nep-rmg New Economics Papers
on Risk Management
Issue of 2021‒06‒14
twenty papers chosen by

  1. Global Risk and Safe Haven Currency: Copula-DCC Approach By Kumamoto, Masao; Zhuo, Juanjuan
  2. Did the COVID-19 Shock Impair the Stock Performance of Companies with Older CEOs? By Giovanni Ferri; Raffaele Lagravinese; Giuliano Resce
  3. Measure for measure: evidence on the relative performance of regulatory requirements for small and large banks By Sanders, Austen; Willison, Matthew
  4. Growth at Risk and Financial Stability By O'Brien, Martin; Wosser, Michael
  5. Is Corporate Social Responsibility investing a free lunch? The relationship between ESG, tail risk, and upside potential of stocks before and during the COVID-19 crisis By Lööf, Hans; Sahamkhadam, Maziar; Stephan, Andreas
  6. Emotions and Risk Attitudes By Armando N. Meier
  7. Emerging Economies' Vulnerability to Changes in Capital Flows: The Role of Global and Local Factors By Yoshihiko Norimasa; Kazuki Ueda; Tomohiro Watanabe
  8. Operational Risk Capital By Conlon, Thomas; Huan, Xing; Ongena, Steven
  9. HCR & HCR-GARCH – novel statistical learning models for Value at Risk estimation By Michał Woźniak; Marcin Chlebus
  10. The impact of geopolitical risk on stock returns: Evidence from inter-Korea geopolitics By Jung, Seungho; Lee, Jongmin; Lee, Seohyun
  11. The Real Effects of Exchange Rate Risk on Corporate Investment: International Evidence By Taylor, Mark P; Wang, Zigan; Xu, Qi
  12. The risk of being a fallen angel and the corporate dash for cash in the midst of COVID By Acharya, Viral V.; Steffen, Sascha
  13. The risk management approach to macro-prudential policy By Chavleishvili, Sulkhan; Engle, Robert F.; Fahr, Stephan; Kremer, Manfred; Manganelli, Simone; Schwaab, Bernd
  14. Backtesting ESG Ratings By Christophe BOUCHER; Wassim LE LANN; Stéphane MATTON; Sessi TOKPAVI
  15. Do Bankruptcy Protection Levels Affect Households' Demand for Stocks? By Mariela Dal Borgo
  16. A quantitative analysis of the countercyclical capital buffer By Faria-e-Castro, Miguel
  17. Does a financial crisis change a bank's exposure to risk? A difference-in-differences approach By Mäkinen, Mikko
  18. Downside Systematic Risk in Pakistani Stock Market: Role of Corporate Governance, Financial Liberalization and Investor Sentiment By Hussain, Shahzad; Akbar, Muhammad; Malik, Qaisar; Ahmad, Tanveer; Abbas, Nasir
  19. A Sentiment-based Risk Indicator for the Mexican Financial Sector By Caterina Rho; Raúl Fernández; Brenda Palma
  20. GARCHNet - Value-at-Risk forecasting with novel approach to GARCH models based on neural networks By Mateusz Buczyński; Marcin Chlebus

  1. By: Kumamoto, Masao; Zhuo, Juanjuan
    Abstract: In this paper, we employ the Copula-Dynamic Conditional Correlation approach to investigate the safe-haven currency status of eight currencies as well as gold and Bitcoin against the main stock markets. Based on the properties of the estimated dynamic conditional correlations, we classify the currencies into a diversifier, a hedge and a safe haven currency. We also employ the threshold approach to investigate whether market uncertainty measured by the VIX would have significant effects on the estimated dynamic conditional correlation. This analysis is closely related to the study of contagion. We find that the CHF and gold are the strong hedges against the U.S. stock market except for the European sovereign crisis period, and the JPY and Bitcoin have hedge and /or safe currency status. We also find that the degrees of the role of Bitcoin as a hedge currency, and roles of the JPY and gold as a hedge and/or safe haven currency are not affected by the increase in market uncertainty, while that of the CHF as a hedge currency would be weakened as market uncertainty increases.
