nep-rmg New Economics Papers
on Risk Management
Issue of 2021‒05‒17
seventeen papers chosen by

  1. Safe Haven or Hedge: Diversification Abilities of Asset Classes in Pakistan By Imran, Zulfiqar Ali; Ahad, Muhammad
  2. Global Index on Financial Losses due to Crime in the United States By Thilini Mahanama; Abootaleb Shirvani; Svetlozar Rachev
  3. Climate Finance By Giglio, Stefano W; Kelly, Bryan; Ströbel, Johannes
  4. Hedging under rough volatility By Masaaki Fukasawa; Blanka Horvath; Peter Tankov
  5. Risk Mitigating versus Risk Shifting: Evidence from Banks Security Trading in Crises By Peydró, José Luis; Polo, Andrea; Sette, Enrico
  6. Incentive contracts when agents distort probabilities By Víctor González-Jiménez
  7. The Expected Return on Risky Assets: International Long-run Evidence By Kuvshinov, Dmitry; Zimmermann, Kaspar
  8. A GPS navigator to monitor risks in emerging economies: the vulnerability dashboard By Irma Alonso; Luis Molina
  9. Bankruptcy Prediction Model Based on Business Risk Reports : Use of Natural Language Processing Techniques By Rasolomanana, Onjaniaina Mianin'Harizo
  10. Interactions of capital and liquidity requirements: a review of the literature By Vo, Quynh-Anh
  11. Aspects of a phase transition in high-dimensional random geometry By Axel Pr\"user; Imre Kondor; Andreas Engel
  12. Dynamics of Firm-level exchange rate risk around the world: Evidence from COVID-19 By Ekta Sikarwar
  13. Pricing Currency Risks By Chernov, Mikhail; Dahlquist, Magnus; Lochstoer, Lars
  14. The People versus the Markets: A Parsimonious Model of Inflation Expectations By Reis, Ricardo
  15. Least squares Monte Carlo methods in stochastic Volterra rough volatility models By Henrique Guerreiro; Jo\~ao Guerra
  16. Optimal Sustainable Intergenerational Insurance By Lancia, Francesco; Russo, Alessia; Worrall, Tim S
  17. Developments in the Credit Score Distribution over 2020 By Sarena Goodman; Geng Li; Alvaro Mezza; Lucas Nathe

  1. By: Imran, Zulfiqar Ali; Ahad, Muhammad
    Abstract: This study compares the safe haven properties of asset classes of real estate (house, plot and residential), gold, dollar, and oil against equity returns in Pakistan for the period January 2011-December 2020. We employ the wavelet coherence to encapsulate the overall dependence and correlation of asset classes. Our results show the dependence is weaker (stronger) in short (long) term investment horizon. We also study the potential of diversification at the tail of returns distribution by applying wavelet value-at-risk (VaR) framework that reveals the degree of co-movement between gold and equity returns greatly affects the portfolio risk followed by residential property and oil. Our findings are beneficial for the individual investor, fund managers and financial advisors looking for the optimal portfolio combination that hedge the excessive negative movements in equity returns subject to the heterogeneity in the investment horizon.
    Keywords: Equity; Real Estate; Oil; Gold, US Dollar; Diversification; Pakistan.
    JEL: F21 G11 G15 Q02
    Date: 2021–04–01
  2. By: Thilini Mahanama; Abootaleb Shirvani; Svetlozar Rachev
    Abstract: Crime can have a volatile impact on investments. Despite the potential importance of crime rates in investments, there are no indices dedicated to evaluating the financial impact of crime in the United States. As such, this paper presents an index-based insurance portfolio for crime in the United States by utilizing the financial losses reported by the Federal Bureau of Investigation for property crimes and cybercrimes. Our research intends to help investors envision risk exposure in our portfolio, gauge investment risk based on their desired risk level, and hedge strategies for potential losses due to economic crashes. Underlying the index, we hedge the investments by issuing marketable European call and put options and providing risk budgets (diversifying risk to each type of crime). We find that real estate, ransomware, and government impersonation are the main risk contributors. We then evaluate the performance of our index to determine its resilience to economic crisis. The unemployment rate potentially demonstrates a high systemic risk on the portfolio compared to the economic factors used in this study. In conclusion, we provide a basis for the securitization of insurance risk from certain crimes that could forewarn investors to transfer their risk to capital market investors.
