nep-rmg New Economics Papers
on Risk Management
Issue of 2019‒01‒14
eighteen papers chosen by
Stan Miles
Thompson Rivers University

  1. An optimization approach to adaptive multi-dimensional capital management By G. A. Delsing; M. R. H. Mandjes; P. J. C. Spreij; E. M. M. Winands
  2. Bank Leverage, Welfare, and Regulation By Anat R. Admati; Martin F. Hellwig
  3. The robust superreplication problem: a dynamic approach By Laurence Carassus; Jan Obloj; Johannes Wiesel
  4. CDS index options in Markov chain models By Herbetsson, Alexander
  5. How vulnerable is risk aversion to wealth, health and other risks? An empirical analysis for Europe By Christophe Courbage; Guillem Montoliu-Montes; Béatrice Rey
  6. Altruism and Risk Sharing in Networks By Renaud Bourlès; Yann Bramoullé; Eduardo Perez-Richet
  7. Dynamic return and volatility spillovers among S&P 500, crude oil and gold By Mehmet Balcilar; Zeynel Abidin Ozdemir; Huseyin Ozdemir
  8. Machine learning applied to accounting variables yields the risk-return metrics of private company portfolios* By Elias Cavalcante-Filho; Flavio Abdenur, Rodrigo De Losso
  9. Bayesian MCMC analysis of periodic asymmetric power GARCH models By Aknouche, Abdelhakim; Demmouche, Nacer; Touche, Nassim
  10. Efficient hedging under ambiguity in continuous time By Ludovic Tangpi
  11. Recovery rates in the Israeli corporate bond market 2008-2015 By Ana Sasi-Brodesky
  12. Modeling Time-Varying Uncertainty of Multiple-Horizon Forecast Errors By Clark, Todd E.; McCracken, Michael W.; Mertens, Elmar
  13. New testing approaches for mean-variance predictability By Gabriele Fiorentini; Enrique Sentana
  14. Conditional Dynamics and the Multi-Horizon Risk-Return Trade-Off By Mikhail Chernov; Lars A. Lochstoer; Stig R. H. Lundeby
  15. The Value of a Statistical Life Under Changes in Ambiguity By Han Bleichrodt; Christophe Courbage; Beatrice Rey
  16. Stochastic comparisons of the largest claim amounts from two sets of interdependent heterogeneous portfolios By Hossein Nadeb; Hamzeh Torabi; Ali Dolati
  17. Optimal execution with dynamic risk adjustment By Xue Cheng; Marina Di Giacinto; Tai-Ho Wang
  18. Conditional heteroskedasticity in crypto-asset returns By Shaw, Charles

  1. By: G. A. Delsing; M. R. H. Mandjes; P. J. C. Spreij; E. M. M. Winands
    Abstract: Firms should keep capital to offer sufficient protection against the risks they are facing. In the insurance context methods have been developed to determine the minimum capital level required, but less so in the context of firms with multiple business lines including allocation. The individual capital reserve of each line can be represented by means of classical models, such as the conventional Cram\'{e}r-Lundberg model, but the challenge lies in soundly modelling the correlations between the business lines. We propose a simple yet versatile approach that allows for dependence by introducing a common environmental factor. We present a novel Bayesian approach to calibrate the latent environmental state distribution based on observations concerning the claim processes. The calibration approach is adjusted for an environmental factor that changes over time. The convergence of the calibration procedure towards the true environmental state is deduced. We then point out how to determine the optimal initial capital of the different business lines under specific constraints on the ruin probability of subsets of business lines. Upon combining the above findings, we have developed an easy-to-implement approach to capital risk management in a multi-dimensional insurance risk model.
    Date: 2018–12
  2. By: Anat R. Admati (Graduate School of Business, Stanford University); Martin F. Hellwig (Max Planck Institute for Research on Collective Goods)
    Abstract: We take issue with claims that the funding mix of banks, which makes them fragile and crisis-prone, is efficient because it reflects special liquidity benefits of bank debt. Even aside from neglecting the systemic damage to the economy that banks’ distress and default cause, such claims are invalid because banks have multiple small creditors and are unable to commit effectively to their overall funding mix and investment strategy ex ante. The resulting market outcomes under laissez-faire are inefficient and involve excessive borrowing, with default risks that jeopardize the purported liquidity benefits. Contrary to claims in the literature that “equity is expensive” and that regulation requiring more equity in the funding mix entails costs to society, such regulation actually helps create useful commitment for banks to avoid the inefficiently high borrowing that comes under laissez-faire. Effective regulation is beneficial even without considering systemic risk; if such regulation also reduces systemic risk, the benefits are even larger.
