nep-rmg New Economics Papers
on Risk Management
Issue of 2023‒09‒04
nineteen papers chosen by
Stan Miles, Thompson Rivers University

  1. Same same but different: credit risk provisioning under IFRS 9 By Behn, Markus; Couaillier, Cyril
  2. Monitoring multicountry macroeconomic risk By Dimitris Korobilis; Maximilian Schröder
  3. Analysis of bank leverage via dynamical systems and deep neural networks By Lillo, Fabrizio; Livieri, Giulia; Marmi, Stefano; Solomko, Anton; Vaienti, Sandro
  4. How Do Financial Crises Redistribute Risk? By Kris J. Mitchener; Angela Vossmeyer; Kris James Mitchener
  5. Option Smile Volatility and Implied Probabilities: Implications of Concavity in IV Curves By Darsh Kachhara; John K. E Markin; Astha Singh
  6. ESG criteria and the credit risk of corporate bond portfolios By Höck, André; Bauckloh, Michael Tobias; Dumrose, Maurice; Klein, Christian
  7. Stock Market Bubbles and the Realized Volatility of Oil Price Returns By Rangan Gupta; Chien-Chiang Lee; Joshua Nielsen; Christian Pierdzioch
  8. Uniform Confidence/Certainty Estimation By Arnold, Rob
  9. The Effect of COVID-19 Transmission on Cryptocurrencies By Nesrine Dardouri; Abdelkader Aguir; Mounir Smida
  10. COVID-19, Mobility Restriction Policies and Stock Market Volatility: A Cross-Country Empirical Study By Richard Mawulawoea Ahadzie; Dan Daugaard; Moses Kangogo; Faisal Khan; Joaquin Vespignani
  11. The state-dependent impact of changes in bank capital requirements By Lang, Jan Hannes; Menno, Dominik
  12. FinPT: Financial Risk Prediction with Profile Tuning on Pretrained Foundation Models By Yuwei Yin; Yazheng Yang; Jian Yang; Qi Liu
  13. How to measure inFLAtion volatility. A note By Alfredo García-Hiernaux; María T. González-Pérez; David E. Guerrero
  14. The spillover effect of managerial taxes on mutual fund risk-taking By Bührle, Anna Theresa; Yen, Chia-Yi
  15. A Non-Parametric Test of Risk Aversion By Jacob K Goeree; Bernardo Garcia-Pola
  16. Investors’ Attitude toward Stock Market Risk-A Chittagong Perspective By Islam, Ayub; Chowdhury, Emon Kalyan
  17. Time-varying ambiguity shocks and business cycles By Takao Asano; Xiaojing Cai; Ryuta Sakemoto
  18. Risk-sharing and optimal contracts with large exogenous risks By Jessica Martin; Stéphane Villeneuve
  19. Analysis of the usability of capital buffers during the crisis precipitated by COVID-19 By Luis Fernández Lafuerza; Matías Lamas; Javier Mencía; Irene Pablos; Raquel Vegas

  1. By: Behn, Markus; Couaillier, Cyril
    Abstract: We analyse the impact of the adoption of expected credit loss accounting (IFRS 9) on the timeliness and potential procyclicality of banks’ loan loss provisioning. We use granular loan-level data from the euro area’s credit register and investigate both firm-level credit events and macroeconomic shocks (2020 COVID-19 pandemic, 2022 energy price shock). We find that provisions under the new standard are higher before default and more responsive to shocks. However, the majority of provisioning still occurs at the time of default and the dynamics around default events are similar to pre-existing national standards. Additionally, banks with a larger capital headroom provision significantly more, particularly for loans using IFRS 9. This suggests a higher risk of underprovisioning for less capitalized banks. JEL Classification: G21, G28, G32
    Keywords: bank regulation, credit risk, financial stability, loan loss accounting
    Date: 2023–08
  2. By: Dimitris Korobilis; Maximilian Schröder
    Abstract: We propose a multicountry quantile factor augmeneted vector autoregression (QFAVAR) to model heterogeneities both across countries and across characteristics of the distributions of macroeconomic time series. The presence of quantile factors allows for summarizing these two heterogeneities in a parsimonious way. We develop two algorithms for posterior inference that feature varying level of trade-off between estimation precision and computational speed. Using monthly data for the euro area, we establish the good empirical properties of the QFAVAR as a tool for assessing the e ects of global shocks on country-level macroeconomic risks. In particular, QFAVAR short-run tail forecasts are more accurate compared to a FAVAR with symmetric Gaussian errors, as well as univariate quantile autoregressions that ignore comovements among quantiles of macroeconomic variables. We also illustrate how quantile impulse response functions and quantile connectedness measures, resulting from the new model, can be used to implemennt joint risk scenario analysis.
