    Abstract: The COVID-19 recession resulted in historic unemployment and a significant shock to much of the service sector. Despite these macroeconomic challenges, banks' risk-based capital buffers remain high and the number of bank failures remains low. Government relief programs, including the Coronavirus Aid, Relief, and Economic Security (CARES) Act, both directly and indirectly helped stabilize bank balance sheets during the crisis.
    Date: 2021–07–30
  10. By: Giancarlo Corsetti; Anna Lipinska; Giovanni Lombardo
    Abstract: Crises and tail events have asymmetric effects across borders, raising the value of arrangements improving insurance of macroeconomic risk. Using a two-country DSGE model, we provide an analytical and quantitative analysis of the channels through which countries gain from sharing (tail) risk. Riskier countries gain in smoother consumption but lose in relative wealth and average consumption. Safer countries benefit from higher wealth and better average terms of trade. Calibrated using the empirical distribution of moments of GDP-growth across countries, the model suggests non-negligible quantitative effects. We offer an algorithm for the correct solution of the equilibrium using DSGE models under complete markets, at higher order of approximation.
    Keywords: International risk sharing; Asymmetry; Fat tails; Welfare
    JEL: F15 F41 G15
    Date: 2021–08–06
  11. By: Dal Borgo, Mariela (Bank of Mexico)
    Abstract: This paper examines empirically the effect of the level of personal bankruptcy protection in the US on households’ demand for financial assets. A Chapter 7 bankruptcy allows protecting the home equity up to a certain limit or "exemption". Previous literature shows that such exemption biases investment towards home equity. This paper tests whether it also lowers investment in stocks, which are not protected in bankruptcy. Using an instrumental variable approach, I estimate a lower stock market participation when the home equity is below the exemption, but the result is not robust, and households at higher risk of bankruptcy do not exhibit a stronger response. Moreover, investment in home equity is not higher when the home is fully protected. These findings suggest no substantial portfolio distortions from the level of home equity that is protected in bankruptcy.
    Keywords: Personal bankruptcy law; Home equity protection; Stock market participation; Portfolio allocation JEL Classification: D14; G00; G11; K35
    Date: 2021
  12. By: Lori Chappell (KBR)
    Abstract: Excess relative risk (ERR) and excess absolute risk (EAR) are important metrics typically used in radiation epidemiology studies. Most studies of long-term radiation effects in Japanese atomic bomb survivors feature Poisson regression of grouped survival data. Risks are modeled on the excess risk scale using linear and log-linear functions of regression parameters, which are generally formulated to produce both ERR and EAR as output. Given the specific assumptions underlying these models, they are dubbed ERR and EAR models, respectively. Typically, these models are fit using the Epicure software that was specifically designed to fit these models, and they are difficult to reproduce in more accessible software. The flexibility of the bayesmh command can be utilized to fit these models within a Bayesian framework, which may increase accessibility in the broader statistical and epidemiological communities. In this presentation, I detail ERR and EAR model fitting and assumptions, and I give an example of how the models can be fit in Stata using Bayesian methods.
    Date: 2021–08–07
  13. By: Benoît Carmichael; Gilles Boevi Koumou; Kevin Moran
    Abstract: We use an equivalent form of Markowitz's mean-variance utility function, based on Rao's Quadratic Entropy (RQE), to enrich the standard capital asset pricing model (CAPM), both in the presence and in the absence of a risk-free asset. The resulting equilibrium, which we denote RQE-CAPM, offers important new insights about the pricing of risk. Notably, it reveals that the reason for which the standard CAPM does not price idiosyncratic risk is not only because the market portfolio is law of large numbers diversifed but also because the model implicitly assumes agents' total risk aversion and their correlation diversifcation risk preference balance each other exactly. We then demonstrate that idiosyncratic risk is priced in a general RQE-CAPM where agents' total risk aversion and their correlation diversifcation risk preference coeffcients are not necessary equal. Our general RQE-CAPM therefore offers a unifying way of thinking about the pricing of idiosyncratic risk, including cases where such risk is negatively priced, and is relevant for the literature assessing the idiosyncratic risk puzzle. It also provides a natural theoretical underpinning for the empirical tests of the CAPM or the pricing of idiosyncratic risk performed in some existence studies. Nous utilisons une forme équivalente de la fonction d'utilité moyenne-variance de Markowitz, basée sur l'entropie quadratique de Rao (RQE), pour enrichir le modèle standard d'évaluation des actifs financiers (CAPM), à la fois en présence et en l'absence d'un actif sans risque. L'équilibre qui en résulte, que nous désignons par RQE-CAPM, offre de nouvelles perspectives importantes sur l'évaluation du risque. Il révèle notamment que la raison pour laquelle le CAPM standard n'évalue pas le risque idiosyncratique n'est pas seulement due au fait que le portefeuille du marché est diversifié par la loi des grands nombres, mais aussi au fait que le modèle suppose implicitement que l'aversion totale au risque des agents et leur préférence pour le risque de diversification de la corrélation s'équilibrent exactement. Nous démontrons ensuite que le risque idiosyncratique est évalué dans un RQE-CAPM général où l'aversion totale au risque des agents et leurs coefficients de préférence pour le risque de diversification de la corrélation ne sont pas nécessairement égaux. Notre modèle RQE-CAPM général offre donc une façon unifiée de penser à la tarification du risque idiosyncratique, y compris les cas où ce risque est évalué négativement, et est pertinent pour la littérature évaluant l'énigme du risque idiosyncratique. Il fournit également une base théorique naturelle pour les tests empiriques du MEDAF ou de la tarification du risque idiosyncratique effectués dans certaines études d'existence.
