Financial Systemic Risk Research Articles

Research on Financial Systemic Risk Early Warning Based on Markov Regime Switching Model

Research on Financial Systemic Risk Early Warning Based on Markov Regime Switching Model

The systemic risk of leveraged and covenant-lite loan syndications

By modelling the whole U.S. syndicated loan market as a financial network from 2000 to 2022, we find that highly connected institutions hold significant shares of leveraged and covenant-lite loans. Our analysis indicates that the size of leveraged and covenant- lite syndicated loan portfolios increases financial institutions' systemic risk, particularly during recession periods. Although banks commonly sell syndicated loans shortly after origination, our results suggest that they remain vulnerable to pipeline risk. Our study has significant implications for policymakers and regulators, as it can aid in identifying banks exposed to systemic risk associated with leveraged and covenant-lite loans and in ranking systemically important financial institutions accordingly.

Connectedness and systemic risk between FinTech and traditional financial stocks: Implications for portfolio diversification

The rapid growth in FinTech is attracting significant investor attention. There are concerns that FinTech stocks may be a source of systemic risk and this has implications for the stability of the financial sector. This study uses a TVP-VAR model to estimate the dynamic connectedness between global FinTech stocks and the stocks of large US banks, regional US banks, US insurance, and global private equity. The findings reveal that FinTech and insurance stocks are net receivers of shocks while large US banks are a major source of shocks. Thus, FinTech stocks are not a source of systemic risk but can be affected by financial contagion and systemic risk originating from large US banks. The highest connectedness was observed at the onset of the COVID-19 lockdowns illustrating the dramatic impact that a health pandemic can have on systemic risk. Systemic risk also increased during the 2023 US bank panic. Connectedness has implications for constructing investment portfolios. The equally weighted, risk parity, and risk parity connectedness portfolios have similar portfolio summary statistics, but lower risk adjusted returns than the maximum Sharpe ratio portfolio which better captures the low correlation between FinTech stocks and traditional financial stocks. These results are robust across various portfolio rebalancing periods (daily, weekly, monthly).

Do commodity prices matter for global systemic risk? Evidence from ML variable selection

We identify robust predictors of global systemic risk proxied by conditional capital shortfall (SRISK) among a comprehensive set of commodity prices for the period between January 2004 and December 2021. The search is based on a battery of ML variable selection algorithms which apply both to price levels and price shocks in the presence of control variables, including the first lag of SRISK, world industrial production, global economic policy uncertainty, geopolitical risk as well as the global stance of monetary and macroprudential policies. We find that these controls outweigh commodity prices as the predictors of global systemic risk. Of the commodities themselves, the prices for agricultural commodities, including food, e.g. chicken, bananas, beef, tea, cocoa, are more important predictors of global systemic risk than the prices for energy commodities, e.g. natural gas and oil prices. The financialization of agricultural commodities, bio-energy expansion as well as commodity-specific dependence of the major economies contributing to global systemic risk, e.g. China, account for our main finding. We also document the positive linkage between commodity prices and systemic risk for the majority of commodities. Thus, monitoring commodity prices to avoid their unbalanced growth is of vast importance to curb global systemic financial risk.

Regulating Buy Now Pay Later (BNPL) in Asean: a Comparative Analysis on Regulatory Challenges and Opportunities

This study provides a comparative analysis of the regulatory frameworks governing Buy Now Pay Later (BNPL) services across ten ASEAN countries: Indonesia, Malaysia, Singapore, Thailand, the Philippines, Laos, Brunei Darussalam, Vietnam, Myanmar, and Cambodia. As BNPL services rapidly expand throughout the region, understanding the diverse regulatory landscapes and their implications becomes increasingly critical for fostering financial stability, consumer protection, and innovation in the digital financial ecosystem. Utilizing a literature review methodology, the research examines existing regulations, legal frameworks, and market trends, assessing their impact on financial stability, consumer protection, and fintech innovation. Singapore is identified as the leader in regulatory practices, effectively balancing fintech innovation with stringent consumer protection. Indonesia and Malaysia emphasize financial inclusion and systemic risk management, with Indonesia's framework focusing on transparency and financial literacy. Thailand and the Philippines are refining their frameworks, while Myanmar, Laos, Brunei, Vietnam and Cambodia are still developing their regulatory approaches. BNPL services, driven by growing e-commerce and fintech ecosystems, offer significant opportunities for financial inclusion but also pose challenges related to over-indebtedness, credit risk, and data protection. The analysis emphasizes that while BNPL presents significant opportunities for financial inclusion and fintech innovation, effective regulation is critical to ensuring sustainable growth and protecting consumers from debt traps and financial instability.