    Keywords: quantile VAR, MCMC, variational Bayes, dynamic factor model.
    JEL: C11 C32 E31 E32 E37 E66
    Date: 2023–06–15
  3. By: Lillo, Fabrizio; Livieri, Giulia; Marmi, Stefano; Solomko, Anton; Vaienti, Sandro
    Abstract: We consider a model of a simple financial system consisting of a leveraged investor that invests in a risky asset and manages risk by using value-at-risk (VaR). The VaR is estimated by using past data via an adaptive expectation scheme. We show that the leverage dynamics can be described by a dynamical system of slow-fast type associated with a unimodal map on [0, 1] with an additive heteroscedastic noise whose variance is related to the portfolio rebalancing frequency to target leverage. In absence of noise the model is purely deterministic and the parameter space splits into two regions: (i) a region with a globally attracting fixed point or a 2-cycle; (ii) a dynamical core region, where the map could exhibit chaotic behavior. Whenever the model is randomly perturbed, we prove the existence of a unique stationary density with bounded variation, the stochastic stability of the process, and the almost certain existence and continuity of the Lyapunov exponent for the stationary measure. We then use deep neural networks to estimate map parameters from a short time series. Using this method, we estimate the model in a large dataset of US commercial banks over the period 2001-2014. We find that the parameters of a substantial fraction of banks lie in the dynamical core, and their leverage time series are consistent with a chaotic behavior. We also present evidence that the time series of the leverage of large banks tend to exhibit chaoticity more frequently than those of small banks.
    Keywords: leverage cycles; Lyapunov exponents; neural networks; random dynamical systems; risk management; systemic risk; unimodal maps;
    JEL: F3 G3 C1
    Date: 2023
  4. By: Kris J. Mitchener; Angela Vossmeyer; Kris James Mitchener
    Abstract: We examine how financial crises redistribute risk, employing novel empirical methods and micro data from the largest financial crisis of the 20th century – the Great Depression. Using balance-sheet and systemic risk measures at the bank level, we build an econometric model with incidental truncation that jointly considers bank survival, the type of bank closure (consolidations, absorption, and failures), and changes to bank risk. Despite roughly 9, 000 bank closures, risk did not leave the financial system; instead, it increased. We show that risk was redistributed to banks that were healthier prior to the financial crisis. A key mechanism driving the redistribution of risk was bank acquisition. Each acquisition increases the balance-sheet and systemic risk of the acquiring bank by 25%. Our findings suggest that financial crises do not quickly purge risk from the system, and that merger policies commonly used to deal with troubled financial institutions during crises have important implications for systemic risk.
    Keywords: Bayesian inference, financial crises, sample selection, mergers, banking networks
    JEL: G21 C30 N12
    Date: 2023
  5. By: Darsh Kachhara; John K. E Markin; Astha Singh
    Abstract: Earnings announcements (EADs) are corporate events that provide investors with fundamentally important information. The prospect of stock price rises may also contribute to EADs increased volatility. Using data on extremely short term options, we study that bimodality in the risk neutral distribution and concavity in the IV smiles are ubiquitous characteristics before an earnings announcement day. This study compares the returns between concave and non concave IV smiles to see if the concavity in the IV curve leads to any information about the risk in the market and showcases how investors hedge against extreme volatility during earnings announcements. In fact, our paper shows in the presence of concave IV smiles; investors pay a significant premium to hedge against the uncertainty caused by the forthcoming announcement.
