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J. Risk Financial Manag., Volume 12, Issue 3 (September 2019)

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Open AccessArticle
Which Cryptocurrencies Are Mostly Traded in Distressed Times?
J. Risk Financial Manag. 2019, 12(3), 135; https://doi.org/10.3390/jrfm12030135 (registering DOI)
Received: 10 July 2019 / Revised: 13 August 2019 / Accepted: 14 August 2019 / Published: 20 August 2019
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Abstract
This paper investigates the level of liquidity of digital currencies during the very intense bearish phase in their markets. The data employed span the period from April 2018 until January 2019, which is the second phase of bearish times with almost constant decreases. [...] Read more.
This paper investigates the level of liquidity of digital currencies during the very intense bearish phase in their markets. The data employed span the period from April 2018 until January 2019, which is the second phase of bearish times with almost constant decreases. The Amihud’s illiquidity ratio is employed in order to measure the liquidity of these digital assets. Findings indicate that the most popular cryptocurrencies exhibit higher levels of liquidity during stressed periods. Thereby, it is revealed that investors’ preferences for trading during highly risky times are favorable for well-known virtual currencies in the detriment of less-known ones. This enhances findings of relevant literature about strong and persistent positive or negative herding behavior of investors based on Bitcoin, Ethereum and highly-capitalized cryptocurrencies in general. Notably though, a tendency towards investing in the TrueUSD stablecoin has also emerged. Full article
(This article belongs to the Special Issue Blockchain and Cryptocurrencies)
Open AccessArticle
Can Higher Capital Discipline Bank Risk: Evidence from a Meta-Analysis
J. Risk Financial Manag. 2019, 12(3), 134; https://doi.org/10.3390/jrfm12030134 (registering DOI)
Received: 23 July 2019 / Revised: 15 August 2019 / Accepted: 15 August 2019 / Published: 20 August 2019
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Abstract
Capital regulation has been among the most important tools for regulators to maintain the credibility and stability of the financial systems. However, the question whether higher capital induce banks to take lower risk remains unanswered. This paper examines the effect of capital on [...] Read more.
Capital regulation has been among the most important tools for regulators to maintain the credibility and stability of the financial systems. However, the question whether higher capital induce banks to take lower risk remains unanswered. This paper examines the effect of capital on bank risk employing a meta-analysis approach, which considers a wide range of empirical papers from 1990 to 2018. We found that the negative effect of bank capital on bank risk, which implies the discipline role of bank capital, is more likely to be reported. However, the reported results are suffered from the publication bias due to the preference for significant estimates and favored results. Our study also shows that the differences in the previous studies’ conclusions are primarily caused by the differences in the study design, particularly the risk and capital measurements; the model specification such as the concern for the dynamic of bank risk behaviors, the endogeneity of the capital and unobserved time fixed effects; along with and the sample characteristics such as the sample size, and whether banks are bank holding companies or located in high-income countries. Full article
(This article belongs to the Special Issue Commercial Banking)
Open AccessArticle
FOMC Forecasts: Are They Useful for Understanding Monetary Policy?
J. Risk Financial Manag. 2019, 12(3), 133; https://doi.org/10.3390/jrfm12030133
Received: 6 June 2019 / Revised: 29 July 2019 / Accepted: 3 August 2019 / Published: 11 August 2019
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Abstract
Monetary policy is forward looking and, in its pursuit of transparency, it communicates its economic projections to the public at large. As a result, there is interest in whether these projections are credible. We argue that central to that credibility is the public’s [...] Read more.
Monetary policy is forward looking and, in its pursuit of transparency, it communicates its economic projections to the public at large. As a result, there is interest in whether these projections are credible. We argue that central to that credibility is the public’s ability to replicate the FOMC’s projections using publicly available data only. In other words, is it possible to anticipate, reliably and independently, what the FOMC will anticipate for the federal funds rate? To address this question, we assemble FOMC projections from 1992 to 2017; examine their statistical properties; postulate models to predict FOMC projections; and estimate the parameters of these models. We are not arguing that the FOMC determines their projections using these models. Rather, these equations are the ones that the public could use to forecast FOMC forecasts and to anticipate interest-rate decisions. Full article
(This article belongs to the Section Banking and Finance)
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Open AccessArticle
What Coins Lead in the Cryptocurrency Market: Using Copula and Neural Networks Models
J. Risk Financial Manag. 2019, 12(3), 132; https://doi.org/10.3390/jrfm12030132
Received: 10 July 2019 / Revised: 31 July 2019 / Accepted: 5 August 2019 / Published: 8 August 2019
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Abstract
Exploring dependence structures between financial time series has been important within a wide range of applications. The main aim of this paper is to examine dependence relationships among five well-known cryptocurrencies—Bitcoin, Ethereum, Litecoin, Ripple, and Stella—by a copula directional dependence (CDD). By employing [...] Read more.
Exploring dependence structures between financial time series has been important within a wide range of applications. The main aim of this paper is to examine dependence relationships among five well-known cryptocurrencies—Bitcoin, Ethereum, Litecoin, Ripple, and Stella—by a copula directional dependence (CDD). By employing a neural network autoregression model to avoid the serial dependence in each individual cryptocurrency, we generate residuals of the fitted models with time series of daily log-returns in percentage of the five cryptocurrencies and then we apply a Gaussian copula marginal beta regression model to the residuals to explore the CDD. The results show that the CDD from Bitcoin to Litecoin is highest among all ordered directional dependencies and the CDDs from Ethereum to the other four cryptocurrencies are relatively higher than the CDDs to Ethereum from those cryptocurrencies. This finding implies that the return shocks of Bitcoin have the most effect on Litecoin and the return shocks of Ethereum relatively influence the shocks on the other four cryptocurrencies instead of being affected by them. This allows investors to build the market-timing strategies by observing the directional flow of return shocks among cryptocurrencies. Full article
(This article belongs to the Special Issue Machine Learning Applications in Finance)
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Open AccessArticle
Role of Bank Regulation on Bank Performance: Evidence from Asia-Pacific Commercial Banks
J. Risk Financial Manag. 2019, 12(3), 131; https://doi.org/10.3390/jrfm12030131
Received: 30 June 2019 / Revised: 1 August 2019 / Accepted: 3 August 2019 / Published: 7 August 2019
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Abstract
The banking industry is an essential financial intermediary, thus the efficient operation of banks is vital for economic development and social welfare. However, the 2008 global financial crisis triggered a reconsideration of the banking systems, as well as the role of government intervention. [...] Read more.
