nep-rmg New Economics Papers
on Risk Management
Issue of 2021‒03‒29
twenty-one papers chosen by

  1. Pandemic Tail Risk By Matthijs Breugem; Raffaele Corvino; Roberto Marfè; Lorenzo Schönleber
  2. Portfolio Risk and Stress across Business Cycle By Aravind Sampath; Sandip Chakraborty; Ram Kumar Kakani
  3. Economic Growth at Risk: An Application to Chile By Nicolás Álvarez; Antonio Fernandois; Andrés Sagner
  4. Measuring Macroeconomic Tail Risk By Roberto Marfè; Julien Pénasse
  5. Risk aggregation and capital allocation using a new generalized Archimedean copula By Fouad Marri; Khouzeima Moutanabbir
  6. Synthetic leverage and fund risk-taking By Fricke, Daniel
  7. Tail Forecasting with Multivariate Bayesian Additive Regression Trees By ; Todd E. Clark; Florian Huber; Gary Koop; Massimiliano Marcellino
  8. The Price and Quantity of Interest Rate Risk By Jennifer N. Carpenter; Fangzhou Lu; Robert F. Whitelaw
  9. Modeling and forecasting macroeconomic downside risk By Delle Monache, Davide; De Polis, Andrea; Petrella, Ivan
  10. Multi-Period Portfolio Optimization using Model Predictive Control with Mean-Variance and Risk Parity Frameworks By Xiaoyue Li; A. Sinem Uysal; John M. Mulvey
  11. Factor Strengths, Pricing Errors, and Estimation of Risk Premia By M. Hashem Pesaran; Ron P. Smith
  12. When and how to unwind COVID-support measures to the banking system? By Haselmann, Rainer; Tröger, Tobias
  13. Decomposing the VIX Index into Greed and Fear By Juan Andrés Serur; José P. Dapena; Julián R. Siri
  14. Towards Greening Finance: Integration of Environmental Factors in Risk Management & Impact of Climate Risks on Asset Portfolios By Apostolou, Apostolos; Papaioannou, Michael
  15. Risk Shocks and Divergence between the Euro Area and the US in the aftermath of the Great Recession By Thomas Brand; Fabien Tripier
  16. Dynamic Equity Slope By Matthijs Breugem; Stefano Colonnello; Roberto Marfè; Francesca Zucchi
  17. Looking into the futures markets: What are they really for? By Prehn, Sören; Glauben, Thomas; Loy, Jens-Peter
  18. Study on the impacts of Shanghai crude oil futures on global oil market and oil industry based on VECM and DAG models By Qi Zhang; Peng Di; Arash Farnoosh
  19. Expecting the unexpected: economic growth under stress By Gloria González-Rivera; Carlos Vladimir Rodríguez-Caballero; Esther Ruiz Ortega
  20. The power of text-based indicators in forecasting the Italian economic activity By Valentina Aprigliano; Simone Emiliozzi; Gabriele Guaitoli; Andrea Luciani; Juri Marcucci; Libero Monteforte
  21. Financial innovation for a sustainable economy By Andrés Alonso; José Manuel Marqués

  1. By: Matthijs Breugem; Raffaele Corvino; Roberto Marfè; Lorenzo Schönleber
    Abstract: This paper shows that tail risk in US equity markets increased in advance of the COVID-19 outbreak in February 2020. While tail risk of the market index did not move much before the outbreak, we document that tail risk of less pandemic-resilient economic sectors boomed in advance. This result is robust to alternative specifications of tail risk, measured from either option or credit default swap contracts. Long-horizon tail risk measures provide information about investors perception of pandemic risk persistence and economic recovery.
    Keywords: COVID-19, tail risk, economic sectors.
