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on Risk Management |
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Issue of 2021‒09‒20
twelve papers chosen by |
| By: | Michal Franta; Jan Libich |
| Abstract: | We put forward a novel macro-financial empirical modelling framework that can examine the tails of distributions of macroeconomic variables and the implied risks. It does so without quantile regression, also allowing for non-normal distributions. Besides methodological innovations, the framework offers a number of relevant insights into the effects of monetary and macroprudential policy on downside macroeconomic risk. This is both from the short-run perspective and from the long-run perspective, which has been remained unexamined in the existing Macro-at-Risk literature. In particular, we estimate the conditional and unconditional US output growth distribution and investigate the evolution of its first four moments. The short-run analysis finds that monetary policy and financial shocks render the conditional output growth distribution asymmetric, and affect downside risk over and above their impact on the conditional mean that policymakers routinely focus on. The long-run analysis indicates, among other things, that US output growth left-tail risk showed a general downward trend in the two decades preceding the Global Financial Crisis, but has started rising in recent years. Our examination strongly points to post-2008 unconventional monetary policies (quantitative easing) as a potential source of elevated long-run downside tail risk. |
| Keywords: | Downside tail risk, growth-at-risk, macroeconomic policy, macro-financial modeling, non-normal distribution, threshold VAR, US output growth |
| JEL: | C53 C54 E32 |
| Date: | 2021–09 |
| URL: | http://d.repec.org/n?u=RePEc:cnb:wpaper:2021/3&r= |
| By: | Jiamin Yu |
| Abstract: | It has been for a long time to use big data of autonomous vehicles for perception, prediction, planning, and control of driving. Naturally, it is increasingly questioned why not using this big data for risk management and actuarial modeling. This article examines the emerging technical difficulties, new ideas, and methods of risk modeling under autonomous driving scenarios. Compared with the traditional risk model, the novel model is more consistent with the real road traffic and driving safety performance. More importantly, it provides technical feasibility for realizing risk assessment and car insurance pricing under a computer simulation environment. |
| Date: | 2021–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2109.07211&r= |
| By: | María T. González-Pérez (Banco de España) |
| Abstract: | This paper estimates the volatility index term structure for the Spanish bank industry (SBVX) using the implied volatility of individual banks and assuming market correlation risk premium. This methodology enables calculating a volatility index for arbitrary (non-traded) portfolios. Using data from 2015 to 2021, we find that SBVX informs about the dynamics of bank returns beyond the standard market volatility index VIBEX, especially when bank returns are negative; and that one-year SBVX beats shorter maturities in explaining bank returns. On the other hand, positive bank returns relate to the dynamics of VIBEX just as much as SBVX, which aligns with the belief that a drop in global volatility (uncertainty) positively affects firm performance and, therefore, bank value projections. We find one-month SBVX better than VIBEX to forecast monthly bank returns volatility, regardless of the tenor we use to compute VIBEX. This paper provides empirical evidence that idiosyncratic implied volatility is just as significant, or even more than global volatility, to monitor current and future banks’ share price performance. We advise using SBVX term structure, short-term VIBEX, and market correlation risk premium to monitor uncertainty and returns in the banking sector and foresee periods of stress in this industry. Our results may be of great interest to those seeking to estimate the banking sector’s sensitivity to uncertainty, volatility, and risk. |
| Keywords: | volatility term-structure, implied volatility, risk |
| JEL: | G53 G1 |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:bde:wpaper:2128&r= |
| By: | Cyril Bénézet (LaMME - Laboratoire de Mathématiques et Modélisation d'Evry - UEVE - Université d'Évry-Val-d'Essonne - ENSIIE - Université Paris-Saclay - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Emmanuel Gobet (CMAP - Centre de Mathématiques Appliquées - Ecole Polytechnique - X - École polytechnique - CNRS - Centre National de la Recherche Scientifique); Rodrigo Targino (FGV/EMAp - Fundação Getulio Vargas - Escola de Matemática Aplicada [Rio de Janeiro]) |
