Journal of Risk and Financial Management

17 pages, 236 KiB

Open AccessArticle

The Impact of Corporate Diversification and Financial Structure on Firm Performance: Evidence from South Asian Countries

by Rashid Mehmood, Ahmed Imran Hunjra and Muhammad Irfan Chani

J. Risk Financial Manag. 2019, 12(1), 49; https://doi.org/10.3390/jrfm12010049 - 25 Mar 2019

Cited by 59 | Viewed by 13546

Abstract

We examined the impact of corporate diversification and financial structure on the firms’ financial performance. We collected data from 520 manufacturing firms from Pakistan, India, Sri Lanka, and Bangladesh. We used panel data of 14 years from 2004–2017 to analyze the results. We [...] Read more.

We examined the impact of corporate diversification and financial structure on the firms’ financial performance. We collected data from 520 manufacturing firms from Pakistan, India, Sri Lanka, and Bangladesh. We used panel data of 14 years from 2004–2017 to analyze the results. We applied a two-step dynamic panel approach to analyze the hypotheses. We found that product diversification and geographic diversification significantly affected the firms’ financial performance. We further found that dividend policy and capital structure had a significant impact on the firm’s financial performance. Full article

(This article belongs to the Special Issue Trends in Emerging Markets Finance, Institutions and Money)

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34 pages, 1356 KiB

Open AccessReview

Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review

by Ruili Sun, Tiefeng Ma, Shuangzhe Liu and Milind Sathye

J. Risk Financial Manag. 2019, 12(1), 48; https://doi.org/10.3390/jrfm12010048 - 24 Mar 2019

Cited by 17 | Viewed by 8962

Abstract

The literature on portfolio selection and risk measurement has considerably advanced in recent years. The aim of the present paper is to trace the development of the literature and identify areas that require further research. This paper provides a literature review of the [...] Read more.

The literature on portfolio selection and risk measurement has considerably advanced in recent years. The aim of the present paper is to trace the development of the literature and identify areas that require further research. This paper provides a literature review of the characteristics of financial data, commonly used models of portfolio selection, and portfolio risk measurement. In the summary of the characteristics of financial data, we summarize the literature on fat tail and dependence characteristic of financial data. In the portfolio selection model part, we cover three models: mean-variance model, global minimum variance (GMV) model and factor model. In the portfolio risk measurement part, we first classify risk measurement methods into two categories: moment-based risk measurement and moment-based and quantile-based risk measurement. Moment-based risk measurement includes time-varying covariance matrix and shrinkage estimation, while moment-based and quantile-based risk measurement includes semi-variance, VaR and CVaR. Full article

(This article belongs to the Special Issue Review Papers for Journal of Risk and Financial Management (JRFM))

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14 pages, 265 KiB

Open AccessArticle

Herding in Smart-Beta Investment Products

by Eduard Krkoska and Klaus Reiner Schenk-Hoppé

J. Risk Financial Manag. 2019, 12(1), 47; https://doi.org/10.3390/jrfm12010047 - 21 Mar 2019

Cited by 11 | Viewed by 8042

Abstract

We highlight herding of investors as one major risk factor that is typically ignored in statistical approaches to portfolio modelling and risk management. Our survey focuses on smart-beta investing where such methods and investor herding seem particularly relevant but its negative effects have [...] Read more.

We highlight herding of investors as one major risk factor that is typically ignored in statistical approaches to portfolio modelling and risk management. Our survey focuses on smart-beta investing where such methods and investor herding seem particularly relevant but its negative effects have not yet come to the fore. We point out promising and novel approaches of modelling herding risk which merit empirical analysis. This financial economists’ perspective supplements the vast statistical exploration of implementing factor strategies. Full article

(This article belongs to the Special Issue Risk Analysis and Portfolio Modelling)

14 pages, 294 KiB

Open AccessArticle

Monetary Policy, Cash Flow and Corporate Investment: Empirical Evidence from Vietnam

by Linh My Tran, Chi Hong Mai, Phuoc Huu Le, Chi Linh Vu Bui, Linh Viet Phuong Nguyen and Toan Luu Duc Huynh

J. Risk Financial Manag. 2019, 12(1), 46; https://doi.org/10.3390/jrfm12010046 - 19 Mar 2019

Cited by 6 | Viewed by 6715

Abstract

This paper examines the relationships between macroscopic determinants (typically, monetary policies) and microscopic factors (mainly, cash flows and other controlling variables) on corporate investment. By employing system-GMM estimation for the 250 Vietnamese non-financial firms, the authors find that the expansionary monetary policy not [...] Read more.

This paper examines the relationships between macroscopic determinants (typically, monetary policies) and microscopic factors (mainly, cash flows and other controlling variables) on corporate investment. By employing system-GMM estimation for the 250 Vietnamese non-financial firms, the authors find that the expansionary monetary policy not only encourages the borrowing activities but also results in more corporate investment activities over the period from 2006 to 2016. Noticeably, the internal cash flow is also significant factor, which enhances the activities of corporate investment. Finally, there are differences between internal cash flow effects on corporate investments between two groups, divided by three theoretical criteria. To recapitulate, our implications highlight the importance of monetary policy stability for sustainable growth in corporate investment in Vietnam. Full article

(This article belongs to the Special Issue Currency Crisis)

21 pages, 1812 KiB

Open AccessArticle

News Co-Occurrences, Stock Return Correlations, and Portfolio Construction Implications

by Yi Tang, Yilu Zhou and Marshall Hong

J. Risk Financial Manag. 2019, 12(1), 45; https://doi.org/10.3390/jrfm12010045 - 19 Mar 2019

Cited by 4 | Viewed by 4199

Abstract

In this paper, we construct a sample of news co-occurrences using big data technologies. We show that stocks that co-occur in news articles are less risky, bigger, and more covered by financial analysts, and economically-connected stocks are mentioned more often in the same [...] Read more.

