nep-rmg New Economics Papers
on Risk Management
Issue of 2021‒06‒21
25 papers chosen by

  1. Is COVID-19 a threat to financial stability in Europe? By Reinders, Henk Jan; Schoenmaker, Dirk; Van Dijk, Mathijs A
  2. Risk Quantization by Magnitude and Propensity By Faugeras, Olivier; Pages, Gilles
  3. System-wide and banks' internal stress tests: Regulatory requirements and literature review By Pliszka, Kamil
  4. A Bayesian realized threshold measurement GARCH framework for financial tail risk forecasting By Chao Wang; Richard Gerlach
  5. The good, the bad, and the asymmetric: Evidence from a new conditional density model By Andreï Kostyrka; Dmitry Igorevich Malakhov,
  6. Credit spread approximation and improvement using random forest regression By Mathieu Mercadier; Jean-Pierre Lardy
  7. The Global Determinants of International Equity Risk Premiums By Juan M. Londono; Nancy R. Xu
  8. Can regulating bank capital help prevent and mitigate financial downturns? By Alejandro García; Josef Schroth
  9. A one-sided Vysochanskii-Petunin inequality with financial applications By Mathieu Mercadier; Frank Strobel
  10. Higher-order comoment contagion among G20 equity markets during the COVID-19 pandemic By Renée Fry-McKibbin; Matthew Greenwood-Nimmo; Cody Yu-Ling Hsiao; Lin Qi
  11. The Long-Term Effects of Capital Requirements By Gianni De Nicolò; Nataliya Klimenko; Sebastian Pfeil; Jean-Charles Rochet
  12. Pricing Algorithmic Insurance By Dimitris Bertsimas; Agni Orfanoudaki
  13. Out-of-Sample Predictability of Gold Market Volatility: The Role of US Nonfarm Payroll By Afees A. Salisu; Elie Bouri; Rangan Gupta
  14. Modeling Portfolios with Leptokurtic and Dependent Risk Factors By Piero Quatto; Gianmarco Vacca; Maria Grazia Zoia
  15. Asset volatility forecasting:The optimal decay parameter in the EWMA model By Axel A. Araneda
  16. Conditional Capital Surplus and Shortfall across Resource Firms By Denny IRAWAN; OKIMOTO Tatsuyoshi
  17. Pricing and Risk Analysis in Hyperbolic Local Volatility Model with Quasi Monte Carlo By Julien Hok; Sergei Kucherenko
  18. Does Secrecy Signal Skill? Characteristics and Performance of Secretive Hedge Funds By Gorovyy, Sergiy; Kelly, Patrick; Kuzmina, Olga
  19. Enterprise Risk Management and Solvency: The Case of the Listed EU Insurers By Duc Khuong Nguyen; Dinh-Tri Vo
  20. Duration-Based Stock Valuation By van Binsbergen, Jules H.
  21. Measuring the impact of a bank failure on the real economy: an EU-wide analytical framework By Vacca, Valerio Paolo; Bichlmeier, Fabian; Biraschi, Paolo; Boschi, Natalie; Álvarez, Antonio J. Bravo; Di Primio, Luciano; Ebner, André; Hoeretzeder, Silvia; Ballesteros, Elisa Llorente; Miani, Claudia; Ricci, Giacomo; Santioni, Raffaele; Schellerer, Stefan; Westman, Hanna
  22. Financial Vulnerability and Risks to Growth in Emerging Markets By Acharya, Viral V.; Bhadury, Soumya; Surti, Jay
  23. Quantifying time-varying forecast uncertainty and risk for the real price of oil By Knut Are Aastveit; Jamie Cross; Herman K. van Dijk
  24. Predicting French SME Failures: New Evidence from Machine Learning Techniques By Christophe Schalck; Meryem Schalck
  25. Optimal Debt Dynamics, Issuance Costs, and Commitment By Luca Benzoni; Lorenzo Garlappi; Robert S. Goldstein; Julien Hugonnier; Chao Ying

  1. By: Reinders, Henk Jan; Schoenmaker, Dirk; Van Dijk, Mathijs A
    Abstract: The severe economic impact of the COVID-19 pandemic could threaten financial stability. However, assessing the gravity of this threat is challenging, since banks' accounting-based loan loss provisions are sluggish. We use a Merton contingent claims model to provide a real-time, market valuation-based assessment of the impact of COVID-19 on euro area banks' corporate loan portfolios. We calibrate the model based on observed stock price responses and use different scenarios for future volatility and incurred losses in case of default. Based on stock prices as of April 20, 2020, we estimate that the market-implied losses for euro area banks could reach over â?¬1 trillion, or 4 to 25% of corporate credits' book value (7 to 43% of available capital and reserves). Our analysis can be viewed as an early warning indicator of potential accounting losses to follow.
