nep-rmg New Economics Papers
on Risk Management
Issue of 2022‒02‒14
23 papers chosen by
Stan Miles
Thompson Rivers University

  1. Hedging cryptos with Bitcoin futures By Liu, Francis; Packham, Natalie; Lu, Meng-Jou; Härdle, Wolfgang
  2. Measuring and stress-testing market-implied bank capital By Martin Indergand; Eric Jondeau; Andreas Fuster
  3. Option-Implied Network Measures of Tail Contagion and Stock Return Predictability By Manuela Pedio
  4. Wage Risk and Portfolio Choice: The Role of Correlated Returns By Johannes König; Maximilian Longmuir
  5. Modeling ex-ante risk premia in the oil market By Georges Prat; Remzi Uctum
  6. Minimum Variance Hedging: Levels versus first Difference By Prehn, Sören
  7. Interaction of Cyclical and Structural Systemic Risks: Insights from Around and After the Global Financial Crisis By Martin Hodula; Jan Janku; Lukas Pfeifer
  8. Vulnerable to the Virus: Globally-Oriented Manufacturing Firms at Risk From the Spread of COVID-19 By SA Quimbo; CT Latinazo; JW Peabody
  9. An unintended consequence of holding dollar assets By Czech, Robert; Huang, Shiyang; Lou, Dong; Wang, Tianyu
  10. Financial Conditions and Macroeconomic Downside Risks in the Euro Area By Lhuissier Stéphane
  11. Modeling and Forecasting Intraday Market Returns: a Machine Learning Approach By Iuri H. Ferreira; Marcelo C. Medeiros
  12. Assessing the Impact of Basel III: Evidence from Structural Macroeconomic Models By Jean-Guillaume Sahuc; Olivier de Bandt; Hibiki Ichiue; Bora Durdu; Yasin Mimir; Jolan Mohimont; Kalin Nikolov; Sigrid Roehrs; Valério Scalone; Michael Straughan
  13. Assessing the Impact of Basel III: Evidence from Structural Macroeconomic Models By Olivier de Bandt; Bora Durdu; Hibiki Ichiue; Yasin Mimir; Jolan Mohimont; Kalin Nikolov; Sigrid Roehrs; Jean-Guillaume Sahuc; Valerio Scalone; Michael Straughan
  14. The repo market under Basel III By Gerba, Eddie; Katsoulis, Petros
  15. New volatility evolution model after extreme events By Mei-Ling Cai; Zhang-HangJian Chen; Sai-Ping Li; Xiong Xiong; Wei Zhang; Ming-Yuan Yang; Fei Ren
  16. Boosting the Forecasting Power of Conditional Heteroskedasticity Models to Account for Covid-19 Outbreaks By Massimo Guidolin; Davide La Cara; Massimiliano Marcellino
  17. Pricing European Options under Stochastic Volatility Models: Case of five-Parameter Gamma-Variance Process By A. H. Nzokem
  18. Risk indeed matters: Uncertainty shocks in an oil-exporting economy By Nurdaulet Abilov
  20. Stablecoins: Growth Potential and Impact on Banking By John Caramichael; Gordon Y. Liao
  21. Supply Chain Risks, Cybersecurity and C-TPAT, a Literature Review By Stephen Sullivan; Diana Garza
  22. On the Real-Time Predictive Content of Financial Conditions Indices for Growth By Aaron Amburgey; Michael W. McCracken
  23. COVID-19 Uncertainty Index in Japan: Newspaper-Based Measures and Economic Activities By Morita, Hiroshi; Ono, Taiki

  1. By: Liu, Francis; Packham, Natalie; Lu, Meng-Jou; Härdle, Wolfgang
    Abstract: The introduction of derivatives on Bitcoin enables investors to hedge risk exposures in cryptocurrencies. Because of volatility swings and jumps in cryptocurrency prices, the traditional variance-based approach to obtain hedge ratios is infeasible. As a consequence, we consider two extensions of the traditional approach: first, different dependence structures are modelled by different copulae, such as the Gaussian, Student-t, Normal Inverse Gaussian and Archimedean copulae; second, different risk measures, such as value-at-risk, expected shortfall and spectral risk measures are employed to and the optimal hedge ratio. Extensive out-of-sample tests give insights in the practice of hedging various cryptos and crypto indices, including Bitcoin, Ethereum, Cardano, the CRIX index and a number of crypto-portfolios in the time period December 2017 until May 2021. Evidences show that BTC futures can effectively hedge BTC and BTC-involved indices. This promising result is consistent across different risk measures and copulae except for Frank. On the other hand, we observe complex and diverse dependence structures between BTC-not-involved assets and the futures. As a consequence, results of hedging other assets and indices are diverse and, in some occasions, not ideal.
