nep-rmg New Economics Papers
on Risk Management
Issue of 2022‒05‒16
seventeen papers chosen by
Stan Miles
Thompson Rivers University

  1. Asymmetric Systemic Risk By Radoslav Raykov; Consuelo Silva-Buston
  2. Forecasting risk measures based on structural breaks in the correlation matrix By Duan, Fang
  3. Back to the Roots of Internal Credit Risk Models: Why Do Banks’ Risk-Weighted Asset Levels Converge over Time? By Victoria Böhnke; Steven Ongena; Florentina Paraschiv; Endre J Reite
  4. Idiosyncratic Equity Risk Two Decades Later By John Y. Campbell; Martin Lettau; Burton G. Malkiel; Yexiao Xu
  5. Country-Based Investing with Exchange Rate and Reserve Currency By Galvani, Valentina
  6. Variational Heteroscedastic Volatility Model By Zexuan Yin; Paolo Barucca
  7. On a Stochastic Model of Diversification By Maria Logvaneva; Mikhail Tselishchev
  8. A Stock Return Decomposition Using Observables By Benjamin Knox; Annette Vissing-Jorgensen
  9. Tackling Large Outliers in Macroeconomic Data with Vector Artificial Neural Network Autoregression By Vito Polito; Yunyi Zhang
  10. What Drives Mortgage Default Risk in Europe and the U.S.? By Mr. Thierry Tressel; Eugen Tereanu; Mr. Marco Gross; Xiaodan Ding
  11. Impact of the COVID-19 Pandemic on Deposit Insurance By Ryan Defina
  12. Pandemic-Era Uncertainty By Meyer, Brent; Mihaylov, Emil; Barrero, Jose Maria; Davis, Steven J.; Altig, David; Bloom, Nicholas
  13. Modeling Uncertainty as Ambiguity: a Review By Cosmin L. Ilut; Martin Schneider
  14. Household Debt and Risk Tolerance: Evidence from China By Jialong Li
  15. The Life Insurance Gap in Finland By Ropponen, Olli; Kuusi, Tero; Valkonen, Tarmo
  16. Crisis Liquidity Facilities with Nonbank Counterparties: Lessons from the Term Asset-Backed Securities Loan Facility By Ralf R. Meisenzahl; Karen M. Pence
  17. The Relationship between Fiscal and Monetary Policies in Colombia: An Empirical Exploration of the Credit Risk Channel By Ignacio Lozano-Espitia; Fernando Arias-Rodríguez

  1. By: Radoslav Raykov; Consuelo Silva-Buston
    Abstract: Bank regulation is based on the premise that risks spill over more easily from large banks to the banking system than vice versa. On the contrary, we document that risk transmission is stronger in the system-to-bank direction. We term this asymmetric systemic risk, measure it with net exposure metrics, and explore the consequences and channels behind it. We show that banks with positive net exposure to the system had higher default risk during the 2008 crisis, and that bank size and trading activities were the main determinants of this net exposure, which increased default risk through trading income volatility and overall profit volatility. We argue that the current bank supervision objectives can be achieved more efficiently if regulation focuses on reducing such net exposures, rather than buffering the default risks arising from them.
    Keywords: Financial institutions; Financial stability; Financial system regulation and policies
    JEL: G10 G20
    Date: 2022–05
  2. By: Duan, Fang
    Abstract: Correlation models, such as Constant Conditional Correlation (CCC) GARCH model or Dynamic Conditional Correlation (DCC) GARCH model, play a crucial role in forecasting Value-at-Risk (VaR) or Expected Shortfall (ES). The additional inclusion of constant correlation tests into correlation models has been proven to be helpful in terms of the improvement of the accuracy of VaR or ES forecasts. Galeano & Wied (2017) suggested an algorithms for detecting structural breaks in the correlation matrix whereas Duan & Wied (2018) proposed a residual based testing procedure for constant correlation matrix which allows for time-varying marginal variances. In this chapter, we demonstrate the application of aforementioned correlation testing procedures and compare its performance in backtesting VaR and ES predictions. Portfolios in consideration are constructed from four stock indices DAX30, STOXX50, FTSE100 and S&P500.
