Journal of Risk and Financial Management

21 pages, 853 KiB

Open AccessArticle

Bootstrapping the Early Exercise Boundary in the Least-Squares Monte Carlo Method

by Pascal Létourneau and Lars Stentoft

J. Risk Financial Manag. 2019, 12(4), 190; https://doi.org/10.3390/jrfm12040190 - 15 Dec 2019

Cited by 4 | Viewed by 3102

This paper proposes an innovative algorithm that significantly improves on the approximation of the optimal early exercise boundary obtained with simulation based methods for American option pricing. The method works by exploiting and leveraging the information in multiple cross-sectional regressions to the fullest [...] Read more.

This paper proposes an innovative algorithm that significantly improves on the approximation of the optimal early exercise boundary obtained with simulation based methods for American option pricing. The method works by exploiting and leveraging the information in multiple cross-sectional regressions to the fullest by averaging the individually obtained estimates at each early exercise step, starting from just before maturity, in the backwards induction algorithm. With this method, less errors are accumulated, and as a result of this, the price estimate is essentially unbiased even for long maturity options. Numerical results demonstrate the improvements from our method and show that these are robust to the choice of simulation setup, the characteristics of the option, and the dimensionality of the problem. Finally, because our method naturally disassociates the estimation of the optimal early exercise boundary from the pricing of the option, significant efficiency gains can be obtained by using less simulated paths and repetitions to estimate the optimal early exercise boundary than with the regular method. Full article

(This article belongs to the Special Issue Computational Finance)

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24 pages, 2714 KiB

Open AccessArticle

Risk Capital and Emerging Technologies: Innovation and Investment Patterns Based on Artificial Intelligence Patent Data Analysis

by Roberto S. Santos and Lingling Qin

J. Risk Financial Manag. 2019, 12(4), 189; https://doi.org/10.3390/jrfm12040189 - 14 Dec 2019

Cited by 14 | Viewed by 6923

Abstract

The promise of artificial intelligence (AI) to drive economic growth and improve quality of life has ushered in a new AI arms race. Investments of risk capital fuel this emerging technology. We examine the role that venture capital (VC) and corporate investments of [...] Read more.

The promise of artificial intelligence (AI) to drive economic growth and improve quality of life has ushered in a new AI arms race. Investments of risk capital fuel this emerging technology. We examine the role that venture capital (VC) and corporate investments of risk capital play in the emergence of AI-related technologies. Drawing upon a dataset of 29,954 U.S. patents from 1970 to 2018, including 1484 U.S. patents granted to 224 VC-backed start-ups, we identify AI-related innovation and investment characteristics. Furthermore, we develop a new measure of knowledge coupling at the firm-level and use this to explore how knowledge coupling influences VC risk capital decisions in emerging AI technologies. Our findings show that knowledge coupling is a better predictor of VC investment in emerging technologies than the breadth of a patent’s technological domains. Furthermore, our results show that there are differences in knowledge coupling between private start-ups and public corporations. These findings enhance our understanding of what types of AI innovations are more likely to be selected by VCs and have important implications for our understanding of how risk capital induces the emergence of new technologies. Full article

(This article belongs to the Special Issue Venture Capital and Private Equity)

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13 pages, 2123 KiB

Open AccessArticle

Influence of Venture Capital and Knowledge Transfer on Innovation Performance in the Big Data Environment

by Chuanrong Wu, Xiaoming Yang, Veronika Lee and Mark E. McMurtrey

J. Risk Financial Manag. 2019, 12(4), 188; https://doi.org/10.3390/jrfm12040188 - 12 Dec 2019

Cited by 5 | Viewed by 2921

Abstract

Technological innovation requires large investments. Venture capital (VC) is a prominent financial source for innovative start-ups. A venture capitalist will inevitably transfer knowledge to facilitate the innovation of a firm while monitoring and advising its portfolio companies. Only when a firm has its [...] Read more.

Technological innovation requires large investments. Venture capital (VC) is a prominent financial source for innovative start-ups. A venture capitalist will inevitably transfer knowledge to facilitate the innovation of a firm while monitoring and advising its portfolio companies. Only when a firm has its own valuable new knowledge and high growth potential would venture capitalists select it. At the same time, big data knowledge, such as customer demands and user preferences, is also important for the new product development of a firm in the big data environment. Therefore, private knowledge transferred from venture capitalists, new knowledge developed independently by a firm itself, and big data knowledge are the three main types of knowledge for venture-backed firms in the big data environment. To find the influences of VC and knowledge transfer on the innovative performance of venture-backed firms, a model of maximizing the present value of the expected profit of new product innovation performance of a venture-backed firm in the big data environment is presented. The model can help venture capitalists to determine the scale of investment and the optimal exit time and predict the internal rate of return (IRR). This model can also help innovative start-ups to illustrate the value and prospects of a project to attract investment in their business prospectus. Full article