In this paper, we construct a sample of news co-occurrences using big data technologies. We show that stocks that co-occur in news articles are less risky, bigger, and more covered by financial analysts, and economically-connected stocks are mentioned more often in the same news articles. We decompose a news co-occurrence into an expected component and a shock component. We find that it is the shock component that arouses abnormal retail investor attention. The expected and shock components significantly predict return correlations 12 months into the future. Finally, a global minimum variance (GMV) portfolio with the covariance matrix augmented by the predictive power of news co-occurrences for future return correlations produces relatively superior performance compared to the benchmark GMV portfolio. Full article

(This article belongs to the Special Issue Empirical Asset Pricing)

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16 pages, 430 KiB

Open AccessArticle

Insomnia: An Important Antecedent Impacting Entrepreneurs’ Health

by Ludvig Levasseur, Jintong Tang and Masoud Karami

J. Risk Financial Manag. 2019, 12(1), 44; https://doi.org/10.3390/jrfm12010044 - 16 Mar 2019

Cited by 5 | Viewed by 5003

Abstract

Insomnia (and sleep deprivation) has an important impact on multiple outcomes such as individuals’ cognitive abilities, decision-making, and affect. In this paper, drawing from sleep research, we focus on entrepreneurs’ insomnia–health relationship and test a serial mediation model that considers entrepreneurs’ insomnia as [...] Read more.

Insomnia (and sleep deprivation) has an important impact on multiple outcomes such as individuals’ cognitive abilities, decision-making, and affect. In this paper, drawing from sleep research, we focus on entrepreneurs’ insomnia–health relationship and test a serial mediation model that considers entrepreneurs’ insomnia as an important predictor of their poor health. More specifically, we hypothesize that insomnia heightens entrepreneurs’ stress, which leads to increased negative affect, which ultimately undermines their health conditions. Using a sample of 152 Iranian entrepreneurs, we found support for our hypotheses as our results suggest that insomnia has a positive (and detrimental) effect on poor health (via more stress and negative affect). Contrary to research calls focused on stress reduction as one performance improvement mechanism, our results suggest sleep quality as a more effective mechanism for entrepreneurs to reduce their stress and to improve their health. Theoretical and practical implications, limitations, and directions for future research are also discussed. Full article

(This article belongs to the Special Issue Financing and Facilitating Entrepreneurship)

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14 pages, 407 KiB

Open AccessArticle

Effects of Global Oil Price on Exchange Rate, Trade Balance, and Reserves in Nigeria: A Frequency Domain Causality Approach

by D. O. Olayungbo

J. Risk Financial Manag. 2019, 12(1), 43; https://doi.org/10.3390/jrfm12010043 - 13 Mar 2019

Cited by 21 | Viewed by 6580

Abstract

This study investigated the relative Granger causal effects of oil price on exchange rate, trade balance, and foreign reserve in Nigeria. We used seasonally adjusted quarterly data from 1986Q4 to 2018Q1 to remove predictable changes in the series. Given the non-stationarity of our [...] Read more.

This study investigated the relative Granger causal effects of oil price on exchange rate, trade balance, and foreign reserve in Nigeria. We used seasonally adjusted quarterly data from 1986Q4 to 2018Q1 to remove predictable changes in the series. Given the non-stationarity of our variables, we found cointegration to exist only between oil price and foreign reserve. The presence of cointegration implied the existence of long run relationship between the variables. The Granger causality result showed that oil price strongly Granger caused foreign reserve in the short period. However, no Granger causal relationships were found between oil price and trade balance and for oil price and exchange rate. The implication of the result is that Nigerian government should not rely solely on oil price to sustain her reserve but to diversify the economy towards non-resource production and export for foreign exchange generation. Full article

(This article belongs to the Special Issue Applied Econometrics)

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27 pages, 1155 KiB

Open AccessArticle

Determining Distribution for the Quotients of Dependent and Independent Random Variables by Using Copulas

by Sel Ly, Kim-Hung Pho, Sal Ly and Wing-Keung Wong

J. Risk Financial Manag. 2019, 12(1), 42; https://doi.org/10.3390/jrfm12010042 - 12 Mar 2019

Cited by 20 | Viewed by 4169

Abstract

Determining distributions of the functions of random variables is a very important problem with a wide range of applications in Risk Management, Finance, Economics, Science, and many other areas. This paper develops the theory on both density and distribution functions for the quotient [...] Read more.

Determining distributions of the functions of random variables is a very important problem with a wide range of applications in Risk Management, Finance, Economics, Science, and many other areas. This paper develops the theory on both density and distribution functions for the quotient

Y = \frac{X_{1}}{X_{2}}

and the ratio of one variable over the sum of two variables

Z = \frac{X_{1}}{X_{1} + X_{2}}

of two dependent or independent random variables

X_{1}

and

X_{2}

by using copulas to capture the structures between

X_{1}

and

X_{2}

. Thereafter, we extend the theory by establishing the density and distribution functions for the quotients

Y = \frac{X_{1}}{X_{2}}

and

Z = \frac{X_{1}}{X_{1} + X_{2}}

of two dependent normal random variables

X_{1}

and

X_{2}

in the case of Gaussian copulas. We then develop the theory on the median for the ratios of both Y and Z on two normal random variables

