nep-rmg New Economics Papers
on Risk Management
Issue of 2022‒04‒25
eighteen papers chosen by

  1. Exploring the hedge, diversifier and safe haven properties of ESG investments: A cross-quantilogram analysis By Pedini, Luca; Severini, Sabrina
  2. Bivariate Distribution Regression with Application to Insurance Data By Yunyun Wang; Tatsushi Oka; Dan Zhu
  3. Exposición al default: estimación para un portafolio de tarjeta de crédito By Bambino-Contreras, Carlos; Morales-Oñate, Víctor
  4. Deep Reinforcement Learning and Convex Mean-Variance Optimisation for Portfolio Management By Ruan Pretorius; Terence van Zyl
  5. Heterogeneous criticality in high frequency finance: a phase transition in flash crashes By Turiel, Jeremy D.; Aste, Tomaso
  6. Dynamic Optimal Hedge Ratio Design when Price and Production are stochastic with Jump By Nyassoke Titi Gaston Clément; Jules Sadefo-Kamdem; Louis Aimé Fono
  7. Collective Moral Hazard and the Interbank Market By Levent Altinoglu; Joseph E. Stiglitz
  8. When does portfolio compression reduce systemic risk? By Veraart, Luitgard A. M.
  9. Returns in US copper companies the face of the volatility and stringency of COVID-19 By Pastén, Boris; Tapia, Pablo; Sepúlveda, Jorge
  10. Dynamics of Subjective Risk Premia By Stefan Nagel; Zhengyang Xu
  11. Endogenous Option Pricing By Andrea Gamba; Alessio Saretto
  12. Discounting Trillions of Dollars in Pension Obligations: A Better Alternative to Using the Expected Return or Risk-Free Rate By Woutersen, Tiemen
  13. The application of techniques derived from artificial intelligence to the prediction of the solvency of bank customers: case of the application of the cart type decision tree (dt) By Karim Amzile; Rajaa Amzile
  14. Macroprudential Policy Efficiency: Assessment for the Uncollateralized Consumer Loans in Russia By Irina Kozlovtceva; Henry Penikas; Ekaterina Petreneva; Yulia Ushakova
  15. The role of asset payouts in the estimation of default barriers By Bougias, Alexandros; Episcopos, Athanasios; Leledakis, George N.
  16. Will Chinese Twenty-four Solar Terms Affect Stock Return: Evidence from Shanghai Index of China By Zhou Tianbao; Li Xinghao; Zhao Junguang
  17. Stock Volatility and the War Puzzle By Gustavo S. Cortes; Angela Vossmeyer; Marc D. Weidenmier
  18. Does Something Change in the Oil Market with the COVID-19 Crisis ? By Dan Zhang; Arash Farnoosh; Frédéric Lantz

  1. By: Pedini, Luca; Severini, Sabrina
    Abstract: This article proposes an empirical investigation, based on a cross-quantilogram analysis, to assess the hedge, diversifier and safe haven properties of Environmental, Social and Governance (ESG) assets in comparison to conventional investment practices (equity index, gold, commodities and cryptocurrencies). Our evidence shows that ESG assets have a weak safe haven properties but still represent an outstanding diversification and hedge asset, depending on the asset class taken as reference. Our results provide important implications for risk management suggesting that investors have started considering sustainable investing as a new measure of value maximization and risk reduction.
    Keywords: cross-quantilogram; ESG investment; safe haven; portfolio allocation
    JEL: C32 C52 G01 G11
    Date: 2022
  2. By: Yunyun Wang; Tatsushi Oka; Dan Zhu
    Abstract: This article introduces an estimation method for the conditional joint distribution of bivariate outcomes, based on the distribution regression approach and the factorization method. The proposed method can apply for discrete, continuous or mixed distribution outcomes. It is semiparametric in that both marginal and joint distributions are left unspecified, conditional on covariates. Unlike the existing parametric approaches, our method is simple yet flexible to encapsulate distributional dependence structures of bivariate outcomes and covariates. Various simulation results confirm that our method can perform similarly or better in finite samples compared to the alternative methods. In an application to the study of a motor third-part liability insurance portfolio, the proposed method effectively captures key distributional features in the data, especially the value at risks conditional on covariates. This result suggests that this semiparametric approach can serve as an alternative in insurance risk management.