| Abstract: | In financial risk management, modelling dependency within a random vector X is crucial, a standard approach is the use of a copula model. Say the copula model can be sampled through realizations of Y having copula function C: had the marginals of Y been known, sampling X^(i) , the i-th component of X, would directly follow by composing Y^(i) with its cumulative distribution function (c.d.f.) and the inverse c.d.f. of X^(i). In this work, the marginals of Y are not explicit, as in a factor copula model. We design an algorithm which samples X through an empirical approximation of the c.d.f. of the Y marginals. To be able to handle complex distributions for Y or rare-event computations, we allow Markov Chain Monte Carlo (MCMC) samplers. We establish convergence results whose rates depend on the tails of X, Y and the Lyapunov function of the MCMC sampler. We present numerical experiments confirming the convergence rates and also revisit a real data analysis from financial risk management. |
| Keywords: | Copula models,Markov chain Monte Carlo MCMC methods,sampling |
| Date: | 2021–09–03 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-03334526&r= |
| By: | Mohammed Abdellaoui (GREGHEC, HEC Paris - Ecole des Hautes Etudes Commerciales, CNRS - Centre National de la Recherche Scientifique); Enrico Diecidue (Insead - INSEAD - INSEAD); Emmanuel Kemel (GREGHEC, HEC Paris - Ecole des Hautes Etudes Commerciales, CNRS - Centre National de la Recherche Scientifique); Ayse Onculer (ESSEC Business School - Essec Business School) |
| Abstract: | This paper reports two experiments in which attitudes towards temporal risk resolution is elicited from choices between two-outcome lotteries that pay out at some future fixed date and can be resolved either now or later. We show that matching probabilities provides a simple method to measure attitudes towards temporal resolution-via the utility scaleunder Kreps and Porteus' (1978) recursive expected utility. We also analyze our data using a general recursive model that can reveal attitudes towards temporal risk resolution through the utility scale and/or the probability weighting scale. In terms of goodness of fit, as well as of prediction accuracy, our results point to a better performance of the probability weighting approach. More specifically, we show that individuals become less sensitive and more pessimistic with respect to winning probabilities when lotteries are resolved later rather than now. |
| Keywords: | Temporal resolution of uncertainty,temporal risk,recursive expected utility,preference for early resolution,probability weighting,recursive rank-dependent utility,time preference,risk preference |
| Date: | 2021–08–31 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-03330225&r= |
| By: | Hansjörg Albrecher (UNIL - University of Lausanne); Dina Finger (UNIL - University of Lausanne); Pierre-Olivier Goffard (UCBL - Université Claude Bernard Lyon 1 - Université de Lyon) |
| Abstract: | The resource-consuming mining of blocks on a blockchain equipped with a proof of work consensus protocol bears the risk of ruin, namely when the operational costs for the mining exceed the received rewards. In this paper we investigate to what extent it is of interest to join a mining pool that reduces the variance of the return of a miner for a specified cost for participation. Using methodology from ruin theory and risk sharing in insurance, we quantitatively study the effects of pooling in this context and derive several explicit formulas for quantities of interest. The results are illustrated in numerical examples for parameters of practical relevance. |
| Date: | 2021–09–07 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-03336851&r= |
| By: | Emmanuel Kemel (GREGHEC, HEC Paris - Ecole des Hautes Etudes Commerciales, CNRS - Centre National de la Recherche Scientifique); Corina Paraschiv (LIRAES - EA 4470 - Laboratoire Interdisciplinaire de Recherche Appliquée en Economie de la Santé - UP - Université de Paris) |
| Abstract: | This paper presents an experiment that investigates differences of risk attitudes in decisions with immediate versus delayed consequences. Our experimental design allows to control for the effects of discounting and timing of risk resolution. We show that individuals are more risk tolerant in situations involving delayed consequences. Investigations based on rank-dependent utility show that this finding is mainly driven by probability weighting. More precisely, probability weighting is more elevated for delayed consequences, suggesting an overall increase in decision maker's optimism regarding the chances of success associated to risks for which consequences materialize in the future. |
| Keywords: | Risk Attitudes,Time,Rank Dependent Utility,Delay,Future Consequences D81,D90,C91 |
| Date: | 2021–08–31 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-03330096&r= |
| By: | Albert Banal-Estañol (Universitat Pompeu Fabra and Barcelona GSE); Enrique Benito (City, University of London); Dmitry Khametshin (Banco de España); Jianxing Wei (University of International Business and Economics) |
| Abstract: | We document that overcollateralisation of banks’ secured liabilities is positively associated with the risk premium on their unsecured funding. We rationalize this finding in a theoretical model in which costs of asset encumbrance increase collateral haircuts and the endogenous risk of a liquidity-driven bank run. We then test the model’s predictions using a novel dataset on asset encumbrance of the European banks. Our empirical analysis demonstrates that banks with more costly asset encumbrance have higher rates of overcollateralisation and rely less on secured debt. Consistent with theory, the effects are stronger for banks that are likely to face higher fire-sales discounts. This evidence acts in favour of the hypothesis that asset encumbrance increases bank risk, although this relationship is rather heterogeneous. |