X_{1}

and

X_{2}

. Furthermore, we extend the result of median for Z to a larger family of symmetric distributions and symmetric copulas of

X_{1}

and

X_{2}

. Our results are the foundation of any further study that relies on the density and cumulative probability functions of ratios for two dependent or independent random variables. Since the densities and distributions of the ratios of both Y and Z are in terms of integrals and are very complicated, their exact forms cannot be obtained. To circumvent the difficulty, this paper introduces the Monte Carlo algorithm, numerical analysis, and graphical approach to efficiently compute the complicated integrals and study the behaviors of density and distribution. We illustrate our proposed approaches by using a simulation study with ratios of normal random variables on several different copulas, including Gaussian, Student-t, Clayton, Gumbel, Frank, and Joe Copulas. We find that copulas make big impacts from different Copulas on behavior of distributions, especially on median, spread, scale and skewness effects. In addition, we also discuss the behaviors via all copulas above with the same Kendall’s coefficient. The approaches developed in this paper are flexible and have a wide range of applications for both symmetric and non-symmetric distributions and also for both skewed and non-skewed copulas with absolutely continuous random variables that could contain a negative range, for instance, generalized skewed-t distribution and skewed-t Copulas. Thus, our findings are useful for academics, practitioners, and policy makers. Full article

(This article belongs to the Special Issue Mathematical Finance with Applications)

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16 pages, 383 KiB

Open AccessArticle

The Role of Entrepreneurial Strategy, Network Ties, Human and Financial Capital in New Venture Performance

by Najib Ullah Khan, Shuangjie Li, Muhammad Nabeel Safdar and Zia Ullah Khan

J. Risk Financial Manag. 2019, 12(1), 41; https://doi.org/10.3390/jrfm12010041 - 11 Mar 2019

Cited by 41 | Viewed by 8608

Abstract

In the current era of globalization and competitive edge, the survival of newly established ventures has become a big challenge. Numerous studies have been carried out to discover factors that are essential for newly initiated ventures but the results are still fragmented. This [...] Read more.

In the current era of globalization and competitive edge, the survival of newly established ventures has become a big challenge. Numerous studies have been carried out to discover factors that are essential for newly initiated ventures but the results are still fragmented. This study focuses on measuring the effect of entrepreneurial strategy, network ties, human capital and financial capital on new venture performance. A structured questionnaire was used to collect data from 196 registered firms located in the emerging market Pakistan. The results indicate that entrepreneurial strategy, network ties and financial capital have a significant positive effect, while human capital showed an insignificant effect on new venture performance. This research recommends owners and managers of new firms build effective entrepreneurial strategies, expand their networks with external bodies (other firms, government and financial institutions) to acquire useful resources that in turn can spur their performance. Further implications are discussed. Policy makers and responsible authorities are advised to encourage and support new ventures which in turn can contribute to GDP and economic development. Practical implications and suggestions are also discussed. Full article

(This article belongs to the Special Issue Financing and Facilitating Entrepreneurship)

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12 pages, 277 KiB

Open AccessArticle

What Factors Affect Income Inequality and Economic Growth in Middle-Income Countries?

by Duc Hong Vo, Thang Cong Nguyen, Ngoc Phu Tran and Anh The Vo

J. Risk Financial Manag. 2019, 12(1), 40; https://doi.org/10.3390/jrfm12010040 - 8 Mar 2019

Cited by 33 | Viewed by 14746

Abstract

Income inequality in many middle-income countries has increased at an alarming level. While the time series relationship between income inequality and economic growth has been extensively investigated, the causal and dynamic link between them, particularly for the middle-income countries, has been largely ignored [...] Read more.

Income inequality in many middle-income countries has increased at an alarming level. While the time series relationship between income inequality and economic growth has been extensively investigated, the causal and dynamic link between them, particularly for the middle-income countries, has been largely ignored in the current literature. This study was conducted to fill in this gap on two different samples for the period from 1960 to 2014: (i) a full sample of 158 countries; and (ii) a sample of 86 middle-income countries. The Granger causality test and a system generalized method of moments (GMM) are utilized in this study. The findings from this study indicate that causality is found from economic growth to income inequality and vice versa in both samples of countries. In addition, this study also finds that income inequality contributes negatively to the economic growth in the middle-income countries in the research period. Full article

(This article belongs to the Special Issue Applied Econometrics)

29 pages, 557 KiB

Open AccessArticle

The Global Legal Entity Identifier System: How Can It Deliver?

by Ka Kei Chan and Alistair Milne

J. Risk Financial Manag. 2019, 12(1), 39; https://doi.org/10.3390/jrfm12010039 - 7 Mar 2019

Cited by 6 | Viewed by 5766

Abstract

We examine the global legal entity identifier (LEI) system for the identification of participants in financial markets. Semi-structured interviews with data professionals revealed the many ways in which the LEI can improve both business process efficiency, and counterparty and credit risk management. Larger [...] Read more.

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

(This article belongs to the Special Issue Financial Crises, Macroeconomic Management, and Financial Regulation)

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19 pages, 1354 KiB

Open AccessArticle

Asymmetric Mean Reversion in Low Liquid Markets: Evidence from BRVM

by Nathaniel Gbenro and Richard Kouamé Moussa

J. Risk Financial Manag. 2019, 12(1), 38; https://doi.org/10.3390/jrfm12010038 - 6 Mar 2019

Cited by 8 | Viewed by 4864

Abstract

This paper analyzes the mean reversion property on the west African stock market (in French, Bourse Régionale des Valeurs Mobilières BRVM). For this purpose, we use two daily indices: (i) the composite index (BRVMC) and (ii) the index of the 10 most liquid [...] Read more.