    Keywords: bank capital; Covid-19 pandemic; Financial Stability; stress test
    JEL: G01 G21 G28
    Date: 2020–06
  2. By: Faugeras, Olivier; Pages, Gilles
    Abstract: We propose a novel approach in the assessment of a random risk variable X by introducing magnitude-propensity risk measures (mX; pX). This bivariate measure intends to account for the dual aspect of risk, where the magnitudes x of X tell how hign are the losses incurred, whereas the probabilities P(X = x) reveal how often one has to expect to suffer such losses. The basic idea is to simultaneously quantify both the severity mX and the propensity pX of the real-valued risk X. This is to be contrasted with traditional univariate risk measures, like VaR or Expected shortfall, which typically conflate both effects. In its simplest form, (mX; pX) is obtained by mass transportation in Wasserstein metric of the law PX of X to a two-points f0;mXg discrete distribution with mass pX at mX. The approach can also be formulated as a constrained optimal quantization problem. This allows for an informative comparison of risks on both the magnitude and propensity scales. Several examples illustrate the proposed approach.
    Date: 2021–06–11
  3. By: Pliszka, Kamil
    Abstract: This paper deals with both system-wide and banks' internal stress tests. For system-wide stress tests it describes the evolution over time, compares the stress test design in major jurisdictions, and discusses academic research. System-wide stress tests have gained in importance and nowadays serve as a key regulatory tool. For instance, they feed into the calculation of capital requirements in the EU. The literature shows that the disclosure of stress test results reveals new information to the market. Furthermore, banks that participate in system-wide stress tests increase their capital ratios and shift lending to less risky borrowers. For banks' internal stress tests, this paper gives an overview of the regulatory requirements under Pillars 1 to 3 of Basel III and reviews the academic literature. Stress testing is deeply embedded in the Basel III framework. Banks that choose to apply internal models for calculating capital requirements are subject to more stringent stress testing requirements and, for example, have to ensure capital adequacy if the internal risk parameters are being stressed. The academic research on banks' internal stress tests shows that stress scenarios derived from expert judgment should be complemented by scenarios which are selected on the basis of algorithms that consider historical characteristics of the risk factors. Furthermore, banks' conventional credit risk models can be modified and used for stress testing. As stress testing is exposed to considerable model and estimation risk, banks should carry out extensive robustness checks. In sum, both system-wide and banks' internal stress tests play a complementary role in ensuring the resilience of individual banks and the financial system to adverse shocks.
    Keywords: literature survey,regulatory expectations,regulatory requirements,stress testing
    JEL: G21 G32 G38
    Date: 2021
  4. By: Chao Wang; Richard Gerlach
    Abstract: In this paper, an innovative threshold measurement equation is proposed to be employed in a Realized-GARCH framework. The proposed framework employs a nonlinear threshold regression specification to consider the leverage effect and model the contemporaneous dependence between the observed realized measures and hidden volatility. A Bayesian Markov Chain Monte Carlo method is adapted and employed for the model estimation and forecasting, with its validity assessed via a simulation study. The usefulness of the proposed measurement equation in a Realized-GARCH model has been evaluated via a comprehensive empirical study, by forecasting the 1% and 2.5% Value-at-Risk and Expected Shortfall on six market indices. The proposed framework is shown to be capable of producing competitive tail risk forecasting results, compared to the original Realized-GARCH. Especially, the proposed model is favoured during the high volatility 2008 Global Financial Crisis period.