    Keywords: Cryptocurrencies,risk management,hedging,copulas
    JEL: G11 G13
    Date: 2021
  2. By: Martin Indergand; Eric Jondeau; Andreas Fuster
    Abstract: We propose a methodology for measuring the market-implied capital of banks by subtracting from the market value of equity (market capitalization) a credit spread-based correction for the value of shareholders' default option. We show that without such a correction, the estimated impact of a severe market downturn is systematically distorted, underestimating the risk of banks with low market capitalization. We argue that this adjusted measure of capital is the relevant market-implied capital measure for policymakers. We propose an econometric model for the combined simulation of equity prices and CDS spreads, which allows us to introduce this correction in the SRISK framework for measuring systemic risk.
    Keywords: Banking, capital, stress test, systemic risk, multifactor model
    JEL: C32 G01 G21 G28 G32
    Date: 2022
  3. By: Manuela Pedio
    Abstract: The Great Financial Crisis of 2008 – 2009 has raised the attention of policy-makers and researchers about the interconnectedness among the volatility of the returns of financial assets as a potential source of risk that extends beyond the usual changes in correlations and include transmission channels that operate through the higher order co-moments of returns. In this paper, we investigate whether a newly developed, forward-looking measure of volatility spillover risk based on option implied volatilities shows any predictive power for stock returns. We also compare the predictive performance of this measure with that of the volatility spillover index proposed by Diebold and Yilmaz (2008, 2012), which is based on realized, backward-looking volatilities instead. While both measures show evidence of in-sample predictive power, only the option-implied measure is able to produce out-of-sample forecasts that outperform a simple historical mean benchmark.
    Keywords: connectedness, volatility networks, implied volatility, realized volatility, equity return predictability, spillover risk
    JEL: G12 G17
    Date: 2021
  4. By: Johannes König; Maximilian Longmuir
    Abstract: From standard portfolio-choice theory it is well-understood that background risk, overwhelmingly due to wage risk, is one of the central determinants of individuals’ portfolio composition: higher background risk reduces risky investments. However, if background risk is negatively correlated with financial market risk, higher background risk implies more risky investment. We quantify the influence of wage risk on German investors’ financial portfolio shares and find that an increase of the residual variance of wages by one standard deviation implies a reduction of the financial portfolio share by 3 percentage points. We do not find that the correlation of wage risk with financial market risk has a significant impact on portfolio choice and provide evidence that this may be due to a lack of salience.
    Keywords: Background risk, portfolio choice, household portfolios, investment behavior
    JEL: D12 D14 D31
    Date: 2021
  5. By: Georges Prat (EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique); Remzi Uctum (EconomiX - UPN - Université Paris Nanterre - CNRS - Centre National de la Recherche Scientifique)
    Abstract: Using survey-based data we show that oil price expectations are not rational, implying that the ex-ante premium is a more relevant concept than the widely popular expost premium. We propose for the 3-and 12-month horizons a portfolio choice model with risky oil assets and a risk-free asset. At the maximized expected utility the risk premium is defined as the risk price times the expected oil return volatility. A state-space model, where the risk prices are represented as stochastic unobservable components and where expected volatilities depend on historical squared returns, is estimated using Kalman filtering. We find that the representative investor is risk seeking at short horizons and risk averse at longer horizons. We examine the economic factors driving risk prices whose signs are shown to be consistent with the predictions of the prospect theory. An upward sloped term structure of oil risk premia prevails in average over the period.