    Keywords: Rao's Quadratic Entropy,Mean-Variance Model,Capital Asset Pricing Model,Idiosyncratic Risk,Correlation Diversiffcation, Entropie quadratique de Rao,modèle moyenne-variance,modèle d'évaluation des actifs financiers,risque idiosyncratique,corrélation et diversification
    JEL: G11 G12
    Date: 2021–08–23
  14. By: Narayana R. Kocherlakota
    Abstract: This paper studies the public debt implications of a class of Aiyagari (1994)-Bewley (1977)-Huggett (1993) (ABH) models of incomplete insurance in which agents face a near-zero probability of a highly adverse outcome. In generic models of this kind, there exists a public debt bubble, so that the government is able to borrow at a real interest rate that is perpetually below the economic growth rate. Given an equilibrium with a public debt bubble, the primary deficit and the level of debt are both strictly increasing in the real interest rate and in the fraction of government expenditures used for lumpsum transfers. There is no upper bound on the deficit level or long-run debt level that is sustainable in equilibrium. In a public debt bubble, regardless of its size, agents are better off in the long run if the government chooses policies that give rise to a larger debt and primary deficit.
    JEL: E62 H62 H63
    Date: 2021–08
  15. By: Adrian Fernandez-Perez (AUT - Auckland University of Technology); Ana-Maria Fuertes (Sir John Cass Business School); Joelle Miffre (Audencia Business School)
    Abstract: This paper studies the energy futures risk premia that can be extracted through long-short portfolios that exploit heterogeneities across contracts as regards various characteristics or signals and integrations thereof. Investors can earn a sizeable premium of about 8% and 12% per annum by exploiting the energy futures contract risk associated with the hedgers' net positions and roll-yield characteristics, respectively, in line with predictions from the hedging pressure hypothesis and theory of storage. Simultaneously exploiting various signals towards style-integration with alternative weighting schemes further enhances the premium. In particular, the style-integrated portfolio that equally weights all signals stands out as the most effective. The findings are robust to transaction costs, data mining and sub-period analyses.
    Keywords: Integration,Long-short portfolios,Risk premium,Energy futures markets
    Date: 2021–10–01
  16. By: Ben Jann (University of Bern)
    Abstract: In this talk, I will present a new Stata command that unites a variety of methods to describe (univariate) statistical distributions. Covered are density estimation, histograms, cumulative distribution functions, probability distributions, quantile functions, Lorenz curves, percentile shares, and a large collection of summary statistics, such as classical and robust measures of location, scale, skewness, and kurtosis, as well as inequality, concentration, and poverty measures. Particular features of the command are that it provides consistent standard errors supporting complex sample designs for all covered statistics and that the simultaneous analysis of multiple statistics across multiple variables and subpopulations is possible. Furthermore, the command supports covariate balancing based on reweighting techniques (inverse probability weighting and entropy balancing), including appropriate correction of standard errors. Standard-error estimation is implemented in terms of influence functions, which can be stored for further analysis, for example, in RIF regressions or counterfactual decompositions.
    Date: 2021–08–07
  17. By: Yixiao Lu; Yihong Wang; Tinggan Yang
    Abstract: In this paper, a new numerical method based on adaptive gradient descent optimizers is provided for computing the implied volatility from the Black-Scholes (B-S) option pricing model. It is shown that the new method is more accurate than the close form approximation. Compared with the Newton-Raphson method, the new method obtains a reliable rate of convergence and tends to be less sensitive to the beginning point.
    Date: 2021–08

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