    Date: 2021–06
  5. By: Andreï Kostyrka (Department of Economics and Management, Université du Luxembourg); Dmitry Igorevich Malakhov, (HSE University, Moscow, RS)
    Abstract: We propose a novel univariate conditional density model and decompose asset returns into a sum of copula-connected unobserved ‘good’ and ‘bad’ shocks. The novelty of this approach comes from two factors: we explicitly model correlation between unobserved shocks and allow for the presence of copula-connected discrete jumps. The proposed framework is very flexible and subsumes other models, such as ‘bad environments, good environments’. Our model shows certain hidden characteristics of returns, explains investors’ behaviour in greater detail, and yields better forecasts of risk measures. The in-sample and out-of-sample performance of our model is better than that of 40 popular GARCH variants. A Monte-Carlo simulation shows that the proposed model recovers the structural parameters of the unobserved dynamics. We estimate the model on S&P 500 data and find that time-dependent non-negative covariance between ‘good’ and ‘bad’ shocks with a leverage-like effect is an important component of total variance. Asymmetric reaction to shocks is present almost in all characteristics of returns. Conditional distribution of seems to be very time-dependent with skewness both in the centre and tails. We conclude that continuous shocks are more important than discrete jumps at least at daily frequency.
    Keywords: GARCH, conditional density, leverage effect, jumps, bad volatility, good volatility.
    JEL: C53 C58 C63 G17
    Date: 2021
  6. By: Mathieu Mercadier (LAPE, Université de Limoges); Jean-Pierre Lardy
    Abstract: Credit Default Swap (CDS) levels provide a market appreciation of companies' default risk. These derivatives are not always available, creating a need for CDS approximations. This paper offers a simple, global and transparent CDS structural approximation, which contrasts with more complex and proprietary approximations currently in use. This Equity-to-Credit formula (E2C), inspired by CreditGrades, obtains better CDS approximations, according to empirical analyses based on a large sample spanning 2016-2018. A random forest regression run with this E2C formula and selected additional financial data results in an 87.3% out-of-sample accuracy in CDS approximations. The transparency property of this algorithm confirms the predominance of the E2C estimate, and the impact of companies' debt rating and size, in predicting their CDS.
    Keywords: Structural Model,Finance,Random Forests,Credit Default Swaps,Risk Analysis
    Date: 2019–08
  7. By: Juan M. Londono; Nancy R. Xu
    Abstract: We examine the commonality in international equity risk premiums by linking empirical evidence for the international stock return predictability of US downside and upside variance risk premiums (DVP and UVP, respectively) with implications from an international asset pricing framework, which takes the perspective of a US/global investor and features asymmetric global macroeconomic, financial market, and risk aversion shocks. We find that DVP and UVP predict international stock returns through different global equity risk premium determinants: bad and good macroeconomic uncertainties, respectively. Across countries, US investors demand lower macroeconomic risk compensation but higher financial market risk compensation for more-integrated countries.
    Keywords: Downside variance risk premium; Upside variance risk premium; International stock markets; Asymmetric state variables; Stock return predictability
    JEL: F36 G12 G13 G15
    Date: 2021–05–18
  8. By: Alejandro García; Josef Schroth
    Abstract: Countercyclical capital buffers are regulatory measures developed in response to the global financial crisis of 2008–09. This note focuses on how time-varying capital buffers can improve financial stability in Canada.
    Keywords: Business fluctuations and cycles; Credit and credit aggregates; Credit risk management; Financial stability; Financial system regulation and policies; Lender of last resort
    JEL: E44
    Date: 2021–06
  9. By: Mathieu Mercadier (Groupe ESC Clermont); Frank Strobel (University of Birmingham)
    Abstract: We derive a one-sided Vysochanskii-Petunin inequality, providing probability bounds for random variables analogous to those given by Cantelli's inequality under the additional assumption of unimodality, potentially relevant for applied statistical practice across a wide range of disciplines. As a possible application of this inequality in a financial context, we examine refined bounds for the individual risk measure of Value-at-Risk, providing a potentially useful alternative benchmark with interesting regulatory implications for the Basel multiplier.
