nep-rmg New Economics Papers
on Risk Management
Issue of 2023‒07‒10
twenty papers chosen by

  1. Changes to Bank Capital Ratios and their Drivers Prior and During COVID-19 Pandemic: Evidence from EU By Pavel Jankulár; Zdeněk Tůma
  2. Large Banks and Systemic Risk: Insights from a Mean-Field Game Model By Yuanyuan Chang; Dena Firoozi; David Benatia
  3. The Impact of the Basel III banking regulation on Moroccan banks By Mohammed Mikou
  4. A Comparative Analysis of Portfolio Optimization Using Mean-Variance, Hierarchical Risk Parity, and Reinforcement Learning Approaches on the Indian Stock Market By Jaydip Sen; Aditya Jaiswal; Anshuman Pathak; Atish Kumar Majee; Kushagra Kumar; Manas Kumar Sarkar; Soubhik Maji
  5. A Review of Macroeconomic Determinants of Credit Risks: Evidence from Low-Income Countries By yeboah, samuel
  6. Modeling and evaluating conditional quantile dynamics in VaR forecasts By F. Cipollini; G.M. Gallo; A. Palandri
  7. Bank credit portfolio allocation in pre and post Covid times: The power of inherent risks By Ndwiga, David M.
  8. Generalized Autoregressive Score Trees and Forests By Andrew J. Patton; Yasin Simsek
  9. Risk-based credit pricing in Kenya: The role of banks' internal factors By Tiriongo, Samuel; Josea, Kiplangat; Mulindi, Hillary
  10. The effect of FinTech development on bank risktaking: Evidence from Kenya By Ochenge, Rogers Ondiba
  11. A Game of Competition for Risk By Louis Abraham
  12. The impact of flood risk on real estate wealth in Italy By Michele Loberto; Matteo Spuri
  13. The Crypto Multiplier By Rodney Garratt; Maarten van Oordt
  14. Unimodal maps perturbed by heteroscedastic noise: an application to a financial systems By F. Lillo; G. Livieri; S. Marmi; A. Solomko; S. Vaienti
  15. Mean-variance dynamic portfolio allocation with transaction costs: a Wiener chaos expansion approach By Areski Cousin; J\'er\^ome Lelong; Tom Picard
  16. Shot-noise cojumps: exact simulation and option pricing By Qu, Yan; Dassios, Angelos; Zhao, Hongbiao
  17. The Overview and Risks of Fund Finance By KANAGUCHI Takehisa; KAWAKAMI Takehito; HASEBE Akira; OGAWA Yoshiya
  18. Sweden: Financial Sector Assessment Program–Technical Note on Stress Testing of the Financial Sector By International Monetary Fund
  19. Pension Systems (Un)sustainability and Fiscal Constraints: A Comparative Analysis By Burkhard Heer; Vito Polito; Mike Wickens
  20. Chinese Insurance Markets: Developments and Prospects By Hanming Fang; Xian Xu

  1. By: Pavel Jankulár; Zdeněk Tůma
    Abstract: We contribute to literature on banks´ strategies to increasing capital requirements in the period of 2017-2021. We analyze a sample of 85 European banks and differentiate between subgroups according to bank's size, capitalization and riskiness. We examine their responses to higher capital requirements following the issuance of finalized Basel III reforms and increased regulatory and supervisory scrutiny after the COVID-19 outbreak. We found evidence that banks´ adjustments in the direction of higher capital ratio were more pronounced and faster in the COVID-19 period, and that they depended on banks´ specific characteristics and positions. Identified variances between banks and periods resulted mainly from different treatment of risk on banks' books. In particular, higher capitalization and lower risk profile enabled banks to take on the risk regardless of period, while banks with increased risk rather limited their balance sheets to manage their capital ratios.