The banking industry is an essential financial intermediary, thus the efficient operation of banks is vital for economic development and social welfare. However, the 2008 global financial crisis triggered a reconsideration of the banking systems, as well as the role of government intervention. The literature has paid little attention to the banking industry in the Asia-Pacific region in the context of bank efficiency. This study employs double bootstrap data envelopment analysis to measure bank efficiency and examine the relationship between regulation, supervision, and state ownership in commercial banks in the Asia-Pacific region for the period 2005 to 2014. Our results indicate that excluding off-balance sheet activities in efficiency estimations lead to underestimating of the pure technical efficiency, while overestimating the scale efficiency of banks in the Asia-Pacific region. Cross-country comparisons reveal that Australian banks exhibit the highest levels of technical efficiency, while Indonesian banks exhibit the lowest average. Our bootstrap regression results suggest that bank regulation and supervision are positively related to bank technical efficiency, while state ownership is not significantly related to bank efficiency. Furthermore, our findings show that tighter regulation and supervision are significantly related to higher efficiency for small and large-sized banks. Full article
(This article belongs to the Special Issue Commercial Banking)
Open AccessArticle
Control-Enhancing Mechanisms and Earnings Management: Empirical Evidence from Pakistan
J. Risk Financial Manag. 2019, 12(3), 130; https://doi.org/10.3390/jrfm12030130
Received: 15 May 2019 / Revised: 6 July 2019 / Accepted: 21 July 2019 / Published: 7 August 2019
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Abstract
Separation of ownership and control plays a significant role in determining the agency cost, and there are many consequences of this agency problem. The control-enhancing mechanisms enhance control of controlling shareholders who expropriate small shareholders. Controlling shareholders are different in different countries; majorly, [...] Read more.
Separation of ownership and control plays a significant role in determining the agency cost, and there are many consequences of this agency problem. The control-enhancing mechanisms enhance control of controlling shareholders who expropriate small shareholders. Controlling shareholders are different in different countries; majorly, family firms are controlling firms in Pakistani context. The use of control-enhancing mechanism is rampant in emerging economies, and even some developed countries, related research especially in Pakistan requires evidence. This study exhibits a pooled cross-sectional analysis of listed companies in Pakistan between 2005 and 2016. In this research, we have examined the influence of control-enhancing mechanisms on firms’ earnings management and which mechanism (pyramid control, multiple control chains, and cross-holding control) is significantly influencing the earnings management of firms. We have analyzed both types of earnings manipulation techniques (accrual and real earning management). Our results explicate that the pyramid control and multiple control chain mechanisms are significantly positively related to the accruals earning management and real earnings management, unveiling that firms with these controls manipulate earnings with discretionary accruals as well as with real activity manipulation. Real activity manipulation enhances firms to overproduce the inventory (decreasing the unit price) and to reduce the discretionary expenses (increasing the reported earnings). Full article
(This article belongs to the Section Financial Markets)
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Open AccessArticle
Splitting Credit Risk into Systemic, Sectorial and Idiosyncratic Components
J. Risk Financial Manag. 2019, 12(3), 129; https://doi.org/10.3390/jrfm12030129
Received: 27 June 2019 / Revised: 30 July 2019 / Accepted: 2 August 2019 / Published: 6 August 2019
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Abstract
We provide a methodology to estimate a global credit risk factor from credit default swap (CDS) spreads that can be very useful for risk management. The global risk factor (GRF) reproduces quite well the different episodes that have affected the credit market over [...] Read more.
We provide a methodology to estimate a global credit risk factor from credit default swap (CDS) spreads that can be very useful for risk management. The global risk factor (GRF) reproduces quite well the different episodes that have affected the credit market over the sample period. It is highly correlated with standard credit indices, but it contains much higher explanatory power for fluctuations in CDS spreads across sectors than the credit indices themselves. The additional information content over iTraxx seems to be related to some financial interest rates. We first use the estimated GRF to analyze the extent to which the eleven sectors we consider are systemic. After that, we use it to split the credit risk of individual firms into systemic, sectorial, and idiosyncratic components, and we perform some analyses to test that the estimated idiosyncratic components are actually firm-specific. The systemic and sectorial components explain around 65% of credit risk in the European industrial and financial sectors and 50% in the North American sectors, while 35% and 50% of risk, respectively, is of an idiosyncratic nature. Thus, there is a significant margin for portfolio diversification. We also show that our decomposition allows us to identify those firms whose credit would be harder to hedge. We end up analyzing the relationship between the estimated components of risk and some synthetic risk factors, in order to learn about the different nature of the credit risk components. Full article
(This article belongs to the Section Financial Markets)
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Open AccessEditorial
Currency Crisis: Are There Signals to Read?
J. Risk Financial Manag. 2019, 12(3), 128; https://doi.org/10.3390/jrfm12030128
Received: 18 July 2019 / Accepted: 23 July 2019 / Published: 2 August 2019
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Abstract
Financial crisis is nothing new in the annals of history of the capitalistic path of economic development; it is a part of the business cycle. The theoretical basis is well entrenched in the concept of ‘Keynesian Cross’. The tale of crisis, dating back [...] Read more.
