Search Results (16)

We develop a dynamic, stochastic general equilibrium (DSGE) model for the euro area that accounts for climate change-related risk considerations. The model features polluting (“brown”) firms and non-polluting (“green”) firms and a climate module with endogenous emissions modeled as a byproduct externality. In the model, exogenous shocks propagate throughout the economy and affect macroeconomic variables through the impact of interest rate spreads. We assess the business cycle and policy implications of transition risk stemming from changes in the carbon tax, and the implications of the micro- and macroprudential tools that account for climate considerations. Our results suggest that a higher carbon tax on brown firms dampens economic activity and volatility, shifting lending from the brown to the green sector and reducing emissions. However, it entails welfare costs. From a policy-making perspective, we find that when the financial regulator integrates climate objectives into its policy toolkit, it can minimize the trade-off between macroeconomic volatility and welfare by fully coordinating its micro- and macroprudential policy tools. Full article

The accelerated growth and interconnectedness of financial institutions and movement towards products and activities outside the regulatory purview have been met with huge concerns. South Africa is one of the emerging economies that this conundrum has beset. Any potential instability in the financial sector likely poses insurmountable consequences and unprecedented government intervention, especially given that the country currently has no deposit insurance scheme. Although it is easy to justify the channels through which banks contribute to destabilising financial markets, it remains a controversial issue for insurers and other non-banking institutions. This study aims to empirically quantify the contribution of banks and insurers to aggregate the systemic risk of their respective industries by employing the component expected shortfall (CES). The CES is a robust quantitative systemic risk measure that allows for a comprehensive assessment of systemic risk by considering the contributions of individual financial components. Our findings demonstrate that the rankings from the CES framework are closely aligned with the regulatory D-SIB surcharges of the banking entities included in the study. The close alignment of both approaches is primarily due to the consideration of the size of an institution, amongst other factors. Full article

Unlike conventional finance, sustainable finance seeks to integrate social, environmental, and climate change considerations into financial institutions’ business strategies. The financial system’s ability to positively respond to sustainability transition demands is contingent upon a directional transformation that involves regulatory, political, structural, theoretical, and relational shifts. Accordingly, this paper performs a quali-quantitative analysis that combines both a bibliometric method with a content analysis process to investigate the trend of sustainable finance literature in the Scopus database and provide directions for potential future research. Our bibliometric performance analysis of 723 publications reveals that the UK, China, the US, Switzerland, and Japan are the major centers of research excellence in sustainable finance. They are the most productive countries and hold the most relevant institutions. Moreover, the prevalence of transdisciplinary journals over mainstream finance and economics sources is obvious. Our network map analysis, on the other hand, shows the substantial relevancy of sustainable/green banks’ involvement in sustainable development. Nonetheless, its relatively low density underlines the existence of relevant research gaps. Therefore, we undertake a content analysis of that particular topic’s literature to derive its conceptual structure and truly understand banks’ important role in sustainability transition. Key research themes in this respect include sustainability performance and banks’ profitability associations; sustainable banks’ risk profile; determinants of banks’ willingness to introduce sustainability criteria into their business strategy; depositors’/customers’ responsiveness to banks’ sustainability performance; and relevant macroprudential regulations, monetary policies, and supervisory guidelines to sustainability transition. Full article

Our research contributes a new point of view on China’s rare earth dynamic risk spillover measurement; this was performed by combining complex network and multivariate nonlinear Granger causality to construct the time-varying connectedness complex network and analyze the formation mechanism using the impulse response. First, our empirical research found that for the dynamic characteristics of China’s rare earth market, due to instability, uncertainty, and geopolitical decisions, disruption can be captured well by the TVP-VAR-SV model. Second, except for praseodymium, oxides are all risk takers and are more affected by the impact of other assets, which means that the composite index and catalysts are main sources of risk spillovers in China’s rare earth trading complex network system. Third, from the perspective of macroeconomic variables, there are significant multivariate nonlinear impacts on the total connectedness index of China’s rare earth market, and they exhibit asymmetric shock characteristics. These findings indicate that the overall linkage of the risk contagion in China’s rare earth trading market is strong. Strengthening the interconnections among the rare earth assets is of important practical significance. Empirical results also provide policy recommendations for establishing trading risk protection measures under macro-prudential supervision. Especially for investors and regulators, rare earth oxides are important assets for risk mitigation. When rare earth systemic trading risk occur, the allocation of oxide rare earth assets can hedge part of the trading risk. Full article