    Keywords: OR in banking,finance,risk management,risk analysis
    Date: 2021–02
  10. By: Renée Fry-McKibbin; Matthew Greenwood-Nimmo; Cody Yu-Ling Hsiao; Lin Qi
    Abstract: We study the distribution of equity returns in the G20 equity markets to test for contagion following the first official report of a COVID19 case in China in December 2019 and the subsequent announcement of a global pandemic in March 2020. We find evidence of contagion of Chinese equity market tail risk in early 2020 followed by widespread evidence of contagion across multiple channels from the U.S. to G20 equity markets after the pandemic announcement. Our results suggest that global equity markets may be exposed to unpriced pandemic risk factors with implications for portfolio diversification, risk management and financial stability.
    Keywords: Financial Contagion, Comoment Contagion Tests
    JEL: C32 E31 E32
    Date: 2021–04
  11. By: Gianni De Nicolò; Nataliya Klimenko; Sebastian Pfeil; Jean-Charles Rochet
    Abstract: We build a stylized dynamic general equilibrium model with financial frictions to analyze costs and benefits of capital requirements in the short-term and long-term. We show that since increasing capital requirements limits the aggregate loan supply, the equilibrium loan rate spread increases, which raises bank profitability and the market-to-book value of bank capital. Hence, banks build up larger capital buffers which (i) lowers the public losses in case of a systemic crisis and (ii) restores the banking sector’s lending capacity after the short-term credit crunch induced by tighter regulation. We confirm our model’s dynamic implications in a panel VAR estimation, which suggests that bank lending has even increased in the long-run after the implementation of Basel III capital regulation.
    Keywords: bank capital requirements, credit crunch, systemic risk
    JEL: E21 E32 F44 G21 G28
    Date: 2021
  12. By: Dimitris Bertsimas; Agni Orfanoudaki
    Abstract: As machine learning algorithms start to get integrated into the decision-making process of companies and organizations, insurance products will be developed to protect their owners from risk. We introduce the concept of algorithmic insurance and present a quantitative framework to enable the pricing of the derived insurance contracts. We propose an optimization formulation to estimate the risk exposure and price for a binary classification model. Our approach outlines how properties of the model, such as accuracy, interpretability and generalizability, can influence the insurance contract evaluation. To showcase a practical implementation of the proposed framework, we present a case study of medical malpractice in the context of breast cancer detection. Our analysis focuses on measuring the effect of the model parameters on the expected financial loss and identifying the aspects of algorithmic performance that predominantly affect the price of the contract.
    Date: 2021–06
  13. By: Afees A. Salisu (Centre for Econometric and Allied Research, University of Ibadan, Ibadan, Nigeria); Elie Bouri (Adnan Kassar School of Business, Lebanese American University, Beirut, Lebanon); Rangan Gupta (Department of Economics, University of Pretoria, Private Bag X20, Hatfield, 0028, South Africa)
    Abstract: In this study, we make a three-fold contribution to the literature on gold market analysis. First, we provide evidence for the predictive value of US Nonfarm Payroll (USNP) in the out-of-sample forecast of gold market volatility. Second, we extend our analysis to other precious metals and the US stock market index for robustness purposes. Third, we utilize mixed data frequencies based on the availability of data, thus, circumventing any bias or information loss due to the use of monthly (low frequency) USNP data and daily (high frequency) gold price data. The results show that the USNP, which reflects gain/loss in US non-farm jobs, is negatively related to gold return volatility implying that deterioration (improvement) in the economy due to job losses (gains) raises (lowers) the gold market volatility as its trading improves (deteriorates) while the reverse is the case for US stocks. The out-of-sample predictive value of USNP in the return volatility of gold is also established as the model which includes the former offers better out-of-sample forecast gains than the benchmark model which ignores it. Additional analyses involving other precious metals, namely palladium, platinum, rhodium, and silver, show the same direction of relationship as gold, albeit with higher forecast gains for silver than the others. Our findings have useful implications for financial analysts and investors.
