nep-rmg New Economics Papers
on Risk Management
Issue of 2022‒02‒21
eighteen papers chosen by

  1. When uncertainty decouples expected and unexpected losses By Juselius, Mikael; Tarashev, Nikola
  2. Portfolio selection models based on interval-valued conditional value at risk (ICVaR) and empirical analysis By Jinping Zhang; Keming Zhang
  3. Risk-sharing rules and their properties, with applications to peer-to-peer insurance By Denuit, Michel; Dhaene, Jan; Robert, Christian Y.
  4. Measuring and Stress-Testing Market-Implied Bank Capital By Martin Indergand; Eric Jondeau; Andreas Fuster
  5. The Hedging Cost of Forgetting the Exchange Rate By Beatriz de la Flor; Javier Ojea-Ferreiro; Eva Ferreira
  6. Capital allocation, the leverage ratio requirement By Neamtu, Ioana; Vo, Quynh-Anh
  7. Neural calibration of hidden inhomogeneous Markov chains -- Information decompression in life insurance By Mark Kiermayer; Christian Wei{\ss}
  8. Spillovers at the Extremes: The Macroprudential Stance and Vulnerability to the Global Financial Cycle By Anusha Chari; Karlye Dilts Stedman; Kristin J. Forbes
  9. Precise Stock Price Prediction for Robust Portfolio Design from Selected Sectors of the Indian Stock Market By Jaydip Sen; Ashwin Kumar R S; Geetha Joseph; Kaushik Muthukrishnan; Koushik Tulasi; Praveen Varukolu
  10. Discrete-time risk sensitive portfolio optimization with proportional transaction costs By Marcin Pitera; {\L}ukasz Stettner
  11. On asymptotically arbitrage-free approximations of the implied volatility By Masaaki Fukasawa
  12. Insurers’ investments before and after the Covid-19 outbreak By Federico Apicella; Raffaele Gallo; Giovanni Guazzarotti
  13. Smooth Nested Simulation: Bridging Cubic and Square Root Convergence Rates in High Dimensions By Wenjia Wang; Yanyuan Wang; Xiaowei Zhang
  14. Mortality credits within large survivor funds By Denuit, Michel; Hieber, Peter; Robert, Christian Y.
  15. The Most Expected Things Often Come as a Surprise: Analysis of the Impact of Monetary Surprises on the Bank's Risk and Activity By Melchisedek Joslem Ngambou Djatche
  16. Defaulting Alone: The Geography of Sme Owner Numbers and Credit Risk in Hungary By Csaba Burger
  17. The adverse effect of contingent convertible bonds on bank stability By Ludolph, Melina
  18. Treatment Effect Risk: Bounds and Inference By Nathan Kallus

  1. By: Juselius, Mikael; Tarashev, Nikola
    Abstract: A parsimonious extension of a well-known portfolio credit-risk model allows us to study a salient stylized fact – abrupt switches between high- and low-loss phases– from a risk-management perspective. As uncertainty about phase switches increases, expected losses decouple from unexpected losses, which reflect a high percentile of the loss distribution. Banks that ignore this decoupling have shortfalls of loss-absorbing resources, which is more detrimental if the portfolio is more diversified within a phase. Likewise, the risk-management benefits of improving phase-switch forecasts increase with diversification. The analysis of these findings leads us to an empirical method for comparing the degree of within-phase default clustering across portfolios.
    JEL: G21 G28 G32
    Date: 2022–01–26
  2. By: Jinping Zhang; Keming Zhang
    Abstract: Risk management is very important for individual investors or companies. There are many ways to measure the risk of investment. Prices of risky assets vary rapidly and randomly due to the complexity of finance market. Random interval is a good tool to describe uncertainty with both randomness and imprecision. Considering the uncertainty of financial market, we employ random intervals to describe the returns of a risk asset and consider the tail risk, which is called the interval-valued Conditional Value at Risk (ICVaR, for short). Such an ICVaR is a risk measure and satisfies subadditivity. Under the new risk measure ICVaR, as a manner similar to the classical portfolio model of Markowitz, optimal interval-valued portfolio selection models are built. Based on the real data from mainland Chinese stock market, the case study shows that our models are interpretable and consistent with the practical scenario.