    JEL: G01 G10 G12 G14
    Date: 2020
  2. By: Aravind Sampath (Indian Institute of Management Kozhikode); Sandip Chakraborty (Indian Institute of Management (IIM) Calcutta, Kolkata); Ram Kumar Kakani (Indian Institute of Management Kozhikode)
    Abstract: Past research on market stress limits the scope to the extent of measuring tail loss (CVaR) by looking after joint asset correlations. We probe further the interactions of daily tail risk estimates of thirty market indices representing a broad spectrum of assets from 2003 till 2015 across the USA and other major financial hubs. We study the dependence structure through Conditional Copula augmented Markov-switching transitions. Results show extent of contagion of tail risk, cross-assets and cross-geographies formed during economy wide stress and role played by alternative assets to mitigate overall state wide risk. Our results also show magnitude of tail risk contagion amongst countries studied. Investment managers allocating capital on cross-border and cross-assets may benefit from the results. Large banks and other international financial institutions may assess potential tail risk awaiting their trade book.
    Keywords: Portfolio Risk; Conditional Copula; CVaR; Stress; Markov-Switching; Business Cycle; Alternative Assets.
    Date: 2020–05
  3. By: Nicolás Álvarez; Antonio Fernandois; Andrés Sagner
    Abstract: This paper applies the Growth-at-Risk (G@R) methodology proposed by Adrian et al. (2019) to the Chilean economy. To this aim, we first develop a Financial Conditions Index (FCI) from a broad set of local and external macro-financial variables covering the period from 1994 to 2020, such as asset prices, short and long-term spreads, and volatility measures that characterizes the vulnerabilities of the domestic financial market. The FCI identifies periods of substantial tight financial conditions that coincide with several episodes of economic downturns and market turmoils such as the 1997 Asian Crisis, the 2007-2009 Global Financial Crisis, and the coronavirus pandemic in mid-March 2020. The G@R analysis reveals that the FCI contains relevant information to forecast lower future GDP growth distribution quantiles. Thus, our results show that downside risks to growth intensify during periods of economic and financial distress. In particular, the 5th percent quantile of economic growth during the 2007-2009 Global Financial crisis reached roughly -10% due to tighter financial conditions propelled by the deterioration of the credit to GDP gap and adverse external conditions such as higher global volatility and lower terms of trade. These findings, and others discussed in the paper, highlight this methodology’s usefulness as an additional tool to support monitoring and risk management duties by policymakers.
    Date: 2021–03
  4. By: Roberto Marfè; Julien Pénasse
    Abstract: This paper proposes a predictive approach to estimate macroeconomic tail risk dynamics over the long run (1876-2015). Our approach circumvents the scarcity of large macroeconomic crises by using observable predictive variables in a large international panel. This method does not require to use asset price information, which allows us to evaluate the empirical validity of rare disasters models. We find that macroeconomic crises are forecastable by a broad array of variables. In particular, our macro risk estimate covaries with asset prices and forecasts future stock returns. This suggests, in line with the rare disaster paradigm, that the equity premium varies over time because agents care about macroeconomic risk. A rare disaster model, calibrated from macroeconomic data alone, further supports this interpretation.
    Keywords: rare disasters, equity premium, return predictability.
    JEL: E44 G12 G17
    Date: 2020
  5. By: Fouad Marri (INSEA - Institut National de Statistique et d’Economie Appliquée [Rabat]); Khouzeima Moutanabbir (UJ - University of Johannesburg)
    Abstract: In this paper, we address risk aggregation and capital allocation problems in the presence of dependence between risks. The dependence structure is defined by a mixed Bernstein copula which represents a generalization of the well-known Archimedean copulas. Using this new copula, the probability density function and the cumulative distribution function of the aggregate risk are obtained. Then, closed-form expressions for basic risk measures, such as tail value-atrisk (TVaR) and TVaR-based allocations, are derived.