| Keywords: | asset encumbrance, collateral, bank risk, credit default swaps |
| JEL: | G01 G21 G28 |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:bde:wpaper:2131&r= |
| By: | Irma Alonso (Banco de España); Pedro Serrano (Universidad Carlos III de Madrid); Antoni Vaello-Sebastià (Universitat des Illes Balears) |
| Abstract: | This article analyzes the impact of the unconventional monetary policies (UMPs) of four major central banks (the Fed, ECB, BoE and BOJ) on the probability of future market crashes. We exploit the heterogeneity of different UMP actions to disentangle their influence on reducing the ex ante perception of extreme events (tail risks) using the information contained in risk-neutral densities from the most liquid stock index options. The empirical findings show that the announcement of UMPs reduces the risk-neutral probability of extreme events across various horizons and thresholds, supporting the hypothesis of the risk-taking channel. Interestingly, foreign UMP actions also prove to be significant variables affecting domestic tail risks, mainly at longer horizons. These results reveal a cross-border effect of foreign UMPs on domestic tail risks. Finally, the dynamics of the UMPs are captured by a structural model that confirms a transitory impact of UMPs on market tail risk perceptions. |
| Keywords: | unconventional monetary policy, risk-neutral density, tail risk, event study, SVAR |
| JEL: | E44 E58 G01 G10 G14 |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:bde:wpaper:2127&r= |
| By: | Roberto Blanco (Banco de España); Sergio Mayordomo (Banco de España); Álvaro Menéndez (Banco de España); Maristela Mulino (Banco de España) |
| Abstract: | This paper analyses the impact of the COVID-19 crisis on the financial vulnerability of the Spanish corporate sector. The simulations conducted show that the crisis significantly increased firms’ liquidity needs in 2020, although the measures adopted by national and international authorities eased access to credit under favourable conditions, which substantially mitigated the short-term liquidity risks. However, the sharp fall in profitability levels, coupled with debt growth, appears to have resulted in a marked increase in the proportion of vulnerable firms (i.e. those with negative equity or high debt levels), which would be more pronounced among SMEs and the sectors hardest hit by the pandemic. The projections for the period 2021-2023 indicate a gradual decline in these percentages, in keeping with the expected recovery in activity. The results also suggest that, as a result of the crisis, the proportion of firms at risk of becoming non-viable on account of persistent losses through to 2023 would rise by between 2 pp and 3 pp, while the proportion of those that will remain viable but struggle to repay their debts out of their expected future earnings (overindebted firms) would rise by between 3 pp and 4.7 pp. In addition, the simulations show that the unsustainable debt of firms that have become overindebted but remain viable would stand between €9 billion and €18.6 billion, depending on the scenario considered, with the bulk of this amount accounted for by SMEs. |
| Keywords: | COVID-19, liquidity needs, profitability, indebtedness, credit, solvency, viability |
| JEL: | E51 E52 G21 |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:bde:opaper:2119e&r= |
| By: | Fabien Le Floc'h; Cornelis W. Oosterlee |
| Abstract: | This paper presents how to apply the stochastic collocation technique to assets that can not move below a boundary. It shows that the polynomial collocation towards a lognormal distribution does not work well. Then, the potentials issues of the related collocated local volatility model (CLV) are explored. Finally, a simple analytical expression for the Dupire local volatility derived from the option prices modelled by stochastic collocation is given. |
| Date: | 2021–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2109.02405&r= |
| By: | Felix Holzmeister (Department of Economics, University of Innsbruck); Christoph Huber (Institute of Markets and Strategy, Vienna University of Economics and Business); Stefan Palan (Institute of Banking and Finance, University of Graz) |
| Abstract: | Risk is one of the key aspects in financial decision-making and therefore an integral part of the behavioral economics and finance literature. Focusing on the conceptualization of the term ``risk'', which researchers have addressed from numerous angles, this comment aims to offer a critical perspective on the interactions between risk preferences (a latent trait), risk perceptions (how individuals judge whether something is risky), and risk-taking behavior as distinct concepts, and hence to guide future research on (individual-level) decision-making processes in this direction. |
| Date: | 2021–09–15 |
| URL: | http://d.repec.org/n?u=RePEc:grz:wpsses:2021-06&r= |