nep-rmg New Economics Papers
on Risk Management
Issue of 2020‒06‒15
27 papers chosen by

  1. Bounding basis risk using s-convex orders on Beta-unimodal distributions By Claude Lefèvre; Stéphane Loisel; Pierre Montesinos
  2. Spillovers beyond the variance: exploring the natural gas and oil higher order risk linkages with the global financial markets By Gomez-Gonzalez, Jose Eduardo; Hirs-Garzon, Jorge; Uribe, Jorge M.
  3. Value-at-Risk substitute for non-ruin capital is fallacious and redundant By Vsevolod Malinovskii
  4. Optimal Investing after Retirement Under Time-Varying Risk Capacity Constraint By Weidong Tian; Zimu Zhu
  5. Impact of Variation Margining on EU Insurers’ Liquidity: An Analysis of Interest Rate Swaps Positions By Alexandra de Jong; Alin Draghiciu; Linda Fache Rousová; Alessandro Fontana; Elisa Letizia
  6. Is heightened political uncertainty priced in stock returns? Evidence from the 2014 Scottish independence referendum By Julia Darby; Jun Gao; Siobhan Lucey; Sheng Zhu
  7. Computation of Expected Shortfall by fast detection of worst scenarios By Bruno Bouchard; Adil Reghai; Benjamin Virrion
  8. Deep Learning for Portfolio Optimisation By Zihao Zhang; Stefan Zohren; Stephen Roberts
  9. Nowcasting Tail Risks to Economic Activity with Many Indicators By Andrea Carriero; Todd E. Clark; Marcellino Massimiliano
  10. Structural Scenario Analysis with SVARs By Antolin-Diaz, Juan; Petrella, Ivan; Rubio-Ramirez, Juan F.
  11. Debt De-risking By Jannic Cutura; Gianpaolo Parise; Andreas Schrimpf
  12. Political Beta By Raymond Fisman; April Knill; Sergey Mityakov; Margarita Portnykh
  13. Parameter estimation of default portfolios using the Merton model and Phase transition By Masato Hisakado; Shintaro Mori
  14. The Role of Global Economic Conditions in Forecasting Gold Market Volatility: Evidence from a GARCH-MIDAS Approach By Afees A. Salisu; Rangan Gupta; Elie Bouri
  15. Pricing Path-Dependent Derivatives under Multiscale Stochastic Volatility Models: a Malliavin Representation By Yuri F. Saporito
  16. Take It to the Limit? The Effects of Household Leverage Caps By Van Bekkum, Sjoerd; Gabarró, Marc; Irani, Rustom; Peydró, José-Luis
  17. Cyclical income risk in Great Britain By Konstantinos Angelopoulos; Spyridon Lazarakis; James Malley
  18. Analyzing the Community Bank Leverage Ratio By Bert Loudis; Daniel Nguyen; Carlo Wix
  19. Canadian Financial Stress and Macroeconomic Conditions By Thibaut Duprey
  20. Aggregate Risk or Aggregate Uncertainty? Evidence from UK Households By Claudio Michelacci; Luigi Paciello
  21. The global effects of global risk and uncertainty By Bonciani, Dario; Ricci, Martino
  22. Tail events, emotions and risk taking By Brice Corgnet; Camille Cornand; Nobuyuki Hanaki
  23. The COVID-19 Shock and Equity Shortfall: Firm-level Evidence from Italy By Elena Carletti; Tommaso Oliviero; Marco Pagano; Loriana Pelizzon; Marti G. Subrahmanyam
  24. Non-concave expected utility optimization with uncertain time horizon: an application to participating life insurance contracts By Christian Dehm; Thai Nguyen; Mitja Stadje
  25. Adverse childhood experiences and risk behaviours later in life: Evidence from SHARE countries By Agar Brugiavini; Raluca Elena Buia; Matija Kovacic; Cristina Elisa Orso
  26. COVID-19 and Global Economic Growth: Policy Simulations with a Pandemic-Enabled Neoclassical Growth Model By Ian M. Trotter; Lu\'is A. C. Schmidt; Bruno C. M. Pinto; Andrezza L. Batista; J\'essica Pellenz; Maritza Isidro; Aline Rodrigues; Attawan G. S. Suela; Loredany Rodrigues
  27. Benin; Sixth Review under the Extended Credit Facility Arrangement, and Request for Augmentation of Access-Press Release; Staff Report; and Statement by the Executive Director for Benin By International Monetary Fund