(This article belongs to the Special Issue Venture Capital and Private Equity)

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13 pages, 209 KiB

Open AccessArticle

Tax Arrears Versus Financial Ratios in Bankruptcy Prediction

by Oliver Lukason and Art Andresson

J. Risk Financial Manag. 2019, 12(4), 187; https://doi.org/10.3390/jrfm12040187 - 11 Dec 2019

Cited by 12 | Viewed by 3730

Abstract

This paper aims to compare the usefulness of tax arrears and financial ratios in bankruptcy prediction. The analysis is based on the whole population of Estonian bankrupted and survived SMEs from 2013 to 2017. Logistic regression and multilayer perceptron are used as the [...] Read more.

This paper aims to compare the usefulness of tax arrears and financial ratios in bankruptcy prediction. The analysis is based on the whole population of Estonian bankrupted and survived SMEs from 2013 to 2017. Logistic regression and multilayer perceptron are used as the prediction methods. The results indicate that closer to bankruptcy, tax arrears’ information yields a higher prediction accuracy than financial ratios. A combined model of tax arrears and financial ratios is more useful than the individual models. The results enable us to outline several theoretical and practical implications. Full article

(This article belongs to the Special Issue Modern Methods of Bankruptcy Prediction)

20 pages, 1343 KiB

Open AccessArticle

Capital Markets Integration and Cointegration: Testing for the Correct Specification of Stock Market Indices

by Maria-Eleni K. Agoraki, Dimitris A. Georgoutsos and Georgios P. Kouretas

J. Risk Financial Manag. 2019, 12(4), 186; https://doi.org/10.3390/jrfm12040186 - 09 Dec 2019

Cited by 8 | Viewed by 2934

Abstract

In this paper we develop a comprehensive Vector Autoregression Model consisting of five variables; the stock market and price indices of pairs of countries, as well as their bilateral nominal exchange rate. Then, we show that under certain long-run restrictions, our approach encompasses [...] Read more.

In this paper we develop a comprehensive Vector Autoregression Model consisting of five variables; the stock market and price indices of pairs of countries, as well as their bilateral nominal exchange rate. Then, we show that under certain long-run restrictions, our approach encompasses a large number of specifications encountered in the voluminous literature on testing for capital integration with cointegration techniques. This approach minimizes the risk of accepting the null of no cointegration between the equity price indices because of the introduction of additional stochastic trends through the transformation of those indices on a “real or nominal US dollar” basis. Furthermore, other interesting long run specifications emerge either with I(1) only stochastic shocks or with the presence of some I(2) disturbances characterizing the system. We apply the testing methodology on monthly data for the US, UK, Germany, and Japan for the period January 1980–May 2019. The main findings provide partial support in favor of cointegration, and therefore for capital markets integration, among stock market indices when proper attention is given to issues like the identification and temporal stability of the cointegration vectors as well as the choice of units that the stock indices are expressed in. Full article

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

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15 pages, 2654 KiB

Open AccessArticle

Dynamic Bankruptcy Prediction Models for European Enterprises

by Tomasz Korol

J. Risk Financial Manag. 2019, 12(4), 185; https://doi.org/10.3390/jrfm12040185 - 09 Dec 2019

Cited by 24 | Viewed by 6051

Abstract

This manuscript is devoted to the issue of forecasting corporate bankruptcy. Determining a firm’s bankruptcy risk is one of the most interesting topics for investors and decision-makers. The aim of the paper is to develop and to evaluate dynamic bankruptcy prediction models for [...] Read more.

This manuscript is devoted to the issue of forecasting corporate bankruptcy. Determining a firm’s bankruptcy risk is one of the most interesting topics for investors and decision-makers. The aim of the paper is to develop and to evaluate dynamic bankruptcy prediction models for European enterprises. To conduct this objective, four forecasting models are developed with the use of four different methods—fuzzy sets, recurrent and multilayer artificial neural network, and decision trees. Such a research approach will answer the question of whether changes in indicators are relevant predictors of a company’s coming financial crisis because declines or increases in values do not immediately indicate that the company’s economic situation is deteriorating. The research relies on two samples of firms—the learning sample of 50 bankrupt and 50 non-bankrupt enterprises and the testing sample of 250 bankrupt and 250 non-bankrupt firms. Full article

(This article belongs to the Special Issue Modern Methods of Bankruptcy Prediction)

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18 pages, 528 KiB

Open AccessArticle

Impact of Readability on Corporate Bond Market

by Jieyan Fang-Klingler

J. Risk Financial Manag. 2019, 12(4), 184; https://doi.org/10.3390/jrfm12040184 - 05 Dec 2019

Cited by 7 | Viewed by 3611

Abstract

This paper investigates the impact of annual report readability on the corporate bond market. My findings indicate that in the US corporate bond market, firms with less readable annual reports tend to have higher credit spreads, higher credit spread volatilities, higher transaction costs, [...] Read more.