This paper analyzes the mean reversion property on the west African stock market (in French, Bourse Régionale des Valeurs Mobilières BRVM). For this purpose, we use two daily indices: (i) the composite index (BRVMC) and (ii) the index of the 10 most liquid assets (BRVM10) collected from 3 January 2005 to 29 June 2018. We estimate an asymmetric nonlinear autoregressive model with an EGARCH innovation to account for heteroskedasticity. The results suggest the existence of a mean reversion property for both indices. The half-life time is 7 days for the composite index and 2 days for the BRVM 10 index. Furthermore, using a rolling regression technique, we show that the estimated half-life time declines slightly for the composite index. Full article

(This article belongs to the Special Issue Financial Time Series: Methods & Models)

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22 pages, 808 KiB

Open AccessArticle

Developments in Risk Management in Islamic Finance: A Review

by Naseem Al Rahahleh, M. Ishaq Bhatti and Faridah Najuna Misman

J. Risk Financial Manag. 2019, 12(1), 37; https://doi.org/10.3390/jrfm12010037 - 20 Feb 2019

Cited by 67 | Viewed by 28666

Abstract

The purpose of this study is to review recent developments pertaining to risk management in Islamic banking and finance literature. The study explores the fundamental features of risks associated with Islamic banks (IBs) as compared to those associated with conventional banks (CBs) in [...] Read more.

The purpose of this study is to review recent developments pertaining to risk management in Islamic banking and finance literature. The study explores the fundamental features of risks associated with Islamic banks (IBs) as compared to those associated with conventional banks (CBs) in order to determine the extent to which IBs engage in effective risk mitigation. The study includes a consideration of the major studies in which the fundamental features of Islamic banks and finance (IBF) and the main characteristics of risk management in IBs are analyzed in comparison with those of CBs. Specifically, these two kinds of banks are compared in relation to the types of risks faced, the characteristics of those risks, and the nature and extent of exposure to those risks. A tabular methodology approach is used in concert with a comparative literature review approach for the analysis. The results show that there is weak support for Shariah-based product development due to the lack of risk mitigation expertise in IBs. The conclusion presented is that in comparison with CBs, IBs are more risk-sensitive due to the nature of their products, contract structure, legal costing, governance practices, and liquidity infrastructure. Furthermore, the determinants of the credit risk of Islamic banks in Malaysia (MIBs) are examined. Overall, bank capital and financing expansion have a significant negative impact on the credit risk level of IBs in Malaysia. Full article

(This article belongs to the Section Banking and Finance)

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20 pages, 3751 KiB

Open AccessArticle

Bitcoin at High Frequency

by Leopoldo Catania and Mads Sandholdt

J. Risk Financial Manag. 2019, 12(1), 36; https://doi.org/10.3390/jrfm12010036 - 15 Feb 2019

Cited by 21 | Viewed by 8503

Abstract

This paper studies the behaviour of Bitcoin returns at different sample frequencies. We consider high frequency returns starting from tick-by-tick price changes traded at the Bitstamp and Coinbase exchanges. We find evidence of a smooth intra-daily seasonality pattern, and an abnormal trade- and [...] Read more.

This paper studies the behaviour of Bitcoin returns at different sample frequencies. We consider high frequency returns starting from tick-by-tick price changes traded at the Bitstamp and Coinbase exchanges. We find evidence of a smooth intra-daily seasonality pattern, and an abnormal trade- and volatility intensity at Thursdays and Fridays. We find no predictability for Bitcoin returns at or above one day, though, we find predictability for sample frequencies up to 6 h. Predictability of Bitcoin returns is also found to be time–varying. We also study the behaviour of the realized volatility of Bitcoin. We document a remarkable high percentage of jumps above

80 %

. We also find that realized volatility exhibits: (i) long memory; (ii) leverage effect; and (iii) no impact from lagged jumps. A forecast study shows that: (i) Bitcoin volatility has become more easy to predict after 2017; (ii) including a leverage component helps in volatility prediction; and (iii) prediction accuracy depends on the length of the forecast horizon. Full article

(This article belongs to the Special Issue Alternative Assets and Cryptocurrencies)

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18 pages, 789 KiB

Open AccessArticle

The Importance of the Financial Derivatives Markets to Economic Development in the World’s Four Major Economies

by Duc Hong Vo, Son Van Huynh, Anh The Vo and Dao Thi-Thieu Ha

J. Risk Financial Manag. 2019, 12(1), 35; https://doi.org/10.3390/jrfm12010035 - 14 Feb 2019

Cited by 31 | Viewed by 19513

Abstract

Over the past three decades, China and India have attained economic power close to that of Japan and the U.S. During this period, the importance of the derivatives market within the financial market has been widely recognized. However, little supporting evidence is available [...] Read more.