  1. By: Claude Lefèvre (ULB - Département de Mathématique [Bruxelles] - ULB - Université Libre de Bruxelles [Bruxelles]); Stéphane Loisel (SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon); Pierre Montesinos (SAF - Laboratoire de Sciences Actuarielle et Financière - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon)
    Abstract: This paper is concerned with properties of Beta-unimodal distributions and their use to assess the basis risk inherent to index-based insurance or reinsurance contracts. To this extent, we first characterize s-convex stochastic orders for Beta-unimodal distributions in terms of the Weyl fractional integral. We then determine s-convex extrema for such distributions , focusing in particular on the cases s = 2, 3, 4. Next, we define an Enterprise Risk Management framework that relies on Beta-unimodality to assess these hedge imperfections , introducing several penalty functions and worst case scenarios. Some of the results obtained are illustrated numerically via a representative catastrophe model.
    Keywords: s-convex extrema,s-convex stochas- tic orders,Beta-unimodality,Basis risk,Parametric index,Risk management
    Date: 2020–05–18
  2. By: Gomez-Gonzalez, Jose Eduardo; Hirs-Garzon, Jorge; Uribe, Jorge M.
    Abstract: We explore the higher order linkages between energy commodity markets and global financial markets. Our focus is on spillovers of realized good and bad volatilities, realized signed jump variation, realized skewness and realized kurtosis. Our results show that the measurement of risk spillovers is sensitive to the definition of risk used in their construction. Asymmetries between good and bad volatility transmission matter, and results when jumps and higher order risk measures are considered are substantially different from those obtained when traditional volatility measures are used. We provide empirical support for theoretical asset pricing models that conduct the optimization required for portfolio balancing in the mean-variance-skewness space by showing that risk diversification opportunities vary greatly when one considers variance or skewness as the fundamental proxy for risk.
    Keywords: Energy commodity markets; Risk spillover; Higher order risk measure; LASSO methods
    JEL: E44 F31 G01 G12 G15
    Date: 2020–06
  3. By: Vsevolod Malinovskii
    Abstract: This seemed impossible to use a theoretically adequate but too sophisticated risk measure called non-ruin capital, whence its widespread (including regulatory documents) replacement with an inadequate, but simple risk measure called Value-at-Risk. Conflicting with the idea by Albert Einstein that "everything should be made as simple as possible, but not simpler", this led to fallacious, and even deceitful (but generally accepted) standards and recommendations. Arguing from the standpoint of mathematical theory of risk, we aim to break this impasse.
    Date: 2020–05
  4. By: Weidong Tian; Zimu Zhu
    Abstract: This paper explores an optimal investing problem for a retiree facing longevity risk and living standard risk. We formulate the optimal investing problem as an optimal portfolio choice problem under a time-varying risk capacity constraint. Under the specific condition on model parameters, we show that the value function is a $C^2$ solution of the HJB equation and derive the optimal investment strategy in terms of second-order ordinary differential equations. The optimal portfolio is nearly neutral to the stock market movement if the portfolio's value is at a sufficiently high level; but, if the portfolio is not worth enough to sustain the retirement spending, the retiree actively invests in the stock market for the higher expected return. In addition, we solve an optimal portfolio choice problem under a leverage constraint and show that the optimal portfolio would lose significantly in stressed markets. This paper shows that the time-varying risk capacity constraint has important implications for asset allocation in retirement.