This paper investigates the impact of annual report readability on the corporate bond market. My findings indicate that in the US corporate bond market, firms with less readable annual reports tend to have higher credit spreads, higher credit spread volatilities, higher transaction costs, higher transaction costs volatility, smaller trade size, higher number of trades and higher number of trades volatility. This paper also provides the first answers to the question as to whether annual report readability matters to international market participants in the corporate bond market. My findings provide evidence that in the EUR corporate bond market, firms with more readable annual reports are associated with lower credit spreads. Full article

(This article belongs to the Special Issue Corporate Debt)

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9 pages, 2139 KiB

Open AccessArticle

Robust Bayesian Inference in Stochastic Frontier Models

by Mike G. Tsionas

J. Risk Financial Manag. 2019, 12(4), 183; https://doi.org/10.3390/jrfm12040183 - 04 Dec 2019

Viewed by 2107

Abstract

We use the concept of coarsened posteriors to provide robust Bayesian inference via coarsening in order to robustify posteriors arising from stochastic frontier models. These posteriors arise from tempered versions of the likelihood when at most a pre-specified amount of data is used, [...] Read more.

We use the concept of coarsened posteriors to provide robust Bayesian inference via coarsening in order to robustify posteriors arising from stochastic frontier models. These posteriors arise from tempered versions of the likelihood when at most a pre-specified amount of data is used, and are robust to changes in the model. Specifically, we examine robustness to changes in the distribution of the composed error in the stochastic frontier model (SFM). Moreover, coarsening is a form of regularization, reduces overfitting and makes inferences less sensitive to model choice. The new techniques are illustrated using artificial data as well as in a substantive application to large U.S. banks. Full article

(This article belongs to the Special Issue Advances in Econometric Analysis and Its Applications)

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14 pages, 273 KiB

Open AccessArticle

Internal Control and SMEs’ Sustainable Growth: The Moderating Role of Multiple Large Shareholders

by Liangcheng Wang, Yining Dai and Yuye Ding

J. Risk Financial Manag. 2019, 12(4), 182; https://doi.org/10.3390/jrfm12040182 - 04 Dec 2019

Cited by 9 | Viewed by 6029

Abstract

Small and medium enterprises (SMEs) face more risks for sustainable growth due to a lack of resources than large firms in emerging economies. Hence, it is more likely for SMEs to look to risk management for survival in turbulent markets. As a tool [...] Read more.

Small and medium enterprises (SMEs) face more risks for sustainable growth due to a lack of resources than large firms in emerging economies. Hence, it is more likely for SMEs to look to risk management for survival in turbulent markets. As a tool of risk management, whether internal control indeed has contributions to the sustainable growth of SMEs, particularly conditional on multiple large shareholders, is empirically unexplored. Using a sample of SMEs listed in China, this study examines the relationship between internal control and sustainable growth, and assesses a moderating role of multiple large shareholders. The results show that effective internal control significantly promotes SMEs to achieve sustainable growth, and the effect is moderated by multiple large shareholders, suggesting that the role of internal control is more prominent in SMEs with multiple large shareholders. These results are robust to a battery of sensitivity tests. This study extends the literature by providing empirical evidence on the role of internal control in SMEs’ sustainable growth. Full article

(This article belongs to the Section Business and Entrepreneurship)

21 pages, 460 KiB

Open AccessArticle

Enhancing Financial Inclusion in ASEAN: Identifying the Best Growth Markets for Fintech

by Mark Kam Loon Loo

J. Risk Financial Manag. 2019, 12(4), 181; https://doi.org/10.3390/jrfm12040181 - 04 Dec 2019

Cited by 23 | Viewed by 10247

Abstract

While most of the advanced economies are facing saturated markets, the Association of Southeast Asian Nations (ASEAN) has been touted a stable and attractive investment region averaging 5.4% growth since 1980. In 2013, ASEAN overtook China as the top foreign direct investment destination. [...] Read more.