    Date: 2022–01
  3. By: Denuit, Michel (Université catholique de Louvain, LIDAM/ISBA, Belgium); Dhaene, Jan (KU Leuven); Robert, Christian Y. (CREST)
    Abstract: This paper offers a systematic treatment of risk-sharing rules for insurance losses, based on a list of relevant properties. A number of candidate risk-sharing rules are considered, including the conditional mean risk-sharing rule proposed in Denuit and Dhaene (2012) and the newly introduced quantile risk-sharing rule. Their compliance with the proposed properties is established. Then, methods for building new risk-sharing rules are discussed. The results derived in this paper are shown to be helpful in the development of peer-to-peer insurance (or crowdsurance), as well as to manage contingent risk funds where a given budget is distributed among claimants.
    Keywords: Pooling ; peer-to-peer (P2P) insurance ; crowdsurance ; conditional mean risk-sharing rule ; quantile risk-sharing rule ; comonotonicity
    Date: 2021–11–23
  4. By: Martin Indergand (Swiss National Bank - Financial Stability); Eric Jondeau (University of Lausanne - Faculty of Business and Economics (HEC Lausanne); Swiss Finance Institute; Swiss Finance Institute); Andreas Fuster (Ecole Polytechnique Fédérale de Lausanne; Swiss Finance Institute; Centre for Economic Policy Research (CEPR))
    Abstract: We propose a methodology for measuring the market-implied capital of banks by subtracting from the market value of equity (market capitalization) a credit-spread-based correction for the value of shareholders' default option. We show that without such a correction, the estimated impact of a severe market downturn is systematically distorted, underestimating the risk of banks with low market capitalization. We argue that this adjusted measure of capital is the relevant market-implied capital measure for policymakers. We propose an econometric model for the combined simulation of equity prices and CDS spreads, which allows us to introduce this correction in the SRISK framework for measuring systemic risk.
    Keywords: Banking, Capital, Stress Test, Systemic Risk, Multifactor Model
    JEL: C32 G01 G21 G28 G32
    Date: 2022–01
  5. By: Beatriz de la Flor (Universidad Complutense de Madrid and ICAE (Spain).); Javier Ojea-Ferreiro (Universidad Complutense de Madrid and ICAE (Spain).); Eva Ferreira (Universidad Complutense de Madrid and ICAE (Spain).)
    Abstract: The safe-haven property of gold has been widely studied, although little attention has been paid to how exchange rate movements could affect hedging strategies. We analyse the exchange rate role in stock portfolios hedged with gold in several regions from the point of view of non-US and US investors, using vine copulas to model the relation between gold, stock and exchange rates. We find a leading role played by exchange rate hedging stock losses, which outstrips the position of gold (index) in non-US (US) portfolios. The inclusion of the exchange rate can reduce the ES between 107 and 162 bps. An out-of-sample exercise supports our results. The implications of this study go beyond risk management decisions. Regulatory and supervisory authorities might find tools to assess the performance of financial assets under market distress scenarios.
    Keywords: Exchange rate risk; Hedging strategy; Risk measures; Tail dependence; Vine copula.
    JEL: C52 C58 C61 F13 G1
    Date: 2022
  6. By: Neamtu, Ioana (Bank of England); Vo, Quynh-Anh (Bank of England)
    Abstract: This paper examines how the level (ie group or business unit level) at which regulatory requirements are applied affects banks’ asset risk. We develop a theoretical model and calibrate it to UK banks. Our main finding is that the impact differs depending on which regulatory constraint is binding at the group consolidated level. If that is the leverage ratio requirement, then the allocation of regulatory constraints to business units either maintains or decreases the riskiness of banks’ investment portfolios. However, if the risk-weighted requirement is the binding constraint at the group level, applying regulatory requirements at the business unit level can lead to banks selecting riskier asset portfolios as optimal. We also find that the impact on banks’ asset risk differs across bank business models.