    Date: 2020–05
  5. By: Alexandra de Jong; Alin Draghiciu; Linda Fache Rousová; Alessandro Fontana; Elisa Letizia (EIOPA)
    Abstract: Insures use derivatives to hedge risks from investments portfolios and underwriting, but this exposes them to liquidity risk. This study uses Solvency II reporting data to assess to what extent European (re-)insurers would be able to meet potential variation margin calls on interest rate swaps portfolios. Interest rate swaps pose the largest share of (re-)insurers derivatives’ portfolios. We consider several shifts to the yield curve, calculate the corresponding variation margin calls, compare them to liquid assets available to insurers and derive the potential liquidity shortfalls. Our results reveal that there may be a liquidity risk for (re-)insurers stemming from the use of derivatives, in particular interest rate swaps (IRS). This reflects both high IRS exposure and insufficient holdings of cash and liquid assets. Based on the analysis presented in this article we conclude that some insurers have not yet adapted their asset allocation and liquidity management practices to the (new) requirements on margining practices which have been introduced as part of the OTC derivatives reform.
    Keywords: insurance, variation margin, liquidity
    JEL: G11 G12 G22
    Date: 2019–12
  6. By: Julia Darby (Department of Economics, University of Strathclyde); Jun Gao (Department of Economics, University College Cork, Ireland); Siobhan Lucey (Department of Economics, University College Cork, Ireland); Sheng Zhu (Department of Economics and Centre for Investment Research, University College Cork, Ireland)
    Abstract: We contribute to a growing literature on economic and financial impacts of political uncertainty by assessing whether heightened uncertainty associated with an important political event is priced into stock returns. Our particular study looks at the period surrounding the 2014 Scottish Independence Referendum, although we argue that our approach and findings have wider relevance to assessing impacts of other political events, including Brexit. Using company data and portfolio-level analysis we document significant variation in returns and demonstrate that uncertainty betas help predict the cross-sectional dispersion of returns. These findings are robust to inclusion of controls (standard risk factors), but no longer hold when a Scottish specific uncertainty measure is replaced with UK-wide measures of either economic policy uncertainty or stock market uncertainty, adding support to the hypothesis that our findings are driven by referendum related uncertainty. We conclude that heightened political uncertainty was priced during the period surrounding the referendum, i.e. that uncertainty averse investors succeeded in gaining compensation for holding the volatile stocks of Scottish headquartered companies.
    Keywords: Political uncertainty, stock market volatility
    JEL: E65 G12 G18 P16
    Date: 2019–09
  7. By: Bruno Bouchard (CEREMADE - CEntre de REcherches en MAthématiques de la DEcision - CNRS - Centre National de la Recherche Scientifique - Université Paris Dauphine-PSL); Adil Reghai (Natixis Asset Management); Benjamin Virrion (CEREMADE - CEntre de REcherches en MAthématiques de la DEcision - CNRS - Centre National de la Recherche Scientifique - Université Paris Dauphine-PSL, Natixis Asset Management)
    Abstract: We consider a multi-step algorithm for the computation of the historical expected shortfall such as defined by the Basel Minimum Capital Requirements for Market Risk. At each step of the algorithm, we use Monte Carlo simulations to reduce the number of historical scenarios that potentially belong to the set of worst scenarios. The number of simulations increases as the number of candidate scenarios is reduced and the distance between them diminishes. For the most naive scheme, we show that the L p-error of the estimator of the Expected Shortfall is bounded by a linear combination of the probabilities of inversion of favorable and unfavorable scenarios at each step, and of the last step Monte Carlo error associated to each scenario. By using concentration inequalities, we then show that, for sub-gamma pricing errors, the probabilities of inversion converge at an exponential rate in the number of simulated paths. We then propose an adaptative version in which the algorithm improves step by step its knowledge on the unknown parameters of interest: mean and variance of the Monte Carlo estimators of the different scenarios. Both schemes can be optimized by using dynamic programming algorithms that can be solved off-line. To our knowledge, these are the first non-asymptotic bounds for such estimators. Our hypotheses are weak enough to allow for the use of estimators for the different scenarios and steps based on the same random variables, which, in practice, reduces considerably the computational effort. First numerical tests are performed.