    Keywords: Gold market volatility, US Nonfarm Payroll, Out-of-sample predictability, GARCH-MIDAS
    JEL: E31 F47 J21 J23
    Date: 2021–06
  14. By: Piero Quatto; Gianmarco Vacca; Maria Grazia Zoia
    Abstract: Recently, an approach to modeling portfolio distribution with risk factors distributed as Gram-Charlier (GC) expansions of the Gaussian law, has been conceived. GC expansions prove effective when dealing with moderately leptokurtic data. In order to cover the case of possibly severe leptokurtosis, the so-called GC-like expansions have been devised by reshaping parent leptokurtic distributions by means of orthogonal polynomials specific to them. In this paper, we focus on the hyperbolic-secant (HS) law as parent distribution whose GC-like expansions fit with kurtosis levels up to 19.4. A portfolio distribution has been obtained with risk factors modeled as GClike expansions of the HS law which duly account for excess kurtosis. Empirical evidence of the workings of the approach dealt with in the paper is included.
    Date: 2021–06
  15. By: Axel A. Araneda
    Abstract: The exponentially weighted moving average (EMWA) could be labeled as a competitive volatility estimator, where its main strength relies on computation simplicity, especially in a multi-asset scenario, due to dependency only on the decay parameter, $\lambda$. But, what is the best election for $\lambda$ in the EMWA volatility model? Through a large time-series data set of historical returns of the top US large-cap companies; we test empirically the forecasting performance of the EWMA approach, under different time horizons and varying the decay parameter. Using a rolling window scheme, the out-of-sample performance of the variance-covariance matrix is computed following two approaches. First, if we look for a fixed decay parameter for the full sample, the results are in agreement with the RiskMetrics suggestion for 1-month forecasting. In addition, we provide the full-sample optimal decay parameter for the weekly and bi-weekly forecasting horizon cases, confirming two facts: i) the optimal value is as a function of the forecasting horizon, and ii) for lower forecasting horizons the short-term memory gains importance. In a second way, we also evaluate the forecasting performance of EWMA, but this time using the optimal time-varying decay parameter which minimizes the in-sample variance-covariance estimator, arriving at better accuracy than the use of a fixed-full-sample optimal parameter.
    Date: 2021–05
  16. By: Denny IRAWAN; OKIMOTO Tatsuyoshi
    Abstract: This study examines the conditional capital surplus and shortfall dynamics of renewable and non-renewable resource firms. To this end, this study uses the systemic risk index by Brownlees and Engle (2017) and considers two conditional systemic events, namely, the stock market crash and the commodity price crash. The results indicate that companies in the resource sector tended to have conditional capital shortfalls before 2000 and conditional capital surpluses after 2000 owing to the boom of the commodity sector stock prices and the careful capital management adopted by these companies. The analysis using the panel vector autoregressive model indicates that commodity price, geopolitical, and economic policy uncertainties have a positive impact on the conditional capital shortfall. These uncertainties have also been proven to increase the conditional failure probability of firms in the sample. Lastly, the analysis of performance shows that conditional capital shortfall positively affects market returns, reflecting a high-risk, high-return trade-off for this sector.
    Date: 2021–04
  17. By: Julien Hok; Sergei Kucherenko
    Abstract: Local volatility models usually capture the surface of implied volatilities more accurately than other approaches, such as stochastic volatility models. We present the results of application of Monte Carlo (MC) and Quasi Monte Carlo (QMC) methods for derivative pricing and risk analysis based on Hyperbolic Local Volatility Model. In high-dimensional integration QMC shows a superior performance over MC if the effective dimension of an integrand is not too large. In application to derivative pricing and computation of Greeks effective dimensions depend on path discretization algorithms. The results presented for the Asian option show the superior performance of the Quasi Monte Carlo methods especially for the Brownian Bridge discretization scheme.
    Date: 2021–06
  18. By: Gorovyy, Sergiy; Kelly, Patrick; Kuzmina, Olga
    Abstract: Using a proprietary database that tracks secrecy with respect to a hedge fund's own investors, we find few benefits to own-investor secrecy. These findings contrast with research on secrecy regarding public disclosure. Secretive funds do not outperform transparent funds, and significantly underperform their strategy-matched peers through the financial crisis, consistent with secretive funds loading on unmeasured risks, but inconsistent with own-investor secrecy signalling skill. Though no different in terms of portfolio concentration and leverage, secretive funds are larger, less liquid, more complex, and more likely to file 13F disclosures and request confidential treatment from those disclosures. Secretive funds have lower flow-to-performance sensitivity, even controlling for illiquidity, suggesting that investors do view secretive and transparent funds differently.