    Keywords: oil market,oil price expectations,ex-ante risk premium JEL classification : D81
    Date: 2021
  6. By: Prehn, Sören
    Keywords: Risk and Uncertainty
    Date: 2020–09–18
  7. By: Martin Hodula; Jan Janku; Lukas Pfeifer
    Abstract: We investigate the extent to which various structural risks exacerbate the materialization of cyclical risk. We use a large database covering all sorts of cyclical and structural features of the financial sector and the real economy for a panel of 30 countries over the period 2006Q1–2019Q4. We show that elevated levels of structural risks may have an important role in explaining the severity of cyclical and credit risk materialization during financial cycle contractions. Among these risks, private and public sector indebtedness, banking sector resilience and concentration of real estate exposures stand out. Moreover, we show that the elevated levels of some of the structural risks identified may be related to long-standing accommodative economic policy. Our evidence implies a stronger role for macroprudential policy, especially in countries with higher levels of structural risks
    Keywords: Cyclical risk, event study, financial cycle, panel regression, structural risks, systemic risk
    JEL: E32 G15 G21 G28
    Date: 2021–12
  8. By: SA Quimbo (House of Repsesentatives, Batasan Complex, Constitution Hills, Quezon City); CT Latinazo (House of Repsesentatives, Batasan Complex, Constitution Hills, Quezon City); JW Peabody (QURE Healthcare, UCSF and UCLA)
    Abstract: COVID-19 risk assessment is multi-faceted. The highly infectious nature of the virus in a naïve population, the high case fatality rate and health system over-burdening each need to be considered in developing a strategy to control the spread of the virus and mitigate its health and economic consequences. This note provides a framework for classifying LGUs by degree of risk and identifies policy options for each risk scenario. It urges the Department of Health (DOH) to: (i) re-assess risk levels of local government units (LGUs), (ii) undertake a 100 percent identification of place of residence of all COVID-19 confirmed cases and 100 percent reporting of number of isolation beds and ventilators by all hospitals, and (iii) develop and immediately implement a COVID-specific disease surveillance protocol, including mass testing, contact tracing, and quarantine. Careful and diligent implementation of these protocols will allow a gradual yet cautious and informed re-opening of the economy.
    Keywords: COVID-19; Philippines; risk-assessment
    Date: 2020–04
  9. By: Czech, Robert (Bank of England); Huang, Shiyang (University of Hong Kong); Lou, Dong (London School of Economics); Wang, Tianyu (Tsinghua University)
    Abstract: We study investor trading behaviour and yield patterns in the UK government bond market during the recent Covid crisis. We show that the yield spike in mid-March 2020 was accompanied by heavy selling of gilts by UK-based insurance companies and pension funds (ICPFs), which we argue was an indirect result of the US dollar’s global prominence. Non-US institutions invest a large portion of their capital in dollar assets and hedge their dollar exposures by selling dollars forward through FX derivatives. In crisis periods, dollars appreciate against other currencies. To meet margin calls on these short-dollar FX positions, non-US institutions sell their domestic safe assets, thereby contributing to the yield spikes in domestic markets.
    Keywords: Covid crisis; gilt yields; variation margin; FX derivatives; global reserve currency; currency hedging
    JEL: F31 G11 G12 G15 G22 G23
    Date: 2021–12–10
  10. By: Lhuissier Stéphane
    Abstract: Motivated by empirically characterizing the relationship between financial conditions and downside macroeconomic risks in the euro area, I develop a regime-switching skew-normal model with time-varying probabilities of transitions. Using Bayesian methods, the model estimates show that a strong cyclical pattern emerges from the conditional skewness (a measure of the asymmetry of the predictive distribution), which has a tendency to rapidly decline to negative territory prior and during recessions. However, the inclusion of financial-specific information in time-varying probabilities does not help to anticipate such skewness nor more generally to provide advance warnings of tail risks.
    Keywords: Financial Conditions, Downside Risks, Predictability, Regime-Switching Models
    JEL: C11 C2 E32
    Date: 2022
  11. By: Iuri H. Ferreira; Marcelo C. Medeiros
    Abstract: In this paper we examine the relation between market returns and volatility measures through machine learning methods in a high-frequency environment. We implement a minute-by-minute rolling window intraday estimation method using two nonlinear models: Long-Short-Term Memory (LSTM) neural networks and Random Forests (RF). Our estimations show that the CBOE Volatility Index (VIX) is the strongest candidate predictor for intraday market returns in our analysis, specially when implemented through the LSTM model. This model also improves significantly the performance of the lagged market return as predictive variable. Finally, intraday RF estimation outputs indicate that there is no performance improvement with this method, and it may even worsen the results in some cases.