    Keywords: ranking and selection,sequential design,Expected Shortfall,Bayesian filter
    Date: 2020–05–25
  8. By: Zihao Zhang; Stefan Zohren; Stephen Roberts
    Abstract: We adopt deep learning models to directly optimise the portfolio Sharpe ratio. The framework we present circumvents the requirements for forecasting expected returns and allows us to directly optimise portfolio weights by updating model parameters. Instead of selecting individual assets, we trade Exchange-Traded Funds (ETFs) of market indices to form a portfolio. Indices of different asset classes show robust correlations and trading them substantially reduces the spectrum of available assets to choose from. We compare our method with a wide range of algorithms with results showing that our model obtains the best performance over the testing period, from 2011 to the end of April 2020, including the financial instabilities of the first quarter of 2020. A sensitivity analysis is included to understand the relevance of input features and we further study the performance of our approach under different cost rates and different risk levels via volatility scaling.
    Date: 2020–05
  9. By: Andrea Carriero; Todd E. Clark; Marcellino Massimiliano
    Abstract: This paper focuses on tail risk nowcasts of economic activity, measured by GDP growth, with a potentially wide array of monthly and weekly information. We consider different models (Bayesian mixed frequency regressions with stochastic volatility, classical and Bayesian quantile regressions, quantile MIDAS regressions) and also different methods for data reduction (either the combination of forecasts from smaller models or forecasts from models that incorporate data reduction). The results show that classical and MIDAS quantile regressions perform very well in-sample but not out-of-sample, where the Bayesian mixed frequency and quantile regressions are generally clearly superior. Such a ranking of methods appears to be driven by substantial variability over time in the recursively estimated parameters in classical quantile regressions, while the use of priors in the Bayesian approaches reduces sampling variability and its effects on forecast accuracy. From an economic point of view, we find that the weekly information flow is quite useful in improving tail nowcasts of economic activity, with initial claims for unemployment insurance, stock prices, a term spread, a credit spread, and the Chicago Fed’s index of financial conditions emerging as particularly relevant indicators. Additional weekly indicators of economic activity do not improve historical forecast accuracy but do not harm it much, either.
    Keywords: mixed frequency; big data; pandemics; downside risk; forecasting; quantile regression.
    JEL: C53 E17 E37 F47
    Date: 2020–05–11
  10. By: Antolin-Diaz, Juan (London Business School); Petrella, Ivan (University of Warwick); Rubio-Ramirez, Juan F. (Emory University)
    Abstract: Macroeconomists seeking to construct conditional forecasts often face a choice between taking a stand on the details of a fully-specified structural model or relying on empirical correlations from vector autoregressions and remain silent about the underlying causal mechanisms. This paper develops tools for constructing “structural scenarios” that can be given an economic interpretation using identified structural VARs. We provide a unified and transparent treatment of conditional forecasting and structural scenario analysis and relate our approach to entropic forecast tilting. We advocate for a careful treatment of uncertainty, making the methods suitable for density forecasting and risk assessment. We also propose a metric to assess and compare the plausibility of alternative scenarios. We illustrate our methods with two applications: assessing the power of forward guidance about future interest rate policies and stress testing the reaction of bank profitability to an economic recession.
    Keywords: conditional forecasts ; SVARs ; Bayesian Methods ; Forward Guidance ; stress testing ;
    JEL: E37
    Date: 2020
  11. By: Jannic Cutura; Gianpaolo Parise; Andreas Schrimpf
    Abstract: We examine the incentive of corporate bond fund managers to manipulate portfolio risk in response to competitive pressure. We find that bond funds engage in a reverse fund tournament in which laggard funds actively de-risk their portfolios, trading-off higher yields for more liquid and safer assets. De-risking is stronger for laggard funds that have a more concave sensitivity of flows-to-performance, in periods of market stress, and when bond yields are high. We provide evidence that debt de-risking also reduces ex post liquidation costs by mitigating the investors' incentive to run ex ante. We argue that, in the presence of de-risking behaviors, flexible NAVs (swing pricing) may be counter-productive and induce moral hazard.
