Portfolio diversification and systemic risk in interbank networks

This paper contributes to a growing literature on the ambiguous effects of risk diversification. In our model, banks hold claims on each other’s liabilities that are marked-to-market on the individual financial leverage of the obligor. The probability of systemic default is determined using a passage-problem approach in a network context and banks are able to internalize the network externalities of contagion through their holdings. Banks do not internalize the social costs to the real economy of a systemic default of the banking system. We investigate the optimal diversification strategy of banks in the face of opposite and persistent economic trends that are ex-ante unknown to banks. We find that the optimal level of risk diversification may be interior or extremal depending on banks exposure the external assets and that a tension arises whereby individual incentives favor a banking system that is over-diversified with respect to the level of diversification that is desirable in the social optimum.     

Understanding the consequences of diversification on financial stability

In this paper, we study the consequences of diversification on financial stability and social welfare using an agent based model that couples the real economy and a financial system. We validate the model against its ability to reproduce several stylized facts reported in real economies. We find that the risk of an isolated bank failure (i.e. idiosyncratic risk) is decreasing with diversification. In contrast, the probability of joint failures (i.e. systemic risk) is increasing with diversification which results in more downturns in the real sector. Additionally, we find that the system displays a “robust yet fragile” behaviour particularly for low diversification. Moreover, we study the impact of introducing preferential attachment into the lending relationships between banks and firms. Finally, we show that a regulatory policy that promotes bank–firm credit transactions that reduce similarity between banks can improve financial stability whilst permitting diversification.

     

Financial development and economic growth in a microfounded small open economy model

The global financial crisis since 2008 revived the debate on whether or not and to what extent financial development contributes to economic growth. This paper reviews different theoretical schools of thought and empirical findings on this nexus, building on which we aim to develop a unified, microfounded model in a small open economy setting to accommodate various theoretical possibilities and empirical observations. The model is then calibrated to match some well-documented stylized facts. Numerical simulations show that, in the long run, the welfare-maximizing level of financial develop is lower than the growth-maximizing level. In the short run, the price channel (through world interest rate) dominates the quantity-channel (through financial productivity), suggesting a vital role of international cooperation in tackling systemic risk of the global financial system.     

An empirical study of the Mexican banking system’s network and its implications for systemic risk

With the aim to measure and monitor systemic risk, we present some topological metrics for the interbank exposures and the payments system networks. The evolution of such networks is analyzed, we draw important conclusions from the systemic risk's perspective and propose a measure of interconnectedness. Additionally, we suggest non-topological measures to describe individual behavior of banks in both networks. The main findings of this paper are: the structures of the payments and exposures networks are different (in terms of connectivity); the topology of the exposures network changed after the collapse of Lehman Brothers, whereas the structure of the payments network does not; the proposed measure of interconnectedness can be used to determine the importance of a bank in terms of connectivity. Finally, we found that interconnectedness of a bank is not necessarily related with its assets size but it is linked to the contagion it might cause.     

Bank competition,financial development and macroeconomic stability: Empirical evidence from emerging economies

In this study, we investigate the potential contribution of bank competition to macroeconomic stability, and the interactive role of financial development. We classify macroeconomic stability into economic and financial stability. Economic stability is represented by the volatility of actual and unexpected output growth, whereas financial stability is assessed by the aggregate Z-score and volatility of the private credit-to-gross domestic product ratio. We employ two structural and two non-structural measures of bank competition in our analysis. Applying a two-step dynamic panel system (GMM) to macroeconomic data from 48 developing nations from 1999 to 2018, we find a bell-shaped relationship between bank competition and macroeconomic stability. The findings imply that a higher level of bank competition promotes macroeconomic stability by reducing output growth volatility, fluctuations in private credit, and the probability of bank default. There is an optimal level of bank competition beyond which it may foster economic and financial instability. Moreover, financial development enhances bank competition’s positive impact on macroeconomic stability.     

Systemic risk in European financial and energy sectors: Dynamic factor copula approach

We perform an analysis of systemic risk in financial and energy sectors in Europe using daily time series of CDS spreads. We employ the factor copula model with GAS dynamics from Oh and Patton (2018) for the purpose of estimating dependency structures between market participants. Based on the estimated models, we perform Monte Carlo simulations to obtain future values of CDS spreads, and then measure the probability of systemic events at given time points. We conclude that substantially higher systemic risk is present in the financial sector compared to the energy sector. We also find that the most systemically vulnerable financial and energy companies come from Spain.     

Financial constraints and corporate investments during the current financial and economic crisis: The credit crunch and investment decisions of Slovenian firms

We investigate the effect of financial constraints on the investment decisions of Slovenian firms during the current financial and economic crisis. By estimating the error-correction model and the Euler-equation specification, we found that corporate investments were significantly affected by financial constraints during the crisis. The effect of financial constraints intensified in 2009 and alleviated slightly in 2010, although still being significantly more intense than before the crisis hit the economy. By estimating a switching regression model with unknown sample separation that enabled us to address the problem of judgemental sample separation, we were also able to estimate the error-correction model separately for financially constrained and financially unconstrained firms. The results indicate that financial constraints have a significant effect on both financially constrained and financially unconstrained firms, although corporate investments were more severely affected in financially constrained firms.     