    Keywords: capital ratio, Basel capital requirements, COVID-19 pandemic, global financial crisis
    JEL: C33 G21 G28
    Date: 2023–05–02
  2. By: Yuanyuan Chang; Dena Firoozi; David Benatia
    Abstract: This paper aims to investigate the impact of large banks on the financial system stability. To achieve this, we employ a linear-quadratic-Gaussian (LQG) mean-field game (MFG) model of an interbank market, which involves one large bank and multiple small banks. Our approach involves utilizing the MFG methodology to derive the optimal trading strategies for each bank, resulting in an equilibrium for the market. Subsequently, we conduct Monte Carlo simulations to explore the role played by the large bank in systemic risk under various scenarios. Our findings indicate that while the major bank, if its size is not too large, can contribute positively to stability, it also has the potential to generate negative spillover effects in the event of default, leading to increased systemic risk. We also discover that as banks become more reliant on the interbank market, the overall system becomes more stable but the probability of a rare systemic failure increases. This risk is further amplified by the presence of a large bank, its size, and the speed of interbank trading. Overall, the results of this study provide important insights into the management of systemic risk.
    Date: 2023–05
  3. By: Mohammed Mikou
    Abstract: This paper estimates the social costs and benefits of the Basel III banking regulation application to Moroccan banks, which, inter alia, imposed higher capital requirements. The paper quantifies the impact of higher capital requirements on (i) lending rates, (ii) bank refinancing costs, and (iii) banking system resilience. Our findings indicate that the increase in capital requirements for Moroccan banks has a limited impact on lending and refinancing costs. The benefit of greater banking system resilience in terms of systemic risk appears to be more significant in expectations.
    Date: 2023–06–21
  4. By: Jaydip Sen; Aditya Jaiswal; Anshuman Pathak; Atish Kumar Majee; Kushagra Kumar; Manas Kumar Sarkar; Soubhik Maji
    Abstract: This paper presents a comparative analysis of the performances of three portfolio optimization approaches. Three approaches of portfolio optimization that are considered in this work are the mean-variance portfolio (MVP), hierarchical risk parity (HRP) portfolio, and reinforcement learning-based portfolio. The portfolios are trained and tested over several stock data and their performances are compared on their annual returns, annual risks, and Sharpe ratios. In the reinforcement learning-based portfolio design approach, the deep Q learning technique has been utilized. Due to the large number of possible states, the construction of the Q-table is done using a deep neural network. The historical prices of the 50 premier stocks from the Indian stock market, known as the NIFTY50 stocks, and several stocks from 10 important sectors of the Indian stock market are used to create the environment for training the agent.
    Date: 2023–05
  5. By: yeboah, samuel
    Abstract: This review aims to provide a comprehensive analysis of the macroeconomic determinants of credit risks in low-income countries. The study explores the factors that influence credit risks, including macroeconomic indicators, institutional frameworks, and external shocks. By examining existing literature and empirical evidence, this review highlights the crucial role of these determinants in shaping credit risk levels in low-income economies. The findings can help policymakers and financial institutions devise appropriate strategies to manage credit risks and promote financial stability in these countries.
    Keywords: credit risks, low-income countries, macroeconomic determinants, review, evidence.
    JEL: G21 G32 O16
    Date: 2023–02–01
  6. By: F. Cipollini; G.M. Gallo; A. Palandri
    Abstract: We focus on the time-varying modeling of VaR at a given coverage τ, assessing whether the quantiles of the distribution of the returns standardized by their conditional means and standard deviations exhibit predictable dynamics. Models are evaluated via simulation, determining the merits of the asymmetric Mean Absolute Deviation as a loss function to rank forecast performances. The empirical application on the Fama–French 25 value–weighted portfolios with a moving forecast window shows substantial improvements in forecasting conditional quantiles by keeping the predicted quantile unchanged unless the empirical frequency of violations falls outside a data-driven interval around τ.