    Date: 2022–03
  3. By: Bambino-Contreras, Carlos; Morales-Oñate, Víctor
    Abstract: This work estimates the exposure at default of a credit card portfolio of an Ecuadorian bank without using the credit conversion factor, a common mechanism used in the expected loss distribution estimation literature and suggested by the Basel Committee. To achieve this goal, the probability distribution of this variable (exposure at default) has been identified so that it can be used in the context of generalized linear models. The results show that the model can be used to make predictions based on assumptions closer to the reality of customer behavior based on the variables used in the regression.
    Keywords: Expected loss, Credit risk, Exposure at default, Generalized linear models, Gamma Distribution, Machine Learning
    JEL: C1 G32
    Date: 2021–12
  4. By: Ruan Pretorius; Terence van Zyl
    Abstract: Traditional portfolio management methods can incorporate specific investor preferences but rely on accurate forecasts of asset returns and covariances. Reinforcement learning (RL) methods do not rely on these explicit forecasts and are better suited for multi-stage decision processes. To address limitations of the evaluated research, experiments were conducted on three markets in different economies with different overall trends. By incorporating specific investor preferences into our RL models' reward functions, a more comprehensive comparison could be made to traditional methods in risk-return space. Transaction costs were also modelled more realistically by including nonlinear changes introduced by market volatility and trading volume. The results of this study suggest that there can be an advantage to using RL methods compared to traditional convex mean-variance optimisation methods under certain market conditions. Our RL models could significantly outperform traditional single-period optimisation (SPO) and multi-period optimisation (MPO) models in upward trending markets, but only up to specific risk limits. In sideways trending markets, the performance of SPO and MPO models can be closely matched by our RL models for the majority of the excess risk range tested. The specific market conditions under which these models could outperform each other highlight the importance of a more comprehensive comparison of Pareto optimal frontiers in risk-return space. These frontiers give investors a more granular view of which models might provide better performance for their specific risk tolerance or return targets.
    Date: 2022–02
  5. By: Turiel, Jeremy D.; Aste, Tomaso
    Abstract: Flash crashes in financial markets have become increasingly important, attracting attention from financial regulators, market makers as well as from the media and the broader audience. Systemic risk and the propagation of shocks in financial markets is also a topic of great relevance that has attracted increasing attention in recent years. In the present work, we bridge the gap between these two topics with an in-depth investigation of the systemic risk structure of co-crashes in high frequency trading. We find that large co-crashes are systemic in their nature and differ from small ones. We demonstrate that there is a phase transition between co-crashes of small and large sizes, where the former involves mostly illiquid stocks, while large and liquid stocks are the most represented and central in the latter. This suggests that systemic effects and shock propagation might be triggered by simultaneous withdrawals or movement of liquidity by HFTs, arbitrageurs and market makers with cross-asset exposures.
    Keywords: criticality; financial networks; flash crash; high frequency trading; market microstructure; phase transition; systemic risk; EP/L015129/1; (EP/P031730/1) and EC (H2020-ICT-2018-2 825215).; ES/K002309/1
    JEL: F3 G3
    Date: 2022–02–10
  6. By: Nyassoke Titi Gaston Clément (Université de Douala); Jules Sadefo-Kamdem (MRE - Montpellier Recherche en Economie - UM - Université de Montpellier, UG - Université de Guyane); Louis Aimé Fono (Université de Douala)
    Abstract: In this paper, we focus on the farmer's risk income, by using commodity futures, when price and output processes are correlated random represented by jump-diffusion models. We evaluate the expected utility of the farmer's wealth and we determine, at each instant of time, the optimal consumption rate and hedge position at given the time to harvest and state variables. We find a closed form optimal position of consumption and position rate in case of CARA utility investor. This result (see table 1.5) is a generalization of Ho (1984) result who consider the particular case where price and output are diffusion models.