Financial crisis is nothing new in the annals of history of the capitalistic path of economic development; it is a part of the business cycle. The theoretical basis is well entrenched in the concept of ‘Keynesian Cross’. The tale of crisis, dating back centuries, has taken a new turn with the call for more globalization—liberalize trade and open up the financial sector. This has made many nations vulnerable to crises that are likely to be repeated, perhaps frequently. Based on recent experience, warning signs can be read from the dollar-centric exchange rate, the mainstay for the stability of the current global financial system. To a careful observer, fatigue in the system cannot be overlooked. Full article
(This article belongs to the Special Issue Currency Crisis)
Open AccessArticle
A Nontechnical Guide on Optimal Incentives for Islamic Insurance Operators
J. Risk Financial Manag. 2019, 12(3), 127; https://doi.org/10.3390/jrfm12030127
Received: 25 May 2019 / Revised: 22 July 2019 / Accepted: 23 July 2019 / Published: 25 July 2019
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Abstract
The takaful industry is searching for an optimal model for Islamic insurance operation, which has turned out to be a challenging task. This paper translates the abstract scientific knowledge accumulated in the optimal contracting literature into a simple, nontechnical, analytical framework to analyze [...] Read more.
The takaful industry is searching for an optimal model for Islamic insurance operation, which has turned out to be a challenging task. This paper translates the abstract scientific knowledge accumulated in the optimal contracting literature into a simple, nontechnical, analytical framework to analyze alternative business models which could be used by regulators to align the best interest of shareholders and policyholders in the takaful industry. This paper shows that the wakalahsurplus-sharing hybrid serves as the optimal structure for takaful operation; in the presence of Akerlof’s (1982) gift-exchange, the wakalah fee reduces the adverse selection problem; and the wakalah fee could be used to protect infant takaful operators. Full article
(This article belongs to the Special Issue Islamic Finance)
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Open AccessFeature PaperArticle
Regulation of the Crypto-Economy: Managing Risks, Challenges, and Regulatory Uncertainty
J. Risk Financial Manag. 2019, 12(3), 126; https://doi.org/10.3390/jrfm12030126
Received: 9 May 2019 / Revised: 12 July 2019 / Accepted: 12 July 2019 / Published: 24 July 2019
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Abstract
Distributed ledger technology, also known as the blockchain, is gaining traction globally. Blockchain offers a secure validation mechanism and decentralized mass collaboration. Cryptocurrencies make use of this technology as a new asset class for investors worldwide. Cryptocurrencies are being used by companies to [...] Read more.
Distributed ledger technology, also known as the blockchain, is gaining traction globally. Blockchain offers a secure validation mechanism and decentralized mass collaboration. Cryptocurrencies make use of this technology as a new asset class for investors worldwide. Cryptocurrencies are being used by companies to raise capital via initial coin offerings (ICOs). The substantial inflow of unregulated capital into a transactional and transnational industry has aroused interest from not just investors, but also national securities and monetary regulatory agencies. In this paper, we review the Security and Exchange Commission’s initial statements and subsequent pronouncements on ICO’s to illustrate the potential problems with applying an older legal framework to an ever-evolving ecosystem. Recognizing the inability of enforcement within existing regulatory frameworks, we discuss the importance of regulation of the crypto asset class and internal collaboration between government agencies and developers in the establishment of an ecosystem that integrates investor protection and investments. Full article
(This article belongs to the Special Issue Financing and Facilitating Entrepreneurship)
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Open AccessArticle
The Role of the Federal Reserve in the U.S. Housing Crisis: A VAR Analysis with Endogenous Structural Breaks
J. Risk Financial Manag. 2019, 12(3), 125; https://doi.org/10.3390/jrfm12030125
Received: 24 June 2019 / Revised: 18 July 2019 / Accepted: 19 July 2019 / Published: 23 July 2019
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Abstract
This paper reexamines the role of the Federal Reserve in triggering the recent housing crisis. Specifically, we explore if the relationship between the federal funds rate and the housing variables underwent structural changes in the wake of the housing crisis. Using quarterly data [...] Read more.
This paper reexamines the role of the Federal Reserve in triggering the recent housing crisis. Specifically, we explore if the relationship between the federal funds rate and the housing variables underwent structural changes in the wake of the housing crisis. Using quarterly data spanning 1960–2017, we estimate a VAR model involving federal funds rate, real GDP growth and a housing variable (captured by house price inflation or residential investment share or housing starts) and conduct time series analysis for the pre- and post-crisis periods. While previous studies mostly set break-dates based on events known a priori to split the full sample to subsamples, we endogenously determine structural break points occurring at multiple unknown dates. Our Granger causality analysis indicates that the federal funds rate did not cause house price inflation, although it caused residential investment share and housing starts in the pre-crisis period. In the post-crisis period, the real GDP growth caused residential investment and housing starts while house price inflation had a momentum of its own. Our impulse response and forecast error variance decomposition analysis reinforce these results. Overall, our findings suggest that housing volume fluctuates more than house prices over the business cycle. Full article
(This article belongs to the Special Issue Housing Market Bubbles, Credit and Crashes)
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Open AccessArticle
Empirical Credit Risk Ratings of Individual Corporate Bonds and Derivation of Term Structures of Default Probabilities
J. Risk Financial Manag. 2019, 12(3), 124; https://doi.org/10.3390/jrfm12030124
Received: 19 June 2019 / Revised: 16 July 2019 / Accepted: 18 July 2019 / Published: 23 July 2019
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Abstract
Undoubtedly, it is important to have an empirically effective credit risk rating method for decision-making in the financial industry, business, and even government. In our approach, for each corporate bond (CB) and its issuer, we first propose a credit risk rating (Crisk-rating) system [...] Read more.