    Date: 2023–07
  6. By: Höck, André; Bauckloh, Michael Tobias; Dumrose, Maurice; Klein, Christian
    Abstract: Demand for sustainable fixed-income investment solutions is surging but there is hardly research on the impact of sustainability on the risk characteristics of fixed-income portfolios. This study examines the impact of sustainability on the credit risk exposure of U.S. corporate bond portfolios between 2013 and 2020 by analyzing the returns of sustainable and non-sustainable portfolios using two different asset pricing models and environmental, social, and governance (ESG) ratings from different providers. Controlling for a set of portfolio characteristics, our results show that sustainable portfolios are significantly less exposed to credit risk than their non-sustainable peer portfolios. This finding implies that considering ESG criteria in portfolio management is a suitable means to systematically manage credit risk. Being the first study to investigate the relationship between sustainability and credit risk on portfolio level, this study contributes to the understanding of the effects of ESG criteria in portfolio management and provides academics and investment professionals with valuable insights.
    Keywords: Sustainability, Credit risk management, Corporate bonds
    JEL: G12 G32 Q56
    Date: 2023
  7. By: Rangan Gupta (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa); Chien-Chiang Lee (School of Economics and Management, Nanchang University, Nanchang, China); Joshua Nielsen (Department of Economics, University of Pretoria, Private Bag X20, Hatfield 0028, South Africa); Christian Pierdzioch (Department of Economics, Helmut Schmidt University, Holstenhofweg 85, P.O.B. 700822, 22008 Hamburg, Germany)
    Abstract: Using monthly data for the G7 countries from 1973 to 2020, we study whether stock market bubbles help to forecast out-of-sample the realized volatility of oil price returns. We use the Multi-Scale Log-Periodic Power Law Singularity Confidence Indicator (MS-LPPLS-CI) approach to identify both positive and negative bubbles in the short-, medium, and long-term. First, we successfully detect major crashes and rallies using the MS-LPPLS-CIs. Having established the relevance of the bubbles indicators, and given the large number of them, we use widelystudied shrinkage (Lasso, elastic net, ridge regression) approaches to estimate our forecasting models. We find that stock market bubbles have predictive value for realized volatility at a short to intermediate forecast horizon. The number of bubble predictors included in the penalized forecasting models tend to increase in the forecast horizon. We obtain our main finding for the various types of stock market bubbles, and for good and bad realized volatilities.
    Keywords: Realized volatility, Oil price, Stock market bubbles, Forecasting, Shrinkage estimators
    JEL: C22 C53 G15 Q02
    Date: 2023–08
  8. By: Arnold, Rob
    Abstract: Uniform Confidence/Certainty Estimation (UC2) is an approach and set of tools that address several issues that are common in risk estimation techniques. Deployed between analysis and modeling, UC2 brings uniformity and interoperability that improve risk model results and improve stakeholder engagement. Its unique features correctly capture confidence and certainty and improve interoperability between data-driven and expert-derived risk estimates and the models that consume them. In turn, UC2 increases uniformity, transparency, and stakeholder engagement, without ripping and replacing existing risk models or analytical workflows.