Over the past three decades, China and India have attained economic power close to that of Japan and the U.S. During this period, the importance of the derivatives market within the financial market has been widely recognized. However, little supporting evidence is available on its economic effects. This paper investigates the dynamic relationship between the derivatives markets and economic development in these four large economies, which we consider together as the CIJU (China, India, Japan, and the U.S.) group. We use a Granger-causality test in the framework of a vector error correction model (VECM) to examine this causal and dynamic relation with data for the period 1998Q1 to 2017Q4. Derivative markets are found to positively contribute to economic development in the short run in the U.S., Japan, and India, but the effect disappears in the long run. In China, the derivatives market has a negative effect on economic development in the short run. However, in the long run, we observe a positive effect from the derivatives market on economic development based on two long-run estimation techniques, namely, dynamic ordinary least squares and fully modified ordinary least squares. Also, the development of derivative markets causes growth volatility in India, both in the short run and long run. Full article

(This article belongs to the Special Issue Applied Econometrics)

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19 pages, 453 KiB

Open AccessArticle

Tax Competitiveness of the New EU Member States

by Askoldas Podviezko, Lyudmila Parfenova and Andrey Pugachev

J. Risk Financial Manag. 2019, 12(1), 34; https://doi.org/10.3390/jrfm12010034 - 14 Feb 2019

Cited by 9 | Viewed by 4672

Abstract

This paper investigates tax competitiveness among the EU member countries. The tax competition of countries causes both positive and negative effects on macroeconomic processes such as the effectiveness of government spending, the rationality of supply of externalities, and the length and amplitudes of [...] Read more.

This paper investigates tax competitiveness among the EU member countries. The tax competition of countries causes both positive and negative effects on macroeconomic processes such as the effectiveness of government spending, the rationality of supply of externalities, and the length and amplitudes of business cycles. A considerable reduction of corporate tax in the EU is related to increased tax competition after new members entered the EU. Multiple criteria methods were chosen for the quantitative evaluation of EU countries from different regions of the EU. Criteria of evaluation were chosen and structured into a hierarchy. The convergence process of the new members of the EU is reinforced with the increasing tax competitiveness of such countries. Results of the multiple criteria evaluation revealed both the factors that increased the tax competitiveness of new members of the EU, and outlined the factors that hampered such competition. Full article

(This article belongs to the Special Issue Quantitative Risk)

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18 pages, 1555 KiB

Open AccessArticle

Clarifying the Response of Gold Return to Financial Indicators: An Empirical Comparative Analysis Using Ordinary Least Squares, Robust and Quantile Regressions

by Takashi Miyazaki

J. Risk Financial Manag. 2019, 12(1), 33; https://doi.org/10.3390/jrfm12010033 - 14 Feb 2019

Cited by 6 | Viewed by 4274

Abstract

In this study, I apply a quantile regression model to investigate how gold returns respond to changes in various financial indicators. The model quantifies the asymmetric response of gold return in the tails of the distribution based on weekly data over the past [...] Read more.

In this study, I apply a quantile regression model to investigate how gold returns respond to changes in various financial indicators. The model quantifies the asymmetric response of gold return in the tails of the distribution based on weekly data over the past 30 years. I conducted a statistical test that allows for multiple structural changes and find that the relationship between gold return and some key financial indicators changed three times throughout the sample period. According to my empirical analysis of the whole sample period, I find that: (1) the gold return rises significantly if stock returns fall sharply; (2) it rises as the stock market volatility increases; (3) it also rises when general financial market conditions tighten; (4) gold and crude oil prices generally move toward the same direction; and (5) gold and the US dollar have an almost constant negative correlation. Looking at each sample period, (1) and (2) are remarkable in the period covering the global financial crisis (GFC), suggesting that investors divested from stocks as a risky asset. On the other hand, (3) is a phenomenon observed during the sample period after the GFC, suggesting that it reflects investors’ behavior of flight to quality. Full article

(This article belongs to the Special Issue Empirical Finance)

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21 pages, 281 KiB

Open AccessArticle

Effect of Corporate Governance on Institutional Investors’ Preferences: An Empirical Investigation in Taiwan

by Su-Lien Lu and Ying-Hui Li

J. Risk Financial Manag. 2019, 12(1), 32; https://doi.org/10.3390/jrfm12010032 - 14 Feb 2019

Cited by 9 | Viewed by 5042

Abstract

This study discusses the institutional investors’ shareholding base on corporate governance system in Taiwan. The sample was 4760 Taiwanese companies from 2005 to 2012. Then, this study established six hypotheses to investigate the effects of corporate governance on institutional investors’ shareholdings. The panel [...] Read more.

This study discusses the institutional investors’ shareholding base on corporate governance system in Taiwan. The sample was 4760 Taiwanese companies from 2005 to 2012. Then, this study established six hypotheses to investigate the effects of corporate governance on institutional investors’ shareholdings. The panel data regression model and piecewise regression model were adopted to determine whether six hypotheses are supported. For sensitive analysis, additional consideration was given on the basis of industrial category (electronics or nonelectronics), and the 2008–2010 global financial crises. This study discovered that a nonlinear relationship exists between the domestic institutional investors’ shareholdings. The managerial ownership ratio and blockholder ownership ratio have positive effects both on domestic and foreign institutional investors. However, domestic and foreign institutional investors have distinct opinions regarding independent director ratios. Finally, the corporate governance did not improve institutional investors’ shareholdings during financial crisis periods; instead, they paid more attention to firm profits or other characteristics. Full article

(This article belongs to the Special Issue Empirical Finance)

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15 pages, 947 KiB

Open AccessArticle

Statistical Arbitrage in Cryptocurrency Markets

by Thomas Günter Fischer, Christopher Krauss and Alexander Deinert

J. Risk Financial Manag. 2019, 12(1), 31; https://doi.org/10.3390/jrfm12010031 - 13 Feb 2019

Cited by 30 | Viewed by 18042

Abstract

Machine learning research has gained momentum—also in finance. Consequently, initial machine-learning-based statistical arbitrage strategies have emerged in the U.S. equities markets in the academic literature, see e.g., ^{Takeuchi and Lee} (²⁰¹³); ^{Moritz and Zimmermann} (²⁰¹⁴); ^{Krauss et al.} ( [...] Read more.