Undoubtedly, it is important to have an empirically effective credit risk rating method for decision-making in the financial industry, business, and even government. In our approach, for each corporate bond (CB) and its issuer, we first propose a credit risk rating (Crisk-rating) system with rating intervals for the standardized credit risk price spread (S-CRiPS) measure presented by Kariya et al. (2015), where credit information is based on the CRiPS measure, which is the difference between the CB price and its government bond (GB)-equivalent CB price. Second, for each Crisk-homogeneous class obtained through the Crisk-rating system, a term structure of default probability (TSDP) is derived via the CB-pricing model proposed in Kariya (2013), which transforms the Crisk level of each class into a default probability, showing the default likelihood over a future time horizon, in which 1545 Japanese CB prices, as of August 2010, are analyzed. To carry it out, the cross-sectional model of pricing government bonds with high empirical performance is required to get high-precision CRiPS and S-CRiPS measures. The effectiveness of our GB model and the S-CRiPS measure have been demonstrated with Japanese and United States GB prices in our papers and with an evaluation of the credit risk of the GBs of five countries in the EU and CBs issued by US energy firms in Kariya et al. (2016a, b). Our Crisk-rating system with rating intervals is tested with the distribution of the ratings of the 1545 CBs, a specific agency’s credit rating, and the ratings of groups obtained via a three-stage cluster analysis. Full article
(This article belongs to the Special Issue Quantitative Risk)
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Open AccessArticle
Some Dynamic and Steady-State Properties of Threshold Auto-Regressions with Applications to Stationarity and Local Explosivity
J. Risk Financial Manag. 2019, 12(3), 123; https://doi.org/10.3390/jrfm12030123
Received: 13 June 2019 / Revised: 17 July 2019 / Accepted: 18 July 2019 / Published: 22 July 2019
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Abstract
The purpose of this paper is to investigate the dynamics and steady-state properties of threshold autoregressive models with exogenous states that follow Markovian processes. Markovian processes are widely used in applied economics although their statistical properties have not been explored in detail. We [...] Read more.
The purpose of this paper is to investigate the dynamics and steady-state properties of threshold autoregressive models with exogenous states that follow Markovian processes. Markovian processes are widely used in applied economics although their statistical properties have not been explored in detail. We use characteristic functions to carry out the analysis, and this allows us to describe limiting distributions for processes not considered in the literature previously. We also calculate analytical expressions for some moments. Furthermore, we see that we can have locally explosive processes that are explosive in one regime whilst being strongly stationary overall. This is explored through simulation analysis, where we also show how the distribution changes when the explosive state becomes more frequent although the overall process remains stationary. In doing so, we are able to relate our analysis to asset prices which exhibit similar distributional properties. Full article
(This article belongs to the Special Issue Financial Econometrics)
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Open AccessArticle
Evidence of the Environmental Kuznets Curve: Unleashing the Opportunity of Industry 4.0 in Emerging Economies
J. Risk Financial Manag. 2019, 12(3), 122; https://doi.org/10.3390/jrfm12030122
Received: 4 July 2019 / Revised: 17 July 2019 / Accepted: 18 July 2019 / Published: 20 July 2019
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Abstract
This study aims to investigate the relationship of economic development, measured as economic growth, energy use, trade and foreign direct investment, on the one hand, and environmental degradation (carbon dioxide (hereafter CO2) emissions), on the other hand, in eleven emerging Eastern European and [...] Read more.
This study aims to investigate the relationship of economic development, measured as economic growth, energy use, trade and foreign direct investment, on the one hand, and environmental degradation (carbon dioxide (hereafter CO2) emissions), on the other hand, in eleven emerging Eastern European and Central Asian countries during the period of 1990 to 2014. The empirical results give an evidence of a carbon emission Kuznets curve for these emerging economies. The current income level indicates that not every country has reached the turning point for CO2 emissions reductions. Income elasticities for CO2 are positive for all eleven countries. The paper concludes that within the group, Ukraine and Kazakhstan have the most sensitive change in economic growth in respect to CO2. In addition, it concludes that there is a negative effect of total energy consumption on environment as such consumption increases CO2 emissions. The results also show a positive effect of foreign direct investment (FDI) on CO2 emissions in Eastern European and Central Asian countries. It is expected that the innovative transition to a low-carbon economy offers great opportunities for economic growth and job creation. Technological leadership (the initiative Industry 4.0) should be accompanied by the development and introduction of new technologies throughout Eastern European and Central Asian countries, hence, the paradigm of “sustainable development” should be considered as fatal. Furthermore, Eastern European and Central Asian economies should consider the experience of policy making implications made by other developing countries in gaining sustainable growth. Econometric analyses prove the existence of different impact on energy consumption of the ICT sector, which plays a key supporting role for intelligent manufacturing. Thus, there is a need for further investigations of the relationship between technology use and CO2 emissions. Full article
(This article belongs to the Special Issue Entrepreneurial Finance at the Dawn of Industry 4.0)
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Open AccessArticle
Bank Interest Rate Margin, Portfolio Composition and Institutional Constraints
J. Risk Financial Manag. 2019, 12(3), 121; https://doi.org/10.3390/jrfm12030121
Received: 4 June 2019 / Revised: 15 July 2019 / Accepted: 16 July 2019 / Published: 18 July 2019
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Abstract
This study empirically examines how the bank specific factors, macro-economic, and institutional variables impact interest margins in China’s banking sector. A panel data analysis of bank data for the period 1988–2015 was carried out. We found a significant association between credit quality, risk [...] Read more.