While most of the advanced economies are facing saturated markets, the Association of Southeast Asian Nations (ASEAN) has been touted a stable and attractive investment region averaging 5.4% growth since 1980. In 2013, ASEAN overtook China as the top foreign direct investment destination. Boasting the world’s fifth largest economy with over 650 million people and 400 million reaching middle class, ASEAN has commendably transitioned from a subsistence economy to product and service industries. Despite the success, many live in marginalized areas without access to banking facilities. Advancing internet capability and availability present investors an opportunity to offer financial technology, or Fintech, to meet the need for financial services in this digital era. The aim of this research is to identify the countries with the highest need for financial inclusion and, hence, the best potential for Fintech growth. The results may help governments formulate policy that improves investment competitiveness. The methodology includes identifying relevant criteria and allocating weight to each criterion to evaluate the best international markets. The findings show Vietnam, Laos, and Cambodia as the countries with the highest potential. The associated risks and opportunities are discussed, followed by managerial implications, limitations, and recommendations for future research. Full article

(This article belongs to the Special Issue Contemporary Issues in Business and Economics)

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3 pages, 172 KiB

Open AccessEditorial

Nonparametric Econometric Methods and Applications

by Thanasis Stengos

J. Risk Financial Manag. 2019, 12(4), 180; https://doi.org/10.3390/jrfm12040180 - 30 Nov 2019

Viewed by 2087

Abstract

An area of very active research in econometrics over the last 30 years has been that of non- and semi-parametric methods. These methods have provided ways to complement more-traditional parametric approaches in terms of robust alternatives, as well as preliminary data analysis. The [...] Read more.

An area of very active research in econometrics over the last 30 years has been that of non- and semi-parametric methods. These methods have provided ways to complement more-traditional parametric approaches in terms of robust alternatives, as well as preliminary data analysis. The present Special Issue collects a number of new contributions, both theoretical and empirical that cover a wide spectrum of areas such as financial economics, microeconomics, macroeconomics, labor economics, and economic growth as well as statistical theory and methodology. Full article

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

11 pages, 257 KiB

Open AccessArticle

Testing the Information-Based Trading Hypothesis in the Option Market: Evidence from Share Repurchases

by Ihsan Badshah, Hardjo Koerniadi and James Kolari

J. Risk Financial Manag. 2019, 12(4), 179; https://doi.org/10.3390/jrfm12040179 - 29 Nov 2019

Cited by 1 | Viewed by 2688

Abstract

The informed options trading hypothesis posits that option prices lead stock prices. In this paper, we extended the research on this hypothesis to open-market share repurchases. Empirical tests showed that the implied volatility spread was not significantly related to buy-and-hold abnormal stock returns. [...] Read more.

The informed options trading hypothesis posits that option prices lead stock prices. In this paper, we extended the research on this hypothesis to open-market share repurchases. Empirical tests showed that the implied volatility spread was not significantly related to buy-and-hold abnormal stock returns. However, further evidence reveal a significant relationship between implied volatility spread and subsequent stock return volatility around open-market share repurchase events. We concluded that option traders have private information on the volatility of stock returns and superior information processing ability that accounts for prescient pricing behavior in options relative to stocks. Full article

(This article belongs to the Special Issue Option Pricing)

14 pages, 245 KiB

Open AccessPerspective

Encouraging Entrepreneurship and Economic Growth

by David Ahlstrom, Amber Y. Chang and Jessie S. T. Cheung

J. Risk Financial Manag. 2019, 12(4), 178; https://doi.org/10.3390/jrfm12040178 - 28 Nov 2019

Cited by 21 | Viewed by 6414

Abstract

The economy has seen unprecedented growth in the past two centuries, raising average incomes by 30-fold. With this added wealth, living standards also improved greatly. Although many factors impact economic growth, it is accepted that entrepreneurship plays a key role. Therefore, understanding the [...] Read more.

The economy has seen unprecedented growth in the past two centuries, raising average incomes by 30-fold. With this added wealth, living standards also improved greatly. Although many factors impact economic growth, it is accepted that entrepreneurship plays a key role. Therefore, understanding the antecedents of entrepreneurship and the link to economic development, often through institutions, should be of higher importance to researchers and policymakers. This Special Issue of the Journal of Risk and Financial Management sought to provide a brief overview of the economic growth literature and its link with entrepreneurship while adding insight through the Special Issue papers regarding the drivers of entrepreneurship in different contexts. Thus, the papers gathered here addressed several aspects of entrepreneurship and how it may be encouraged through networking, cornerstone investors in initial public offerings, new financing methods such as with cryptocurrencies, and through entrepreneur health. The research sites were primarily in Asia. This lead paper summarizes the issue’s papers while also providing a short overview of the economic growth literature and its link to entrepreneurship and institutions. This Special Issue, thus contributes to the empirical and theoretic research on the drivers of entrepreneurship and the association with economic growth. Full article