Brazilian banks risk-taking and systemic risk

This study analyzes the marginal contribution of Brazilian banks to the systemic risk. The objective is to identify whether banks that share common characteristics similarly contribute to systemic financial shocks. First, the risk assumed by a sample of listed banks is measured from the accounting, market, and regulatory perspectives. Sample banks were segregated using an unsupervised clustering model. The results were compared with the methodology currently used by the Central Bank of Brazil to segment the banking institutions. Finally, we evaluate the banking groups’ marginal contribution to systemic financial risk using ΔCoVaR. These results suggest that institutions that share similar characteristics in relation to their risk profiles behave similarly during times of greater market stress. Notably, size, geographic diversification, and liquidity were common attributes among banks contributing significantly to systemic risk during financial crises. This study advances the field of banking finance by introducing an analytical framework that goes beyond the traditional focus on bank balance sheet size, aligning with international standards for evaluating the systemic importance of financial institutions.

Board gender diversity and default risk in a bank-based financial system: A pre-registered report

This pre-registered report investigates the mitigating effect of board gender diversity on default risk in Japanese firms. We will also examine the potential mitigating effect of close bank-firm relationships on default risk. Importantly, we seek to determine whether women on boards (WOB) complements or substitutes bank monitoring in mitigating the default risk in the bank-based (financial) system. Our study will provide insight into the regulatory discussions concerning the Corporate Governance (CG) code, which seeks to enhance WOB and contribute to the debate on “who are the effective monitors in mitigating default risk” in a bank-based system.

Dynamic impact of climate risks on financial systemic risk: Evidence from China

Dynamic impact of climate risks on financial systemic risk: Evidence from China

Monte Carlo Estimation of CoVaR

CoVaR is an important measure of financial systemic risk due to its ability to capture tail dependence between the losses of different portfolios and its capacity to predict financial crises. Estimating CoVaR is challenging because its definition involves a zero-probability event, which is unobservable in the data. The existing model-based methods address this issue by assuming simplified structural models, which introduce biases that are difficult to eliminate. In “Monte Carlo Estimation of CoVaR,” Huang, Lin, and Hong propose using Monte Carlo methods to estimate CoVaR, leveraging the modeling flexibility of Monte Carlo simulation. Specifically, they introduce a batching estimator applicable to a wide range of financial models and prove that its best rate of convergence is [Formula: see text], where n is the sample size. Under the widely used delta-gamma approximation model, they further introduce an importance sampling–inspired estimator and prove that its best rate of convergence can be improved to [Formula: see text].

Ambiguity, limited market participation, and the cross-sectional stock return

Using expected utility under uncertain probability theory (EUUP, Izhakian, 2017, 2020), we study whether the ambiguity related to individual stocks is priced in the Chinese A-share market and the mechanism behind the ambiguity premium phenomenon. Theoretically, when the asset price is within a specific range, ambiguity-averse investors refrain from participating in trading. As asset ambiguity increases, high ambiguity-averse investors exit the market, with those with lower aversion remaining in the market (limited market participation phenomenon). Investors who remain in the market due to lower ambiguity aversion are willing to accept a low ambiguity premium. Empirically, we measure monthly ambiguity using the volatility of daily stock return distributions within a month and find the following: (1) The equal-weighted average returns of the most ambiguous portfolios (top 20%) are significantly lower than those of the least ambiguous portfolios (bottom 20%). (2) Ambiguity still significantly negatively affects the cross-sectional stock return after controlling for common firm characteristics. (3) The higher the ambiguity, the lower the future trading activity, supporting our theoretical predictions. These findings reveal the mechanism of the negative ambiguity premium in the Chinese A-share market. This study provides new ideas for building a factor-pricing model suitable for the A-share market and a fresh perspective for preventing systemic financial risk.

