nep-rmg New Economics Papers
on Risk Management
Issue of 2023‒11‒06
fourteen papers chosen by
Stan Miles, Thompson Rivers University

  1. Corporate FX hedging: An introduction for the corporate treasury By Heidorn, Thomas; Pavicic, Tim; Sieber, Antje
  2. Combining Deep Learning and GARCH Models for Financial Volatility and Risk Forecasting By Jakub Micha\'nk\'ow; {\L}ukasz Kwiatkowski; Janusz Morajda
  3. Estimating systemic risk for non-listed euro-area banks By Engle, Robert F.; Emambakhsh, Tina; Manganelli, Simone; Parisi, Laura; Pizzeghello, Riccardo
  4. Resolving a Clearing Member's Default, A Radner Equilibrium Approach By Dorinel Bastide; St\'ephane Cr\'epey; Samuel Drapeau; Mekonnen Tadese
  5. Bitcoin versus S&P 500 Index: Return and Risk Analysis By A. H. Nzokem
  6. An estimation of the default probabilities of Spanish non-financial corporations and their application to evaluate public policies By Roberto Blanco; Elena Fernández; Miguel García-Posada; Sergio Mayordomo
  7. Changing patterns of risk-sharing channels in the United States and the euro area By Cimadomo, Jacopo; Giuliodori, Massimo; Lengyel, Andras; Mumtaz, Haroon
  8. Risk Aversion and Insurance Propensity By Fabio Maccheroni; Massimo Marinacci; Ruodu Wang; Qinyu Wu
  9. BEAST: A model for the assessment of system-wide risks and macroprudential policies By Budnik, Katarzyna; Groß, Johannes; Vagliano, Gianluca; Dimitrov, Ivan; Lampe, Max; Panos, Jiri; Velasco, Sofia; Boucherie, Louis; Jančoková, Martina
  10. Assessing and mitigating fire sales risk under partial information By Pang, Raymond Ka-Kay; Veraart, Luitgard A. M.
  11. An In-Depth Examination of Requirements for Disclosure Risk Assessment By Ron S. Jarmin; John M. Abowd; Robert Ashmead; Ryan Cumings-Menon; Nathan Goldschlag; Michael B. Hawes; Sallie Ann Keller; Daniel Kifer; Philip Leclerc; Jerome P. Reiter; Rolando A. Rodríguez; Ian Schmutte; Victoria A. Velkoff; Pavel Zhuravlev
  12. Multi-period static hedging of European options By Purba Banerjee; Srikanth Iyer; Shashi Jain
  13. Does age affect the relation between risk and time preferences? Evidence from a representative sample By Zexuan Wang; Ismaël Rafaï; Marc Willinger
  14. Impact of Economic Uncertainty, Geopolitical Risk, Pandemic, Financial & Macroeconomic Factors on Crude Oil Returns -- An Empirical Investigation By Sarit Maitra

  1. By: Heidorn, Thomas; Pavicic, Tim; Sieber, Antje
    Abstract: FX rates are increasingly volatile in recent macroeconomic and geopolitical times of uncertainty. FX risk if not dealt with properly can pose existential threads to companies. Especially fast-growing companies, that have previously not hedged FX risks due to insignificance, need to build up a proper FX risk management. This working paper delivers a comprehensive guide on FX hedging for small and medium enterprises. It should help a treasurer to setup and/or improve their FX hedging approach. The goal of this paper is to provide a treasurer with the necessary tools and knowledge to manage and hedge his company's FX exposure. The paper provides insights on the practical implementation, regulatory framework, and accounting perspective of an FX risk management.
    Keywords: Corporate Treasury, Risk management, Corporate hedging, FX hedging, Foreign currency risk
    JEL: G11 G24 G32 Q56
    Date: 2022
  2. By: Jakub Micha\'nk\'ow; {\L}ukasz Kwiatkowski; Janusz Morajda
    Abstract: In this paper, we develop a hybrid approach to forecasting the volatility and risk of financial instruments by combining common econometric GARCH time series models with deep learning neural networks. For the latter, we employ Gated Recurrent Unit (GRU) networks, whereas four different specifications are used as the GARCH component: standard GARCH, EGARCH, GJR-GARCH and APARCH. Models are tested using daily logarithmic returns on the S&P 500 index as well as gold price Bitcoin prices, with the three assets representing quite distinct volatility dynamics. As the main volatility estimator, also underlying the target function of our hybrid models, we use the price-range-based Garman-Klass estimator, modified to incorporate the opening and closing prices. Volatility forecasts resulting from the hybrid models are employed to evaluate the assets' risk using the Value-at-Risk (VaR) and Expected Shortfall (ES) at two different tolerance levels of 5% and 1%. Gains from combining the GARCH and GRU approaches are discussed in the contexts of both the volatility and risk forecasts. In general, it can be concluded that the hybrid solutions produce more accurate point volatility forecasts, although it does not necessarily translate into superior VaR and ES forecasts.