    Keywords: Disclosure; Hedge Funds; risk premia; Secrecy; transparency
    JEL: G01 G11 G23 G32
    Date: 2020–06
  19. By: Duc Khuong Nguyen; Dinh-Tri Vo
    Abstract: We investigate the relationship between Enterprise Risk Management (ERM) adoption and solvency for publicly listed insurers in the European Union. Our results, which control for endogeneity problem, show that ERM-adoption insurers experience a decrease in their solvency level, which may trigger their financial vulnerability in the case of unexpected shocks. Firmspecific characteristics such as leverage, ROA, combined-ratio and business type are also found to significantly increase the EU insurers? solvency, whereas the impact of firm size and age is insignificant. Moreover, insurers that have adopted the ERM share the common characteristics of higher performance, higher leverage, bigger size, and more diversified businesses. Finally, the demand of the market is an important factor of ERM adoption and insurance solvency.
    Keywords: risk management, ERM, insurance, solvency
    JEL: G22 G31 G34
    Date: 2021–01–01
  20. By: van Binsbergen, Jules H.
    Abstract: Interest rates across maturities have dropped to all-time low levels around the world. These unexpected shocks to discount rates have an important effect on the valuation of long duration assets. To quantify this effect, I construct a number of counterfactual fixed income portfolios that match the duration of the dividend strips of the aggregate stock market. I show that such fixed income portfolios have performed as well, if not better, than the U.S. stock market in the past five decades, while exhibiting similar (or higher) levels of volatility. Therefore, investors have received little to no compensation for taking long duration nominal dividend risk in the past half century. Further, if anything, stocks seem to have too little volatility (not excess volatility) compared to these fixed income counterfactuals. I discuss several explanations for these findings, including a secular decline in economic growth rates, dividends' potential to hedge against inflation, as well as the diversification of dividend risk across maturities. These results also have important implications for research on the cross-section of stock returns and capital structure.
    Keywords: COVID-19; growth; Stock Market Performance
    Date: 2020–06
  21. By: Vacca, Valerio Paolo; Bichlmeier, Fabian; Biraschi, Paolo; Boschi, Natalie; Álvarez, Antonio J. Bravo; Di Primio, Luciano; Ebner, André; Hoeretzeder, Silvia; Ballesteros, Elisa Llorente; Miani, Claudia; Ricci, Giacomo; Santioni, Raffaele; Schellerer, Stefan; Westman, Hanna
    Abstract: The crisis management framework for banks in the European Union (EU) requires the resolution authorities to identify the existence of a public interest to resolve an ailing bank, rather than to open normal insolvency proceedings (NIPs). The Public Interest Assessment (PIA) determines whether resolution objectives, including the safeguard of financial stability, can be better preserved using resolution tools than NIPs .This paper provides a contribution to the ongoing discussion on the implementation of the PIA, by presenting an analytical framework to quantify the potential impact on the real economy stemming from a bank’s failure under NIPs through the interruption of the lending activity (“credit channel”). The framework is harmonized across the jurisdictions belonging to the Banking Union and aims to improve the quantitative leg of the PIA, to be coupled with qualitative elements. In a first step, we quantify the potential credit shortfall faced by firms and households due to the abrupt closure of a bank. In a second step, the impact of the credit shortfall on real outcomes is estimated via a FAVAR model and via a micro-econometric model. Reference values are provided to assess the relevance of the estimated outcomes. The illustrative results show that such a harmonized approach can be applied across the Banking Union and to banks of heterogeneous size. In case of mid-sized banks, this common analytical framework could reduce the uncertainty regarding the extent to which the failure of the institution could have a negative impact to the real economy if the lending activity is interrupted as possibly the case under NIPs. JEL Classification: E58, G01, G21, G28
    Keywords: bank insolvency, bank lending, bank resolution, EU crisis management framework, public interest assessment
    Date: 2021–06
  22. By: Acharya, Viral V.; Bhadury, Soumya; Surti, Jay
    Abstract: This paper introduces a new financial vulnerability index for emerging market economies by exploiting key differences in their business cycles relative to those of advanced economies. Information on the domestic price of risk, cost of dollar hedging and market-based measures of bank vulnerability combine to generate indexes significantly more effective in capturing macro-financial vulnerability and stress compared to those based on information in trade and global factors. Our index significantly augments early warning surveillance capacity, as evidenced by out-of-sample forecasting gains around a majority of turning points in GDP growth relative to distributed lag models that are augmented with information from macro-financial indexes that are custom-built to optimize such forecasts.