    Date: 2021–12
  12. By: Jean-Guillaume Sahuc; Olivier de Bandt; Hibiki Ichiue; Bora Durdu; Yasin Mimir; Jolan Mohimont; Kalin Nikolov; Sigrid Roehrs; Valério Scalone; Michael Straughan
    Abstract: This paper (i) reviews the different channels of transmission of prudential policy highlighted in the literature and (ii) provides a quantitative assessment of the impact of Basel III reforms using "off-the-shelf" DSGE models. It shows that the effects of regulation are positive on GDP whenever the costs and benefits of regulation are both introduced. However, this result may be associated with a temporary economic slowdown in the transition to Basel III, which can be accommodated by monetary policy. The assessment of liquidity requirements is still an area for research, as most models focus on costs, rather than on benefits, in particular in terms of lower contagion risk.
    Keywords: Basel III reforms, DSGE models, solvency requirements, liquidity requirements
    JEL: E3 E44 G01 G21 G28
    Date: 2022
  13. By: Olivier de Bandt; Bora Durdu; Hibiki Ichiue; Yasin Mimir; Jolan Mohimont; Kalin Nikolov; Sigrid Roehrs; Jean-Guillaume Sahuc; Valerio Scalone; Michael Straughan
    Abstract: This paper reviews the different channels of transmission of prudential policy highlighted in the literature and provides a quantitative assessment of the impact of Basel III reforms using “off-the-shelf” DSGE models. It shows that the effects of regulation are positive on GDP whenever the costs and benefits of regulation are both introduced. However, this result may be associated with a temporary economic slowdown in the transition to Basel III, which can be accommodated by monetary policy. The assessment of liquidity requirements is still an area for research, as most models focus on costs, rather than on benefits, in particular in terms of lower contagion risk.
    Keywords: Basel III Reforms, DSGE Models, Solvency Requirements, Liquidity Requirements
    JEL: E3 E44 G01 G21 G28
    Date: 2022
  14. By: Gerba, Eddie (Bank of England); Katsoulis, Petros (Bank of England)
    Abstract: This paper assesses the impact of banking regulation (Basel III) on financial market dynamics using the repo market as an important case study. To this end, we use unique proprietary data sets from the Bank of England to examine the individual and joint impact of leverage, capital and liquidity coverage ratios on participants’ trading in all collateral segments of the UK repo market. We find non-uniform effects across ratios and participants and non-linear effects across time. For instance, we find that the leverage ratio induces participants to charge lower (higher) interest margins on repo (reverse repo) trades that are non-nettable compared to the nettable ones. Second,we document a change in market microstructure under the new regulatory regime. Specifically, we evidence a substitution effect of banks’ long-term repo borrowing backed by gilts from dealers to investment funds which can be fragile during times of stress. Likewise, we find an increasing prominence of central counterparties. Third, we find evidence that participants who are jointly constrained by multiple ratios and closer to the regulatory thresholds during times of stress reduce their activity to a greater extent than those that are constrained by a single ratio or not constrained, with implications for market liquidity.
    Keywords: Banking regulation; repo market; market microstructure; liquidity; monetary policy transmission
    JEL: E44 E52 G11 G21 G28
    Date: 2021–12–17
  15. By: Mei-Ling Cai; Zhang-HangJian Chen; Sai-Ping Li; Xiong Xiong; Wei Zhang; Ming-Yuan Yang; Fei Ren
    Abstract: In this paper, we propose a new dynamical model to study the two-stage volatility evolution of stock market index after extreme events, and find that the volatility after extreme events follows a stretched exponential decay in the initial stage and becomes a power law decay at later times by using high frequency minute data. Empirical study of the evolutionary behaviors of volatility after endogenous and exogenous events further demonstrates the descriptive power of our new model. To further explore the underlying mechanisms of volatility evolution, we introduce the sequential arrival of information hypothesis (SAIH) and the mixture of distribution hypothesis (MDH) to test the two-stage assumption, and find that investors transform from the uninformed state to the informed state in the first stage and informed investors subsequently dominate in the second stage. The testing results offer a supporting explanation for the validity of our new model and the fitted values of relevant parameters.