This study empirically examines how the bank specific factors, macro-economic, and institutional variables impact interest margins in China’s banking sector. A panel data analysis of bank data for the period 1988–2015 was carried out. We found a significant association between credit quality, risk aversion, liquidity risk, and the proportion of corporate and industrial loans and the adjusted interest spread (AIS). GDP growth rate, inflation, and the proportion of national savings to the GDP were found to have significant association with the AIS. Furthermore, institutional variables were found to have a significant moderating effect on the AIS. We contribute to the literature by examining a unique context and a more accurate measure of bank interest margin not used in prior studies. Full article
(This article belongs to the Section Banking and Finance)
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Open AccessArticle
The Good and Bad News about the New Liquidity Rules of Basel III in Islamic Banking of Malaysia
J. Risk Financial Manag. 2019, 12(3), 120; https://doi.org/10.3390/jrfm12030120
Received: 6 June 2019 / Revised: 7 July 2019 / Accepted: 15 July 2019 / Published: 17 July 2019
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Abstract
How has Basel III (Bank for International Settlements), regarding the computation, measurement, and management of the liquidity coverage ratio (LCR), vitalized the Islamic banking sector in emerging economies? Vice versa, what is the Islamic banking sector’s capacity to respond in embracing Basel III? [...] Read more.
How has Basel III (Bank for International Settlements), regarding the computation, measurement, and management of the liquidity coverage ratio (LCR), vitalized the Islamic banking sector in emerging economies? Vice versa, what is the Islamic banking sector’s capacity to respond in embracing Basel III? This study aims to review the current issues faced by a bank as it discusses the current regulatory guidelines and operational challenges in implementing the system. Based on the implementation of LCR preliminary secondary data of Malaysian banks between 2010 and 2016, this study finds that the readiness of LCR system implementation in the Islamic banking industry is currently low because LCR is still relatively new for all financial institutions and vendors. There is a huge gap between the present system infrastructure of the banks and the LCR model requirements as defined by BNM (Bank Negara Malaysia) under Basel III. Nevertheless, this finding opens new horizons of understanding and practically offers further investigations for the whole banking sector in Malaysia. Thus, policy makers, regulators, and industry players should utilize a unique framework for Islamic banks when strategizing liquidity risk management. Full article
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Open AccessArticle
Dealing with Low Interest Rates in Life Insurance: An Analysis of Additional Reserves in the German Life Insurance Industry
J. Risk Financial Manag. 2019, 12(3), 119; https://doi.org/10.3390/jrfm12030119
Received: 15 June 2019 / Revised: 12 July 2019 / Accepted: 15 July 2019 / Published: 16 July 2019
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Abstract
Interest rates have been very low for several years, which is particularly challenging for life insurers. Since 2001, German life insurers have had to set an additional reserve due to low interest rates to ensure the protection of policyholders. However, the method introduced [...] Read more.
Interest rates have been very low for several years, which is particularly challenging for life insurers. Since 2001, German life insurers have had to set an additional reserve due to low interest rates to ensure the protection of policyholders. However, the method introduced at that time to calculate these reserves was criticized, therefore, the German Federal Ministry of Finance replaced it with a new approach. In this article, we investigated the effects of the different methods on a typical German life insurer in various future interest rate scenarios and from various perspectives. For this purpose, we modelled such a life insurer holistically, considered its asset liability management and projected its future development in different interest rate scenarios using simulation techniques. Taking into account dependencies between assets, liabilities and interest rates, we analyzed and discussed our results from the life insurer’s, equity holders’, policyholders’ and regulators’ perspectives. The results show that the new method eliminated the weaknesses of the previous one and seems to be a suitable alternative to determine the additional reserve. Full article
(This article belongs to the Section Risk)
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Open AccessArticle
Does Fiscal Decentralization Encourage Corruption in Local Governments? Evidence from Indonesia
J. Risk Financial Manag. 2019, 12(3), 118; https://doi.org/10.3390/jrfm12030118
Received: 26 June 2019 / Revised: 9 July 2019 / Accepted: 12 July 2019 / Published: 14 July 2019
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Abstract
This study examines the effects of fiscal decentralization on corruption by analyzing whether the degree of fiscal decentralization facilitates or mitigates the number of corruption cases in Indonesia’s local governments. The research utilizes a panel data model and a system Generalized Method of [...] Read more.
This study examines the effects of fiscal decentralization on corruption by analyzing whether the degree of fiscal decentralization facilitates or mitigates the number of corruption cases in Indonesia’s local governments. The research utilizes a panel data model and a system Generalized Method of Moments (GMM) estimator to assess the degree of fiscal decentralization on corruption in 19 provinces for the period between 2004 and 2014. The estimation results reveal that the degree of fiscal decentralization, both expenditure and tax revenue sides, drives a growing number of corruption cases in local governments. A lack of human capital capacity, low transparency and accountability, and a higher dependency on intergovernmental grants from the central government may worsen the adverse effects of corruption. Our results suggest that a more heterogeneous population and higher political stability mitigate the adverse effects of corruption. Furthermore, this is the first corruption study in Indonesia to create corruption measures from the number of corruption cases investigated by the Indonesia Corruption Eradication Commission as well as extensive, provincial-level government financial data. As a result of using these different datasets, this research advances existing empirical studies and makes policy recommendations for the local governments in Indonesia. Full article
(This article belongs to the Section Applied Economics and Finance)
Open AccessArticle
On Combining Evidence from Heteroskedasticity Robust Panel Unit Root Tests in Pooled Regressions
J. Risk Financial Manag. 2019, 12(3), 117; https://doi.org/10.3390/jrfm12030117
Received: 17 May 2019 / Revised: 4 July 2019 / Accepted: 9 July 2019 / Published: 12 July 2019
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Abstract
Volatility break robust panel unit root tests (PURTs) recently proposed by Herwartz and Siedenburg (Computational Statistics & Data Analysis 2008, 53, 137–150) and Demetrescu and Hanck (Econometrics Letters 2012, 117, 10–13) have different performances under both the null and local alternatives. Common practice [...] Read more.