    Keywords: Safe haven currency, Bitcoin, Contagion, Copula-DCC, Threshold
    JEL: F31 G15
    Date: 2021–06–03
  2. By: Giovanni Ferri (Università di Roma LUMSA); Raffaele Lagravinese (Università degli Studi di Bari "Aldo Moro"); Giuliano Resce (Università degli Studi del Molise)
    Abstract: Since its lethality increases exponentially with age, the early 2020 COVID-19 shock unexpectedly raised the risk of corporate disruption at companies led by older CEOs. While normally unprepared successions might be beneficial by replacing entrenched CEOs, this systemic shock projected a possible crowding of older CEOs' successions, with disruption costs dominating changeover benefits. Within this natural experiment, we find that stock returns and volatility worsened at S&P 500 listed companies with older CEOs when the COVID-19 lethal risk emerged. Our results resist various robustness checks. This advises companies to adopt contingency strategies of top managers’ replacement against possibly recurring pandemics.
    Keywords: COVID-19; Stock Performance; CEO’s Age; S&P 500
    JEL: C23 G12 G32 M12
    Date: 2021–06
  3. By: Sanders, Austen (Bank of England); Willison, Matthew (Bank of England)
    Abstract: This paper compares the performance of regulatory thresholds as predictors of distress for large banks with their performance for small banks. Using a data set of capital and liquidity ratios for a sample of UK‑focused banks in 2007, we apply simple threshold-based rules to assess how regulatory thresholds might have identified banks that subsequently became distressed. We compare results for large banks with results for small banks, optimising thresholds separately for the two groups. Our results suggest that the regulatory ratios we use are better aligned with risks which cause distress of large banks than with those which cause distress of small banks. We find that when thresholds are set to correctly identify a high proportion of banks which subsequently became distressed, they generate materially lower false alarm rates for large banks than for small. This result is robust to definitional choices and to resampling. We also test whether supervisors’ judgements about the quality of banks’ governance have predictive power with regard to distress. We find that adding supervisors’ judgements to regulatory ratios improves predictions for small banks but not for large banks.
    Keywords: Banking regulation; Basel III; bank failure; global financial crisis; regulatory complexity
    JEL: G01 G21 G28
    Date: 2021–05–28
  4. By: O'Brien, Martin (Central Bank of Ireland); Wosser, Michael (Central Bank of Ireland)
    Abstract: Growth at Risk (GaR) provides a methodology for understanding how financial conditions and the level of financial vulnerabilities contribute to the possibility of future episodes of weak economic growth. Using the GaR framework, we show that the likelihood and severity of future weak or negative economic growth in Ireland rises during periods where risks to financial stability are growing. In particular, we show that near term tail risks are heavily influenced by prevailing financial market conditions, but that medium horizon risks are more dependent upon systemic financial vulnerabilities, such as when credit growth is excessive. Our empirical analysis also suggests that structural characteristics of Ireland’s economy or financial system make it more exposed to potential weak growth outcomes, compared with other countries in our sample. We discuss how macroprudential policy can be better informed by tracking developments in the severity and likelihood of weak or negative economic outcomes made possible by a GaR framework.
    Date: 2021–04
  5. By: Lööf, Hans (CESIS - Centre of Excellence for Science and Innovation Studies, Royal Institute of Technology); Sahamkhadam, Maziar (Linnaeus University); Stephan, Andreas (Jönköping International Business School and CESIS, KTH)
    Abstract: Did Corporate Social Responsibility investing benefit shareholders during the COVID-19 pandemic crisis? Distinguishing between downside tail risk and upside reward potential of stock returns, we provide evidence from 5,073 stocks listed on stock markets in ten countries. The findings suggests that better ESG ratings are associated with lower downside risk, but also with lower upside return potential. Thus, ESG ratings help investors to reduce their risk exposure to the market turmoil caused by the pandemic, while maintaining the fundamental trade-off between risk and reward.
    Keywords: ESG; COVID 19; downside risk; upside potential; Sustainalytics; financial markets
    JEL: D22 G11 G14 G32
    Date: 2021–05–27
  6. By: Armando N. Meier
    Abstract: Previous work has shown that preferences are not always stable across time, but surprisingly little is known about the reasons for this instability. I examine whether variation in people’s emotions over time predicts changes in risk attitudes. Using a large panel data set, I identify happiness, anger, and fear as significant correlates of within-person changes in risk attitudes. Robustness checks indicate a limited role of alternative explanations. An event study around the death of a parent or child further confirms a large relationship between emotions and risk attitudes.