    Keywords: Risk modeling; Risk analysis; Risk estimation; Scales; Confidence; Certainty; Accuracy and Precision; Quantitative; Qualitative; Objective; Subjective; Binomial probability; Probability distribution
    JEL: C13 C51 C53 D81 D83
    Date: 2023–08–07
  9. By: Nesrine Dardouri; Abdelkader Aguir (ESPI - Ecole Supérieure des Professions Immobilières); Mounir Smida (Université de Sousse)
    Abstract: In recent years, Bitcoin and other cryptocurrencies like Ethereum and Dogecoin have emerged as important asset classes in general, and diversification and hedging instruments in particular. The recent COVID-19 pandemic has provided the chance to examine and assess cryptocurrencies' behavior during extremely stressful times. The methodology of this study is based on an estimate using the ARDL model from 22 January 2020 to 12 March 2021, allowing us to analyze the long-term and short-term relationship between cryptocurrencies and COVID-19. Our results demonstrate that there is cointegration between the chosen cryptocurrencies in the market and COVID-19. The results indicate that Bitcoin, ETH, and DOGE prices were affected by COVID-19, which means that the pandemic seriously affected the three cryptocurrency prices.
    Keywords: COVID-19, coronavirus, cryptocurrency, price volatility, liquidity
    Date: 2023–07–27
  10. By: Richard Mawulawoea Ahadzie; Dan Daugaard; Moses Kangogo; Faisal Khan; Joaquin Vespignani
    Abstract: This study investigates the impact of COVID-19 infections and mobility restriction policies on stock market volatility. We estimate panel data models for seven countries using daily data from February 12, 2020 to April 14, 2021. Our results show that the number of new cases of COVID-19 infections and the introduction of mobility restriction policies plays a crucial role in shaping stock market volatility during the pandemic. We found that new cases of COVID-19 infections and mobility restrictions policies increase stock market jumps, rather than increase continuous volatility. We also find that mobility restriction policies lessen the impact of new COVID-19 cases on stock market volatility.
    Keywords: Stock Market Volatility, New Cases of COVID-19 Infections, Mobility Restriction Policies
    JEL: G10 G11 G12
    Date: 2023–08
  11. By: Lang, Jan Hannes; Menno, Dominik
    Abstract: Based on a non-linear equilibrium model of the banking sector with an occasionally binding equity issuance constraint, we show that the economic impact of changes in bank capital requirements depends on the state of the macro-financial environment. In 'normal' states where banks do not face problems to retain enough profits to satisfy higher capital requirements, the impact on bank loan supply works through a 'pricing channel' which is small: around 0.1% less loans for a 1pp increase in capital requirements. In 'bad' states where banks are not able to come up with sufficient equity to satisfy capital requirements, the impact on loan supply works through a 'quantity channel', which acts like a financial accelerator and can be very large: up to 10% more loans for a capital requirement release of 1pp. Compared to existing DSGE models with a banking sector, which usually feature a constant lending response of around 1%, our state-dependent impact is an order of magnitude lower in 'normal' states and an order of magnitude higher in 'bad' states. Our results provide a theoretical justification for building up a positive countercyclical capital buffer in 'normal' macro-financial environments.
    Keywords: Bank capital requirements, loan supply, dynamic stochastic equilibrium model, financial accelerator, global solution methods
    JEL: D21 E44 E51 G21 G28
    Date: 2023
  12. By: Yuwei Yin; Yazheng Yang; Jian Yang; Qi Liu
    Abstract: Financial risk prediction plays a crucial role in the financial sector. Machine learning methods have been widely applied for automatically detecting potential risks and thus saving the cost of labor. However, the development in this field is lagging behind in recent years by the following two facts: 1) the algorithms used are somewhat outdated, especially in the context of the fast advance of generative AI and large language models (LLMs); 2) the lack of a unified and open-sourced financial benchmark has impeded the related research for years. To tackle these issues, we propose FinPT and FinBench: the former is a novel approach for financial risk prediction that conduct Profile Tuning on large pretrained foundation models, and the latter is a set of high-quality datasets on financial risks such as default, fraud, and churn. In FinPT, we fill the financial tabular data into the pre-defined instruction template, obtain natural-language customer profiles by prompting LLMs, and fine-tune large foundation models with the profile text to make predictions. We demonstrate the effectiveness of the proposed FinPT by experimenting with a range of representative strong baselines on FinBench. The analytical studies further deepen the understanding of LLMs for financial risk prediction.