Volatility break robust panel unit root tests (PURTs) recently proposed by Herwartz and Siedenburg (Computational Statistics & Data Analysis 2008, 53, 137–150) and Demetrescu and Hanck (Econometrics Letters 2012, 117, 10–13) have different performances under both the null and local alternatives. Common practice in empirical research is to apply multiple tests if none is uniformly superior. We show that this approach tends to produce contradictory evidence for the tests considered, making it unclear whether to reject the null. To address this problem, we advocate a combined testing procedure. Simulation evidence shows that the combined test has good size control and closely tracks the more powerful test. An empirical application reinvestigates whether there is a unit root in OECD inflation rates. We find evidence that inflation is stationary for long observation periods, but we cannot reject nonstationarity in most subsets of countries for the last three decades. Full article
(This article belongs to the Special Issue Panel Data and Factor Models in Empirical Finance)
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Open AccessArticle
Modeling and Forecasting Realized Portfolio Diversification Benefits
J. Risk Financial Manag. 2019, 12(3), 116; https://doi.org/10.3390/jrfm12030116
Received: 17 May 2019 / Revised: 5 July 2019 / Accepted: 9 July 2019 / Published: 11 July 2019
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Abstract
For a financial portfolio, we suggest a realized measure of diversification benefits, which is based on intraday high-frequency returns. Our measure quantifies volatility reduction, which could be achieved by including an additional asset in the portfolio. In order to make our approach feasible [...] Read more.
For a financial portfolio, we suggest a realized measure of diversification benefits, which is based on intraday high-frequency returns. Our measure quantifies volatility reduction, which could be achieved by including an additional asset in the portfolio. In order to make our approach feasible for investors, we also provide time series modeling of both the realized diversification measure and realized portfolio weight. The performance of our approach is evaluated in-sample and out-of-sample. We find out that our approach is helpful for the purpose of portfolio variance minimization. Full article
(This article belongs to the Special Issue Panel Data and Factor Models in Empirical Finance)
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Open AccessCommunication
Contagion Effect in Cryptocurrency Market
J. Risk Financial Manag. 2019, 12(3), 115; https://doi.org/10.3390/jrfm12030115
Received: 11 June 2019 / Revised: 7 July 2019 / Accepted: 8 July 2019 / Published: 10 July 2019
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Abstract
The rapid development of cryptocurrencies has drawn attention to this particular market, with investors trying to understand its behaviour and researchers trying to explain it. The evolution of cryptocurrencies’ prices showed a kind of bubble and a crash at the end of 2017. [...] Read more.
The rapid development of cryptocurrencies has drawn attention to this particular market, with investors trying to understand its behaviour and researchers trying to explain it. The evolution of cryptocurrencies’ prices showed a kind of bubble and a crash at the end of 2017. Based on this event, and on the fact that Bitcoin is the most recognized cryptocurrency, we propose to evaluate the contagion effect between Bitcoin and other major cryptocurrencies. Using the Detrended Cross-Correlation Analysis correlation coefficient (ΔρDCCA) and comparing the period after and before the crash, we found evidence of a contagion effect, with this particular market being more integrated now than in the past—something that should be taken into account by current and potential investors. Full article
(This article belongs to the Special Issue Blockchain and Cryptocurrencies)
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Open AccessArticle
The Role of Governance and Bank Funding in the Determination of Cornerstone Allocations in Chinese Equity Offers
J. Risk Financial Manag. 2019, 12(3), 114; https://doi.org/10.3390/jrfm12030114
Received: 10 June 2019 / Revised: 25 June 2019 / Accepted: 27 June 2019 / Published: 2 July 2019
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Abstract
This article investigates the causal factors underlying cornerstone investor (CI) participation in initial public offerings in China’s offshore Hong Kong market. Prospectus-based declarations on such allocations suggest that CI undertakings offer strong certification effects. Entrepreneurs planning for IPO thus have a material incentive [...] Read more.
This article investigates the causal factors underlying cornerstone investor (CI) participation in initial public offerings in China’s offshore Hong Kong market. Prospectus-based declarations on such allocations suggest that CI undertakings offer strong certification effects. Entrepreneurs planning for IPO thus have a material incentive to court CIs. The present analysis reveals that a firm’s pre-IPO financials and governance attributes strongly correlate with success in this field. Specifically, CI participation is greater in issuers with established long-term loan positions. Firms housing younger CEOs and a greater number of family-connected board officers also generate more CI interest. In contrast, the fraction of independent directors and women on boards exert minimal effect. However, further analysis reveals that greater independent director presence strongly supports CI participation in family-centric entities, but imparts little to no effect on such investment in either state-run or non-family-controlled private issuers. Additionally, an issuer’s political connections galvanize CI participation. Moreover, the present study highlights the importance of family resources (in non-state sponsored entities) and political connections (in state-held firms) in drawing-in CI involvement. Given the spread of CI arrangements to other primary market settings, the present enterprise also offers guidance on anchor investment elsewhere. Full article
(This article belongs to the Special Issue Financing and Facilitating Entrepreneurship)
Open AccessArticle
VIX Futures as a Market Timing Indicator
J. Risk Financial Manag. 2019, 12(3), 113; https://doi.org/10.3390/jrfm12030113
Received: 10 June 2019 / Revised: 24 June 2019 / Accepted: 28 June 2019 / Published: 1 July 2019
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Abstract
Our work relates to the literature supporting that the VIX also mirrors investor sentiment and, thus, contains useful information regarding future S&P500 returns. The objective of this empirical analysis is to verify if the shape of the volatility futures term structure has signaling [...] Read more.