    Date: 2021–05
  3. By: Giglio, Stefano W; Kelly, Bryan; Ströbel, Johannes
    Abstract: We review the literature studying interactions between climate change and financial markets. We first discuss various approaches to incorporating climate risk in macro-finance models. We then review the empirical literature that explores the pricing of climate risks across a large number of asset classes including real estate, equities, and fixed income securities. In this context, we also discuss how investors can use these assets to construct portfolios that hedge against climate risk. We conclude by proposing several promising directions for future research in climate finance.
    Date: 2020–12
  4. By: Masaaki Fukasawa; Blanka Horvath; Peter Tankov
    Abstract: In this chapter we first briefly review the existing approaches to hedging in rough volatility models. Next, we present a simple but general result which shows that in a one-factor rough stochastic volatility model, any option may be perfectly hedged with a dynamic portfolio containing the underlying and one other asset such as a variance swap. In the final section we report the results of a back-test experiment using real data, where VIX options are hedged with a forward variance swap. In this experiment, using a rough volatility model allows to almost completely remove the bias and reduce the overall hedging error by a factor of 27% compared to traditional diffusion-based models.
    Date: 2021–05
  5. By: Peydró, José Luis; Polo, Andrea; Sette, Enrico
    Abstract: We show that risk mitigating incentives dominate risk shifting incentives in fragile banks. Risk shifting could be particularly severe in banking since it is the most opaque industry and banks are one of the most leveraged corporations with very low skin in the game. To analyze this question, we exploit security trading by banks during financial crises, as banks can easily and quickly change their risk exposure within their security portfolio. However, in contrast with the risk shifting hypothesis, we find that less capitalized banks take relatively less risk after financial market stress shocks. We show this using the supervisory ISIN-bank-month level dataset from Italy with all securities for each bank. Our results are over and above capital regulation as we show lower reach-for-yield effects by less capitalized banks within government bonds (with zero risk weights) or within securities with the same rating and maturity in the same month (which determines regulatory capital). Effects are robust to controlling for the covariance with the existence portfolio, and less capitalized banks, if anything, reduce concentration risk. Further, effects are stronger when uncertainty is higher, despite that risk shifting motives may be then higher. Moreover, three separate tests â?? based on different accounting portfolios (trading book versus held to maturity), the distribution of capital and franchise value â?? suggest that bank own incentives, instead of supervision, are the main drivers. Results are confirmed if we consider other sources of balance sheet fragility and different measures of risk-taking. Finally, evidence from the recent COVID-19 shock corroborates findings from the Global Financial Crisis and the Euro Area Sovereign Crisis.
    Keywords: bank capital; concentration risk; COVID-19; held to maturity; interbank funding; risk shifting; risk weights; trading book; uncertainty
    JEL: G01 G21 G28
    Date: 2020–11
  6. By: Víctor González-Jiménez
    Abstract: I show that stochastic contracts are powerful motivational devices when agents distort probabilities. Stochastic contracts allow the principal to target probabilities that, when distorted by the agent, enhance the agent's motivation to exert effort on the delegated task. This novel source of incentives is absent in traditional contracts. A theoretical framework and an experiment demonstrate that stochastic contracts targeting small probabilities, and thus exposing the agent to a large degree of risk, generate higher performance levels than traditional contracting modalities. A result that contradicts the standard rationale that optimal contracts should feature a tradeoff between insurance and efficiency. This unintuitive finding is attributed to probability distortions caused by likelihood insensitivity - cognitive limitations that restrict the accurate evaluation of probabilities.