    Keywords: Jump-diffusion process,futures,stochastic dynamic programming,Lévy measure,risk management
    Date: 2022
  7. By: Levent Altinoglu; Joseph E. Stiglitz
    Abstract: The concentration of risk within the financial system leads to systemic instability. We propose a theory to explain the structure of the financial system and show how it alters the risk taking incentives of financial institutions when the government optimally intervenes during crises. By issuing interbank claims, risky institutions endogenously become too interconnected to fail. This concentrated structure enables institutions to share the risk of systemic crises in a privately optimal way, but leads to excessive risk taking even by peripheral institutions. Interconnectedness and excessive risk taking reinforce one another. Macroprudential regulation which limits the interconnectedness of risky institutions improves welfare.
    JEL: E44 E61 G01 G18 G28
    Date: 2022–02
  8. By: Veraart, Luitgard A. M.
    Abstract: We analyze the consequences of portfolio compression for systemic risk. Portfolio compression is a post-trade netting mechanism that reduces gross positions while keeping net positions unchanged and it is part of the financial legislation in the United States (Dodd–Frank Act) and in Europe (European Market Infrastructure Regulation). We derive necessary structural conditions for portfolio compression to be harmful and discuss policy implications. We show that any potential harmfulness of portfolio compression arises from contagion effects. We show how portfolio compression affects systemic risk depends on the resilience of nodes taking part in compression, on the proportion of debt that they can repay, and on the recovery rates in case of default. In particular, the potential danger of portfolio compression comes from defaults of firms that conduct portfolio compression. If no defaults occur among the firms that engage in compression, then portfolio compression always reduces systemic risk.
    Keywords: systemic risk; portfolio compression; financial networks; cycles; netting
    JEL: D85 G28 G33
    Date: 2022–03–01
  9. By: Pastén, Boris; Tapia, Pablo; Sepúlveda, Jorge
    Abstract: Copper plays an important role in the production of technology and portfolios, yet it still faces the consequences of COVID-19. The financial literature that includes copper does so together with other commodities, resulting in reduced coverage of the determinants of this metal, leaving questions. We will use linear and VAR-X models to relate the financial market volatility (VIX) and the management of the spread of COVID-19 (stringency) to the returns of copper companies in the United States. We found evidence that the VIX and stringency have a negative effect on the returns of these companies, with Chile’s stringency being the most negative. This evidence suggests that investors seem to prioritize their actions on copper production (Chile), and more on volatility, if present. This may help to better understand investors’ actions in the face of such scenarios.
    Keywords: Mining; Copper; COVID-19; Lockdown Stringency; Uncertainty.
    JEL: G11 G12 G15 G18
    Date: 2022–03–28
  10. By: Stefan Nagel; Zhengyang Xu
    Abstract: We examine subjective risk premia implied by return expectations of individual investors and professionals for aggregate portfolios of stocks, bonds, currencies, and commodity futures. While in-sample predictive regressions with realized excess returns suggest that objective risk premia vary countercyclically with business cycle variables and aggregate asset valuation measures, subjective risk premia extracted from survey data do not comove much with these variables. This lack of cyclicality of subjective risk premia is a pervasive property that holds in expectations of different groups of market participants and in different asset classes. A similar lack of cyclicality appears in out-of-sample forecasts of excess returns, which suggests that investors’ learning of forecasting relationships in real time may explain much of the cyclicality gap. These findings cast doubt on models that explain time-varying objective risk premia inferred from in-sample regressions with countercyclical variation in perceived risk or risk aversion. We further find a link between subjective perceptions of risk and subjective risk premia, which points toward a positive risk-return tradeoff in subjective beliefs.