    Keywords: Bernstein copulas,Capital allocation,Copulas,Dependence,Tail value at risk,Value-at-Risk
    Date: 2021–03–15
  6. By: Fricke, Daniel
    Abstract: Mutual fund risk-taking via active portfolio rebalancing varies both in the cross- section and over time. In this paper, I show that the same is true for funds' off- balance sheet risk-taking, even after controlling for on-balance sheet activities. For this purpose, I propose a novel measure of synthetic leverage, which can be estimated based on publicly available information. In the empirical application, I show that German equity funds have increased their risk-taking via synthetic leverage from mid-2015 up until early 2019. In the cross-section, I find that synthetically leveraged funds tend to underperform and display higher levels of fragility.
    Keywords: leverage,risk-taking,derivatives,securities lending,mutual funds
    JEL: E44 G11 G23
    Date: 2021
  7. By: ; Todd E. Clark; Florian Huber; Gary Koop; Massimiliano Marcellino
    Abstract: We develop novel multivariate time series models using Bayesian additive regression trees that posit nonlinear relationships among macroeconomic variables, their lags, and possibly the lags of the errors. The variance of the errors can be stable, driven by stochastic volatility (SV), or follow a novel nonparametric specification. Estimation is carried out using scalable Markov chain Monte Carlo estimation algorithms for each specification. We evaluate the real-time density and tail forecasting performance of the various models for a set of US macroeconomic and financial indicators. Our results suggest that using nonparametric models generally leads to improved forecast accuracy. In particular, when interest centers on the tails of the posterior predictive, flexible models improve upon standard VAR models with SV. Another key finding is that if we allow for nonlinearities in the conditional mean, allowing for heteroskedasticity becomes less important. A scenario analysis reveals highly nonlinear relations between the predictive distribution and financial conditions.
    Keywords: nonparametric VAR; regression trees; macroeconomic forecasting
    JEL: C11 C32 C53
    Date: 2021–03–22
  8. By: Jennifer N. Carpenter; Fangzhou Lu; Robert F. Whitelaw
    Abstract: Studies of the dynamics of bond risk premia that do not account for the corresponding dynamics of bond risk are hard to interpret. We propose a new approach to modeling bond risk and risk premia. For each of the US and China, we reduce the government bond market to its first two principal-component bond-factor portfolios. For each bond-factor portfolio, we estimate the joint dynamics of its volatility and Sharpe ratio as functions of yield curve variables, and of VIX in the US. We have three main findings. (1) There is an important second factor in bond risk premia. (2) Time variation in bond return volatility is as important as time variation in bond Sharpe ratios. (3) Bond risk premia are solely compensation for bond risk, as no-arbitrage theory predicts. Our approach also allows us to document interesting cyclical and secular time-variation in the term structure of bond risk premia in both the US and China.
    JEL: G12 G15
    Date: 2021–02
  9. By: Delle Monache, Davide (Bank of Italy); De Polis, Andrea (Univeristy of Warwick); Petrella, Ivan (Univeristy of Warwick)
    Abstract: We document a substantial increase in downside risk to US economic growth over the last 30 years. By modelling secular trends and cyclical changes of the predictive density of GDP growth, we find an accelerating decline in the skewness of the conditional distributions, with significant, procyclical variations. Decreasing trend-skewness, which turned negative in the aftermath of the Great Recession, is associated with the long-run growth slowdown started in the early 2000s. Short-run skewness fluctuations imply negatively skewed predictive densities ahead of and during recessions, often anticipated by deteriorating financial conditions, while positively skewed distributions characterize expansions. The model delivers competitive out-of-sample (point, density and tail) forecasts, improving upon standard benchmarks, due to the strong signals of increasing downside risk provided by current financial conditions.
    Keywords: business cycle, financial conditions, downside risk, skewness, score driven models.