    JEL: C91 C92 J16 J24
    Date: 2101–05
  7. By: Kuvshinov, Dmitry; Zimmermann, Kaspar
    Abstract: This paper estimates the expected return on equity and housing for 17 advanced economies between years 1870 and 2015. We show that the expected risky return has been in steady decline, but its trend is markedly different to that in the safe rate. As a consequence, the ex ante risk premium exhibits large secular movements, and risk premia and safe rates are strongly negatively correlated. Our findings suggest that time-varying risk appetite is a key driver of expected risky and safe returns - not only in the short, but also in the long run.
    Keywords: expected returns; long-run trends; real interest rates; return predictability; risk premia
    JEL: E43 E44 G12 G15 N20
    Date: 2020–12
  8. By: Irma Alonso (Banco de España); Luis Molina (Banco de España)
    Abstract: This paper presents a simple, transparent and model-free framework for monitoring the build-up of vulnerabilities in emerging economies that may affect financial stability in Spain through financial, foreign direct investment or trade linkages, or via global turbulences. The vulnerability dashboards proposed are based on risk percentiles for a set of 34 key indicators according to their historical and cross-section frequency distributions. The framework covers financial market variables, macroeconomic fundamentals –which are grouped into real, fiscal, banking and external variables– and institutional quality and political indicators. This methodology is a valuable complement to other existing tools such as the Basel credit-to-GDP gap and vulnerability indices.
    Keywords: emerging economies, crisis, vulnerabilities, heat maps, risks
    JEL: F01 F34 G01 G32
    Date: 2021–04
  9. By: Rasolomanana, Onjaniaina Mianin'Harizo
    Abstract: The purpose of this study is to assess how useful risk information is in bankruptcy prediction, by performing a sentiment analysis of the texts. The proposed method involves the use of Natural Language Processing (NLP) and machine learning techniques. The results show that neural networks performed better than other classifiers, with a classification accuracy of 96.15% for this particular text classification problem. This work demonstrates that business risks reports carry information that helps predict the likelihood of bankruptcy.
    Keywords: Bankruptcy prediction, Business risk, Natural language processing, NLP, Sentiment analysis, Neural Networks,
    Date: 2021–04
  10. By: Vo, Quynh-Anh (Bank of England)
    Abstract: One prominent feature of the regulatory framework put in place after the global financial crisis of 2008 is its reliance on multiple regulatory metrics, which has prompted new research on the interactions between them. This paper reviews the growing literature on the interactions between capital and liquidity requirements – the two primary requirements of the Basel III framework – with the focus on what the literature conveys on the extent to which capital and liquidity requirements are substitutes or complements. The paper also identifies gaps for further research.
    Keywords: Capital requirements; liquidity requirements; substitutability; complementarity
    JEL: G21 G28
    Date: 2021–04–16
  11. By: Axel Pr\"user; Imre Kondor; Andreas Engel
    Abstract: A phase transition in high-dimensional random geometry is analyzed as it arises in a variety of problems. A prominent example is the feasibility of a minimax problem that represents the extremal case of a class of financial risk measures, among them the current regulatory market risk measure Expected Shortfall. Others include portfolio optimization with a ban on short selling, the storage capacity of the perceptron, the solvability of a set of linear equations with random coefficients, and competition for resources in an ecological system. These examples shed light on various aspects of the underlying geometric phase transition, create links between problems belonging to seemingly distant fields and offer the possibility for further ramifications.
    Date: 2021–05
  12. By: Ekta Sikarwar (Indian Institute of Management Kozhikode)
    Abstract: The objective of this study is to examine the dynamics of asymmetry and nonlinearity in firms’ exchange rate risk during crisis periods. The study investigates the exchange rate exposure of 1,577 firms across 13 industry sectors in 21 countries around the world using an extended Jorion (1990) model. The analysis covers two time periods?January 2017–November 2019 (preCOVID-19 period) and December 2019–November 2020 (COVID-19 period). The results provide evidence of a strong presence and a substantial increase in asymmetric and nonlinear exchange rate exposure of firms during the COVID-19 period.