    JEL: G12 G41
    Date: 2022–02
  11. By: Andrea Gamba; Alessio Saretto
    Abstract: We show that a structural model of firm decisions can produce very flexible implied volatility surfaces: upward and downward sloping, u-shaped. A calibrated version of the model is able to match many unconditional financial characteristics of the average option-able stock, and can help explain how, contrary to simple economic intuition, more valuable growth and contraction options are associated with a more negatively sloped implied volatility curve (i.e., a more negatively skewed implied distribution).
    Keywords: option pricing; risk-neutral skewness; growth options; leverage; investments
    JEL: G12 G32
    Date: 2022–03–24
  12. By: Woutersen, Tiemen (The Johns Hopkins Institute for Applied Economics, Global Health, and the Study of Business Enterprise)
    Abstract: This paper proposes a new discount rate that pension funds can use to discount their future obligations. If the payouts of a pension fund depend on the return of the fund's assets, then neither the risk-free rate nor the expected return is an equitable way to discount future liabilities. Using the newly proposed rate, the expected utilities of a particular stream of payments are the same in each period. This proposed rate is higher than the discount rate that is used by some pension funds but lower than the rate that the U.S. States are required to use.
    Keywords: Discount rate; Pension fund obligations; valuation future obligations
    JEL: G20 G28 H50 H55 H60
    Date: 2022–03
  13. By: Karim Amzile; Rajaa Amzile
    Abstract: In this study we applied the CART-type Decision Tree (DT-CART) method derived from artificial intelligence technique to the prediction of the solvency of bank customers, for this we used historical data of bank customers. However we have adopted the process of Data Mining techniques, for this purpose we started with a data preprocessing in which we clean the data and we deleted all rows with outliers or missing values as well as rows with empty columns, then we fixed the variable to be explained (dependent or Target) and we also thought to eliminate all explanatory (independent) variables that are not significant using univariate analysis as well as the correlation matrix, then we applied our CART decision tree method using the SPSS tool. After completing our process of building our model (AD-CART), we started the process of evaluating and testing the performance of our model, by which we found that the accuracy and precision of our model is 71%, so we calculated the error ratios, and we found that the error rate equal to 29%, this allowed us to conclude that our model at a fairly good level in terms of precision, predictability and very precisely in predicting the solvency of our banking customers.
    Date: 2022–03
  14. By: Irina Kozlovtceva (Bank of Russia, Russian Federation); Henry Penikas (Bank of Russia, Russian Federation); Ekaterina Petreneva (Bank of Russia, Russian Federation); Yulia Ushakova (Bank of Russia, Russian Federation)
    Abstract: We use the Russian banks’ 2015-2019 data to evaluate the effectiveness of the macro- prudential measures in curbing the booming consumer lending segment. We find that the measures are successful in reducing the overall loan portfolio riskiness and in capital cushion accumulation by banks. In the short-run of up to 1-2 quarters after the measure announcement date banks tend to reduce both the new loan volumes and the average consumer loan portfolio growth rate. Such reduction is more typical with the smallest market players. However, in the longer time horizon up to a year from the measure application date we observe the increase in the average credit growth rates. Such findings correspond to the experience of the emerging markets of Argentine, Colombia, Thailand. In general, we consider that the observed credit growth after the measure implementation is smaller than it could have been without the measures in place. We also expect that the observed lending growth rate brings less financial instability risks and it reflects the potential for the natural loan extension in Russia.
    Keywords: financial stability, risk-weight, consumer loan, macroprudential
    JEL: G21 G28 G32
    Date: 2020–11
  15. By: Bougias, Alexandros; Episcopos, Athanasios; Leledakis, George N.
    Abstract: In the barrier option model of corporate security valuation, the firm’s creditors impose a default-triggering barrier on the firm value to protect their claim. Two disputed issues in the literature are whether the implied default barrier is positive, and whether it is above or below the book value of the firm’s liabilities. We extend the model of Brockman and Turtle (2003, Journal of Financial Economics 67, 511–529) by embedding asset payouts in the valuation of shareholders’ equity. Using a sample of US stocks from the NYSE, AMEX, and NASDAQ exchanges, our paper exploits market and firm information to compute the implied default barrier for thirty 2-digit SIC groups, including industrials and banks. Our results show that the implied default barrier is lower than it is in the received literature, and it can be less than total liabilities, even zero for some firms. The implied physical default probabilities are significantly lower in the presence of payouts, providing a closer fit to the historical corporate default rates, particularly for issuers of speculative-grade bonds.