    Date: 2023–07
  13. By: Alfredo García-Hiernaux (DANAE and ICAE); María T. González-Pérez (Banco de España); David E. Guerrero (CUNEF)
    Abstract: This paper proposes a statistical model and a conceptual framework to estimate inflation volatility assuming rational inattention, where the decay in the level of attention reflects the arrival of news in the market. We estimate trend inflation and the conditional inflation volatility for Germany, Spain, the euro area and the United States using monthly data from January 2002 to March 2022 and test whether inflation was equal to or below 2% in this period in these regions. We decompose inflation volatility into positive and negative surprise components and characterise different inflation volatility scenarios during the Great Financial Crisis, the Sovereign Debt Crisis, and the post-COVID period. Our volatility measure outperforms the GARCH(1, 1) model and the rolling standard deviation in one-step ahead volatility forecasts both in-sample and out-of-sample. The methodology proposed in this article is appropriate for estimating the conditional volatility of macro-financial variables. We recommend the inclusion of this measure in inflation dynamics monitoring and forecasting exercises.
    Keywords: inflation, inflation trend, inflation volatility, rational inattention, positive and negative surprises.
    JEL: C22 C32 E3 E4 E5
    Date: 2023–06
  14. By: Bührle, Anna Theresa; Yen, Chia-Yi
    Abstract: When faced with higher managerial taxes, mutual fund managers who personally invest in the funds they manage take on greater risk. By exploiting the enactment of the American Taxpayer Relief Act 2012 as an exogenous tax shock, we observe that co-investing fund managers increase risk-taking by 8%. Specifically, these managers adjust their portfolios by investing in stocks with higher beta. The observed effect appears to be driven by agency incentives, particularly for funds with a more convex flow-performance relationship and for managers who have underperformed compared to their peers in the past two years. Such tax-induced behavior is associated with negative fund performance. We highlight the role of co-investment in transmitting managerial tax shocks to mutual funds.
    Keywords: risk-taking, taxation, mutual funds, co-investment
    JEL: G11 G18 G23 H24
    Date: 2023
  15. By: Jacob K Goeree; Bernardo Garcia-Pola
    Abstract: In economics, risk aversion is modeled via a concave Bernoulli utility within the expected-utility paradigm. We propose a simple test of expected utility and concavity. We find little support for either: only 30 percent of the choices are consistent with a concave utility, only two out of 72 subjects are consistent with expected utility, and only one of them fits the economic model of risk aversion. Our findings contrast with the preponderance of seemingly "risk-averse" choices that have been elicited using the popular multiple-price list methodology, a result we replicate in this paper. We demonstrate that this methodology is unfit to measure risk aversion, and that the high prevalence of risk aversion it produces is due to parametric misspecification.
    Date: 2023–08
  16. By: Islam, Ayub; Chowdhury, Emon Kalyan
    Abstract: The purpose of this study is to examine the extent to which investor awareness and perceived risk attitudes affect stock market investors’ behavior in the Chittagong Stock Exchange (CSE). CSE performances do not reflect the attitude of investors in this market and bridging the gap between these two is the main objective of this research. This study is the ever first to examine the attitude of investors toward stock market risk in CSE. A cross sectional quantitative research is designed using proportional sampling approach. Total 100 investors were selected from different brokerage houses in Chittagong. The questionnaire includes four parts where Likert scale was used to understand their level of risk. This research finds negative relation between investor awareness and their behavior. It finds positive relation between perceived risk attitude and investment behavior. Study also reveals that there is huge scope to orient investors in this market as they do not posses necessary knowledge and skill to play active role to give birth of efficient market. Law enforcing authority also needs to be more careful to implement the existing rules to bring back the confidence of investors toward trading system, transparency, practicing corporate governance etc.