    Keywords: Liquidity in banking, leverage in banking, banking regulation, capital structure, capital regulations, agency costs, commitment, contracting, maturity rat race, leverage ratchet effect, Basel
    JEL: D53 D61 G01 G18 G21 G24 G28 G32 G38 H81 K23
    Date: 2018–11
  3. By: Laurence Carassus; Jan Obloj; Johannes Wiesel
    Abstract: In the frictionless discrete time financial market of Bouchard et al.(2015) we consider a trader who, due to regulatory requirements or internal risk management reasons, is required to hedge a claim $\xi$ in a risk-conservative way relative to a family of probability measures $\mathcal{P}$. We first describe the evolution of $\pi_t(\xi)$ - the superhedging price at time $t$ of the liability $\xi$ at maturity $T$ - via a dynamic programming principle and show that $\pi_t(\xi)$ can be seen as a concave envelope of $\pi_{t+1}(\xi)$ evaluated at today's prices. Then we consider an optimal investment problem for a trader who is rolling over her robust superhedge and phrase this as a robust maximisation problem, where the expected utility of inter-temporal consumption is optimised subject to a robust superhedging constraint. This utility maximisation is carrried out under a new family of measures $\mathcal{P}^u$, which no longer have to capture regulatory or institutional risk views but rather represent trader's subjective views on market dynamics. Under suitable assumptions on the trader's utility functions, we show that optimal investment and consumption strategies exist and further specify when, and in what sense, these may be unique.
    Date: 2018–12
  4. By: Herbetsson, Alexander (Department of Economics, School of Business, Economics and Law, Göteborg University)
    Abstract: We study CDS index options in a credit risk model where the defaults times have intensities which are driven by a finite-state Markov chain representing the underlying economy. In this setting we derive compact computationally tractable formulas for the CDS index spread and the price of a CDS index option. In particular, the evaluation of the CDS index option is handled by translating the Cox-framework into a bivariate Markov chain. Due to the potentially very large, but extremely sparse matrices obtained in this reformulating, special treatment is needed to efficiently compute the matrix exponential arising from the Kolmogorov Equation. We provide details of these computational methods as well as numerical results. The finite-state Markov chain model is calibrated to data with perfect fits, and several numerical studies are performed. In particular we show that under same exogenous circumstances, the CDS index options prices in the Markov chain framework can be close to or sometimes larger than prices in models which assume that the CDS index spreads follows a log-normal process. We also study the different default risk components in the option prices generated by the Markov model, an investigation which is difficult to do in models where the CDS index spreads follows a log-normal process.
    Keywords: Credit risk; CDS index; CDS index options; intensity-based models; dependence modelling; Markov chains; matrix-analytical methods; numerical methods
    JEL: C02 C63 G13 G32 G33
    Date: 2019–01–07
  5. By: Christophe Courbage (Geneva School of Business Administration - University of Applied Sciences Western Switzerland); Guillem Montoliu-Montes (UNIL - Université de Lausanne); Béatrice Rey (GATE Lyon Saint-Étienne - Groupe d'analyse et de théorie économique - ENS Lyon - École normale supérieure - Lyon - UL2 - Université Lumière - Lyon 2 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UJM - Université Jean Monnet [Saint-Étienne] - Université de Lyon - CNRS - Centre National de la Recherche Scientifique)
    Abstract: This paper empirically assesses how financial risk aversion reacts to a change in individuals' wealth and health and to the presence of both financial and health risks using the Survey of Health, Ageing, and Retirement in Europe (SHARE). Individuals in our sample exhibit financial risk aversion decreasing both in wealth and health. Financial risk aversion is also found to increase in the presence of a background financial risk and a background health risk. Interestingly, risk aversion is shown to be convex in wealth but linear in health. Such findings complement the literature on risk aversion behaviours and can help to better understand various economic decisions in a risky environment.