Interactions between financial constraints and economic growth

The financial economy and the real economy are interconnected through various, complex, and evolving transmission mechanisms, whose literary coverage is far from comprehensive. In this context, we wish to contribute to the literature on the interactions between financial constraints and economic growth. We introduce financial dynamics in the R&D-based growth literature, by bringing Bernanke, Gertler and Gilchrist’s (1999) informational asymmetries into Romer’s (1990) growth model. With the developed framework, our main goal is to examine if and how such asymmetries impact economic growth. We find that the overall impact of this form of financial constraints on long-term growth is negative.     

Nowcasting and forecasting global financial sector stress and credit market dislocation

We introduce a new international model for the systematic distress risk of financial institutions from the US, the European Union, and the Asia-Pacific region. Our proposed dynamic factor model can be represented as a nonlinear, non-Gaussian state space model with parameters that we estimate using Monte Carlo maximum likelihood methods. We construct measures of global financial sector risk and of credit market dislocation, where credit market dislocation is defined as a significant and persistent decoupling of the credit risk cycle from macro-financial fundamentals in one or more regions. We show that, in the past, such decoupling has preceded episodes of systemic financial distress. Our new measure provides a risk-based indicator of credit conditions, and as such, complements earlier quantity-based indicators from the literature. In an extensive comparison with such quantity-based systemic risk indicators, we find that the behaviour of the new indicator is competitive with that of the best quantity-based indicators.     

Systemic event prediction by an aggregate early warning system: An application to the Czech Republic

This work develops an early warning framework for assessing systemic risks and predicting systemic events over a short horizon of six quarters and a long horizon of 12 quarters on a panel of 14 countries, both advanced and developing. First, we build a financial stress index to identify the starting dates of systemic financial crises for each country in the panel. Second, early warning indicators for the assessment and prediction of systemic risk are selected in a two-step approach; we find relevant prediction horizons for each indicator by a univariate logit model followed by the application of Bayesian model averaging to identify the most useful indicators. Finally, we observe the performance of the constructed EWS over both horizons on the Czech data and find that the model over the long horizon outperforms the EWS over the short horizon. For both horizons, out-of-sample probability estimates do not deviate substantially from their in-sample estimates, indicating a good out-of-sample performance for the Czech Republic.     

A time-varying copula approach for constructing a daily financial systemic stress index

This paper develops a financial systemic stress index (FSSI) for the US financial market. We propose a time-varying copula method to model the dependence structure among financial sectors in order to build a correlated financial stress model that can signal systemic financial risks. The copula method is preferable to the traditional approach, enabling the modeling of non-linear correlations. Our analyses show that the dependencies across banking, security, and forex markets are best modeled by Archimedian copulas. Finally, we conduct a Markov Switching Autoregressive (MS-AR) model for FSSI and identify high financial stress episodes taking place in 2008–2009, 2011 and 2020.     

金融压力对中国实体经济冲击研究

本文首先参考现有文献对已有的金融压力度量方法及应用做了梳理,然后选择2006年1月~2014年9月,包含金融政策环境、银行业为主的金融机构、金融市场和外汇市场等在内的主要因素指标,并通过加权平均后再进行标准化处理的方式合成各自项风险压力指数,再汇总合成系统性金融压力指数并做出判断分析。然后利用采购经理合成指数以代替实体经济的发展状况,通过格兰杰因果关系检定得到金融压力与实体经济发展之间的因果关系,并建立自回归模型以达到对系统性金融压力的预测,并最后针对金融风险的防范提出政策建议。     

Basel III capital surcharges for G-SIBs are far less effective in managing systemic risk in comparison to network-based,systemic risk-dependent financial transaction taxes

In addition to constraining bilateral exposures of financial institutions, there exist essentially two options for future financial regulation of systemic risk: First, regulation could attempt to reduce the financial fragility of global or domestic systemically important financial institutions (G-SIBs or D-SIBs), as for instance proposed by Basel III. Second, it could focus on strengthening the financial system as a whole by reducing the probability of large-scale cascading events. This can be achieved by re-shaping the topology of financial networks. We use an agent-based model of a financial system and the real economy to study and compare the consequences of these two options. By conducting three computer experiments with the agent-based model we find that re-shaping financial networks is more effective and efficient than reducing financial fragility. Capital surcharges for G-SIBs could reduce systemic risk, but they would have to be substantially larger than those specified in the current Basel III proposal in order to have a measurable impact. This would cause a loss of efficiency.     