    Keywords: Investor’s attitude; stock market; Chittagong Stock Exchange; risk
    JEL: A2 A20
    Date: 2023–03–07
  17. By: Takao Asano (Okayama University); Xiaojing Cai (Okayama University); Ryuta Sakemoto (Okayama University)
    Abstract: This study investigates how ambiguity has driven output and inflation in the U.S. over the past 70 years. We adopt the recently developed techniques that disentangle ambiguity from risk and assess the responses of output and inflation to ambiguity shocks. We observe that an increase in ambiguity led to an increase in output during high inflation periods, indicating the ambiguity lover behavior. We also uncover that ambiguity and risk estimated by realized volatility have the opposite impacts on business cycles, which is consistent with the prevailing asset pricing literature.
    Keywords: Ambiguity, Risk premiums, Uncertainty, TVP-VAR
    JEL: E32 E44
    Date: 2023–08
  18. By: Jessica Martin (IMT - Institut de Mathématiques de Toulouse UMR5219 - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - INSA Toulouse - Institut National des Sciences Appliquées - Toulouse - INSA - Institut National des Sciences Appliquées - UT - Université de Toulouse - UT2J - Université Toulouse - Jean Jaurès - UT - Université de Toulouse - UT3 - Université Toulouse III - Paul Sabatier - UT - Université de Toulouse - CNRS - Centre National de la Recherche Scientifique); Stéphane Villeneuve (TSE-R - Toulouse School of Economics - UT Capitole - Université Toulouse Capitole - UT - Université de Toulouse - EHESS - École des hautes études en sciences sociales - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)
    Abstract: What type of delegation contract should be offered when facing a risk of the magnitude of the pandemic we are currently experiencing and how does the likelihood of an exogenous early termination of the relationship modify the terms of a full-commitment contract? We study these questions by considering a dynamic principal-agent model that naturally extends the classical Holmström-Milgrom setting to include a risk of shutdown before the maturity of the contract. We obtain an explicit characterization of the optimal wage along with the optimal action provided by the agent when the shutdown risk is independent of the inherent agency problem. The optimal contract is linear by offering both a fixed share of the output which is similar to the standard shutdown-free Holmström Milgrom model and a linear prevention mechanism that is proportional to the random lifetime of the contract. We then extend the model in two directions. We first allow the agent to control the intensity of the shutdown risk. We also consider a structural agency model where the shutdown risk materializes when the state process hits zero.
    Keywords: Principal-Agent problems, Shutdown risk, Hamilton-Jacobi Bellman equations
    Date: 2023
  19. By: Luis Fernández Lafuerza (BANCO DE ESPAÑA); Matías Lamas (BANCO DE ESPAÑA); Javier Mencía (BANCO DE ESPAÑA); Irene Pablos (BANCO DE ESPAÑA); Raquel Vegas (BANCO DE ESPAÑA)
    Abstract: This paper analyses the ability of banks to use voluntary and regulatory capital buffers, taking advantage of the experience of the COVID-19 pandemic. In the first place, we find that the usability of macroprudential buffers is not hampered in Spain by other parallel banks’ requirements. Additionally, we find that the existing voluntary buffers over capital requirements at the beginning of the pandemic have had significant effects on the financial markets, affecting the evolution of European bank stock prices, as well as the holdings of bank shares by investment funds. Lastly, we find no significant aggregate effect of voluntary capital buffers on the provision of financing to non-financial companies in Spain. However, we do identify negative effects in the supply of credit from banks with lower voluntary buffers to companies with which they had more recent relationships. Likewise, if the analysis is carried out exclusively on credit operations without public guarantees, we observe that those banks with lower voluntary capital buffers reduced credit more.
    Keywords: capital usability, voluntary capital buffers, bank stock prices, provision of credit
    JEL: G20 G21 G28
    Date: 2023–03

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