    Keywords: Exchange rate exposure; COVID-19; nonlinear; asymmetry
    Date: 2021–02
  13. By: Chernov, Mikhail; Dahlquist, Magnus; Lochstoer, Lars
    Abstract: The currency market features a relatively small cross-section and conditional expected returns can be characterized by only a few signals â?? interest differentials, trend and mean-reversion. We exploit these properties to construct a conditional projection of the stochastic discount factor onto excess returns of individual currencies. Our approach is implementable in real time and prices all currencies and prominent strategies conditionally as well as unconditionally. We document that the fraction of unpriced risk in these assets is at least 85%. Extant explanations of carry strategies based on intermediary capital or global volatility are related to these unpriced components, while consumption growth is related to the priced component of returns.
    Keywords: currency risk premiums; factor models; Stochastic discount factor
    JEL: F31 G12 G15
    Date: 2020–12
  14. By: Reis, Ricardo
    Abstract: Expected long-run inflation is sometimes inferred using market prices, other times using surveys. The discrepancy between the two measures has large business-cycle fluctuations, is systematically correlated with monetary policies, and is mostly driven by disagreement, both between households and traders, and between different traders. A parsimonious model that captures both the dispersed expectations in surveys, and the trading of inflation risk in financial markets, can fit the data, and it provides estimates of the underlying expected inflation anchor. Applied to US data, the estimates suggest that inflation became gradually, but steadily, unanchored from 2014 onwards. The model detects this from the fall in cross-person expectations skewness, first across traders, then across people. In general equilibrium, when inflation and the discrepancy are jointly determined, monetary policy faces a trade-off in how strongly to respond to the discrepancy.
    JEL: D84 E31 E52
    Date: 2021–01
  15. By: Henrique Guerreiro; Jo\~ao Guerra
    Abstract: In stochastic Volterra rough volatility models, the volatility follows a truncated Brownian semi-stationary process with stochastic vol-of-vol. Recently, efficient VIX pricing Monte Carlo methods have been proposed for the case where the vol-of-vol is Markovian and independent of the volatility. Following recent empirical data, we discuss the VIX option pricing problem for a generalized framework of these models, where the vol-of-vol may depend on the volatility and/or not be Markovian. In such a setting, the aforementioned Monte Carlo methods are not valid. Moreover, the classical least squares Monte Carlo faces exponentially increasing complexity with the number of grid time steps, whilst the nested Monte Carlo method requires a prohibitive number of simulations. By exploring the infinite dimensional Markovian representation of these models, we device a scalable least squares Monte Carlo for VIX option pricing. We apply our method firstly under the independence assumption for benchmarks, and then to the generalized framework. We also discuss the rough vol-of-vol setting, where Markovianity of the vol-of-vol is not present. We present simulations and benchmarks to establish the efficiency of our method.
    Date: 2021–05
  16. By: Lancia, Francesco; Russo, Alessia; Worrall, Tim S
    Abstract: Optimal intergenerational insurance is examined in a stochastic overlapping generations endowment economy with limited enforcement of risk-sharing transfers. Transfers are chosen by a benevolent planner who maximizes the expected discounted utility of all generations while respecting the participation constraint of each generation. We show that the optimal sustainable intergenerational insurance is history dependent. The risk from a shock is unevenly spread into the future, generating heteroscedasticity and autocorrelation of consumption even in the long run. The optimum can be interpreted as a social security scheme characterized by a minimum welfare entitlement for the old and state-contingent entitlement thresholds.
    Keywords: Intergenerational insurance; Limited Commitment; Risk Sharing; stochastic overlapping generations
    JEL: D64 E21 H55
    Date: 2020–12
  17. By: Sarena Goodman; Geng Li; Alvaro Mezza; Lucas Nathe
    Abstract: The distribution of household credit risk can vary with aggregate economic and credit conditions. For example, the share of subprime-scored borrowers declined at a relatively steady pace during the economic recovery from the Global Financial Crisis. Although the COVID-19 pandemic interrupted the economic conditions that supported this trend, the pace of decline accelerated following the pandemic’s onset in March 2020. The analysis that follows suggests that this acceleration was largely driven by the Coronavirus Aid, Relief, and Economic Security Act’s (CARES Act) forbearance provisions.
    Date: 2021–04–30

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