Our work relates to the literature supporting that the VIX also mirrors investor sentiment and, thus, contains useful information regarding future S&P500 returns. The objective of this empirical analysis is to verify if the shape of the volatility futures term structure has signaling effects regarding future equity price movements, as several investors believe. Our findings generally support the hypothesis that the VIX term structure can be employed as a contrarian market timing indicator. The empirical analysis of this study has important practical implications for financial market practitioners, as it shows that they can use the VIX futures term structure not only as a proxy of market expectations on forward volatility, but also as a stock market timing tool. Full article
(This article belongs to the Section Financial Markets)
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Open AccessArticle
Cross-Border Venture Capital Investments: What Is the Role of Public Policy?
J. Risk Financial Manag. 2019, 12(3), 112; https://doi.org/10.3390/jrfm12030112
Received: 3 June 2019 / Revised: 25 June 2019 / Accepted: 26 June 2019 / Published: 1 July 2019
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Abstract
(1) Background: Cross-border venture capital (VC) investments play an important role in the scaling up of high-growth companies. However, policymakers worry that foreign VC investments transfer the majority of economic activity to the investor country. On the one hand, start-ups welcome the foreign [...] Read more.
(1) Background: Cross-border venture capital (VC) investments play an important role in the scaling up of high-growth companies. However, policymakers worry that foreign VC investments transfer the majority of economic activity to the investor country. On the one hand, start-ups welcome the foreign capital, expertise, and networks that accompany cross-border investments. On the other hand, policymakers are concerned that cross-border investments predominantly benefit foreign economies and fail to develop the local entrepreneurial ecosystem. This paper describes a framework for how policymakers can develop a set of policies toward cross-border VC investments. (2) Methods: The paper examines available data and trends about the role of cross-border investing, focusing on Europe, Israel, and Canada. Then, the paper explains the underlying economic challenges and develops a policy framework. (3) Results: The analysis shows that in addition to policies that aim to attract foreign investors, there are also important policies for the development of the domestic VC market. The analysis encompasses policies that are both financial and non-financial in nature. (4) Conclusions: A core insight for policymakers is to retain a balance of initiatives, attracting foreign investors while simultaneously making sure to strengthen the country’s domestic VC industry and innovation ecosystem. The mix of policies will adjust as the domestic ecosystem matures. Full article
(This article belongs to the Special Issue Venture Capital and Private Equity)
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Open AccessArticle
Analysis of a Global Futures Trend-Following Strategy
J. Risk Financial Manag. 2019, 12(3), 111; https://doi.org/10.3390/jrfm12030111
Received: 9 June 2019 / Revised: 22 June 2019 / Accepted: 25 June 2019 / Published: 29 June 2019
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Abstract
Systematic traders employ algorithmic strategies to manage their investments. As a result of the deterministic nature of such strategies, it is possible to determine their exact responses to any conceivable set of market conditions. Consequently, sensitivity analysis can be conducted to systematically uncover [...] Read more.
Systematic traders employ algorithmic strategies to manage their investments. As a result of the deterministic nature of such strategies, it is possible to determine their exact responses to any conceivable set of market conditions. Consequently, sensitivity analysis can be conducted to systematically uncover undesirable strategy behavior and enhance strategy robustness by adding controls to reduce exposure during periods of poor performance/unfavorable market conditions, or to increase exposure during periods of strong performance/favorable market conditions. In this study, we formulate both a simple systematic trend-following strategy (i.e., trading model) to simulate investment decisions and a market model to simulate the evolution of instrument prices. We then map the relationship between market model parameters under various conditions and strategy performance. We focus, in particular, on identifying the performance impact of changes in both serial dependence in price variability and changes in the trend. The long-range serial dependence of the true range worsens performance of the simple classic trend-following strategy. During periods of strong performance, the dispersion of trading outcomes increases significantly as long-range serial dependence increases. Full article
(This article belongs to the Section Financial Markets)
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Open AccessArticle
Sectoral Analysis of Factors Influencing Dividend Policy: Case of an Emerging Financial Market
J. Risk Financial Manag. 2019, 12(3), 110; https://doi.org/10.3390/jrfm12030110
Received: 27 May 2019 / Revised: 20 June 2019 / Accepted: 22 June 2019 / Published: 26 June 2019
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Abstract
This study aims to determine whether a firm’s dividends are influenced by the sector to which it belongs. This paper also examines the explanatory factors for dividends across individual sectors in India. This longitudinal study uses balanced data consisting of companies listed on [...] Read more.
This study aims to determine whether a firm’s dividends are influenced by the sector to which it belongs. This paper also examines the explanatory factors for dividends across individual sectors in India. This longitudinal study uses balanced data consisting of companies listed on the National Stock Exchange (NSE) of India for 12 years—from 2006 to 2017. Pooled ordinary least squares (POLSs) and fixed effects panel models are used in our estimation. We find that size, profitability, and interest coverage ratios have a significant positive relation to dividend policy. Furthermore, business risk and debt reveal a significantly negative relation with dividends. The findings on profitability support the free cash flow hypothesis for India. However, we also found that Indian companies prefer to follow a stable dividend policy. As a result of this, even firms with higher growth opportunities and lower cash flows continue to pay dividends. We also find evidence that dividend policies vary significantly across industrial sectors in India. The results of this study can be used by financial managers and policymakers in order to make appropriate dividend decisions. They can also help investors make portfolio selection decisions based on sectoral dividend paying behavior. Full article
(This article belongs to the Special Issue Corporate Finance)
Open AccessArticle
On Tuning Parameter Selection in Model Selection and Model Averaging: A Monte Carlo Study
J. Risk Financial Manag. 2019, 12(3), 109; https://doi.org/10.3390/jrfm12030109
Received: 24 May 2019 / Revised: 17 June 2019 / Accepted: 24 June 2019 / Published: 26 June 2019
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Abstract
Model selection and model averaging are popular approaches for handling modeling uncertainties. The existing literature offers a unified framework for variable selection via penalized likelihood and the tuning parameter selection is vital for consistent selection and optimal estimation. Few studies have explored the [...] Read more.