    Keywords: corporate bond funds, bond market liquidity, asset managers, risk-taking, competitive pressures
    JEL: G11 G23 G32 E43
    Date: 2020–06
  12. By: Raymond Fisman (Boston University); April Knill (Florida State University); Sergey Mityakov (Florida State University); Margarita Portnykh (Carnegie Mellon University)
    Abstract: Using a framework akin to portfolio theory in asset pricing, we introduce the concept of “political beta†to model firm-level export diversification in response to global political risk. The main implication of our model is that a firm is less responsive to changes in political relations with a destination market when that country contributes less to (has lower political beta) or even hedges against (has negative political beta) the firm’s total political risk. This result follows the diversification logic of portfolio theory, in which an investor values a given asset depending on the asset’s comovement with his/her overall investment portfolio. We find patterns consistent with our model using disaggregated Russian firm-by-destination-country data during 1999-2011: trade is positively correlated with political relations, though the effect is far weaker for trading partners whose political relations with Russia are relatively uncorrelated with those of other partners in a firm’s export portfolio. Our results highlight the importance of viewing firms’ political relations as an undiversifiable source of risk, and more generally points to the value of modeling firms’ treatment of risks as a portfolio diversification problem.
    Keywords: Political Risk, Asset Pricing Theory; Portfolio Theory; Exports; Diversification
    JEL: F14 F23 F51 G11 G32
    Date: 2020–03
  13. By: Masato Hisakado; Shintaro Mori
    Abstract: We discuss the parameter estimation of the probability of default (PD), the correlation between the obligors, and a phase transition. In our previous work, we studied the problem using the beta-binomial distribution. A non-equilibrium phase transition with an order parameter occurs when the temporal correlation decays by power law. In this article, we adopt the Merton model, which uses an asset correlation as the default correlation, and find that a phase transition occurs when the temporal correlation decays by power law. When the power index is less than one, the PD estimator converges slowly. Thus, it is difficult to estimate PD with limited historical data. Conversely, when the power index is greater than one, the convergence speed is inversely proportional to the number of samples. We investigate the empirical default data history of several rating agencies. The estimated power index is in the slow convergence range when we use long history data. This suggests that PD could have a long memory and that it is difficult to estimate parameters due to slow convergence.
    Date: 2020–05
  14. By: Afees A. Salisu (Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam; Faculty of Business Administration, Ton Duc Thang University, Ho Chi Minh City, Vietnam); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, 0002, South Africa); Elie Bouri (USEK Business School, Holy Spirit University of Kaslik, Jounieh, Lebanon)
    Abstract: In this study, we examine the role of global economic conditions in forecasting gold market volatility using alternative measures. Based on the available data frequency for the relevant series, we adopt the GARCH-MIDAS approach which allows for mixed data frequencies. We find that global economic conditions contribute significantly to gold market volatility albeit with mixed outcomes. While the results lend support to the safe-haven properties of the gold market, the outcome is influenced by the choice of measure of global economic conditions. For completeness, we extend the analyses to other precious metals such as silver, platinum, palladium, and rhodium and find that global economic conditions forecast the volatility of gold returns better than other precious metals. Our results are robust to multiple forecast horizons and offer useful insights into plausible investment choices in the precious metals market.
    Keywords: Precious Metals Volatility, Global Economic Conditions, Mixed-Frequency
    JEL: C32 C53 E32 Q02
    Date: 2020–05
  15. By: Yuri F. Saporito
    Abstract: In this paper we derive a efficient Monte Carlo approximation for the price of path-dependent derivatives under the multiscale stochastic volatility models of Fouque \textit{et al}. Using the formulation of this pricing problem under the functional It\^o calculus framework and making use of Greek formulas from Malliavin calculus, we derive a representation for the first-order approximation of the price of path-dependent derivatives in the form $\mathbb{E}[\mbox{payoff} \times \mbox{weight}]$. The weight is known in closed form and depends only on the group market parameters arising from the calibration of the multiscale stochastic volatility to the market's implied volatility. Moreover, only simulations of the Black-Scholes model is required. We exemplify the method for a couple path-dependent derivatives.