    Keywords: structural break tests,correlation model,value-at-risk,expected shortfall
    JEL: C12 C32 C53 C58
    Date: 2022
  3. By: Victoria Böhnke (University of Münster); Steven Ongena (University of Zurich - Department of Banking and Finance; Swiss Finance Institute; KU Leuven; NTNU Business School; Centre for Economic Policy Research (CEPR)); Florentina Paraschiv (Zeppelin University, Chair of Finance; Norwegian University of Science and Technology, Faculty of Economics and Management, NTNU Business School; University of St. Gallen, Institute for Operations Research and Computational Finance); Endre J Reite (Norwegian University of Science and Technology (NTNU) - Department of International Business)
    Abstract: The internal ratings-based (IRB) approach maps banks’ risk profiles more adequately than the standardized approach. After switching to IRB, banks’ risk-weighted asset (RWA) densities are thus expected to diverge, especially across countries with different supervisory strictness and risk levels. However, when examining 52 listed banks headquartered in 14 European countries that adopted the IRB approach, we observe a convergence of their RWA densities over time. We test if this convergence can be entirely explained by differences in the size of the banks, loss levels, country risk, and/or time of IRB implementation, yet this is not the case. Whereas banks in high-risk countries, with lax regulation, reduce their RWA densities, banks elsewhere increase theirs. Especially for banks in high-risk countries, RWA densities underestimate banks’ actual economic risk. Hence, the IRB approach allows for regulatory arbitrage, whereby authorities only enforce strict supervision on capital requirements if they do not jeopardize bank resilience.
    Keywords: Capital regulation, credit risk, internal ratings-based approach, regulatory arbitrage, risk-weighted assets
    JEL: G21 G28
    Date: 2022–04
  4. By: John Y. Campbell; Martin Lettau; Burton G. Malkiel; Yexiao Xu
    Abstract: This paper reviews the literature on idiosyncratic equity volatility since the publication of “Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk” in 2001. We respond to replication studies by Chiah, Gharghori, and Zhong and by Leippold and Svaton, and we present volatility estimates through the end of 2021, significantly extending the period covered in our original paper as well as the two replication studies. After spiking in the 1999- 2000 period, idiosyncratic volatility declined thereafter; but sharp increases in market, industry, and idiosyncratic volatility occurred during the global financial crisis of 2008-2009 and the COVID-19 pandemic of 2020-2021. We argue that market microstructure effects are not of first-order importance for volatility measurement, and we discuss the roles of fundamental factors and investor sentiment in driving the observed fluctuations in volatility.
    JEL: G10 G12
    Date: 2022–04
  5. By: Galvani, Valentina (University of Alberta, Department of Economics)
    Abstract: This study examines how style investing impacts correlations in a small and large economy, with exchange rate risk, and a reserve currency. The results show that style investing increases correlations in both economies, but more so in the smaller market. The impact of style investing on either country's correlations depends nonlinearly on the volatility of the exchange rate and the strength of the reserve currency effect. Higher levels of risk aversion amplify the impact of style investing on correlations. Imprecise signals and country preferences increase correlation distortions. The results have risk management implications for portfolio diversification.
    Keywords: Style investing; International Markets; Portfolio Diversification; Return Correlations; International Markets
    JEL: G10 G11 G12
    Date: 2022–03–24
  6. By: Zexuan Yin; Paolo Barucca
    Abstract: We propose Variational Heteroscedastic Volatility Model (VHVM) -- an end-to-end neural network architecture capable of modelling heteroscedastic behaviour in multivariate financial time series. VHVM leverages recent advances in several areas of deep learning, namely sequential modelling and representation learning, to model complex temporal dynamics between different asset returns. At its core, VHVM consists of a variational autoencoder to capture relationships between assets, and a recurrent neural network to model the time-evolution of these dependencies. The outputs of VHVM are time-varying conditional volatilities in the form of covariance matrices. We demonstrate the effectiveness of VHVM against existing methods such as Generalised AutoRegressive Conditional Heteroscedasticity (GARCH) and Stochastic Volatility (SV) models on a wide range of multivariate foreign currency (FX) datasets.