    Keywords: Emotions, happiness, risk attitudes, risk preferences, preference stability, SOEP
    JEL: D01 D90 D91
    Date: 2021
  7. By: Yoshihiko Norimasa (Bank of Japan); Kazuki Ueda (Bank of Japan); Tomohiro Watanabe (Nippon Life Insurance Company)
    Abstract: This study uses panel quantile regression to examine the risk of capital outflows in times of stress (capital flows-at-risk, CFaR) for 16 emerging economies. Our analysis shows that changes in financial conditions in advanced economies and in the monetary policy stance of the United States affect the risk of large capital outflows for some countries. In particular, we find that tighter financial conditions in advanced economies during a phase when the U.S. monetary policy stance is changing significantly affect emerging economies' CFaR. Further, using government debt as a measure of emerging economies' structural vulnerability, we find that an increase in government debt substantially raises the risk of capital outflows in times of stress. Moreover, while in the case of debt investment, CFaR tend to be greater the higher the level of government debt, in the case of other investment (consisting mainly of bank lending), CFaR tend to increase when financial conditions in advanced economies deteriorate.
    Keywords: Risk of Capital Outflows (CFaR: Capital Flows-at-Risk); Global Factors; Local Factors; Panel Quantile Regression; Relative Entropy
    JEL: E52 F32 F34 F37
    Date: 2021–05–26
  8. By: Conlon, Thomas; Huan, Xing; Ongena, Steven
    Abstract: We study the response of banks to the introduction of a new capital requirement relating to operational risk. To isolate the effect of this new regulation on realized operational risk losses, we take advantage of the partial US implementation relative to full European adoption. Operational risk losses are reduced in treated banks. The extent of loss reduction depends upon the measurement approach used to calibrate operational risk capital requirements. Banks with low institutional ownership and those without binding regulatory capital constraints also present significant loss reduction. We link these findings to incentives for improved risk management and governance post treatment.
    Keywords: Bank Regulation; Basel II; Measurement Approach; Monitoring; Operational Risk
    JEL: G21 G32
    Date: 2020–07
  9. By: Michał Woźniak (Faculty of Economic Sciences, University of Warsaw); Marcin Chlebus (Faculty of Economic Sciences, University of Warsaw)
    Abstract: Market risk researchers agree that an ideal model for Value at Risk (VaR) estimation does not exist, different models performance strongly depends on current economic circumstances. Under the conditions of sudden volatility increase, such as during the global economic crisis caused by the Covid-19 pandemic, no classical VaR model worked properly even for the group of the largest market indices. Therefore, the aim of the article is to present and formally test three novel statistical learning models for VaR estimation: HCR, HCR-GARCH and HCR-QML-GARCH, which, by considering additional volatility term (due to time context and statistical moments), should be able to perform well in times of market turbulence. In the benchmark procedure we compare the 1% and 2.5% one-day-ahead VaR forecasts obtained with the above models against the estimates of classical methods like: Historical Simulation, KDE, Modified Cornish-Fisher Expansion, GARCH(1,1) with varied distributions, RiskMetrics™, EVT and QML-GARCH. Four periods that vary in terms of market volatility: 2006-9, 2008-11, 2014-17 and mid-2016 to mid-2020 for six different stock market indexes: DAX, WIG 20, MOEX, S&P 500, Nikkei and SHC are selected. Models quality is tested from two perspectives: fulfilling regulatory requirements and forecasting adequateness. Obtained results show that HCR-GARCH outperforms other models during periods of sudden increased volatility in the markets. At the same time, HCR-QML-GARCH liberalizes the conservative estimates of HCR-GARCH and allows its use under moderate volatility, without any major loss of quality in times of crisis.
    Keywords: Value at Risk, Hierarchical Correlation Reconstruction, GARCH, Standardized Residuals
    JEL: G32 C52 C53 C58
    Date: 2021
  10. By: Jung, Seungho; Lee, Jongmin; Lee, Seohyun
    Abstract: We investigate how corporate stock returns respond to geopolitical risk in the case of South Korea, which has experienced large and unpredictable geopolitical swings that originate from North Korea. To do so, a monthly index of geopolitical risk from North Korea (the GPRNK index) is constructed using automated keyword searches in South Korean media. The GPRNK index, designed to capture both upside and downside risk, corroborates that geopolitical risk sharply increases with the occurrence of nuclear tests, missile launches, or military confrontations, and decreases significantly around the times of summit meetings or multilateral talks. Using firm-level data, we find that heightened geopolitical risk reduces stock returns, and that the reductions in stock returns are greater especially for large firms, firms with a higher share of domestic investors, and for firms with a higher ratio of fixed assets to total assets. These results suggest that international portfolio diversification and investment irreversibility are important channels through which geopolitical risk affects stock returns.