    Keywords: Risk management;Value at Risk;dynamic quantile;asymmetric loss function;forecast evaluation
    Date: 2023
  7. By: Ndwiga, David M.
    Abstract: The study seeks to determine how the bank credit allocation has evolved in pre - covid, covid and post covid era amid possible uncertainties. Study focused on credit risk, liquidity risk, industry competition and operating efficiency for 2010 - 2021 period. Panel Autoregressive Distributed Lag and panel Generalized Method of Moments were applied for bank level data while sectoral level Autoregressive Distributed Lag models were applied for sectoral analysis. The study found credit, liquidity, covid are all negatively related to bank credit allocation. In addition, interaction of covid with credit and liquidity risks reveal that the effect of liquidity risk is more pronounced. Recovery era simulation posits that personal household sector would register the highest allocation with real estate sector allocation being last. The study calls for more vigilance in the post pandemic times as credit risk is likely to reveal itself amid relaxation in loan reclassification. Further, a more proactive monetary policy is advocated for to address the liquidity distribution challenges.
    Date: 2023
  8. By: Andrew J. Patton; Yasin Simsek
    Abstract: We propose methods to improve the forecasts from generalized autoregressive score (GAS) models (Creal et. al, 2013; Harvey, 2013) by localizing their parameters using decision trees and random forests. These methods avoid the curse of dimensionality faced by kernel-based approaches, and allow one to draw on information from multiple state variables simultaneously. We apply the new models to four distinct empirical analyses, and in all applications the proposed new methods significantly outperform the baseline GAS model. In our applications to stock return volatility and density prediction, the optimal GAS tree model reveals a leverage effect and a variance risk premium effect. Our study of stock-bond dependence finds evidence of a flight-to-quality effect in the optimal GAS forest forecasts, while our analysis of high-frequency trade durations uncovers a volume-volatility effect.
    Date: 2023–05
  9. By: Tiriongo, Samuel; Josea, Kiplangat; Mulindi, Hillary
    Abstract: Globally, credit scoring adoption has been on the rise on account of increased access to data, computing power, and the need for efficient credit allocation that is supportive of entrenching financial inclusion and economic growth. Relatedly, the adoption of risk-based pricing has gained traction, and, in this paper, we use annual bank level and macroeconomic data spanning the period 2003-2021, to estimate a panel model assessing the drivers of price of credit. Credit pricing in Kenya is affected by the bank size, credit risk, and efficiency among others. In particular, the larger the size of the bank, the lower the price of credit. Overall, the results reveals that the implementation of riskbased pricing will be heterogenous and dependent on bank-specific characteristics and internal policies, while the macroeconomic environment will have a negligible role on the credit prices determined by the banks.
    Date: 2023
  10. By: Ochenge, Rogers Ondiba
    Abstract: Cognizant of the recent revolution in financial technology (FinTech), this paper explores the effect of FinTech development on bank risk-taking behavior in Kenya over the period 2008 to 2021. The study first develops a FinTech index using text mining technology and then relates this index to bank-risk taking in a dynamic panel regression model. The study uncovers the following empirical results: (i) The impact of FinTech on bank's risktaking shows a "U" shape, first falling bank risk and then rising. That is, at early stage of development, FinTech reduces risk-taking, but as key technologies mature and FinTech companies directly compete with traditional commercial banks, FinTech exacerbates risktaking. (ii) The impact of FinTech is heterogeneous across bank sizes. Specifically, large banks appear to be more sensitive to changes in FinTech development compared to small and medium-sized banks.
    Date: 2023
  11. By: Louis Abraham
    Abstract: In this study, we present models where participants strategically select their risk levels and earn corresponding rewards, mirroring real-world competition across various sectors. Our analysis starts with a normal form game involving two players in a continuous action space, confirming the existence and uniqueness of a Nash equilibrium and providing an analytical solution. We then extend this analysis to multi-player scenarios, introducing a new numerical algorithm for its calculation. A key novelty of our work lies in using regret minimization algorithms to solve continuous games through discretization. This groundbreaking approach enables us to incorporate additional real-world factors like market frictions and risk correlations among firms. We also experimentally validate that the Nash equilibrium in our model also serves as a correlated equilibrium. Our findings illuminate how market frictions and risk correlations affect strategic risk-taking. We also explore how policy measures can impact risk-taking and its associated rewards, with our model providing broader applicability than the Diamond-Dybvig framework. We make our methodology and open-source code available at Finally, we contribute methodologically by advocating the use of algorithms in economics, shifting focus from finite games to games with continuous action sets. Our study provides a solid framework for analyzing strategic interactions in continuous action games, emphasizing the importance of market frictions, risk correlations, and policy measures in strategic risk-taking dynamics.