Machine learning research has gained momentum—also in finance. Consequently, initial machine-learning-based statistical arbitrage strategies have emerged in the U.S. equities markets in the academic literature, see e.g., ^{Takeuchi and Lee} (²⁰¹³); ^{Moritz and Zimmermann} (²⁰¹⁴); ^{Krauss et al.} (²⁰¹⁷). With our paper, we pose the question how such a statistical arbitrage approach would fare in the cryptocurrency space on minute-binned data. Specifically, we train a random forest on lagged returns of 40 cryptocurrency coins, with the objective to predict whether a coin outperforms the cross-sectional median of all 40 coins over the subsequent 120 min. We buy the coins with the top-3 predictions and short-sell the coins with the flop-3 predictions, only to reverse the positions after 120 min. During the out-of-sample period of our backtest, ranging from 18 June 2018 to 17 September 2018, and after more than 100,000 trades, we find statistically and economically significant returns of 7.1 bps per day, after transaction costs of 15 bps per half-turn. While this finding poses a challenge to the semi-strong from of market efficiency, we critically discuss it in light of limits to arbitrage, focusing on total volume constraints of the presented intraday-strategy. Full article

(This article belongs to the Special Issue Alternative Assets and Cryptocurrencies)

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17 pages, 1800 KiB

Open AccessArticle

Predicting Micro-Enterprise Failures Using Data Mining Techniques

by Aneta Ptak-Chmielewska

J. Risk Financial Manag. 2019, 12(1), 30; https://doi.org/10.3390/jrfm12010030 - 10 Feb 2019

Cited by 18 | Viewed by 5802

Abstract

Research analysis of small enterprises are still rare, due to lack of individual level data. Small enterprise failures are connected not only with their financial situation abut also with non-financial factors. In recent research we tend to apply more and more complex models. [...] Read more.

Research analysis of small enterprises are still rare, due to lack of individual level data. Small enterprise failures are connected not only with their financial situation abut also with non-financial factors. In recent research we tend to apply more and more complex models. However, it is not so obvious that increasing complexity increases the effectiveness. In this paper the sample of 806 small enterprises were analyzed. Qualitative factors were used in modeling. Some simple and more complex models were estimated, such as logistic regression, decision trees, neural networks, gradient boosting, and support vector machines. Two hypothesis were verified: (i) not only financial ratios but also non-financial factors matter for small enterprise survival, and (ii) advanced statistical models and data mining techniques only insignificantly increase the prediction accuracy of small enterprise failures. Results show that simple models are as good as more complex model. Data mining models tend to be overfitted. Most important financial ratios in predicting small enterprise failures were: operating profitability of assets, current assets turnover, capital ratio, coverage of short-term liabilities by equity, coverage of fixed assets by equity, and the share of net financial surplus in total liabilities. Among non-financial factors only two of them were important: the sector of activity and employment. Full article

(This article belongs to the Special Issue Empirical Finance)

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20 pages, 376 KiB

Open AccessArticle

The Determinants of Sovereign Risk Premium in African Countries

by Jane Mpapalika and Christopher Malikane

J. Risk Financial Manag. 2019, 12(1), 29; https://doi.org/10.3390/jrfm12010029 - 9 Feb 2019

Cited by 7 | Viewed by 5781

Abstract

This paper investigates the determinants of the sovereign risk premium in African countries. We employ the dynamic fixed effects model to determine the key drivers of sovereign bond spreads. Country-specific effects are fixed and the inclusion of dummy variables using the Bai–Perron multiple [...] Read more.

This paper investigates the determinants of the sovereign risk premium in African countries. We employ the dynamic fixed effects model to determine the key drivers of sovereign bond spreads. Country-specific effects are fixed and the inclusion of dummy variables using the Bai–Perron multiple structural break test is significant at a 5% level. For robustness, the time-series generalized method of moments (GMM) is used where the null hypothesis of the Sargan Test of over-identifying restrictions (OIR) and the Arellano–Bond Test of no autocorrelation are not rejected. This implies that the instruments used are valid and relevant. In addition, there is no autocorrelation in the error terms. Our results show that the exchange rate, Money supply/GDP (M2/GDP) ratio, and trade are insignificant. Furthermore, our findings indicate that public debt/GDP ratio, GDP growth, inflation rate, foreign exchange reserves, commodity price, and market sentiment are significant at a 5% and 10% level. Full article

(This article belongs to the Special Issue Risk Analysis and Portfolio Modelling)

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21 pages, 670 KiB

Open AccessArticle

Multivariate Student versus Multivariate Gaussian Regression Models with Application to Finance

by Thi Huong An Nguyen, Anne Ruiz-Gazen, Christine Thomas-Agnan and Thibault Laurent

J. Risk Financial Manag. 2019, 12(1), 28; https://doi.org/10.3390/jrfm12010028 - 9 Feb 2019

Cited by 3 | Viewed by 4442

Abstract

To model multivariate, possibly heavy-tailed data, we compare the multivariate normal model (N) with two versions of the multivariate Student model: the independent multivariate Student (IT) and the uncorrelated multivariate Student (UT). After recalling some facts about these distributions and models, known but [...] Read more.