    Keywords: risk aversion,(cross-) DARA,(cross-) risk vulnerability,background risk,health risk
    Date: 2018
  6. By: Renaud Bourlès (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - Ecole Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique); Yann Bramoullé (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - Ecole Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique); Eduardo Perez-Richet (IEP Paris - Sciences Po Paris - Institut d'études politiques de Paris, CEPR)
    Abstract: We provide the first analysis of the risk-sharing implications of altruism networks. Agents are embedded in a fixed network and care about each other. We study whether altruistic transfers help smooth consumption and how this depends on the shape of the network. We identify two benchmarks where altruism networks generate efficient insurance: for any shock when the network of perfect altruism is strongly connected and for any small shock when the network of transfers is weakly connected. We show that the extent of informal insurance depends on the average path length of the altruism network and that small shocks are partially insured by endogenous risk-sharing communities. We uncover complex structural effects. Under iid incomes, central agents tend to be better insured, the consumption correlation between two agents is positive and tends to decrease with network distance, and a new link can decrease or increase the consumption variance of indirect neighbors. Overall, we show that altruism in networks has a first-order impact on risk and generates specific patterns of consumption smoothing.
    Keywords: altruism,networks,risk sharing,informal insurance
    Date: 2018–11
  7. By: Mehmet Balcilar (Department of Economics, Eastern Mediterranean University); Zeynel Abidin Ozdemir (Gazi University, Ankara, Turkey); Huseyin Ozdemir (Gazi University, Ankara, Turkey)
    Abstract: This paper examines the return and volatility spillover effects among S&P 500, crude oil and gold by employing the spillover index of Diebold and Yilmaz (2012). Monthly realized volatility and return series covering the period from January 1986 to August 2018 are used to examine the return and volatility spillovers. Our findings indicate a bi-directional return and volatility spillover among these assets. The full sample empirical evidence is consistent with the structure in which oil plays a central role in the information transmission mechanism. The role of oil and gold as a safe haven has changed over time in financial and non-financial economic turbulence time-span. Commodity market financialization has decreased the effectiveness of adding commodities to portfolios after 2002.
    Keywords: S&P 500 index; Oil price; Gold Price; Return spillover; Volatility spillover
    JEL: C13 C53 C58 G10 G12 G14 Q43
    Date: 2018
  8. By: Elias Cavalcante-Filho; Flavio Abdenur, Rodrigo De Losso
    Abstract: Constructing optimal Markowitz Mean-Variance portfolios of publicly-traded stock is a straighforward and well-known task. Doing the same for portfolios of privately-owned firms, given the lack of historical price data, is a challenge. We apply machine learning models to historical accounting variable data to estimate risk-return metrics – specifically, expected excess returns, price volatility and (pairwise) price correlation – of private companies, which should allow the construction of Mean-Variance optimized portfolios consisting of private companies. We attain out-of-sample 𠑅2 s around 45%, while linear regressions yield 𠑅2 s of only about 10%. This short paper is the result of a real-world consulting project on behalf of Votorantim S.A (“VSA†), a multinational holding company. To the authors’ best knowledge this is a novel application of machine learning in the finance literature.
    Keywords: assent pricing; Machine Learning; Portfolio Theory
    JEL: G12 G17
    Date: 2018–12–20
  9. By: Aknouche, Abdelhakim; Demmouche, Nacer; Touche, Nassim
    Abstract: A Bayesian MCMC estimate of a periodic asymmetric power GARCH (PAP-GARCH) model whose coefficients, power, and innovation distribution are periodic over time is proposed. The properties of the PAP-GARCH model such as periodic ergodicity, finiteness of moments and tail behaviors of the marginal distributions are first examined. Then, a Bayesian MCMC estimate based on Griddy-Gibbs sampling is proposed when the distribution of the innovation of the model is standard Gaussian or standardized Student with a periodic degree of freedom. Selecting the orders and the period of the PAP-GARCH model is carried out via the Deviance Information Criterion (DIC). The performance of the proposed Griddy-Gibbs estimate is evaluated through simulated and real data. In particular, applications to Bayesian volatility forecasting and Value-at-Risk estimation for daily returns on the S&P500 index are considered.