Decomposition of oil price shock, changes in market conditions and systemic risk transmission – an analysis from the Chinese perspective

ABSTRACT This research aims to investigate the heterogeneous responses of each specific risk variable across different states in the context of varying levels of crude oil price shocks. Using data period from 27 December 2007 to 28 October 2022, we construct proxy variables for systemic financial risks based on the considerations of four specific perspectives. The results of the empirical analysis indicate that oil price fluctuation observed in short, medium, and long-term time periods has an obvious impact on each risk variable. From the evaluation of conditional value-at-risk difference as well as the marginal expected shortfall, both short-term and long-term shocks have an apparent amplifying effect on market risk when it is at a high level. When evaluated from the angle of liquidity, oil price shocks generally exhibit positive effects on market liquidity, where this effect is more significant in the long term rather than terms. When considering the effect of volatility specifically, oil price shocks are found to cause sharp shocks to the market, whether the market itself is in a stable or volatile state.

Does climate change matter for bank profitability? Evidence from China

Using panel data from 87 China’s banks from 2011 to 2022, this research investigates whether and how climate change affects bank profitability. It is discovered that the improvement of bank profitability is severely hampered by climate change. The main ways that climate change affects bank profitability are by causing financial losses to bank creditors, changing the likelihood of defaults and the quality of bank credit assets. Energy conservation and carbon reduction, the implementation of green financial policies, and ensuring that banks have enough capital are all factors that can help mitigate the negative effects of climate change on bank profitability. In addition, climate change has a greater negative effect on the profitability of small-sized banks, regional banks, and banks with lower levels of liquidity. In conclusion, this study offers forward-looking suggestions for banks to reduce risks from climate change, which is critical for encouraging low-carbon and green development and averting systemic financial risks. It also offers theoretical references for Chinese banks to develop customized policies and strategies to address these risks.

The characteristics of the new dual-cycle development pattern and systemic financial risk based on TVP-SVAR and MS-VAR model analyses

The new development pattern of the dual cycle is an important strategic deployment by the Chinese government in response to the complex and changing economic environment and a new stage of economic development. Based on the perspective of this new dual-cycle development pattern, this paper explores the time-varying nonlinear relationship between this new development pattern and systemic financial risk by constructing two models: the TVP-SVAR-SV and the MS-VAR. The empirical results show that, first, there was a significant negative impulse response effect between the new dual-cycle development pattern and systemic financial risk. The inhibitory effects of the domestic cycle and short-term pulse response were more significant than those of the international cycle and medium- and long-term pulse responses. In addition, the inhibitory effect of the new dual-cycle development pattern on systemic financial risk exerted different impact effects at different timepoints, with significant variability. Second, there was a significant nonlinear relationship between the new development pattern and systemic financial risk. The MSIH(2)-VAR(1) model identified two regional states: the financial risk release stage and the financial risk accumulation stage. This effect lasted longer in zone 2 (financial risk accumulation phase), with a sample size of more than 60 % of the total sample and a duration of 6.12. Third, in the impulse response analysis of different zones, a mutually reinforcing effect was found between the domestic and international cycles, and both exerted a significant suppressive effect on systemic financial risk, which was more significant in zone 1. The findings of this paper have important theoretical and practical significance for constructing and perfecting the new dual-cycle development pattern, promoting the high-quality development of China's financial market, and preventing the accumulation and occurrence of systemic financial risk.

Systemic Financial Risk of Stock Market Based on Multiscale Networks

Systemic Financial Risk of Stock Market Based on Multiscale Networks

Assessing the Impact of Financial Technology Innovations on the Sustainable Profitability of Listed Commercial Banks in China

Commercial banks constitute a crucial segment of China’s financial system, and their efficient operation is directly linked to the development of other sectors within the national economy. The sustainable profitability of these banks is vital for maintaining the stability of China’s financial system. In the context of the current digital economy, it is of great theoretical and practical significance to conduct an in-depth analysis of the impact of financial technology (fintech) development on the sustainable profitability of commercial banks and its underlying mechanisms. Such research can promote the digital transformation of commercial banks, enhance risk supervision policies, and mitigate systemic financial risks. This study utilizes EViews software Version 13 to analyze annual data from 13 listed commercial banks in China over the period from 2011 to 2021. It examines the influence of fintech on the profitability of these banks, considering their unique characteristics and drawing insights from the existing literature on the mechanisms through which fintech affects bank profitability. Employing both a static panel fixed effects variable-intercept model and a dynamic panel generalized method of moments (GMM) model, the empirical findings indicate that fintech development significantly impacts the profitability of listed commercial banks.