    Date: 2023–05
  12. By: Michele Loberto (Bank of Italy); Matteo Spuri (Bank of Italy)
    Abstract: This paper outlines the main data sources and the methodology used to estimate the impact of flood risk in Italy. It assesses the potential physical damage to the housing stock, identifying the main gaps in the current information set. Estimates of exposure and expected annual loss vary greatly depending on the hazard scenarios used, the assumptions about building vulnerability, and the data’s spatial granularity level. Based on our most reliable estimates, the value of homes potentially exposed to flooding is close to €1 trillion (2020 values), about a quarter of the total housing wealth. The resulting expected annual loss can be estimated at around €3 billion.
    Keywords: climate change, real estate, flooding risk
    JEL: O18 Q54
    Date: 2023–05
  13. By: Rodney Garratt; Maarten van Oordt
    Abstract: The exchange rates of cryptocurrencies are highly volatile. This paper provides insight into the source of this volatility by developing the concept of a "crypto multiplier, " which measures the equilibrium response of a cryptocurrency's market capitalization to aggregate inflows and outflows of investors' funds. The crypto multiplier takes high values when a large share of a cryptocurrency's coins is held as an investment rather than being used as a means of payment. Empirical evidence shows that the number of coins held for the purpose of making payments is rather small for major cryptocurrencies suggesting large crypto multipliers. The analysis explains why announcements by large investors, celebrity endorsements or financial crises can result in substantial price movements.
    Keywords: Bitcoin, cryptocurrency, exchange rates, monetary economics, risk management
    JEL: E42 E51
    Date: 2023–06
  14. By: F. Lillo; G. Livieri; S. Marmi; A. Solomko; S. Vaienti
    Abstract: We investigate and prove the mathematical properties of a general class of one-dimensional unimodal smooth maps perturbed with a heteroscedastic noise. Specifically, we investigate the stability of the associated Markov chain, show the weak convergence of the unique stationary measure to the invariant measure of the map, and show that the average Lyapunov exponent depends continuously on the Markov chain parameters. Representing the Markov chain in terms of random transformation enables us to state and prove the Central Limit Theorem, the large deviation principle, and the Berry-Ess\`een inequality. We perform a multifractal analysis for the invariant and the stationary measures, and we prove Gumbel's law for the Markov chain with an extreme index equal to 1. In addition, we present an example linked to the financial concept of systemic risk and leverage cycle, and we use the model to investigate the finite sample properties of our asymptotic results.
    Date: 2023–05
  15. By: Areski Cousin (IRMA); J\'er\^ome Lelong (LJK); Tom Picard (LJK)
    Abstract: This paper studies the multi-period mean-variance portfolio allocation problem with transaction costs. Many methods have been proposed these last years to challenge the famous uni-period Markowitz strategy.But these methods cannot integrate transaction costs or become computationally heavy and hardly applicable. In this paper, we try to tackle this allocation problem by proposing an innovative approach which relies on representing the set of admissible portfolios by a finite dimensional Wiener chaos expansion. This numerical method is able to find an optimal strategy for the allocation problem subject to transaction costs. To complete the study, the link between optimal portfolios submitted to transaction costs and the underlying risk aversion is investigated. Then a competitive and compliant benchmark based on the sequential uni-period Markowitz strategy is built to highlight the efficiency of our approach.