    Keywords: Periodic Asymmetric Power GARCH model, probability properties, Griddy-Gibbs estimate, Deviance Information Criterion, Bayesian forecasting, Value at Risk.
    JEL: C11 C15 C58
    Date: 2018–05–11
  10. By: Ludovic Tangpi
    Abstract: It is well known that the minimal superhedging price of a contingent claim is too high for practical use. In a continuous-time model uncertainty framework, we consider a relaxed hedging criterion based on acceptable shortfall risks. Combining existing aggregation and convex dual representation theorems, we derive duality results for the minimal price on the set of upper semicontinuous discounted claims.
    Date: 2018–12
  11. By: Ana Sasi-Brodesky (Bank of Israel)
    Abstract: This paper examines default events in Israel's corporate bond market between 2008 and 2015. Using a sample of 106 distress events, the variation in expected recovery rates over time is analyzed. The value of distressed firms at the time of default was found to be mostly influenced by the financial conditions of peers in the industry and in the market. In particular, low liquidity and high average leverage ratios of other market participants had a negative effect on the anticipated recovery rate. Firm-specific characteristics were found to have negligible effect on expected recovery rates. Average recovery and default rates are shown to compare well with the experience in other countries.
    Keywords: recovery rates, default, bond market, Israel, market price
    JEL: G33
    Date: 2017–07
  12. By: Clark, Todd E. (Federal Reserve Bank of Cleveland); McCracken, Michael W. (Federal Reserve Bank of St. Louis); Mertens, Elmar (Bank for International Settlements)
    Abstract: We estimate uncertainty measures for point forecasts obtained from survey data, pooling information embedded in observed forecast errors for different forecast horizons. To track time-varying uncertainty in the associated forecast errors, we derive a multiple-horizon specification of stochastic volatility. We apply our method to forecasts for various macroeconomic variables from the Survey of Professional Forecasters. Compared to constant variance approaches, our stochastic volatility model improves the accuracy of uncertainty measures for survey forecasts. Our method can also be applied to other surveys like the Blue Chip Consensus, or the Federal Open Market Committee’s Summary of Economic Projections.
    Keywords: Stochastic volatility; survey forecasts; fan charts;
    JEL: C53 E37
    Date: 2017–09–01
  13. By: Gabriele Fiorentini (Università di Firenze, Italy; Rimini Centre for Economic Analysis); Enrique Sentana (CEMFI, Spain)
    Abstract: We propose tests for smooth but persistent serial correlation in risk premia and volatilities that exploit the non-normality of financial returns. Our parametric tests are robust to distributional misspecification, while our semiparametric tests are as powerful as if we knew the true return distribution. Local power analyses confirm their gains over existing methods, while Monte Carlo exercises assess their finite sample reliability. We apply our tests to quarterly returns on the five Fama-French factors for international stocks, whose distributions are mostly symmetric and fat-tailed. Our results highlight noticeable differences across regions and factors and confirm the fragility of Gaussian tests.
    Keywords: financial forecasting, moment tests, misspecification, robustness, volatility
    JEL: C12 C22 G17
    Date: 2019–01
  14. By: Mikhail Chernov; Lars A. Lochstoer; Stig R. H. Lundeby
    Abstract: We propose testing asset-pricing models using multi-horizon returns (MHR). MHR serve as powerful source of conditional information that is economically important and not data-mined. We apply MHR-based testing to linear factor models. These models seek to construct the unconditionally mean-variance efficient portfolio. We reject all state-of-the-art models that imply high maximum Sharpe ratios in a single-horizon setting. Thus, the models do a poor job in accounting for the risk-return trade-off at longer horizons. Across the different models, the mean absolute pricing errors associated with MHR are positively related to the magnitude of maximal Sharpe ratio in the single-horizon setting. Model misspecification manifests itself in strong intertemporal dynamics of the factor loadings in the SDF representation. We suggest that misspecification of the dynamics of loadings arises from the common approach towards factor construction via portfolio sorts.