    Keywords: Geopolitical risk, Textual analysis, Stock returns, Inter-Korean relations
    JEL: D80 G10 H56
    Date: 2021–05–27
  11. By: Taylor, Mark P; Wang, Zigan; Xu, Qi
    Abstract: We empirically investigate the real effects of exchange rate risk on investment activities of international firms. We provide cross-country, firm-level evidence that greater unexpected currency volatility leads to significantly lower capital expenditures. The effect is stronger for countries with higher economic openness and for firms that do not use currency derivatives to hedge. We empirically test the implications of two potential mechanisms: Real options and precautionary savings. Our findings are consistent with both explanations. Two historical events in the FX markets strengthen the identification of our results.
    Keywords: corporate investment; Exchange rate; uncertainty
    JEL: F31 G31 G32
    Date: 2020–07
  12. By: Acharya, Viral V.; Steffen, Sascha
    Abstract: Data on firm-loan-level daily credit line drawdowns in the United States reveals a corporate "dash for cash" induced by COVID-19. In the first phase of extreme precaution and heightened aggregate risk, all firms drew down bank credit lines and raised cash levels. In the second phase following the adoption of stabilization policies, only the highest-rated firms switched to capital markets to raise cash. Consistent with the risk of becoming a fallen angel, the lowest-quality BBB-rated firms behaved more similarly to non-investment grade firms. The observed corporate behavior reveals the significant impact of credit risk on corporate cash holdings.
    Keywords: Bank lines of credit; cash holdings; liquidity; liquidity risk; Pandemic
    JEL: G01 G14 G32 G35
    Date: 2020–07
  13. By: Chavleishvili, Sulkhan; Engle, Robert F.; Fahr, Stephan; Kremer, Manfred; Manganelli, Simone; Schwaab, Bernd
    Abstract: Macro-prudential authorities need to assess medium-term downside risks to the real economy, caused by severe financial shocks. Before activating policy measures, they also need to consider their short-term negative impact. This gives rise to a risk management problem, an inter-temporal trade-off between expected growth and downside risk. Predictive distributions are estimated with structural quantile vector autoregressive models that relate economic growth to measures of financial stress and the financial cycle. An empirical study with euro area and U.S. data shows how to construct indicators of macro-prudential policy stance and to assess when interventions may be beneficial. JEL Classification: G21, C33
    Keywords: financial conditions, growth-at-risk, macro-prudential policy, quantile vector autoregression, stress testing
    Date: 2021–06
  14. By: Christophe BOUCHER; Wassim LE LANN; Stéphane MATTON; Sessi TOKPAVI
    Keywords: , Backtesting, ESG ratings, ESG risks, ESG-related events, Idiosyncratic realised volatility, Test of equal predictive power, Panel data, Consensus ESG ratings
    Date: 2021
  15. By: Mariela Dal Borgo
    Abstract: This paper examines empirically the effect of the level of personal bankruptcy protection in the US on households' demand for financial assets. A Chapter 7 bankruptcy allows protecting the home equity up to a certain limit or "exemption". Previous literature shows that such exemption biases investment towards home equity. This paper tests whether it also lowers investment in stocks, which are not protected in bankruptcy. Using an instrumental variable approach, I estimate a lower stock market participation when the home equity is below the exemption, but the result is not robust, and households at higher risk of bankruptcy do not exhibit a stronger response. Moreover, investment in home equity is not higher when the home is fully protected. These findings suggest no substantial portfolio distortions from the level of home equity that is protected in bankruptcy.
    JEL: D14 G00 G11 K35
    Date: 2021–05
  16. By: Faria-e-Castro, Miguel
    Abstract: What are the quantitative macroeconomic effects of the countercyclical capital buffer (CCyB)? I study this question in a nonlinear DSGE model with occasional financial crises, which is calibrated and combined with US data to estimate sequences of structural shocks. Raising capital buffers during leverage expansions can reduce the frequency of crises by more than half. A quantitative application to the 2007-08 financial crisis shows that the CCyB in the 2:5% range (as in the Federal Reserve's current framework) could have greatly mitigated the financial panic of 2008, for a cumulative gain of 29% in aggregate consumption. The threat of raising capital requirements is effective even if this tool is not used in equilibrium. JEL Classification: E4, E6, G2
    Keywords: countercyclical capital buffer, financial crises, macroprudential policy
    Date: 2021–06
  17. By: Mäkinen, Mikko
    Abstract: Can a major financial crisis trigger changes in a bank’s risk-taking behavior? Using the 2008 Global Financial Crisis as a quasi-natural experiment and a difference-in-differences approach, I examine whether the worst crisis-hit Russian banks – the banks that have strong incentives to behavior-altering changes – can decrease their post-crisis exposure to risk. A shift in risk-taking behavior by these banks indicates the learning hypothesis. The findings are mixed. The evidence concerning credit risk is inconsistent with the learning hypothesis. On the other hand, the evidence concerning solvency risk is consistent with the learning hypothesis and corroborates evidence from the Nordic countries (Berglund and Mäkinen, 2019). As such, bank learning from a financial crisis may not depend on the institutional context and the level of development of national financial market. Several robustness checks with alternative regression specifications are provided.