To model multivariate, possibly heavy-tailed data, we compare the multivariate normal model (N) with two versions of the multivariate Student model: the independent multivariate Student (IT) and the uncorrelated multivariate Student (UT). After recalling some facts about these distributions and models, known but scattered in the literature, we prove that the maximum likelihood estimator of the covariance matrix in the UT model is asymptotically biased and propose an unbiased version. We provide implementation details for an iterative reweighted algorithm to compute the maximum likelihood estimators of the parameters of the IT model. We present a simulation study to compare the bias and root mean squared error of the ensuing estimators of the regression coefficients and covariance matrix under several scenarios of the potential data-generating process, misspecified or not. We propose a graphical tool and a test based on the Mahalanobis distance to guide the choice between the competing models. We also present an application to model vectors of financial assets returns. Full article

(This article belongs to the Special Issue Applied Econometrics)

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15 pages, 425 KiB

Open AccessArticle

Contribution to the Valuation of BRVM’s Assets: A Conditional CAPM Approach

by Mamadou Cisse, Mamadou Konte, Mohamed Toure and Smael Afolabi Assani

J. Risk Financial Manag. 2019, 12(1), 27; https://doi.org/10.3390/jrfm12010027 - 6 Feb 2019

Cited by 6 | Viewed by 3997

Abstract

The conditional capital asset pricing model (CAPM) theory postulates that the systematic risk (

β

) of an asset or portfolio varies over time. Several dynamics are thus given to systematic risk in the literature. This article looks for the dynamic that seems [...] Read more.

The conditional capital asset pricing model (CAPM) theory postulates that the systematic risk (

β

) of an asset or portfolio varies over time. Several dynamics are thus given to systematic risk in the literature. This article looks for the dynamic that seems to best explain the returns of the assets of the Regional Stock Exchange of West Africa (BRVM) by comparing two dynamics: one by the Kalman filter (assuming that the

β

follow a random walk) and the other by the Markov switching (MS) model (assuming that

β

varies according to regimes) for four portfolios of the BRVM. Having found a link between the beta of the market portfolio and the size criterion (measured by capitalization), the two previous models were re-estimated with the addition of the SMB (Small Minus Big) variable. The results show according to the RMSE criterion that the estimation by the Kalman filter fits better than MS, which suggests that investors cannot anticipate systematic risk because of its high volatility. Full article

(This article belongs to the Special Issue Stock Market Volatility Modelling and Forecasting)

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17 pages, 360 KiB

Open AccessArticle

Geometric No-Arbitrage Analysis in the Dynamic Financial Market with Transaction Costs

by Wanxiao Tang, Jun Zhao and Peibiao Zhao

J. Risk Financial Manag. 2019, 12(1), 26; https://doi.org/10.3390/jrfm12010026 - 6 Feb 2019

Viewed by 2737

Abstract

The present paper considers a class of financial market with transaction costs and constructs a geometric no-arbitrage analysis frame. Then, this paper arrives at the fact that this financial market is of no-arbitrage if and only if the curvature 2-form of a specific [...] Read more.

The present paper considers a class of financial market with transaction costs and constructs a geometric no-arbitrage analysis frame. Then, this paper arrives at the fact that this financial market is of no-arbitrage if and only if the curvature 2-form of a specific connection is zero. Furthermore, this paper derives the fact that the no-arbitrage condition for the one-period financial market is equivalent to the geometric no-arbitrage condition. Finally, an example states the equivalence between the geometric no-arbitrage condition and the existence of the solutions for a maximization problem of expected utility. Full article

(This article belongs to the Section Financial Markets)

30 pages, 787 KiB

Open AccessArticle

Testing Stylized Facts of Bitcoin Limit Order Books

by Matthias Schnaubelt, Jonas Rende and Christopher Krauss

J. Risk Financial Manag. 2019, 12(1), 25; https://doi.org/10.3390/jrfm12010025 - 5 Feb 2019

Cited by 15 | Viewed by 10335

Abstract

The majority of electronic markets worldwide employ limit order books, and the recently emerging exchanges for cryptocurrencies pose no exception. With this work, we empirically analyze whether commonly observed empirical properties from established limit order exchanges transfer to the cryptocurrency domain. Based on [...] Read more.

The majority of electronic markets worldwide employ limit order books, and the recently emerging exchanges for cryptocurrencies pose no exception. With this work, we empirically analyze whether commonly observed empirical properties from established limit order exchanges transfer to the cryptocurrency domain. Based on the literature, we establish a structured methodological framework to conduct analyses in a systematic and comprehensive way. We then present results from a unique and extensive limit order data set acquired from major cryptocurrency exchanges for the currency pair Bitcoin to US Dollar. We recover many observations from mature markets, such as a symmetry between the average ask and the average bid side of the order book, autocorrelation in returns on the smallest time scales only, volatility clustering and the timing of large trades. We also observe some idiosyncrasies: The distributions of trade size and limit order prices deviate from commonly observed patterns. Also, we find limit order books to be relatively shallow and liquidity costs to be relatively high when compared to established markets. Full article

(This article belongs to the Special Issue Alternative Assets and Cryptocurrencies)

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14 pages, 1320 KiB

Open AccessArticle

Has ‘Too Big To Fail’ Been Solved? A Longitudinal Analysis of Major U.S. Banks

by Satish Thosar and Bradley Schwandt

J. Risk Financial Manag. 2019, 12(1), 24; https://doi.org/10.3390/jrfm12010024 - 1 Feb 2019

Cited by 1 | Viewed by 4990

Abstract

In the wake of the global financial crisis that erupted in 2008, there has been extensive commentary and regulatory focus on the ‘Too Big to Fail’ issue. In this paper, we survey the proposed solutions and regulatory initiatives that have been undertaken. We [...] Read more.