    Keywords: Leverage ratio requirement; risk-weighted capital requirements; capital allocation
    JEL: G21 G28
    Date: 2021–12–17
  7. By: Mark Kiermayer; Christian Wei{\ss}
    Abstract: Markov chains play a key role in a vast number of areas, including life insurance mathematics. Standard actuarial quantities as the premium value can be interpreted as compressed, lossy information about the underlying Markov process. We introduce a method to reconstruct the underlying Markov chain given collective information of a portfolio of contracts. Our neural architecture explainably characterizes the process by explicitly providing one-step transition probabilities. Further, we provide an intrinsic, economic model validation to inspect the quality of the information decompression. Lastly, our methodology is successfully tested for a realistic data set of German term life insurance contracts.
    Date: 2022–01
  8. By: Anusha Chari; Karlye Dilts Stedman; Kristin J. Forbes
    Abstract: Evidence suggests that macroprudential policy has small and insignificant effects on the volume of portfolio flows. We show, however, that these minor effects mask very different relationships across the global financial cycle. A tighter ex-ante macroprudential stance amplifies the impact of global risk shocks on bond and equity flows—increasing outflows by significantly more during risk-off episodes and increasing inflows significantly more during risk on episodes. These amplification effects are more prominent at the “extremes,” especially for extreme risk-off periods, and are larger for regulations that target specific risks (such as currency or housing exposures) than those which strengthen generalized cyclical buffers (such as the CCyB). This paper estimates these relationships using a policy-shocks approach that corrects for reverse causality by combining high-frequency risk measures with weekly data on portfolio investment and a new measure of macroprudential regulations that captures the intensity of policy stances. Overall, the results support a growing body of evidence that macroprudential regulation can reduce the volume and volatility of bank flows but shift risks in ways that aggravate vulnerabilities in other parts of the financial system.
    Keywords: Macroprudential regulation
    JEL: F32 F34 F38 G15 G23 G28
    Date: 2021–12–17
  9. By: Jaydip Sen; Ashwin Kumar R S; Geetha Joseph; Kaushik Muthukrishnan; Koushik Tulasi; Praveen Varukolu
    Abstract: Stock price prediction is a challenging task and a lot of propositions exist in the literature in this area. Portfolio construction is a process of choosing a group of stocks and investing in them optimally to maximize the return while minimizing the risk. Since the time when Markowitz proposed the Modern Portfolio Theory, several advancements have happened in the area of building efficient portfolios. An investor can get the best benefit out of the stock market if the investor invests in an efficient portfolio and could take the buy or sell decision in advance, by estimating the future asset value of the portfolio with a high level of precision. In this project, we have built an efficient portfolio and to predict the future asset value by means of individual stock price prediction of the stocks in the portfolio. As part of building an efficient portfolio we have studied multiple portfolio optimization methods beginning with the Modern Portfolio theory. We have built the minimum variance portfolio and optimal risk portfolio for all the five chosen sectors by using past daily stock prices over the past five years as the training data, and have also conducted back testing to check the performance of the portfolio. A comparative study of minimum variance portfolio and optimal risk portfolio with equal weight portfolio is done by backtesting.
    Date: 2022–01
  10. By: Marcin Pitera; {\L}ukasz Stettner
    Abstract: In this paper we consider a discrete-time risk sensitive portfolio optimization over a long time horizon with proportional transaction costs. We show that within the log-return i.i.d. framework the solution to a suitable Bellman equation exists under minimal assumptions and can be used to characterize the optimal strategies for both risk-averse and risk-seeking cases. Moreover, using numerical examples, we show how a Bellman equation analysis can be used to construct or refine optimal trading strategies in the presence of transaction costs.