The impact of national culture on systemic risk

We investigate the effects of national culture on systemic risk using a comprehensive dataset from global banks in 58 countries over the period 2003–2016. Our results reveal that systemic risk measures are associated with cultural values. In particular, our results show that individualism and masculinity are the main drivers of banks' contribution to systemic risk. In addition, the impact of cultural variables on the systemic risk measures is nonlinear. This variation may be driven by both information in the national cultural measures and the skewness of the systemic risk measures. The findings have implications for prudential policies: designing uniform prudential and regulatory policies in banking to avoid financial distress for countries with heterogeneous cultures might not have the desire impact; rather, they might be more effective if the type of culture in each individual country is considered.     

Brokers’ financial network and stock return

Brokerage firms are usually not only known for trading stocks for their retail clients in return for commission fee but also known for being information distributors of their clients’ investment recommenders. However, only a few studies have examined investors’ trading behaviors within a brokerage firm. This study proposes a financial network model in modeling the information diffusion process of investors within brokerage firms and investigates the potential effect of interconnectedness among brokerage firms on stock returns. We find that the centrality of brokerage firms has strong explanatory power to stock returns even if we control for the Fama–French pricing factors and other characteristics of stock.     

对我国区际经济与金融差距关联性的实证分析

各区域间金融发展的差异对经济发展差距有无影响以及影响机制如何成为经济学研究的一项任务。以塞尔指标衡量我国经济与金融发展差距,发现我国区域间经济发展差距与金融发展差距呈现一致的变动关系,且金融差距大于经济差距。由此引出的基本判断是我国区际经济差距的逻辑原因有金融因素,进而采用格兰杰因果关系检验判断我国省际金融发展与经济增长间的关系,从中可以明确我国东部地区金融成长偏重于内生状态,而中西部地区更倾向于外生状态。考虑到改革的总体方向,并借鉴东部地区的经验,放松金融抑制、催化内生金融成长无疑是全面促进中西部经济发展的必然选择。     

Measuring the interconnectedness of financial institutions

This paper uses sophisticated empirical methodology to measure the interconnectedness of financial institutions in five developed economies – France, Germany, Japan, UK and USA – for the period January 2000 to November 2009. The study goes beyond the conventional use of first and second moments of returns and uses the timevarying equity price of risk methodology to measure the level of convergence of the financial sectors in the countries of interest. More specifically, Kalman filter convergence tests are applied to the weekly equity price of risk data to measure the interconnectedness between these countries’ and the US finance sectors. Results indicate the presence of short-term timevarying interconnectedness of the finance sectors of France, Germany and the UK with that of the US and steady-state longer term interconnectedness only between Germany and the US. Short-term and long-term steady-state interconnectedness between Japan and the US is not evident. We conclude that going forward in an environment of increased interconnectedness of international financial markets, a coordinated global financial regulatory policy with discretionary allocation of resources and execution strategy at a national level is the preferred regulatory structure to ensure sound operations of international financial systems.     

A network based fintech inclusion platform

The paper evaluates, from a sustainable finance viewpoint, a machine learning model implemented in a fintech platform, whose aim is to assign credit ratings. The aim of the model is to learn from both micro economic data and macro economic trends the credit rating of companies that ask for credit. We show that the proposed model is able to reward the companies that have better financial performances with better ratings and, therefore, a higher probability/lower cost of obtaining credit. At the same time, the model correctly takes into account the overall evolution of the economy, favoring financial inclusion for the more penalized economic sectors, particularly during crisis times. The model, its application to credit rating, and its evaluation, are illustrated with reference to more than 100,000 European companies before and during the COVID-19 pandemic crisis. The results shows that, while the impact of the financial variables does not change over time, and particularly during the pandemic, the impact of sectors changes considerably, favoring financial inclusion and resilience.     

Foreign direct investment and its impact on the Thai economy: the role of financial development

This paper examines the roles of foreign direct investment and financial development in the process of economic development using Thailand as the case study. We argue that better developed financial systems allow an economy to exploit the benefits of foreign direct investment more efficiently. The estimation draws upon an unrestricted error-correction model to avoid omitted lagged variable bias, and an instrumental variable estimator to correct for endogeneity bias. Using annual time series data from 1970 to 2004, the results show that financial development stimulates economic development whereas foreign direct investment impacts negatively on output expansion in the long run. However, an increased level of financial development enables Thailand to gain more from foreign direct investment, suggesting that the impact of foreign direct investment on output growth can be enhanced through financial development. The results are robust to different measures of financial development.      

Trade openness,financial openness,and macroeconomic volatility

This paper develops a new model of an open economy for a study of macroeconomic dynamics under different degrees of trade and financial openness. The model is estimated using quarterly data on the Chinese economy over the period 2005Q3-2020Q4 and then applied to analyze how macroeconomic volatility varies with trade and financial openness in several representative settings. We find that the impacts on macroeconomic volatility of trade openness and financial openness depend on the nature of the underlying shocks and a moderate degree of trade openness, together with a high degree of financial openness, yield the optimal welfare results in most cases. These results highlight that the effects of trade and financial openness on macroeconomic volatility differ in various situations and that their interactions can lead to different welfare results.