    Keywords: Contingent claims; Barrier option; Issuer credit ratings; Default barrier; Asset payouts
    JEL: G12 G33
    Date: 2022–02–24
  16. By: Zhou Tianbao; Li Xinghao; Zhao Junguang
    Abstract: In this article, readers will see the impact on Chinese stock index brought by twenty-four solar terms, a unique division of annual season in Chinese tradition. Based on the data in the past 26 years, the study focused on whether the daily return (revenue) of Shanghai Index shows significant value and special feature on and after each solar term.On several solar terms did the index return result large mean value and high probability of extreme value occurrence such as on solar term No.1 and No.3 while on solar term No.2 and solar term No.4, the results were completely the opposite.The study also found that the volatility of index return during those solar terms in the beginning of the year were more active than the rest of them. Index return 10 days and 15days after solar term No.6 and solar term No.8 displayed high final return and large volatility whereas in any cases, the index went very steady after solar term No.18.The study also proposed that it is almost impossible to make numeric prediction with the current technical analysis tools, the effective way in stock analysis to collect more feature and characteristics based on historical data, identifying if the similar situation is happening when similar feature of stock shows up in the future.
    Date: 2022–03
  17. By: Gustavo S. Cortes; Angela Vossmeyer; Marc D. Weidenmier
    Abstract: U.S. stock volatility is 33 percent lower during wartime and periods of conflict. This is true even for World Wars I and II, which would seemingly increase uncertainty. In a seminal paper, Schwert (1989) identified the “war puzzle” as one of the most surprising facts from two centuries of stock volatility data. We propose an explanation for the puzzle: the profits of firms become easier to forecast during wartime due to massive government spending. We test this hypothesis using newly-constructed data on more than 100 years of defense spending. The aggregate analysis finds that defense spending reduces stock volatility. The sector level regressions show that defense spending predicts lower stock volatility for firms that produce military goods. Finally, an event-study demonstrates that earnings forecasts of defense firms by equity analysts become significantly less disperse after 9/11 and the invasions of Afghanistan (2001) and Iraq (2003).
    JEL: E30 G1 H56 N12
    Date: 2022–03
  18. By: Dan Zhang (China University of Petroleum, IFPEN - IFP Energies nouvelles - IFPEN - IFP Energies nouvelles, IFP School); Arash Farnoosh (IFPEN - IFP Energies nouvelles - IFPEN - IFP Energies nouvelles, IFP School); Frédéric Lantz (IFPEN - IFP Energies nouvelles - IFPEN - IFP Energies nouvelles, IFP School)
    Abstract: This paper examines the price discovery of three international crude oil futures markets (WTI, Brent, INE) before and after the outbreak of the COVID-19 with the application of the information share and component share model. Our study shows that there is a structural break of the date of March 6, 2020, in each price series with Zivot and Andrew's unit root tests. Using Gregory and Hansen cointegration tests, cointegration relationships with the structural break in May 2020 are detected. According to results of Information Share (IS) and Component Share (CS) measures Brent futures price mainly plays a leading role in WTI and INE futures prices and occupies an absolutely dominant position all the time in the three crude oil futures markets systems. In the post-covid period, the price discovery efficiency of INE has been improved slightly but is still weak compared with other two markets. After the outbreak of COVID-19, the dominant position in price contribution in the relationship with INE has transferred from Brent to WTI. These findings offer practical implications for regulators and portfolio risk managers during the unprecedented uncertainty period provoked by the COVID-19 pandemic.
    Keywords: Oil Market,Price Discovery,Structural Break
    Date: 2022–05

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