    Date: 2020–05
  16. By: Van Bekkum, Sjoerd; Gabarró, Marc; Irani, Rustom; Peydró, José-Luis
    Abstract: We analyze the effects of borrower-based macroprudential policy at the household-level. For identification, we exploit administrative Dutch tax-return and property ownership data linked to the universe of housing transactions, and the introduction of a mortgage loan-to-value limit. The regulation reduces mortgage leverage, with bunching in its limit. Ex-ante more-affected households substantially reduce overall leverage and debt servicing costs but consume greater liquidity to satisfy the regulation. Improvements in household solvency result in less financial distress and, given negative idiosyncratic shocks, better liquidity management. However, fewer households transition from renting into ownership. All of these effects are stronger for liquidity-constrained households.
    Keywords: macroprudential policy,residential mortgages,solvency vs. liquidity tradeoff,household leverage,loan-to-valud ratio
    JEL: E21 E58 G21 G28
    Date: 2019
  17. By: Konstantinos Angelopoulos; Spyridon Lazarakis; James Malley
    Abstract: This paper establishes new evidence on the cyclical behaviour of household income risk in Great Britain and assesses the role of social insurance policy in mitigating against this risk. We address these issues using the British Household Panel Survey (1991-2008) by decomposing stochastic idiosyncratic income into its transitory, persistent and fixed components. We then estimate how income risk, measured by the variance and the skewness of the probability distribution of shocks to the persistent component, varies between expansions and contractions of the aggregate economy. We first find that the volatility and left-skewness of these shocks is a-cyclical and counter-cyclical respectively. The latter implies a higher probability of receiving large negative income shocks in contractions. We also find that while social insurance (tax-benefits) policy reduces the levels of both measures of risk as well as the counter-cyclicality of the asymmetry measure, the mitigation effects work mainly via benefits.
    Keywords: household income risk, social insurance policy, aggregate áuctuations
    JEL: D31 E24 J31
    Date: 2019–03
  18. By: Bert Loudis; Daniel Nguyen; Carlo Wix
    Abstract: This note analyzes the newly introduced Community Bank Leverage Ratio ("CBLR") framework. The analysis covers the framework's eligibility, its capital stringency, and its potential impact on system-wide capital levels under a hypothetical adverse scenario.
    Date: 2020–05–26
  19. By: Thibaut Duprey
    Abstract: I construct a new composite measure of systemic financial market stress for Canada. Compared with existing measures, it better captures the 1990 housing market correction and more accurately reflects the absence of diversification opportunities during systemic events. The index can be used for monitoring. For instance, it reached a peak during the COVID-19 pandemic second only to the 2008 global financial crisis. The index can also be used to introduce non-linear macrofinancial dynamics in empirical macroeconomic models of the Canadian economy. Macroeconomic conditions are shown to deteriorate significantly when the Canadian financial stress index is above its 90th percentile.
    Keywords: Central bank research; Financial markets; Financial stability; Monetary and financial indicators
    JEL: C3 C32 E4 E44 G0 G01
    Date: 2020–06
  20. By: Claudio Michelacci (EIEF and CEPR); Luigi Paciello (EIEF and CEPR)
    Abstract: Using the Bank of England Inflation Attitudes Survey we find that households with preferences for higher inflation and higher interest rates have lower expected inflation. The wedge is mildly correlated with existing measures of uncertainty and increases after major economic events such as the failure of Lehman Brothers or the Brexit referendum. We interpret the wedge as due to Knightian uncertainty about future monetary policy and the underlying economic environment. If households had treated uncertainty as measurable risk, consumption and output would have been around 1 percent higher both during the Great Recession and in recent years.