    Date: 2022–04
  7. By: Maria Logvaneva; Mikhail Tselishchev
    Abstract: We propose a definition of diversification as a binary relationship between financial portfolios. According to it, a convex linear combination of several risk positions with some weights is considered to be less risky than the probabilistic mixture of the same risk positions with the same weights. It turns out to be that the proposed partial ordering coincides with the well-known second order stochastic dominance, but allows to take a look at it from another perspective.
    Date: 2022–04
  8. By: Benjamin Knox; Annette Vissing-Jorgensen
    Abstract: We propose a method to decompose stock returns period by period. First, we argue that one can directly estimate expected stock returns from securities available in modern financial markets (using the real yield curve and the Martin (2017) equity risk premium). Second, we derive a return decomposition which is based on stock price elasticities with respect to expected returns and expected dividends. We calculate elasticities from dividend futures. Our decomposition is an alternative to the Campbell-Shiller log-linearization which relies on an assumption about the log-linearization constant. An application to the COVID crisis in 2020 reveals that risk premium changes drove much of the crash and rebound in the SP500 while a fall in long-term real yields drove a strong positive return for 2020 as a whole.
    Keywords: Asset pricing; Duration; Return decomposition; Stock Market
    JEL: G10 G12 G14
    Date: 2022–03–23
  9. By: Vito Polito (Department of Economics, University of Sheffield, UK); Yunyi Zhang (Xiamen University, China)
    Abstract: We develop a regime switching vector autoregression where artificial neural networks drive time variation in the coefficients of the conditional mean of the endogenous variables and the variance covariance matrix of the disturbances. The model is equipped with a stability constraint to ensure non-explosive dynamics. As such, it is employable to account for nonlinearity in macroeconomic dynamics not only during typical business cycles but also in a wide range of extreme events, like deep recessions and strong expansions. The methodology is put to the test using aggregate data for the United States that include the abnormal realizations during the recent Covid-19 pandemic. The model delivers plausible and stable structural inference, and accurate out-of-sample forecasts. This performance compares favourably against a number of alternative methodologies recently proposed to deal with large outliers in macroeconomic data caused by the pandemic.
    Keywords: Tax avoidance; Nonlinear time series; Regime switching models; Extreme events; Covid-19; Macroeconomic forecasting
    JEL: C45 C5 E37
    Date: 2022–03
  10. By: Mr. Thierry Tressel; Eugen Tereanu; Mr. Marco Gross; Xiaodan Ding
    Abstract: We present an analysis of the sensitivity of household mortgage probabilities of default (PDs) and loss given default (LGDs) on unemployment rates, house price growth, interest rates, and other drivers. A structural micro-macro simulation model is used to that end. It is anchored in the balance sheets and income-expense flow data from about 95,000 households and 230,000 household members from 21 EU countries and the U.S. We present country-specific nonlinear regressions based on the structural model simulation-implied relation between PDs and LGDs and their drivers. These can be used for macro scenario-conditional forecasting, without requiring the conduct of the micro simulation. We also present a policy counterfactual analysis of the responsiveness of mortgage PDs, LGDs, and bank capitalization conditional on adverse scenarios related to the COVID-19 pandemic across all countries. The economics of debt moratoria and guarantees are discussed against the background of the model-based analysis.
    Keywords: Credit risk, household sector, micro-macro simulation modeling, financial policies
    Date: 2022–04–01
  11. By: Ryan Defina (International Association of Deposit Insurers)
    Abstract: The Survey Brief offers key insights acquired through the IADI Follow-up Survey on COVID-19 Implications for Deposit Insurers, conducted in January 2021.