    Date: 2023–10
  3. By: Engle, Robert F.; Emambakhsh, Tina; Manganelli, Simone; Parisi, Laura; Pizzeghello, Riccardo
    Abstract: The systemic risk measure (SRISK) by V-Lab provides a market view of the vulnerability of financial institutions to a sudden downturn in the economy. To overcome the shortcoming that it cannot be applied to non-listed banks, SRISK characteristics of listed banks are mapped on balance sheet information. Systemic risk tends to be higher for banks that are larger, less profitable and have lower equity funding. Balance sheet information provides a surprisingly good approximation of SRISK for non-listed banks, when compared with banks’ capital depletion from the EU-wide stress testing exercises in 2018 and 2021. The proposed methodology can usefully complement the more thorough overview provided by traditional stress tests, providing supervisors the option to evaluate the systemic risks of the banking system at a higher frequency and at a fraction of the costs. JEL Classification: G21, G28, G1
    Keywords: banks’ balance sheet information content, stress testing, systemic risk
    Date: 2023–10
  4. By: Dorinel Bastide (LaMME); St\'ephane Cr\'epey (LPSM); Samuel Drapeau (LPSM, CMAP); Mekonnen Tadese (LPSM, CMAP)
    Abstract: For vanilla derivatives that constitute the bulk of investment banks' hedging portfolios, central clearing through central counterparties (CCPs) has become hegemonic. A key mandate of a CCP is to provide an efficient and proper clearing member default resolution procedure. When a clearing member defaults, the CCP can hedge and auction or liquidate its positions. The counterparty credit risk cost of auctioning has been analyzed in terms of XVA metrics in Bastide, Cr{\'e}pey, Drapeau, and Tadese (2023). In this work we assess the costs of hedging or liquidating. This is done by comparing pre- and post-default market equilibria, using a Radner equilibrium approach for portfolio allocation and price discovery in each case. We show that the Radner equilibria uniquely exist and we provide both analytical and numerical solutions for the latter in elliptically distributed markets. Using such tools, a CCP could decide rationally on which market to hedge and auction or liquidate defaulted portfolios.
    Date: 2023–10
  5. By: A. H. Nzokem
    Abstract: The S&P 500 index is considered the most popular trading instrument in financial markets. With the rise of cryptocurrencies over the past years, Bitcoin has also grown in popularity and adoption. The paper aims to analyze the daily return distribution of the Bitcoin and S&P 500 index and assess their tail probabilities through two financial risk measures. As a methodology, We use Bitcoin and S&P 500 Index daily return data to fit The seven-parameter General Tempered Stable (GTS) distribution using the advanced Fast Fractional Fourier transform (FRFT) scheme developed by combining the Fast Fractional Fourier (FRFT) algorithm and the 12-point rule Composite Newton-Cotes Quadrature. The findings show that peakedness is the main characteristic of the S&P 500 return distribution, whereas heavy-tailedness is the main characteristic of the Bitcoin return distribution. The GTS distribution shows that $80.05\%$ of S&P 500 returns are within $-1.06\%$ and $1.23\%$ against only $40.32\%$ of Bitcoin returns. At a risk level ($\alpha$), the severity of the loss ($AVaR_{\alpha}(X)$) on the left side of the distribution is larger than the severity of the profit ($AVaR_{1-\alpha}(X)$) on the right side of the distribution. Compared to the S&P 500 index, Bitcoin has $39.73\%$ more prevalence to produce high daily returns (more than $1.23\%$ or less than $-1.06\%$). The severity analysis shows that at a risk level ($\alpha$) the average value-at-risk ($AVaR(X)$) of the bitcoin returns at one significant figure is four times larger than that of the S&P 500 index returns at the same risk.
    Date: 2023–10
  6. By: Roberto Blanco (Banco de España); Elena Fernández (Banco de España); Miguel García-Posada (Banco de España); Sergio Mayordomo (Banco de España)
    Abstract: We model the one-year ahead probability for default of Spanish non-financial corporations using data for the period 1996-2019. While most previous literature considers that a firm is in default if it files for bankruptcy, we define default as having non-performing loans during at least three months of a given year. This broader definition allows us to predict firms’ financial distress at an earlier stage that cannot generally be observed by researchers, before their financial conditions become too severe and they have to file for bankruptcy or engage in private workouts with their creditors. We estimate, by means of logistic regressions, both a general model that uses all the firms in the sample and six models for different size-sector combinations. The selected explanatory variables are five accounting ratios, which summarise firms’ creditworthiness, and the growth rate of aggregate credit to non-financial corporations, to take into account the role of credit availability in mitigating the risk of default. Finally, we carry out two applications of our prediction models: we construct credit rating transition matrices and evaluate a programme implemented by the Spanish government to provide direct aid to firms severely affected by the COVID-19 crisis.