    JEL: G01 G21 G32
    Date: 2021–05–28
  18. By: Hussain, Shahzad; Akbar, Muhammad; Malik, Qaisar; Ahmad, Tanveer; Abbas, Nasir
    Abstract: Purpose –We examine the impact of corporate governance, investor sentiment and financial liberalization on downside systematic risk and the interplay of socio-political turbulence on this relationship through static and dynamic panel estimation models.Design/methodology/approach – Our evidence is based on a sample of 230 publicly listed non-financial firms from Pakistan Stock Exchange (PSX) over the period 2008-2018. Furthermore, we analyze the data through Blundell and Bond (1998) technique in full sample as well sub-samples (Big & Small Firms). Findings –We document that corporate governance mechanism reduces the downside risk, whereas, investor sentiment and financial liberalization increase the investors’ exposure toward downside risk. Particularly, the results provide some new insights that the socio-political turbulence as a moderator weakens the impact of corporate governance and strengthens the effect of investor sentiment and financial liberalization on downside risk. Consistent with prior studies, the analysis of sub-samples reveal some statistical variations in large and small-size sampled firms. Theoretically, the findings mainly support agency theory, noise trader theory and the Keynesians hypothesis.Originality/value –Stock market volatility has become a prime area of concern for investors, policy makers and regulators in emerging economies. Primarily, the existence of market volatility is attributed to weak governance, irrational behavior of market participants, liberation of financial policies and sociopolitical turbulence. Therefore, the present study provides simultaneous empirical evidence to determine whether corporate governance, investor sentiment and financial liberalization hinder or spur downside risk in an emerging economy. Furthermore, our work relates to a small number of studies that examine the role of socio-political turbulence as a moderator on the relationship of corporate governance, investor sentiment and financial liberalization with downside systematic risk.
    Date: 2021–05–27
  19. By: Caterina Rho; Raúl Fernández; Brenda Palma
    Abstract: We apply text analysis to Twitter messages in Spanish to build a sentiment- based risk index for the financial sector in Mexico. We classify a sample of tweets for the period 2006-2019 to identify messages in response to positive or negative shocks to the Mexican financial sector. We use a voting classifier to aggregate three different classifiers: one based on word polarities from a pre-defined dictionary; one based on a support vector machine; and one based on neural networks. Next, we compare our Twitter sentiment index with existing indicators of financial stress. We find that this novel index captures the impact of sources of financial stress not explicitly encompassed in quantitative risk measures. Finally, we show that a shock in our Twitter sentiment index correlates positively with an increase in financial market risk, stock market volatility, sovereign risk, and foreign exchange rate volatility.
    JEL: G1 G21 G41
    Date: 2021–05
  20. By: Mateusz Buczyński (Interdisciplinary Doctoral School, University of Warsaw); Marcin Chlebus (Faculty of Economic Sciences, University of Warsaw)
    Abstract: This study proposes a new GARCH specification, adapting a long short-term memory (LSTM) neural network's architecture. Classical GARCH models have been proven to give substantially good results in the case of financial modeling, where high volatility can be observed. In particular, their high value is often praised in the case of Value-at-Risk. However, the lack of nonlinear structure in most of the approaches entails that the conditional variance is not represented in the model well enough. On the contrary, recent rapid advancement of deep learning methods is said to be capable of describing any nonlinear relationships prominently. We suggest GARCHNet - a nonlinear approach to conditional variance that combines LSTM neural networks with maximum likelihood estimators of probability in GARCH. The distributions of the innovations considered in the paper are: normal, t and skewed t, however the approach does enable extensions to other distributions as well. To evaluate our model, we have executed an empirical study on the log returns of WIG 20 (Warsaw Stock Exchange Index) in four different time periods throughout 2005 and 2021 with varying levels of observed volatility. Our findings confirm the validity of the solution, however we present several directions to develop it further.
    Keywords: Value-at-Risk, GARCH, neural networks, LSTM
    JEL: G32 C52 C53 C58
    Date: 2021

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