Model selection and model averaging are popular approaches for handling modeling uncertainties. The existing literature offers a unified framework for variable selection via penalized likelihood and the tuning parameter selection is vital for consistent selection and optimal estimation. Few studies have explored the finite sample performances of the class of ordinary least squares (OLS) post-selection estimators with the tuning parameter determined by different selection approaches. We aim to supplement the literature by studying the class of OLS post-selection estimators. Inspired by the shrinkage averaging estimator (SAE) and the Mallows model averaging (MMA) estimator, we further propose a shrinkage MMA (SMMA) estimator for averaging high-dimensional sparse models. Our Monte Carlo design features an expanding sparse parameter space and further considers the effect of the effective sample size and the degree of model sparsity on the finite sample performances of estimators. We find that the OLS post-smoothly clipped absolute deviation (SCAD) estimator with the tuning parameter selected by the Bayesian information criterion (BIC) in finite sample outperforms most penalized estimators and that the SMMA performs better when averaging high-dimensional sparse models. Full article
(This article belongs to the Special Issue Financial Econometrics)
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Open AccessArticle
The Outperformance Probability of Mutual Funds
J. Risk Financial Manag. 2019, 12(3), 108; https://doi.org/10.3390/jrfm12030108
Received: 5 May 2019 / Revised: 17 June 2019 / Accepted: 19 June 2019 / Published: 26 June 2019
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Abstract
We propose the outperformance probability as a new performance measure, which can be used in order to compare a strategy with a specified benchmark, and develop the basic statistical properties of its maximum-likelihood estimator in a Brownian-motion framework. The given results are used [...] Read more.
We propose the outperformance probability as a new performance measure, which can be used in order to compare a strategy with a specified benchmark, and develop the basic statistical properties of its maximum-likelihood estimator in a Brownian-motion framework. The given results are used to investigate the question of whether mutual funds are able to beat the S&P 500 or the Russell 1000. Most mutual funds that are taken into consideration are, in fact, able to beat the market. We argue that one should refer to differential returns when comparing a strategy with a given benchmark and not compare both the strategy and the benchmark with the money-market account. This explains why mutual funds often appear to underperform the market, but this conclusion is fallacious. Full article
(This article belongs to the Special Issue Risk Analysis and Portfolio Modelling)
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Open AccessArticle
CVaR Regression Based on the Relation between CVaR and Mixed-Quantile Quadrangles
J. Risk Financial Manag. 2019, 12(3), 107; https://doi.org/10.3390/jrfm12030107
Received: 16 May 2019 / Revised: 19 June 2019 / Accepted: 20 June 2019 / Published: 26 June 2019
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Abstract
A popular risk measure, conditional value-at-risk (CVaR), is called expected shortfall (ES) in financial applications. The research presented involved developing algorithms for the implementation of linear regression for estimating CVaR as a function of some factors. Such regression is called CVaR (superquantile) regression. [...] Read more.
A popular risk measure, conditional value-at-risk (CVaR), is called expected shortfall (ES) in financial applications. The research presented involved developing algorithms for the implementation of linear regression for estimating CVaR as a function of some factors. Such regression is called CVaR (superquantile) regression. The main statement of this paper is: CVaR linear regression can be reduced to minimizing the Rockafellar error function with linear programming. The theoretical basis for the analysis is established with the quadrangle theory of risk functions. We derived relationships between elements of CVaR quadrangle and mixed-quantile quadrangle for discrete distributions with equally probable atoms. The deviation in the CVaR quadrangle is an integral. We present two equivalent variants of discretization of this integral, which resulted in two sets of parameters for the mixed-quantile quadrangle. For the first set of parameters, the minimization of error from the CVaR quadrangle is equivalent to the minimization of the Rockafellar error from the mixed-quantile quadrangle. Alternatively, a two-stage procedure based on the decomposition theorem can be used for CVaR linear regression with both sets of parameters. This procedure is valid because the deviation in the mixed-quantile quadrangle (called mixed CVaR deviation) coincides with the deviation in the CVaR quadrangle for both sets of parameters. We illustrated theoretical results with a case study demonstrating the numerical efficiency of the suggested approach. The case study codes, data, and results are posted on the website. The case study was done with the Portfolio Safeguard (PSG) optimization package, which has precoded risk, deviation, and error functions for the considered quadrangles. Full article
(This article belongs to the Special Issue Mathematical Finance with Applications)
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Open AccessArticle
Bank Competition, Foreign Bank Entry, and Risk-Taking Behavior: Cross Country Evidence
J. Risk Financial Manag. 2019, 12(3), 106; https://doi.org/10.3390/jrfm12030106
Received: 14 May 2019 / Revised: 9 June 2019 / Accepted: 14 June 2019 / Published: 26 June 2019
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Abstract
This unique study examines the interactive role of bank competition and foreign bank entry in explaining the risk-taking of banks over the globe. We used cross-country data for the banking sector from 2000 to 2016. Using the pooled regression model and Two-stage Least [...] Read more.
This unique study examines the interactive role of bank competition and foreign bank entry in explaining the risk-taking of banks over the globe. We used cross-country data for the banking sector from 2000 to 2016. Using the pooled regression model and Two-stage Least Squares model (2SLS with Generalized Method of Moments GMM), we document that foreign bank entry decreases the risk-taking behavior of the banks to a certain level and exhibits an inverted U-shaped relation with financial stability. Furthermore, the joint effect of bank competition and foreign bank entry brings financial fragility because host banks tend to make risky investments due to undue competition induced by foreign bank entry. We support the competition–fragility hypothesis when foreign bank entry goes beyond a certain threshold. Our results also suggest that restrictions on bank activities and capital regulation stringency reduce the level of the risk factor. We also applied various robustness tests, which further confirm our mainstream results. Our findings have policy implications for foreign investors and regulatory authorities. Full article
(This article belongs to the Special Issue Commercial Banking)
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