    Date: 2020
  21. By: Bonciani, Dario (Bank of England); Ricci, Martino (European Central Bank)
    Abstract: In this paper, we analyse the effects of a shock to global financial uncertainty and risk aversion on real economic activity. To this end, we extract a common factor from the realised volatilities of about 1,000 risky asset returns from around the world. We then study how shocks to the factor affect economic activity in 44 advanced and emerging small open economies by estimating local projections in a panel regression framework. We find that the output responses are quite heterogeneous across countries but, in general, negative and persistent. Furthermore, the effects of shocks to the global factor are stronger in countries with a higher degree of trade and/or financial openness, as well as in countries with a higher level of vulnerabilities.
    Keywords: Global uncertainty; global risk aversion; global financial cycle; small open economies
    JEL: E32 F41 F65
    Date: 2020–05–22
  22. By: Brice Corgnet (emlyon business school, GATE Lyon Saint-Étienne - Groupe d'analyse et de théorie économique - CNRS - Centre National de la Recherche Scientifique - Université de Lyon - UJM - Université Jean Monnet [Saint-Étienne] - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UL2 - Université Lumière - Lyon 2 - ENS Lyon - École normale supérieure - Lyon); Camille Cornand (GATE Lyon Saint-Étienne - Groupe d'analyse et de théorie économique - CNRS - Centre National de la Recherche Scientifique - Université de Lyon - UJM - Université Jean Monnet [Saint-Étienne] - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UL2 - Université Lumière - Lyon 2 - ENS Lyon - École normale supérieure - Lyon); Nobuyuki Hanaki (Osaka University [Osaka])
    Abstract: Recent works have shown how tail events could account for financial anomalies such as the equity premiumpuzzle. These models do not explore, however, why investors would discount tail risk so heavily. We take on this challenge by designing a novel tail-event experiment to assess both investors' behavioral and physiological reactions. We show that investors who observe the tail event without suffering losses tend to decrease their pricing of the asset subsequently. By contrast, loss-averse investors who suffer tail losses tend to increase their bids. This response is especially pronounced for those who exhibit a strong emotional response to tail losses. This demonstrates the key role played by emotions in influencing investors' response to tail events. Finally, investors who exhibit high anticipatory arousal, as measured with electrodermal activity, posted lower bids and were less likely to suffer tail losses and go bankrupt. They also achieved higher earnings when tail events occurred frequently. This finding contrasts with the common view that investors should silence their emotions.
    Keywords: tail events,emotions,risk
    Date: 2020
  23. By: Elena Carletti (Università Bocconi and CEPR); Tommaso Oliviero (Università di Napoli Federico II and CSEF); Marco Pagano (Università di Napoli Federico II, CSEF and EEIF); Loriana Pelizzon (SAFE, Goethe University Frankfurt and Università di Venezia Ca' Foscari); Marti G. Subrahmanyam (Stern School of Business, New York University)
    Abstract: This paper estimates the drop in profits and the equity shortfall triggered by the COVID-19 shock and the subsequent lockdown, using a representative sample of 80,972 Italian firms. We find that a 3-month lockdown entails an aggregate yearly drop in profits of €170 billion, with an implied equity erosion of €117 billion for the whole sample, and €31 billion for firms that became distressed, i.e., ended up with negative book value after the shock. As a consequence of these losses, about 17% of the sample firms, whose employees account for 8.8% of total employment in the sample (about 800 thousand employees), become distressed. Small and medium-sized enterprises (SMEs) are affected disproportionately, with 18.1% of small firms, and 14.3% of medium-sized ones becoming distressed, against 6.4% of large firms. The equity shortfall and the extent of distress are concentrated in the Manufacturing and Wholesale Trading sectors and in the North of Italy. Since many firms predicted to become distressed due to the shock had fragile balance sheets even prior to the COVID-19 shock, restoring their equity to their pre-crisis levels may not suffice to ensure their long-term solvency.