    Date: 2022–01
  16. By: Massimo Guidolin; Davide La Cara; Massimiliano Marcellino
    Abstract: With reference to S&P 500 daily returns, we report evidence of an in-sample predictive accuracy breakdown for realized variance by GARCH models in correspondence to the March 2020 Covid-19 outbreak. However, a variety of macroeconomic risk, political and social media sentiment uncertainty factors, and crucially a few variables capturing the evolution of the Covid-19 pandemics, successfully predict the direction and size of GARCH forecast errors between November 2019 and June 2020. Predictors related to diagnosed cases, their rate of growth, and the progression of the curve of deceased, infected people in the United States are featured prominently. We test a number of “augmented” GARCH models to include the most precisely estimated exogenous variables and find that they offer precise forecasts in samples that include the Covid-19 outbreak. In genuine out-of-sample tests, augmenting GARCH with Covid-19 related exogenous variables increases the percentage of days in which the direction of change in realized variance is correctly predicted.
    Keywords: Conditionally heteroskedastic models, Covid-19, volatility forecasting
    JEL: C32 C53 E47 G01
    Date: 2021
  17. By: A. H. Nzokem
    Abstract: We consider a $\Gamma(\alpha, \theta)$ Ornstein-Uhlenbeck process and build a continuous sample path Variance-Gamma (VG) Process with five parameters ($\mu, \delta, \sigma, \alpha, \theta$): location ($\mu$), symmetric ($\delta$), volatility ($\sigma$), and shape ($\alpha$) and scale ($\theta$). We investigate the associated L\'evy process and show that the l\'evy density belongs to the KoPoL family of order $\nu=0$, intensity $\alpha$ and steepness parameters $\frac{\delta}{\sigma^2} - \sqrt{\frac{\delta^2}{\sigma^4}+\frac{2}{\theta \sigma^2}}$ and $\frac{\delta}{\sigma^2}+ \sqrt{\frac{\delta^2}{\sigma^4}+\frac{2}{\theta \sigma^2}}$. The associated L\'evy process is also shown to converge in distribution to a l\'evy process driven by a Normal distribution with mean $(\mu + \alpha \theta \delta)$ and variance $\alpha (\theta^2\delta^2 + \sigma^2\theta)$. The data used as illustrations comes from the fitting of the five-parameter Variance Gamma (VG) model to the SPY ETF daily price by Nzokem (Nzokem 2021 J. Phys.: Conf. Ser. 2090 012094). The five-parameter Variance Gamma (VG) process is used subsequently to investigate how well the VG model fits the European option price compare to the Black-Schole option. The Esscher martingale of the VG model is shown to be another VG model with adjusted parameter. The closed form of the VG option price is provided. The numerical solution is computed using Fractional Fast Fourier (FRFT) algorithm. Compare to the Black-Scholes (BS) model, we find that the VG option is overvalued for deep out of the money (OTM) options. The error sign changes for Deep in the money (ITM) and long term time to maturity, where the VG option is undervalued.
    Date: 2022–01
  18. By: Nurdaulet Abilov (NAC Analytica, Nazarbayev University)
    Abstract: We extend the literature on the role of uncertainty shocks in small open economies using a dynamic stochastic general equilibrium (DSGE) model with stochastic volatility for the economy of Kazakhstan. We build a small-scale DSGE model for Kazakhstan with non-linear time-varying volatility of shock processes. Due to the inherent non-linearity in the model we estimate the parameters of the volatility processes using the Particle filter, and then estimate structural parameters of the model via simulated method of moments (SMM)
    Keywords: DSGE model; Oil price uncertainty; Particle filter; Simulated method of moments; Kazakhstan.
    JEL: E20 E32 E43
    Date: 2021–12
  19. By: Gérard Mondello (UCA - Université Côte d'Azur)
    Abstract: Starting from the standard analysis of accident theory, this paper shows that determining the first-best level of care of ultra-hazardous activities also involves determining the best industrial structure. The analysis assesses the impact of the civil nuclear liability on the organization of given electro-nuclear parks. The object is to know whether these liability rules induce horizontally concentrating the management of nuclear industry or not. In a model extended from two to n plants, we show that the institutional conditions (cap on the operator's liability and the insurance compensation) play a fundamental role in the inducement to centralize or not this management. Hence, a priori, no organization framework is more efficient than the other one.