    Date: 2022–01
  11. By: Masaaki Fukasawa
    Abstract: Following-up Fukasawa and Gatheral (Frontiers of Mathematical Finance, 2022), we prove that the BBF formula, the SABR formula, and the rough SABR formula provide asymptotically arbitrage-free approximations of the implied volatility under, respectively, the local volatility model, the SABR model, and the rough SABR model.
    Date: 2022–01
  12. By: Federico Apicella (Bank of Italy); Raffaele Gallo (Bank of Italy); Giovanni Guazzarotti (Bank of Italy)
    Abstract: This paper examines the impact of the pandemic outbreak on Italian insurers’ investment decisions between 2017 and 2020. By adopting a unique security-by-security holding dataset, we test how the investments of insurance companies in a single security varies when its price changes. Our findings suggest that Italian insurers on average play a stabilizing role in financial markets by increasing their exposure to securities whose price has fallen. However, their ability to weather shocks diminished on average after the pandemic outbreak, arguably as the abrupt fall of asset prices reduced insurers’ balance sheet capacity to absorb short-term losses on their security holdings. Indeed, insurers’ investment decisions were heavily affected by capital considerations after the pandemic outbreak: insurers did not play a stabilizing role if they had a lower solvency level and for assets more exposed to the risk of an increase in capital absorption (e.g. BBB-rated corporate bonds). Finally, insurers reduced their exposure to securities whose price had fallen for assets relating to more volatile liabilities, such as life unit-linked portfolios.
    Keywords: insurance companies, investments, pandemic, financial stability, solvency ratio
    JEL: G01 G11 G22 G28
    Date: 2022–02
  13. By: Wenjia Wang; Yanyuan Wang; Xiaowei Zhang
    Abstract: Nested simulation concerns estimating functionals of a conditional expectation via simulation. In this paper, we propose a new method based on kernel ridge regression to exploit the smoothness of the conditional expectation as a function of the multidimensional conditioning variable. Asymptotic analysis shows that the proposed method can effectively alleviate the curse of dimensionality on the convergence rate as the simulation budget increases, provided that the conditional expectation is sufficiently smooth. The smoothness bridges the gap between the cubic root convergence rate (that is, the optimal rate for the standard nested simulation) and the square root convergence rate (that is, the canonical rate for the standard Monte Carlo simulation). We demonstrate the performance of the proposed method via numerical examples from portfolio risk management and input uncertainty quantification.
    Date: 2022–01
  14. By: Denuit, Michel (Université catholique de Louvain, LIDAM/ISBA, Belgium); Hieber, Peter (University of Lausanne); Robert, Christian Y. (CREST - ENSAE)
    Abstract: Survivor funds are financial arrangements where participants agree to share the proceeds of a collective investment pool in a pre-described way depending on their survival. This offers investors a way to benefit from mortality credits, boosting financial returns. Following Denuit (2019), participants are assumed to adopt the conditional mean risk sharing rule introduced in Denuit and Dhaene (2012) to assess their respective shares in mortality credits. This paper considers the case of a large pool and studies the asymptotic behavior of mortality credits. A law of large numbers and a central-limit theorem are established, as well as simple approximations for a sufficiently large number of participants. A risk transfer network structure is also proposed to allow participants to restrict sharing to a community of individuals with whom they are connected. Lifelong incomes can be obtained by combining investments in survivor funds over consecutive periods, offering an alternative to modern tontines or pooled annuity funds.
    Keywords: Mortality risk pooling ; tontine ; conditional mean risk sharing ; risk transfer network structure
    Date: 2021–12–06
  15. By: Melchisedek Joslem Ngambou Djatche (Université Côte d'Azur; GREDEG CNRS)
    Abstract: In this paper, we analyse the link between monetary surprises and banks' activity and risk-taking. Some theoretical and empirical studies show that monetary easing increases banks' appetite for risk, affect credit allocation and bank's profitability. Our study adds to analyses of the monetary risk-taking channel considering monetary surprise, i.e. the impact of unexpected changes in monetary policy on bank's risk and activity. Using a dataset of US banks, we find that negative monetary surprises (higher increase or lower decrease of interest rates than expected) lead banks to take more risk, to grant more corporate loans than consumption loans, and to be more profitable. We complement the literature on the risk-taking channel and provide arguments that Central Banks can manage financial stability.