    Keywords: deposit insurance, bank resolution
    JEL: G21 G33
    Date: 2021–05
  12. By: Meyer, Brent (Federal Reserve Bank of Atlanta); Mihaylov, Emil (Federal Reserve Bank of Atlanta); Barrero, Jose Maria (Instituto Tecnológico Autónomo de México Business School); Davis, Steven J. (University of Chicago); Altig, David (Federal Reserve Bank of Atlanta); Bloom, Nicholas (Stanford University)
    Abstract: We examine several measures of uncertainty to make five points. First, equity market traders and executives at nonfinancial firms have shared similar assessments about one-year-ahead uncertainty since the pandemic struck. Both the one-year VIX and our survey-based measure of firm-level uncertainty at a one-year forecast horizon doubled at the onset of the pandemic and then fell about half-way back to pre-pandemic levels by mid 2021. Second, and in contrast, the 1-month VIX, a Twitter-based Economic Uncertainty Index, and macro forecaster disagreement all rose sharply in reaction to the pandemic but retrenched almost completely by mid 2021. Third, Categorical Policy Uncertainty Indexes highlight the changing sources of uncertainty – from healthcare and fiscal policy uncertainty in spring 2020 to elevated uncertainty around monetary policy and national security as of March 2022. Fourth, firm-level risk perceptions skewed heavily to the downside in spring 2020 but shifted rapidly to the upside from fall 2020 onwards. Perceived upside uncertainty remains highly elevated as of early 2022. Fifth, our survey evidence suggests that elevated uncertainty is exerting only mild restraint on capital investment plans for 2022 and 2023, perhaps because perceived risks are so skewed to the upside.
    Keywords: business expectations, uncertainty, subjective forecast distributions, capital investments, COVID-19
    JEL: D80 E22 E32
    Date: 2022–04
  13. By: Cosmin L. Ilut; Martin Schneider
    Abstract: We survey literature on ambiguity with an emphasis on recent applications in macroeconomics and finance. Like risk, ambiguity leads to cautious behavior and uncertainty premia in asset markets. Unlike risk, ambiguity can generate first order welfare losses. As a result, precautionary behavior and ambiguity premia obtain even when agents have linear utility and are reflected in linear approximations to model dynamics. Quantitative work exploits this insight to estimate models that jointly match the dynamics of asset prices and macro aggregates. In micro data, inertia and inaction due to ambiguity help understand patterns such as non-participation in asset markets, price rigidities and simple contracts. Learning under ambiguity generates asymmetric responses to news that help connect higher moments in micro and macro data. Survey evidence is increasingly used to provide direct evidence on ambiguity averse behavior, as well as to discipline quantitative models.
    JEL: D8 E2 E3 E4 G1
    Date: 2022–04
  14. By: Jialong Li (Department of Economics, University of Sheffield, UK)
    Abstract: This paper examines the relationship between the head of household’s risk tolerance and household debt in China for a sample of 49,621 households drawn from the China Household Finance Survey, 2011, 2013, 2015 and 2017. The effect of risk tolerance on both the decision to hold and the amount of total household debt, housing debt and non-housing debt held is analysed. The key findings indicate that risk tolerance is positively associated with household debt and non-housing debt. In addition, differences are found in the effect of risk tolerance on household debt across rural and urban households. For example, there exists a positive relationship between risk tolerance and the probability of holding housing debt for rural households while such a relationship is not found for urban households. In addition, the effect of risk tolerance on household debt is larger for rural households
    Keywords: China; Household debt; Risk Tolerance
    JEL: D12 D14 G51
    Date: 2022–02
  15. By: Ropponen, Olli; Kuusi, Tero; Valkonen, Tarmo
    Abstract: Abstract This report employs individual-level register data to study the coverage and amounts of voluntary term life insurances, the monetary losses following from the death of a breadwinner, and the life insurance gap arising as the difference of the two. The data include information on the life insurances of Finnish individuals and their individual and household level information between 2018 and 2020. We find that 8 % of the individuals have at least one type of term life insurance in the data. For them the average life insurance is 73 000 €. The take up of life insurances differ between groups, and it is more frequent among working-age, married and higher income individuals. The life insurance gap calculations account for a number of changes in living standards following from a death of a breadwinner, including those in household income, consumption, existing wealth, survivors’ pensions and life insurances. For those individuals who have earned income and who live in families consisting of at least two persons the average life insurance gap is between 65 000 € and 70 000 €. This is the amount of additional life insurance that would retain the consumption possibilities the same as before the breadwinner’s death. For those who have a voluntary life insurance the gap is on average close to zero. Therefore, the life insurance gap arises mainly among those people not having a life insurance at all.