    Keywords: COVID-19, pandemics, losses, distress, equity, recapitalization.
    JEL: G01 G32 G33
    Date: 2020–05–28
  24. By: Christian Dehm; Thai Nguyen; Mitja Stadje
    Abstract: We examine an expected utility maximization problem with an uncertain time horizon, a classical example being a life insurance contract due at the time of death. Life insurance contracts usually have an option-like form leading to a non-concave optimization problem. We consider general utility functions and give necessary and sufficient optimality conditions, deriving a computationally tractable algorithm. A numerical study is done to illustrate our findings. Our analysis suggests that the possible occurrence of a premature stopping leads to a reduced performance of the optimal portfolio compared to a setting without time-horizon uncertainty.
    Date: 2020–05
  25. By: Agar Brugiavini (Department of Economics, University Of Venice Cà Foscari); Raluca Elena Buia (Department of Economics, University Of Venice Cà Foscari); Matija Kovacic (European Commission, Joint Research Centre (JRC); Department of Economics, University Of Venice Cà Foscari); Cristina Elisa Orso (Department of Economics, University Of Verona)
    Abstract: In this paper we investigate whether exposure to adverse experiences during childhood such as physical and emotional abuse affects the likelihood of unhealthy habits and separately the insurgency of chronic diseases and disabilities later in life. The novelty of our approach consists in exploiting the recently published data on adverse childhood experiences for 19 SHARE countries, which enables us to account for country-specific heterogeneity and investigate the long-run effects of exposure to adverse early-life circumstances on risk behaviour such as smoking, drinking, overweight and obesity. Our results highlight a significant positive effect of exposure to adverse childhood experiences (ACEs) on the probability of unhealthy lifestyles as well as on the insurgency of chronic diseases and disabilities in the long run.
    Keywords: Adverse Childhood Experiences, Smoking Behaviour, Heavy drinking, Obesity
    JEL: H4 I12
    Date: 2020
  26. By: Ian M. Trotter; Lu\'is A. C. Schmidt; Bruno C. M. Pinto; Andrezza L. Batista; J\'essica Pellenz; Maritza Isidro; Aline Rodrigues; Attawan G. S. Suela; Loredany Rodrigues
    Abstract: During the COVID-19 pandemic of 2019/2020, authorities have used temporary ad-hoc policy measures, such as lockdowns and mass quarantines, to slow its transmission. However, the consequences of widespread use of these unprecedented measures are poorly understood. To contribute to the understanding of the economic and human consequences of such policy measures, we therefore construct a mathematical model of an economy under the impact of a pandemic, select parameter values to represent the global economy under the impact of COVID-19, and perform numerical experiments by simulating a large number of possible policy responses. By varying the starting date of the policy intervention in the simulated scenarios, we find that the most effective policy intervention occurs around the time when the number of active infections is growing at its highest rate. The degree of the intervention, above a certain threshold, does not appear to have a great impact on the outcomes in our simulations, due to the strongly concave relationship we assume between production shortfall and reduction in the infection rate. Our experiments further suggest that the intervention should last until after the peak determined by the reduced infection rate. The model and its implementation, along with the general insights from our policy experiments, may help policymakers design effective emergency policy responses in the face a serious pandemic, and contribute to our understanding of the relationship between the economic growth and the spread of infectious diseases.
    Date: 2020–05
  27. By: International Monetary Fund
    Abstract: Program implementation continues to be strong, with all end-December 2019 quantitative performance criteria (QPCs) and the structural benchmarks (SB) under review being met. Economic activity is expected to decelerate sharply in 2020 due to the COVID-19 pandemic. The authorities have prepared a response plan of 1.7 percent of GDP to contain health risks and support the economy. As a result of the projected revenue shortfall and the new measures, the 2020 fiscal deficit is revised upward to 3.5 percent of GDP.
    Keywords: Extended Credit Facility;
    Date: 2020–05–20

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