The analysis and prediction of systemic financial risks in the US during the COVID-19 pandemic is of great significance to the stability of financial markets in the US and even the world. This paper aims to predict the systemic financial risk in the US before and during the COVID-19 pandemic by using copula–GJR–GARCH models with component expected shortfall (CES), and also identify systemically important financial institutions (SIFIs) for the two comparative periods. The empirical results show that the overall systemic financial risk increased after the outbreak of the COVID-19 pandemic, especially in the first half of the year. We predicted four extreme risks that were basically successful in capturing the high risks in the US financial markets. Second, we identified the SIFIs, and depository banks made the greatest contribution to systemic risk from four financial groups. Third, after the outbreak of the epidemic, the share of Broker–Dealer and Other Institutions in the overall systemic risk has apparently increased. Finally, we recommend that the US financial regulators should consider macro-prudential guidance for major financial institutions, and we should pay more attention to Broker–Dealers, thereby improving the financial stability of the US and the global financial markets. Full article

While previous academic research highlights the potential of machine learning and big data for predicting corporate bond recovery rates, the operations management challenge is to identify the relevant predictive variables and the appropriate model. In this paper, we use meta-learning to combine the predictions from 20 candidates of linear, nonlinear and rule-based algorithms, and we exploit a data set of predictors including security-specific factors, macro-financial indicators and measures of economic uncertainty. We find that the most promising approach consists of model combinations trained on security-specific characteristics and a limited number of well-identified, theoretically sound recovery rate determinants, including uncertainty measures. Our research provides useful indications for practitioners and regulators targeting more reliable risk measures in designing micro- and macro-prudential policies. Full article

The paper presents an alternative approach to measuring systemic illiquidity applicable to countries with frontier and emerging financial markets, where other existing methods are not applicable. We develop a novel Systemic Illiquidity Noise (SIN)-based measure, using the Nelson–Siegel–Svensson methodology in which we utilize the curve-fitting error as an indicator of financial system illiquidity. We empirically apply our method to a set of 10 divergent Central and Eastern Europe countries—Bulgaria, Croatia, Czechia, Estonia, Hungary, Latvia, Lithuania, Poland, Romania, and Slovakia—in the period of 2006–2020. The results show three periods of increased risk in the sample period: the global financial crisis, the European public debt crisis, and the COVID-19 pandemic. They also allow us to identify three divergent sets of countries with different systemic liquidity risk characteristics. The analysis also illustrates the impact of the introduction of the euro on systemic illiquidity risk. The proposed methodology may be of consequence for financial system regulators and macroprudential bodies: it allows for contemporaneous monitoring of discussed risk at a minimal cost using well-known models and easily accessible data. Full article

The influence of real estate on finance and the whole economy has captured significant attention, especially since the aftermath of the Great Recession, because of the potential of this sector to destabilize markets. This paper explores the other way around: housing markets’ capacity to stabilize the economy through different macroprudential policies facing several types of shocks to achieve financial stability as a driver of sustainability. Specifically, a dynamic stochastic general equilibrium model is used to evaluate the effectiveness to stabilize the economy of different macroprudential tools based on the loan-to-value ratio for real estate, on the countercyclical capital buffer for the financial sector and a combination of both tools, facing a housing price shock, a technology shock and a financial shock. The model presents three types of agents (borrowers, entrepreneurs and banks) in an economy with a real estate market, a financial sector, a labor market and a production sector. The government can use different macroprudential policies to stabilize the economy, leaning against the wind of several shocks to achieve economic and financial sustainability. The assessment of the effectiveness of each policy shows that, in the case of a housing sector shock and a technology shock, the more effective policy is the one based on a countercyclical rule on the loan-to-value ratio for the real estate sector as a macroprudential tool. Furthermore, with a house price shock, if the macroprudential authority applies a macroprudential policy based on the countercyclical capital buffer, the shock may be exacerbated. Additionally, when there is a financial shock, the macroprudential authority may face a trade-off between several macro-financial policies depending on its objective. Therefore, it is not recommendable to automatically apply a macroprudential policy without a meticulous analysis of the nature of the shock that the economy is experimenting with and how different policies can stabilize or destabilize the different markets and, therefore, reach higher or lower sustainability. Full article

The recent evolution of prudential regulation establishes a new requirement for banks and supervisors to perform reverse stress test exercises in their risk assessment processes, aimed at detecting default or near-default scenarios. We propose a reverse stress test methodology based on a stochastic simulation optimization system. This methodology enables users to derive the critical combination of risk factors that, by triggering a preset key capital indicator threshold, causes the bank’s default, thus detecting the set of assumptions that defines the reverse stress test scenario. This article presents a theoretical presentation of the approach, providing a general description of the stochastic framework and, for illustrative purposes, an example of the application of the proposed methodology to the Italian banking sector, in order to illustrate the possible advantages of the approach in a simplified framework, which highlights the basic functioning of the model. In the paper, we also show how to take into account some relevant risk factor interactions and second round effects such as liquidity–solvency interlinkage and modeling of Pillar 2 risks including interest rate risk, sovereign risk, and reputational risk. The reverse stress test technique presented is a practical and manageable risk assessment approach, suitable for both micro- and macro-prudential analysis. Full article