    Date: 2021–12–26
  20. By: John Caramichael; Gordon Y. Liao
    Abstract: Stablecoins have experienced tremendous growth in the past year, serving as a possible breakthrough innovation in the future of payments. In this paper, we discuss the current use cases and growth opportunities of stablecoins, and we analyze the potential for stablecoins to broadly impact the banking system. The impact of stablecoin adoption on traditional banking and credit provision can vary depending on the sources of inflow and the composition of stablecoin reserves. Among the various scenarios, a two-tiered banking system can both support stablecoin issuance and maintain traditional forms of credit creation. In contrast, a narrow bank approach for digital currencies can lead to disintermediation of traditional banking, but may provide the most stable peg to fiat currencies. Additionally, dollar-pegged stablecoins backed by adequately safe and liquid collateral can potentially serve as a digital safe haven currency during periods of crypto market distress.
    Keywords: Stablecoins; Digital currencies; Credit intermediation; Banking; Systemic risk; Fintech; Financial innovation; Payment system
    JEL: E40 E50 F33 G10 G20 O30
    Date: 2022–01–31
  21. By: Stephen Sullivan (University of the Incarnate Word, United States); Diana Garza (University of the Incarnate Word, United States)
    Abstract: The past year has seen critical fluctuations in business operations throughout the US and the world. Due to COVID-19, employees have been encouraged or forced to work from home instead of commuting to a regular work location. Remote work has disrupted and weakened security processes. Cyber criminals have seen an opportunity in this weakened infrastructure. Cybersecurity attacks have disrupted supply chains for businesses, schools, healthcare organizations and other entities. Organizations will need to reassess security strategies with the assumption that work-from-home will become permanent. The US Department of Homeland Security has stepped up its efforts to meet this risk head-on and has incorporated supply chain cybersecurity measures within the constructs of the Customs-Trade Partnership Against Terrorism (C-TPAT) program. This all-volunteer program was launched immediately after 9/11 to thwart potential supply chain risks that could open the door to major terrorist attacks on the US homeland. This research will explore the reasons why cybersecurity has become the nation’s number one commercial concern for supply chains and logistics management and how C-TPAT is enabling the proper change to the current business climate as a risk mitigating option.
    Keywords: cyber-security, C-TPAT, supply chain, risk
    Date: 2021–08
  22. By: Aaron Amburgey; Michael W. McCracken
    Abstract: We provide evidence on the real-time predictive content of the National Financial Conditions Index (NFCI), for conditional quantiles of U.S. real GDP growth. Our work is distinct from the literature in two specific ways. First, we construct (unofficial) real-time vintages of the NFCI. This allows us to conduct out-of-sample analysis without introducing the kind of look-ahead biases that are naturally introduced when using a single current vintage. We then develop methods for conducting asymptotic inference on tests of equal tick loss between nested quantile regression models when the data are subject to revision. We conclude by evaluating the real-time predictive content of NFCI vintages for quantiles of real GDP growth. While our results largely reinforce the literature, we find gains to using real-time vintages leading up to recessions — precisely when policymakers need such a monitoring device.
    Keywords: out-of-sample forecasts; real-time data; quantiles
    JEL: C12 C32 C38 C52
    Date: 2022–01–18
  23. By: Morita, Hiroshi; Ono, Taiki
    Abstract: Measuring uncertainty and its economic impact are of major concern during the unprecedented crisis triggered by the coronavirus disease 2019 (COVID-19) pandemic. This paper constructs a newspaper-based measure that captures the uncertainty induced by COVID-19 and examines its economic impacts using a structural VAR model applied to Japanese data. We develop two types of uncertainty indices and identify two types of structural shocks in the VAR model: one measuring an epidemiological uncertainty, the other a policy-related uncertainty. Our findings are summarized as follows. First, the constructed series of uncertainty shows a spike after COVID-19 related events, indicating that our indices work well as a measure of COVID-19 induced uncertainty. Second, stock market variables show statistically significant responses to a policy-related uncertainty shock rather than an epidemiological uncertainty shock. Third, in contrast, real variables such as mobility and consumption tend to respond significantly to an epidemiological uncertainty shock. These findings highlight the importance of considering different types of uncertainty in order to properly assess the impact of COVID-19 induced uncertainty on economic activity.
    Keywords: COVID-19, uncertainty, newspaper-based approach, VAR model
    JEL: C32 D80 E44
    Date: 2022–01

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