    JEL: C12 C22 C51 C53 E37 E44
    Date: 2021–03
  10. By: Xiaoyue Li; A. Sinem Uysal; John M. Mulvey
    Abstract: We employ model predictive control for a multi-period portfolio optimization problem. In addition to the mean-variance objective, we construct a portfolio whose allocation is given by model predictive control with a risk-parity objective, and provide a successive convex program algorithm that provides 30 times faster and robust solutions in the experiments. Computational results on the multi-asset universe show that multi-period models perform better than their single period counterparts in out-of-sample period, 2006-2020. The out-of-sample risk-adjusted performance of both mean-variance and risk-parity formulations beat the fix-mix benchmark, and achieve Sharpe ratio of 0.64 and 0.97, respectively.
    Date: 2021–03
  11. By: M. Hashem Pesaran; Ron P. Smith
    Abstract: This paper examines the implications of pricing errors and factors that are not strong for the Fama-MacBeth two-pass estimator of risk premia and its asymptotic distribution when T is fixed with n → ∞, and when both n and T → ∞, jointly. While the literature just distinguishes strong and weak factors we allow for degrees of strength using a recently developed measure. Our theoretical results have important practical implications for empirical asset pricing. Pricing errors and factor strength matter for consistent estimation of risk premia and subsequent inference, thus an estimate of factor strength is required before attempting to estimate risk. Finally, using a recently developed procedure we provide rolling estimates of factor strengths for the five Fama-French factors, and show that only the market factor can be viewed as strong.
    Keywords: factor strength, pricing errors, risk premia, Fama and MacBeth two-pass estimators, Fama-French factors, panel R2
    JEL: C38 G12
    Date: 2021
  12. By: Haselmann, Rainer; Tröger, Tobias
    Abstract: This in-depth analysis proposes ways to retract from supervisory COVID-19 support measures without perils for financial stability. It simulates the likely impact of the corona crisis on euro area banks' capital and predicts a significant capital shortfall. We recommend to end accounting practices that conceal loan losses and sustain capital relief measures. Our in-depth analysis also proposes how to address the impending capital shortfall in resolution/liquidation and a supranational recapitalisation.
    Keywords: Covid-19,Forbearance,Bank Capitalization,Bank Resolution,Supervisory Relief Measures,Financial Stability
    Date: 2021
  13. By: Juan Andrés Serur; José P. Dapena; Julián R. Siri
    Abstract: Greed and fear are the main psychological factors driving investment deci-sions, and the VIX Index is regarded as the most important measure of howfearful the market feels about future returns of the main equity index, theS&P 500 Index. However, given that the VIX is calculated by combiningboth upside expected volatility implicit in out-of-the-money calls and down-side expected volatility implicit in the value of out-of-the-money puts, thetaken-for-granted assumption that a rising VIX should be interpreted as asign of growing fear in the equities market can be misleading. In this paperwe formally deconstruct the index into two components, the upside and thedownside expected volatility, in a similar fashion as it is done in statisticswith the semi-variance. We then propose a Greed-Fear index using the dataobtained to provide a better gauge about investors’ sentiment on the market.
    Keywords: VIX, Volatility, Greed-Fear index, Variance Swap
    Date: 2021–03
  14. By: Apostolou, Apostolos; Papaioannou, Michael
    Abstract: It is increasingly realized that financial-asset investors individually are not likely able to affect climate developments significantly, while the financial sector collectively cannot hedge all climate-related risks. Nevertheless, the financial sector could help channel savings into green projects through both equity and bond markets, and thus facilitate divestment from heavy carbon-footprint producers. This paper provides a novel framework for understanding climate-related adaptation, mitigation, and transition risks and outlines a method for valuing these risks in investors’ portfolios. Our proposed comprehensive set up can serve as a call for action to longer-term institutional investors to obtain accurate information on climate-related risks, develop appropriate frameworks for understanding these risks, and regularly value them. We maintain that through improvements in the assessment of risks, financial stakeholders would be able to help better manage climate-related risks and facilitate an easier transition from brown to sustainable green finance.