    JEL: C51 G12
    Date: 2018–12
  15. By: Han Bleichrodt (Erasmus School of Economics - Erasmus University Rotterdam, ANU - Australian National University); Christophe Courbage (HES-SO - University of Applied Sciences and Arts Northwestern Switzerland); Beatrice Rey (GATE Lyon Saint-Étienne - Groupe d'analyse et de théorie économique - ENS Lyon - École normale supérieure - Lyon - UL2 - Université Lumière - Lyon 2 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UJM - Université Jean Monnet [Saint-Étienne] - Université de Lyon - CNRS - Centre National de la Recherche Scientifique)
    Abstract: The value of a statistical life (VSL) is a key parameter in the analysis of government policy. Most policy decisions are made under ambiguity. This paper studies the effect of changes in ambiguity perception on the value of a statistical life (VSL). We propose a definition of increases in ambiguity perception based on Ekern's (1980) definition of increases in risk. Ambiguity aversion alone is not sufficient to lead to an increase in the VSL when the decision maker perceives more ambiguity. Our results highlight the importance of higher order ambiguity attitudes, particularly ambiguity prudence.
    Keywords: neoadditive preferences,Value of a statistical life,ambiguity,prudence,smooth ambiguity model
    Date: 2018
  16. By: Hossein Nadeb; Hamzeh Torabi; Ali Dolati
    Abstract: Let $ X_{\lambda_1},\ldots,X_{\lambda_n}$ be dependent non-negative random variables and $Y_i=I_{p_i} X_{\lambda_i}$, $i=1,\ldots,n$, where $I_{p_1},\ldots,I_{p_n}$ are independent Bernoulli random variables independent of $X_{\lambda_i}$'s, with ${\rm E}[I_{p_i}]=p_i$, $i=1,\ldots,n$. In actuarial sciences, $Y_i$ corresponds to the claim amount in a portfolio of risks. In this paper, we compare the largest claim amounts of two sets of interdependent portfolios, in the sense of usual stochastic order, when the variables in one set have the parameters $\lambda_1,\ldots,\lambda_n$ and $p_1,\ldots,p_n$ and the variables in the other set have the parameters $\lambda^{*}_1,\ldots,\lambda^{*}_n$ and $p^*_1,\ldots,p^*_n$. For illustration, we apply the results to some important models in actuary.
    Date: 2018–12
  17. By: Xue Cheng; Marina Di Giacinto; Tai-Ho Wang
    Abstract: This paper considers the problem of optimal liquidation of a position in a risky security in a financial market, where price evolution are risky and trades have an impact on price as well as uncertainty in the filling orders. The problem is formulated as a continuous time stochastic optimal control problem aiming at maximizing a generalized risk-adjusted profit and loss function. The expression of the risk adjustment is derived from the general theory of dynamic risk measures and is selected in the class of g-conditional risk measures. The resulting theoretical framework is nonclassical since the target function depends on backward components. We show that, under a quadratic specification of the driver of a backward stochastic differential equation, it is possible to find a closed form solution and an explicit expression of the optimal liquidation policies. In this way it is immediate to quantify the impact of risk-adjustment on the profit and loss and on the expression of the optimal liquidation policies.
    Date: 2019–01
  18. By: Shaw, Charles
    Abstract: In a recent contribution to the financial econometrics literature, Chu et al. (2017) provide the first examination of the time-series price behaviour of the most popular cryptocurrencies. However, insufficient attention was paid to correctly diagnosing the distribution of GARCH innovations. When these data issues are controlled for, their results lack robustness and may lead to either underestimation or overestimation of future risks. The main aim of this paper therefore is to provide an improved econometric specification. Particular attention is paid to correctly diagnosing the distribution of GARCH innovations by means of Kolmogorov type non-parametric tests and Khmaladze's martingale transformation. Numerical computation is carried out by implementing a Gauss-Kronrod quadrature. Parameters of GARCH models are estimated using maximum likelihood. For calculating P-values, the parametric bootstrap method is used. Further reference is made to the merits and demerits of statistical techniques presented in the related and recently published literature.
    Keywords: Autoregressive conditional heteroskedasticity (ARCH), generalized autoregressive conditional heteroskedasticity (GARCH), market volatility, nonlinear time series, Khmaladze transform.
    JEL: C22 C58
    Date: 2018–11–01

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