    Keywords: default, financial distress, non-performing loans, logistic regression
    JEL: G30 G33 G21
    Date: 2023–09
  7. By: Cimadomo, Jacopo; Giuliodori, Massimo; Lengyel, Andras; Mumtaz, Haroon
    Abstract: In this paper, we assess how risk-sharing channels have evolved over time in the United States and the Euro Area, and whether they have operated as ‘complements’ or ‘substitutes’. In particular, we focus on the capital channel (income from cross-border ownership of productive assets), the credit channel (interstate or cross-country bank lending), and the fiscal channel (federal or international fiscal transfers). We offer three main contributions. First, we propose a time-varying parameter panel VAR model, with stochastic volatility, which allows us to formally quantify time variation in risk-sharing channels. Second, we develop a new test of the complementarity vs. substitutability hypothesis of the three risk-sharing channels, based on the correlation between the impulse responses of these channels to idiosyncratic output shocks. Third, for the United States, we explain time variation in the risk-sharing channels based on some key macroeconomic and financial variables. JEL Classification: C11, C33, E21, E32
    Keywords: complementarity, risk-sharing channels, substitutability, time variation
    Date: 2023–10
  8. By: Fabio Maccheroni; Massimo Marinacci; Ruodu Wang; Qinyu Wu
    Abstract: We provide a new foundation of risk aversion by showing that the propension to exploit insurance opportunities fully describes this attitude. Our foundation, which applies to any probabilistically sophisticated preference, well accords with the commonly held prudential interpretation of risk aversion that dates back to the seminal works of Arrow (1963) and Pratt (1964). In our main results, we first characterize the Arrow-Pratt risk aversion in terms of propension to full insurance and the stronger notion of risk aversion of Rothschild and Stiglitz (1970) in terms of propension to partial insurance. We then extend the analysis to comparative risk aversion by showing that the notion of Yaari (1969) corresponds to comparative propension to full insurance, while the stronger notion of Ross (1981) corresponds to comparative propension to partial insurance.
    Date: 2023–10
  9. By: Budnik, Katarzyna; Groß, Johannes; Vagliano, Gianluca; Dimitrov, Ivan; Lampe, Max; Panos, Jiri; Velasco, Sofia; Boucherie, Louis; Jančoková, Martina
    Abstract: The Banking Euro Area Stress Test (BEAST) is a large-scale semi-structural model developed to analyse the euro area banking system from a macroprudential perspective. The model combines the dynamics of approximately 90 of the largest euro area banks with those of individual euro area economies. It reflects the heterogeneity of banks by replicat-ing the structure of their balance sheets and profit and loss accounts. Additionally, it allows banks to adjust their assets, funding mix, pricing decisions, management buffers, and profit distribution along with individual bank conditions, including their capital and liquidity re-quirements, and other supervisory limits. The responses of banks impact credit supply con-ditions and have feedback effects on the macroeconomic environment. Stochastic solutions of the model provide a solid foundation for investigating multiple scenarios, deriving at-risk measures, and estimating model uncertainty. The model is regularly utilised to assess the resilience of the euro area banking sector, including in the biennial ECB macroprudential stress tests, as well as to analyse the effects of regulatory, macroprudential, and monetary policy changes. JEL Classification: E37, E58, G21, G28
    Keywords: banking sector deleveraging, macroprudential policy, macro stress test, real economy-financial sector feedback loop
    Date: 2023–10
  10. By: Pang, Raymond Ka-Kay; Veraart, Luitgard A. M.
    Abstract: We consider the problem of assessing and mitigating fire sales risk for banks under partial information. Using data from the European Banking Authority's stress tests, we consider the matrix of asset holdings of different banks. We first analyse fire sales risk under both full and partial information using different matrix reconstruction methods. We then investigate how well some policy interventions aimed at mitigating fire sales risk perform if they are applied based on only partial information. We find that even under partial information, using suitable network reconstruction methods to decide on policy interventions can significantly mitigate risk from fire sales. Furthermore, we show that some interventions based on reconstructed networks significantly outperform ad hoc methods that decide on interventions only based on the size of an institution and do not account for overlapping portfolios.