    Keywords: Life insurances, Life insurance gap, Households, Social security, Forgone income
    JEL: G22 H31 H55 J17
    Date: 2022–05–10
  16. By: Ralf R. Meisenzahl; Karen M. Pence
    Abstract: In response to immense strains in the asset-backed securities market in 2008 and 2020, the Federal Reserve and the U.S. Treasury twice launched the Term Asset-Backed Securities Loan Facility (TALF). TALF was an unusual crisis facility because it provided loans to a wide range of nonbank financial institutions. Using detailed loan-level data unexplored by previous researchers, we study the behavior of nonbank borrowers in TALF. We find the extent to which the actions of these borrowers supported key program goals--stabilizing markets quickly, winding down the program when it was no longer needed, providing liquidity to a wide range of assets, and having borrowers internalize credit risk rather than shift it to the government--were related to institutional differences across nonbanks. Since all TALF borrowers faced the same program terms and conditions, our study is able to highlight the role of these institutional constraints.
    Keywords: Non-Bank Financial Institutions; Securitization; Lender of Last Resort; Term Asset-Backed Securities Loan Facility; TALF
    JEL: E52 E53 G12 G23
    Date: 2022–04–13
  17. By: Ignacio Lozano-Espitia; Fernando Arias-Rodríguez
    Abstract: This paper aims to provide evidence on the relationship between fiscal and monetary policy in Colombia through an empirical exploration of the credit risk channel. Under this approach, fiscal policy plays an important explanatory role in the sovereign risk premium, which, in turn, could affect the exchange rate and inflation expectations. The Central Bank reacts to inflation expectations using the policy interest rate; consequently, such reaction could be indirectly influenced by fiscal behavior. Using monthly data from January 2003 to December 2019, we estimate both jointly and independently the reduced-form core equations of a system that describes the credit risk channel in a small open economy. Our findings are in line with the model predictions. Fiscal policy affected the country’s sovereign risk during this period, but only slightly. Hence, there is insufficient evidence to sustain the idea that monetary policy has been significantly influenced by government fiscal management. **** Este documento analiza la relación entre las políticas fiscal y monetaria en Colombia, mediante la evaluación empírica del canal de riesgo crediticio. En este enfoque, la política fiscal explicaría la prima de riesgo soberano la cual, a su vez, puede afectar la tasa de cambio nominal y las expectativas de inflación. El Banco Central reacciona a las expectativas de inflación usando la tasa de interés de política; así, dicha reacción estaría influenciada indirectamente por la política fiscal. Utilizando información mensual de 2003 a 2019 se estima, de manera conjunta e independiente, un sistema de ecuaciones que describe de forma reducida el funcionamiento del canal de riesgo de crédito en una economía pequeña y abierta. Nuestros resultados son coherentes con las predicciones del modelo teórico. Se encuentra que la política fiscal afectó el riesgo soberano del país durante el período de estudio, aunque de manera modesta. Sin embargo, no hay suficiente evidencia para afirmar que la política monetaria haya sido influenciada de manera importante por la política fiscal, descartándose situaciones de dominancia fiscal.
    Keywords: Policy interaction, fiscal policy, monetary policy, sovereign credit risk, Interacción de políticas, política fiscal, política monetaria, riesgo de crédito soberano.
    JEL: E61 E63 E62 E52
    Date: 2022–04

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