    Keywords: Green Finance, Climate, Investors Portfolios
    JEL: G32 M2 Q54
    Date: 2021
  15. By: Thomas Brand; Fabien Tripier
    Abstract: Highly synchronized during the Great Recession of 2008-2009, the Euro area and the US have diverged in the period that followed. To explain this divergence, we provide a structural interpretation of these episodes through the estimation for both economies of a business cycle model with ?nancial frictions and risk shocks, measured as the volatility of idiosyncratic uncertainty in the ?nancial sector. Our results show that risk shocks have stimulated US growth in the aftermath of the Great Recession and have been the main driver of the double-dip recession in the Euro area. They play a positive role in the Euro area only after 2015. Risk shocks therefore seem well suited to account for the consequences of the sovereign debt crisis in Europe and the subsequent positive e?ects of unconventional monetary policies, notably the ECB’s Asset Purchase Programme (APP).
    Keywords: Great recession;Business cycles;Uncertainty;Risk Shocks;Divergence
    JEL: E3 E4 G3
    Date: 2021–03
  16. By: Matthijs Breugem; Stefano Colonnello; Roberto Marfè; Francesca Zucchi
    Abstract: The term structure of equity and its cyclicality are key to understand the risks driving equilibrium asset prices. We propose a general equilibrium model that jointly explains four important features of the term structure of equity: (i) a negative unconditional term premium, (ii) countercyclical term premia, (iii) procyclical equity yields, and (iv) premia to value and growth claims respectively increasing and decreasing with the horizon. The economic mechanism hinges on the interaction between heteroskedastic long-run growth—which helps price long-term cash flows and leads to countercyclical risk premia—and homoskedastic short-term shocks in the presence of limited market participation — which produce sizeable risk premia to short-term cash flows. The slope dynamics hold irrespective of the sign of its unconditional average. We provide empirical support to our model assumptions and predictions.
    Keywords: Term Structure of Equity, Dynamics, General Equilibrium, Expected Growth Volatility.
    JEL: D51 D53 E30 G10 G12
    Date: 2020
  17. By: Prehn, Sören; Glauben, Thomas; Loy, Jens-Peter
    Abstract: First things first - contrary to popular opinion, the main reason farmers and grain traders use futures markets is not to hedge spot price and basis risks, but to ensure the profitability of the storage business. The scientific literature mainly discusses the minimum variance hedge ratio, which aims at minimizing spot price and basis risks. In practice, however, it is of little use to farmers and grain traders and has the potential to yield negative economic consequences. Minimum variance hedging (MVH) leads to over-hedging on inverse markets and under-hedging on carry markets. In both cases, the costs of storage cannot be (adequately) covered. It is therefore not surprising that farmers and grain traders do not actually use MVH. On a carry market, a good strategy is to trade the basis. The opposite is true for inverse markets where hedging on futures markets does not make sense. Here, it is better to follow a rather speculative strategy that takes account of price trends. In a nutshell: buy on a weak basis and sell on a strong basis (carry market), or speculate (inverse market).
    Keywords: Agricultural Finance, International Relations/Trade, Risk and Uncertainty
    Date: 2021
  18. By: Qi Zhang (China University of Petroleum); Peng Di (China University of Petroleum, IFP School); Arash Farnoosh (IFP School)
    Abstract: In the present study, the daily settlement data of Shanghai crude oil futures and world's major crude oils are selected. The role of Shanghai crude oil futures is studied regarding its pricing power and hedging risk. The dynamic relation analysis between Shanghai crude oil futures and international oil market is conducted by using rolling window causality test. The vector error correction model (VECM) and directed acyclic graph (DAG) are used to explore the long-term relationship and identify the contemporaneous causality structure respectively. Then Shanghai crude oil futures' impacts on other oil price fluctuations are analyzed by using variance decomposition method. The obtained analysis results show that the pricing power of Shanghai crude oil futures is limited compared with the international benchmark oil price, but it has begun to have a contemporaneous influence in the Asian oil market price transmission and better reflect oil supply and demand. Moreover, Shengli crude oil has stronger impact on the pricing mechanism after the listing of Shanghai crude oil futures. Furthermore, it also establishes an effective hedging tool for oil importers and refineries. Therefore, although the Shanghai crude oil futures is still in its initial development stage at present, it provides an important basis for becoming a regional benchmark in Asia and a useful instrument for energy market participants, influencing China's oil industry in import price and consumption.