    Keywords: Systemic risk; fire sales; stress testing; financial networks; matrix reconstruction; policy interventions; PhD Studentship; Elsevier deal
    JEL: G20 G33 G32 G28
    Date: 2023–10–01
  11. By: Ron S. Jarmin; John M. Abowd; Robert Ashmead; Ryan Cumings-Menon; Nathan Goldschlag; Michael B. Hawes; Sallie Ann Keller; Daniel Kifer; Philip Leclerc; Jerome P. Reiter; Rolando A. Rodríguez; Ian Schmutte; Victoria A. Velkoff; Pavel Zhuravlev
    Abstract: The use of formal privacy to protect the confidentiality of responses in the 2020 Decennial Census of Population and Housing has triggered renewed interest and debate over how to measure the disclosure risks and societal benefits of the published data products. Following long-established precedent in economics and statistics, we argue that any proposal for quantifying disclosure risk should be based on pre-specified, objective criteria. Such criteria should be used to compare methodologies to identify those with the most desirable properties. We illustrate this approach, using simple desiderata, to evaluate the absolute disclosure risk framework, the counterfactual framework underlying differential privacy, and prior-to-posterior comparisons. We conclude that satisfying all the desiderata is impossible, but counterfactual comparisons satisfy the most while absolute disclosure risk satisfies the fewest. Furthermore, we explain that many of the criticisms levied against differential privacy would be levied against any technology that is not equivalent to direct, unrestricted access to confidential data. Thus, more research is needed, but in the near-term, the counterfactual approach appears best-suited for privacy-utility analysis.
    Keywords: federal statistical system, data disclosure risk, data access
    Date: 2023–10
  12. By: Purba Banerjee; Srikanth Iyer; Shashi Jain
    Abstract: We consider the hedging of European options when the price of the underlying asset follows a single-factor Markovian framework. By working in such a setting, Carr and Wu \cite{carr2014static} derived a spanning relation between a given option and a continuum of shorter-term options written on the same asset. In this paper, we have extended their approach to simultaneously include options over multiple short maturities. We then show a practical implementation of this with a finite set of shorter-term options to determine the hedging error using a Gaussian Quadrature method. We perform a wide range of experiments for both the \textit{Black-Scholes} and \textit{Merton Jump Diffusion} models, illustrating the comparative performance of the two methods.
    Date: 2023–10
  13. By: Zexuan Wang (CREM - Centre de recherche en économie et management - UNICAEN - Université de Caen Normandie - NU - Normandie Université - UR - Université de Rennes - CNRS - Centre National de la Recherche Scientifique); Ismaël Rafaï (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - UNS - Université Nice Sophia Antipolis (1965 - 2019) - CNRS - Centre National de la Recherche Scientifique - UCA - Université Côte d'Azur); Marc Willinger (CEE-M - Centre d'Economie de l'Environnement - Montpellier - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Montpellier - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement - UM - Université de Montpellier)
    Abstract: We examine the links between age, risk tolerance, and impatience in a large French representative sample. We combine elicited preferences data based on an incentivized web experiment and stated preferences data based on self-reported surveys. Our findings highlight distinct patterns: when considering stated preferences, both risk tolerance and impatience exhibit a decline with age. Higher risk tolerance is associated with higher impatience, and this relationship strengthens with age in the financial domain. In contrast, our analysis of elicited measures uncovers a different dynamic. Specifically, risk tolerance tends to increase with age, while age exhibits no significant influence on impatience. Furthermore, individuals endowed with higher risk tolerance tend to demonstrate lower levels of impatience, irrespective of their age.
    Keywords: age, elicited preferences, risk preferences, stated preferences, time preferences
    Date: 2023
  14. By: Sarit Maitra
    Abstract: This study aims to use simultaneous quantile regression (SQR) to examine the impact of macroeconomic and financial uncertainty including global pandemic, geopolitical risk on the futures returns of crude oil (ROC). The data for this study is sourced from the FRED (Federal Reserve Economic Database) economic dataset; the importance of the factors have been validated by using variation inflation factor (VIF) and principal component analysis (PCA). To fully understand the combined effect of these factors on WTI, study includes interaction terms in the multi-factor model. Empirical results suggest that changes in ROC can have varying impacts depending on the specific period and market conditions. The results can be used for informed investment decisions and to construct portfolios that are well-balanced in terms of risk and return. Structural breaks, such as changes in global economic conditions or shifts in demand for crude oil, can cause return on crude oil to be sensitive to changes in different time periods. The unique aspect ness of this study also lies in its inclusion of explanatory factors related to the pandemic, geopolitical risk, and inflation.
    Date: 2023–10

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