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

(This article belongs to the Special Issue Financial Crises, Macroeconomic Management, and Financial Regulation)

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22 pages, 814 KiB

Open AccessArticle

Growth and Debt: An Endogenous Smooth Coefficient Approach

by Mustafa Koroglu

J. Risk Financial Manag. 2019, 12(1), 23; https://doi.org/10.3390/jrfm12010023 - 1 Feb 2019

Cited by 3 | Viewed by 4591

Abstract

The new growth theories with an emphasis on fundamental determinants such as institutions suggest a non-linear cross-country growth process. In this paper, we investigate the public debt and economic growth relationship using the semi-parametric smooth coefficient approach that allows democracy to influence this [...] Read more.

The new growth theories with an emphasis on fundamental determinants such as institutions suggest a non-linear cross-country growth process. In this paper, we investigate the public debt and economic growth relationship using the semi-parametric smooth coefficient approach that allows democracy to influence this relationship and parameter heterogeneity in the unknown functional form and addresses the endogeneity of variables. We find results consistent with the previous literature that identified a significant adverse effect of public debt on growth for the countries below a particular democracy level. However, we also find conclusive evidence that countries with high institutional quality have an adverse effect of public debt on growth for the period 1980–2009, as well as for the extended period including the years 2010–2014. A 10-percentage point increase in the debt-to-GDP ratio is associated with a 0.12% and 0.07% decrease in the subsequent 10-year period real GDP growth rate for the zero democracy countries and for the countries with a democracy score of 10, respectively. Full article

(This article belongs to the Special Issue Nonparametric Econometric Methods and Application)

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11 pages, 226 KiB

Open AccessArticle

Does the Misery Index Influence a U.S. President’s Political Re-Election Prospects?

by Bahram Adrangi and Joseph Macri

J. Risk Financial Manag. 2019, 12(1), 22; https://doi.org/10.3390/jrfm12010022 - 1 Feb 2019

Cited by 11 | Viewed by 5782

Abstract

We seek to determine whether a United States President’s job approval rating is influenced by the Misery Index. This hypothesis is examined in two ways. First, we employ a nonlinear model that includes several macroeconomic variables: the current account deficit, exchange rate, unemployment, [...] Read more.

We seek to determine whether a United States President’s job approval rating is influenced by the Misery Index. This hypothesis is examined in two ways. First, we employ a nonlinear model that includes several macroeconomic variables: the current account deficit, exchange rate, unemployment, inflation, and mortgage rates. Second, we employ probit and logit regression models to calculate the probabilities of U.S. Presidents’ approval ratings to the Misery Index. The results suggest that Layton’s model does not perform well when adopted for the United States. Conversely, the probit and logit regression analysis suggests that the Misery Index significantly impacts the probability of the approval of U.S. Presidents’ performances. Full article

(This article belongs to the Special Issue Applied Econometrics)

14 pages, 265 KiB

Open AccessArticle

Valuation of Environmental Management Standard ISO 14001: Evidence from an Emerging Market

by Hammad Riaz, Abubakr Saeed, Muhammad Saad Baloch, Nasrullah and Zeeshan Ahmad Khan

J. Risk Financial Manag. 2019, 12(1), 21; https://doi.org/10.3390/jrfm12010021 - 29 Jan 2019

Cited by 14 | Viewed by 4981

Abstract

ISO 14001 (Environmental Management Standard) helps corporations to build legitimacy and goodwill, and can be also viewed as an organizational response to institutional pressure to act proactively towards the environment. The purpose of this paper is to investigate how investors in the emerging [...] Read more.

ISO 14001 (Environmental Management Standard) helps corporations to build legitimacy and goodwill, and can be also viewed as an organizational response to institutional pressure to act proactively towards the environment. The purpose of this paper is to investigate how investors in the emerging country value voluntary environmental management standard ISO 14001 certification. The impact of voluntary environmental management standard ISO 14001 on market performance is still not clear. By using event study methodology, this study matched ISO-certified firms with non-certified ones based on three different matching principles that include return on assets, size, and industry. The findings indicated that investors negatively valued ISO 14001 in both the short and long run. The study recommended policy implications for managers, policy makers, and non-government organizations. Full article

(This article belongs to the Section Sustainability and Finance)

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30 pages, 563 KiB

Open AccessArticle

Finance and Jobs: How Financial Markets and Prudential Regulation Shape Unemployment Dynamics

by Ekkehard Ernst

J. Risk Financial Manag. 2019, 12(1), 20; https://doi.org/10.3390/jrfm12010020 - 24 Jan 2019

Cited by 7 | Viewed by 4643

Abstract

This article explores the impact of financial market regulation on jobs. It argues that understanding the impact of finance on labor markets is key to an understanding of the trade-off between economic stability and financial sector growth. The article combines information on labor [...] Read more.

This article explores the impact of financial market regulation on jobs. It argues that understanding the impact of finance on labor markets is key to an understanding of the trade-off between economic stability and financial sector growth. The article combines information on labor market flows with indicators of financial market development and reforms to assess the implications of financial markets on employment dynamics directly, using information from the International Labour Organization (ILO) datatabse on unemployment flows. On the basis of a matching model of the labor market, it analyses the economic, institutional, and policy determinants of unemployment in- and out-flows. Against a set of basic controls, we present evidence regarding the relationship between financial sector development and reforms and their impact on unemployment dynamics. Using scenario analysis, the article demonstrates the importance of broad financial sector re-regulation to stabilize unemployment inflows and to promote faster employment growth. In particular, we find that encompassing financial sector regulation, had it been in place prior to the global financial crisis in 2008, would have helped a faster recovery in jobs. Full article

(This article belongs to the Special Issue Financial Crises, Macroeconomic Management, and Financial Regulation)

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