One of the main issues in the recent Chinese financial reform is aimed at effectively measuring systemic risk and taking appropriate measures to ensure its sustainability and prevent new crises. In this paper, we firstly introduced the present macro-prudential policies implied in China and pointed out the existing problems. Secondly, we analyzed the banks’ assets riskiness and the banks’ probability to default, then, by means of a leave-one-out model, we measured each commercial bank systemic risk contribution. Thirdly, based on comprehensive empirical results and theoretical analysis, we provided some references for macro-prudential regulation and supervision. Results show that systemic risk is increasing in 2013–2017, in particular with reference to contagion risk, with a specific concentration within joint-stock commercial banks, suggesting a specific attention of regulators and supervisors for this category. Full article

After the financial crisis, financial stability and sustainability became key to global economic and social development, and the coordination of monetary policy and macroprudential policy plays a crucial role in maintaining financial stability and sustainability. This paper provides a theoretical analysis and empirical evidence from China on the impact of monetary policy and macroprudential policy coordination on financial stability and sustainability. We collect data from 2003 to 2017; from the micro level, we use the System Generalized Method of Moments (System GMM) method to analyze the monetary policy and macroprudential policy coordination effect on 88 commercial banks’ risk-taking; from the macro level, we use the Structural Vector Autoregression (SVAR) method to analyze the two policies coordination effect on housing prices and stock price bubbles. The conclusions are as follows: firstly, for regulating bank risk-taking, monetary policy and macroprudential policy should conduct counter-cyclical regulation simultaneously; secondly, for regulating housing prices, tight monetary policy and tight macroprudential policy should be implemented alternately; thirdly, for regulating stock price bubbles, macroprudential policy should be the first line of defense and monetary policy should be the second one. Full article

We examine the global legal entity identifier (LEI) system for the identification of participants in financial markets. Semi-structured interviews with data professionals revealed the many ways in which the LEI can improve both business process efficiency, and counterparty and credit risk management. Larger social benefits, including the monitoring of systemic financial risk, are achievable if it becomes the accepted universal standard for legal entity identification. Our interviews also review the substantial co-ordination and investment barriers to LEI adoption. To address these, a clear regulatory-led road map is needed for its future development, with widespread application in regulatory reporting. Full article

In the wake of the global financial crisis that erupted in 2008, there has been extensive commentary and regulatory focus on the ‘Too Big to Fail’ issue. In this paper, we survey the proposed solutions and regulatory initiatives that have been undertaken. We conduct a longitudinal analysis of major U.S. banks in four discrete time periods: pre-crisis (2005–2007), crisis (2008–2010), post-crisis (2011–2013) and normalcy (2014–2016). We find that risk metrics such as leverage and volatility which spiked during the crisis have reverted to pre-crisis levels and there has been improvement in the proportion of equity capital available to cushion against asset value deterioration. However, banks have grown in size and it does not appear as if their business models have been redirected toward more traditional lending activities. We believe that it is premature to conclude that ‘Too Big to Fail” has been solved, but macro-prudential regulation is now much more effective and, consequently, banks are on a considerably sounder footing since the depths of the crisis. Full article

There has been little quantitative research on macro-prudential regulation for the Chinese banking system while the existing relevant research in other countries has not considered the network structure. Therefore, the present paper constructs a dynamic Chinese banking network system with complete and random structures and a quantitative model of macro-prudential regulation using four risk allocation mechanisms (Component VaR, Incremental VaR, Shapley value EL, and ΔCoVaR). Then we analyze empirically the macro-prudential regulation effect on the dynamic Chinese banking network system. The results show that the macro-prudential regulation focus on capital requirements for the Chinese banking network system is very effective in that most banks’ default probabilities have been reduced. Moreover, the regulation effect of the ΔCoVaR mechanism is the most significant and it has strong applicability because it is not affected by the two network structures. The next effective methods are Component VaR and Shapley value EL mechanisms. The last is the Incremental VaR mechanism. The Chinese banking system with random network is more stable in most years than that of the complete network. Lastly, our analysis suggests that setting up capital requirements based on each bank’s systemic risk contribution is able to promote the stability of the Chinese banking system. Full article

This paper provides a rationale for the macro-prudential regulation of insurance companies, where capital requirements increase in their contribution to systemic risk. In the absence of systemic risk, the formal model in this paper predicts that optimal regulation may be implemented by capital regulation (similar to that observed in practice, e.g., Solvency II ) and by actuarially fair technical reserve. However, these instruments are not sufficient when insurance companies are exposed to systemic risk: prudential regulation should also add a systemic component to capital requirements that is non-decreasing in the firm’s exposure to systemic risk. Implementing the optimal policy implies separating insurance firms into two categories according to their exposure to systemic risk: those with relatively low exposure should be eligible for bailouts, while those with high exposure should not benefit from public support if a systemic event occurs. Full article