Assessing network risk with FRM: links with pricing kernel volatility and application to cryptocurrencies

The Financial Risk Meter (FRM) employs Quantile-LASSO regression to identify systemic financial risk and dependencies among tail events across financial assets. This paper establishes, both theoretically and empirically, a meaningful economic relationship between the FRM index, derived from the penalization parameter in quantile LASSO regression, and the volatility of assets' pricing kernels, the attainable maximal Sharpe ratio, and market volatility. Despite the rapid growth of the crypto market and its increasing integration with traditional financial markets, there remains a dearth of risk measures in this space. FRM @ Crypto exhibits robust predictive capabilities in anticipating future market risk, potentially filling a critical void in this market.

Monetary Policy, Capital Regulation and Systemic Risk in Commercial Banks: Evidence from in China

This paper examines the impact of monetary policy and capital regulation on commercial banks' systemic risk using a fixed panel model with data from 16 listed commercial banks in China from Q1 2011 to Q4 2019. The results show that both quantity-based monetary policy instruments, represented by currency issuance, and price-based monetary policy instruments, represented by interest rates, affect systemic risk. And they both show that accommodative monetary policies amplify commercial banks systemic risk. Besides, capital regulation has a dampening effect on systemic risk, and the intensity of regulation moves inversely with systemic risk. In addition, there is a synergistic effect between monetary policy and capital regulation. Furthermore, a symbiotic relationship exists between monetary policy and capital regulation. The findings of this study assist nations in managing systemic financial risks through macroeconomic policies.

Systematic financial risk detection based on DTW dynamic algorithm and sensor network

Traditional financial risk detection methods are mainly based on statistical models and market data, in which sensor network has a wide application prospect. The research can improve the accuracy and efficiency of financial risk detection by using the data and information of sensor network. By making full use of the data collection capabilities of sensor networks to obtain more comprehensive and accurate financial data, it helps to identify potential risk factors more accurately. This paper introduces DTW (Dynamic Time warping) algorithm as the main financial risk detection method, which can effectively capture the similarity between time series data and apply it to the financial data obtained by sensor network. Through regularization and matching of time series data, abnormal changes and abnormal patterns can be identified, so as to timely warn and control financial risks. By comparing the data of sensor network with that of traditional methods, we found that the financial risk detection method based on DTW algorithm and sensor network has higher accuracy and efficiency, and can identify potential risk factors more accurately.

Does common institutional ownership restrain corporate financialization?

Using a sample of Chinese non-financial listed firms from 2007 to 2021, we investigate the impact of common institutional ownership on corporate financialization. Our results show that common institutional ownership generates the “synergy effect” by restraining corporate financialization. We then assess the channels and find that common institutional ownership plays dual roles as an “information disseminator” and a “governance practitioner,” effectively curbing corporate financialization by enhancing information acquisition abilities and mitigating managerial myopia. Our cross-sectional tests reveal that the “synergy effect” is more pronounced when there is common institutional ownership without business affiliations or with larger network size, and when firms have lower state or management ownership. Finally, common institutional ownership guides firms toward developing the core business while enhancing firm value. Our findings have potential implications for regulatory authorities in guiding the benign interaction between real and virtual economies and preventing systemic financial risks.

Tail risk connectedness among GCC banks episodes from the Global Financial Crisis to COVID-19 pandemic

This paper aims to analyze the impact of the COVID-19 pandemic on market-based systemic risk and the connectedness of commercial banks in Gulf Cooperation Council countries. The results suggest that systemic risk has increased significantly after the pandemic by employing two very well-known systemic risk measures, the Delta conditional value-at-risk (ΔCoVaR) and the marginal expected shortfall (MES), but heterogeneously across GCC nations. Using the Granger-Causality network method, the results reveal a remarkable rise in the percentage and number of significant connectedness between banks for Kuwait and KSA during the pandemic. Oman and Qatar experienced an unnoticeable increase in bank return connectedness. Furthermore, the study identifies the bank characteristics that provide shelter from the systemic shocks of the pandemic. The study findings indicate that income diversification is the most crucial variable for enhancing bank stability amid the pandemic. Our findings provide policy-related implications for understanding and mitigating risk shock transmission and the containment of systemic financial risk, in addition to multiple future lines of research.