    Date: 2023–05
  16. By: Qu, Yan; Dassios, Angelos; Zhao, Hongbiao
    Abstract: We consider a parsimonious framework of jump-diffusion models for price dynamics with stochastic price volatilities and stochastic jump intensities in continuous time. They account for conditional heteroscedasticity and also incorporate key features appearing in financial time series of price volatilities and jump intensities, such as persistence of contemporaneous jumps (cojumps), mean reversion and feedback effects. More precisely, the stochastic variance and stochastic intensity are jointly modelled by a generalised bivariate shot-noise process sharing common jump arrivals with any non-negative jump-size distributions. This framework covers many classical and important models in the literature. The main contribution of this paper is that, we develop a very efficient scheme for its exact simulation based on perfect decomposition where neither numerical inversion nor acceptance/rejection scheme is required, which means that it is not only accurate but also the efficiency would not be sensitive to the parameter choice. Extensive numerical implementations and tests are reported to demonstrate the accuracy and effectiveness of this scheme. Our algorithm substantially outperforms the classical discretisation scheme. Moreover, we unbiasedly estimate the prices of discrete-barrier European options to show the applicability and flexibility of our algorithms.
    Keywords: exact simulation; Monte Carlo simulation; jump-diffusion models; stochastic volatility models; Shot-noise process; contemporaneous jumps; cojumps; shot-noise cojumps; option pricing; systemic risk; #71401147
    JEL: C63 C15 G13
    Date: 2023–03–01
  17. By: KANAGUCHI Takehisa (Bank of Japan); KAWAKAMI Takehito (Bank of Japan); HASEBE Akira (Bank of Japan); OGAWA Yoshiya (Bank of Japan)
    Abstract: The funds see an increase in their financing demand, depending on their own investment stage, as the inflow into private equity funds and other funds continues. Under these circumstances, financial institutions promote their businesses based on the high profitability of Fund Finance. In addition, they have established a risk management system that pays attention to the risk characteristics associated with such finance. On the other hand, the funds lengthen loan terms and increase the leverage of Fund Finance in order to boost investment returns to investors, and increasing risks associated with Fund Finance have been identified. Therefore, it is important to understand the real picture of Fund Finance and carefully monitor its potential risks.
    Date: 2023–06–19
  18. By: International Monetary Fund
    Abstract: Sweden’s financial system has weathered the COVID-19 pandemic well. Strong macro- fundamentals, regulatory capital buffers exceeding minimum requirements by a wide margin, ample liquidity reserves of banks, and prompt market liquidity support measures by the authorities helped the financial system exit the COVID-19 crisis without a significant impact on profitability, including loan portfolio losses.
    Date: 2023–05–25
  19. By: Burkhard Heer (Department of Economics, University of Ausburg, CESifo, Netspar); Vito Polito (Department of Economics, University of Sheffield, CESifo, Netspar); Mike Wickens (Department of Economics, University of York, CESifo, CEPR, Netspar, Cardiff University)
    Abstract: Using an overlapping generations model, two new indicators of public pension system sustainability are proposed: the pension space, which measures the capacity to pay for pension expenditures out of labour taxation, and the pension space exhaustion probability reflecting demographic uncertainties. These measures reveal that the pension spaces of advanced economies are strikingly different. Most nations have little scope to further finance pensions out of labour income taxation over the next thirty years. There is no one-size-fits-all solution. Risk-equivalent pension reforms enhance welfare in the long run, particularly for rapidly ageing nations, but also entail non-negligible transitional costs.
    Keywords: Ageing, Fiscal Space, Public Pension Sustainability, Overlapping Generations Model
    JEL: E62 H55 H20
    Date: 2023–06
  20. By: Hanming Fang; Xian Xu
    Abstract: In this chapter, we review the development of the insurance industry in China. We provide a comprehensive discussion of its regulatory framework, major insurance segments, market structure, InsurTech, social insurance and the prospects for the future development.
    JEL: G22 G28 H55 L11 O16
    Date: 2023–05

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