    Keywords: monetary surprise, financial stability, bank risk-taking, VAR model, dynamic panel regression
    JEL: E44 E58 G21
    Date: 2021–12
  16. By: Csaba Burger (Magyar Nemzeti Bank (Central Bank of Hungary))
    Abstract: The transition from the state ownership to market mechanisms in Hungary fundamentally altered the geography of domestic micro, small, and medium enterprises (SMEs). This study investigates the spatial and temporal evolution of owner numbers, using data on all Hungarian SMEs between 1991 and 2019 and across 175 regional districts. Then it explores the relationship between the number of owners and the probability of credit default by joining data from the Credit Registry (KHR) for the period between 2007 and 2019. The number of owners at an average SME sank from four in 1991 to two in 2019, with consistently higher averages in less populated regions. Meanwhile, SMEs with one owner only have up to twice as high credit default probability as SMEs with more owners over all geographies in all years. Therefore, regionally varying ownership structures mean regionally differing ownership and management practices and hence risk levels. These could be mitigated with targeted regional policy measures.
    Keywords: financial geography, ownership structures, credit risk, SMEs
    JEL: G21 G3 R3 R11 R1
    Date: 2022
  17. By: Ludolph, Melina
    Abstract: This paper examines the impact of issuing contingent convertible (CoCo) bonds on bank risk. I apply a matching-based difference-in-differences approach to banklevel data for 246 publicly traded European banks and 61 CoCo issues from 2008−2018. My estimation results reveal that issuing CoCo bonds that meet the criteria for additional tier 1 (AT1) capital results in significantly higher z-scores one to three years after the issuance. Rather than having a net negative impact, issuing CoCos seems to impede a positive time trend towards greater bank stability. This study adds to the empirical literature on the risk-effect of contingent convertibles by identifying the causal effect of AT1 CoCo bonds on reported risk changes over a three-year post-treatment horizon based on a comprehensive sample of European banks. The results confirm theoretical predictions that currently outstanding CoCo bonds create incentives for excessive risk-taking.
    Keywords: AT1 capital,bank risk,Basel III,CoCo bonds
    JEL: G21 G23 G32 G38
    Date: 2022
  18. By: Nathan Kallus
    Abstract: Since the average treatment effect (ATE) measures the change in social welfare, even if positive, there is a risk of negative effect on, say, some 10% of the population. Assessing such risk is difficult, however, because any one individual treatment effect (ITE) is never observed so the 10% worst-affected cannot be identified, while distributional treatment effects only compare the first deciles within each treatment group, which does not correspond to any 10%-subpopulation. In this paper we consider how to nonetheless assess this important risk measure, formalized as the conditional value at risk (CVaR) of the ITE distribution. We leverage the availability of pre-treatment covariates and characterize the tightest-possible upper and lower bounds on ITE-CVaR given by the covariate-conditional average treatment effect (CATE) function. Some bounds can also be interpreted as summarizing a complex CATE function into a single metric and are of interest independently of being a bound. We then proceed to study how to estimate these bounds efficiently from data and construct confidence intervals. This is challenging even in randomized experiments as it requires understanding the distribution of the unknown CATE function, which can be very complex if we use rich covariates so as to best control for heterogeneity. We develop a debiasing method that overcomes this and prove it enjoys favorable statistical properties even when CATE and other nuisances are estimated by black-box machine learning or even inconsistently. Studying a hypothetical change to French job-search counseling services, our bounds and inference demonstrate a small social benefit entails a negative impact on a substantial subpopulation.
    Date: 2022–01

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