    Keywords: Shanghai crude oil futures,price transmission,vector error correction model,directed acyclic graph,hedging risk
    Date: 2021–05–15
  19. By: Gloria González-Rivera (University of California, Riverside); Carlos Vladimir Rodríguez-Caballero (Mexico Autonomous Institute of Technology (ITAM) and CREATES); Esther Ruiz Ortega (Universidad Carlos III de Madrid)
    Abstract: Large and unexpected moves in the factors underlying economic growth should be the main concern of policy makers aiming to strengthen the resilience of the economies. We propose measuring the effects of these extreme moves in the quantiles of the distribution of growth under stressed factors (GiS) and compare them with the popular Growth at Risk (GaR). In this comparison, we consider local and global macroeconomic and financial factors affecting US growth. We show that GaR underestimates the extreme and unexpected fall in growth produced by the COVID19 pandemic while GiS is much more accurate.
    Keywords: Growth vulnerability, Multi-level factor model, Stressed growth
    JEL: C32 C55 E32 E44 F44 F47 O41
    Date: 2021–03–15
  20. By: Valentina Aprigliano (Bank of Italy); Simone Emiliozzi (Bank of Italy); Gabriele Guaitoli (University of Warwick); Andrea Luciani (Bank of Italy); Juri Marcucci (Bank of Italy); Libero Monteforte (Ufficio Parlamentare di Bilancio, Bank of Italy)
    Abstract: Can we use newspaper articles to forecast economic activity? Our answer is yes and, to this end, we propose a brand new economic dictionary in Italian with valence shifters, and we apply it to a corpus of about two million articles from four popular newspapers. We produce a set of high-frequency text-based sentiment and policy uncertainty indicators (TESI and TEPU respectively), which are constantly updated, not revised and computed both for the whole economy and for specific sectors or economic topics. To test the predictive power of our text-based indicators, we propose two forecasting exercises. First, by using Bayesian Model Averaging (BMA) techniques, we show that our monthly text-based indicators greatly reduce the uncertainty surrounding the short-term forecasts of the main macroeconomic aggregates, especially during recessions. Secondly, we employ these indices in a weekly GDP growth tracker, achieving sizeable gains in forecasting accuracy in both normal and turbulent times.
    Keywords: Forecasting, Text Mining, Sentiment, Economic Policy Uncertainty, Big data, BMA.
    JEL: C11 C32 C43 C52 C55 E52 E58
    Date: 2021–03
  21. By: Andrés Alonso (Banco de España); José Manuel Marqués (Banco de España)
    Abstract: Climate change and its management and mitigation are unquestionably among the main risks facing our society in the coming decades. The financial sector plays a key role in this challenge, firstly because of its exposure and the consequent capital shocks if this risk crystallises, and secondly because it has the task of financing the investments needed to transform our economy into a sustainable one. This article reviews various initiatives under way in the private financial sector to introduce the variable “sustainability” into its decision-making process in order to achieve a balance sheet with a smaller carbon footprint (transformation of stock) and to develop a business strategy aligned with responsible investment principles and international standards (transformation of flow). We analyse the innovations emerging along the path to sustainable finance, looking particularly at: 1) new suppliers and services in the market, 2) the creation of sustainability-linked financial instruments, 3) the adaptation of financial risk management policies, and 4) the interaction of technological progress with climate change.
    Keywords: fintech, sustainable development goals, climate change, sustainability, green bonds, innovation, artificial intelligence
    JEL: Q54 Q55 Q56
    Date: 2019–10

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