    Keywords: business cycles; early warning indicators; financial conditions; price of risk; Vulnerability
    JEL: C53 E32 E44
    Date: 2020–06
  23. By: Knut Are Aastveit (BI Norwegian Business School); Jamie Cross (BI Norwegian Business School); Herman K. van Dijk (Erasmus University Rotterdam)
    Abstract: We propose a novel and numerically efficient quantification approach to forecast uncertainty of the real price of oil using a combination of probabilistic individual model forecasts. Our combination method extends earlier approaches that have been applied to oil price forecasting, by allowing for sequentially updating of time-varying combination weights, estimation of time-varying forecast biases and facets of miscalibration of individual forecast densities and time-varying inter-dependencies among models. To illustrate the usefulness of the method, we present an extensive set of empirical results about time-varying forecast uncertainty and risk for the real price of oil over the period 1974-2018. We show that the combination approach systematically outperforms commonly used benchmark models and combination approaches, both in terms of point and density forecasts. The dynamic patterns of the estimated individual model weights are highly time-varying, reflecting a large time variation in the relative performance of the various individual models. The combination approach has built-in diagnostic information measures about forecast inaccuracy and/or model set incompleteness, which provide clear signals of model incompleteness during three crisis periods. To highlight that our approach also can be useful for policy analysis, we present a basic analysis of profit-loss and hedging against price risk.
    Keywords: Oil price, Forecast density combination, Bayesian forecasting, Instabilities, Model uncertainty
    Date: 2021–06–13
  24. By: Christophe Schalck; Meryem Schalck
    Abstract: The aim of this study is to provide new insights into French small and medium-sized enterprises (SME) failure prediction using a unique database of French SMEs over the 2012?2018 period including both financial and nonfinancial variables. We also include text variables related to the type of activity. We compare the predictive performance of three estimation methods: a dynamic Probit model, logistic Lasso regression, and XGBoost algorithm. The results show that the XGBoost algorithm has the highest performance in predicting business failure from a broad dataset. We use SHAP values to interpret the results and identify the main factors of failure. Our analysis shows that both financial and nonfinancial variables are failure factors. Our results confirm the role of financial variables in predicting business failure, while self-employment is the factor that most strongly increases the probability of failure. The size of the SME is also a business failure factor. Our results show that a number of nonfinancial variables, such as localization and economic conditions, are drivers of SME failure. The results also show that certain activities are associated with a prediction of lower failure probability while some activities are associated with a prediction of higher failure.
    Keywords: SME; failure prediction; Machine learning; XGBoost; SHAP values
    JEL: G33 C41 C46
    Date: 2021–01–01
  25. By: Luca Benzoni; Lorenzo Garlappi; Robert S. Goldstein; Julien Hugonnier; Chao Ying
    Abstract: We investigate optimal capital structure and debt maturity policies in the presence of fixed issuance costs. We identify the global-optimal policy that generates the highest values of equity across all states of nature consistent with limited liability. The optimal policy without commitment provides almost as much tax benefits to debt as does the global-optimal policy and, in the limit of vanishing issuance costs, allows firms to extract 100% of EBIT. This limiting case does not converge to the equilibrium of DeMarzo and He (2019), who report no tax benefits to debt when issuance costs are set to zero at the outset.
    Keywords: Capital Structure; Bankruptcy; Issuance Costs; Commitment; Coase Conjecture; Credit Spreads; Asset Pricing; Trading Volume; Bond Interest Rates; Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill; Liquidation
    JEL: G12 G32 G33
    Date: 2020–10–14

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