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

27 pages, 1356 KiB

Open AccessConcept Paper

Blockchain Economical Models, Delegated Proof of Economic Value and Delegated Adaptive Byzantine Fault Tolerance and their implementation in Artificial Intelligence BlockCloud

by Qi Deng

J. Risk Financial Manag. 2019, 12(4), 177; https://doi.org/10.3390/jrfm12040177 - 25 Nov 2019

Cited by 8 | Viewed by 4739

Abstract

The Artificial Intelligence BlockCloud (AIBC) is an artificial intelligence and blockchain technology based large-scale decentralized ecosystem that allows system-wide low-cost sharing of computing and storage resources. The AIBC consists of four layers: a fundamental layer, a resource layer, an application layer, and an [...] Read more.

The Artificial Intelligence BlockCloud (AIBC) is an artificial intelligence and blockchain technology based large-scale decentralized ecosystem that allows system-wide low-cost sharing of computing and storage resources. The AIBC consists of four layers: a fundamental layer, a resource layer, an application layer, and an ecosystem layer (the latter three are the collective “upper-layers”). The AIBC layers have distinguished responsibilities and thus performance and robustness requirements. The upper layers need to follow a set of economic policies strictly and run on a deterministic and robust protocol. While the fundamental layer needs to follow a protocol with high throughput without sacrificing robustness. As such, the AIBC implements a two-consensus scheme to enforce economic policies and achieve performance and robustness: Delegated Proof of Economic Value (DPoEV) incentive consensus on the upper layers, and Delegated Adaptive Byzantine Fault Tolerance (DABFT) distributed consensus on the fundamental layer. The DPoEV uses the knowledge map algorithm to accurately assess the economic value of digital assets. The DABFT uses deep learning techniques to predict and select the most suitable BFT algorithm in order to enforce the DPoEV, as well as to achieve the best balance of performance, robustness, and security. The DPoEV-DABFT dual-consensus architecture, by design, makes the AIBC attack-proof against risks such as double-spending, short-range and 51% attacks; it has a built-in dynamic sharding feature that allows scalability and eliminates the single-shard takeover. Our contribution is four-fold: that we develop a set of innovative economic models governing the monetary, trading and supply-demand policies in the AIBC; that we establish an upper-layer DPoEV incentive consensus algorithm that implements the economic policies; that we provide a fundamental layer DABFT distributed consensus algorithm that executes the DPoEV with adaptability; and that we prove the economic models can be effectively enforced by AIBC’s DPoEV-DABFT dual-consensus architecture. Full article

(This article belongs to the Special Issue AI and Financial Markets)

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11 pages, 247 KiB

Open AccessArticle

Foreign Direct Investment and Economic Growth in the Short Run and Long Run: Empirical Evidence from Developing Countries

by Trang Thi-Huyen Dinh, Duc Hong Vo, Anh The Vo and Thang Cong Nguyen

J. Risk Financial Manag. 2019, 12(4), 176; https://doi.org/10.3390/jrfm12040176 - 25 Nov 2019

Cited by 114 | Viewed by 17526

Abstract

A contribution of foreign direct investment to economic growth is possibly one of the widely examined topics in academic research in the last five decades. However, few studies have examined both the short run and long run impacts of this effect concurrently for [...] Read more.

A contribution of foreign direct investment to economic growth is possibly one of the widely examined topics in academic research in the last five decades. However, few studies have examined both the short run and long run impacts of this effect concurrently for developing and emerging markets, in particular during the period of economic turmoil that includes the global financial crisis. As such, this paper examines and provides additional and relevant quantitative evidence on the impact of foreign direct investment (FDI) on economic growth, both in the short run and the long run in developing countries of the lower-middle-income group in 2000–2014. Various econometric methods are employed such as the panel-based unit root test, Johansen cointegration test, Vector Error Correction Model (VECM), and Fully Modified OLS (FMOLS) to ensure the robustness of the findings. The results of this study show that FDI helps stimulate economic growth in the long run, although it has a negative impact in the short run for the countries in this study. Other macroeconomic factors also play an important role in explaining economic growth in these countries. Money supply has a positive effect on growth in the short run while total credit for private sector has a negative effect. In addition, long-run economic growth is driven by money supply, human capital, total domestic investment, and domestic credit for the private sector. Based on these results, recommendations for the governments of these countries have been developed. Full article

(This article belongs to the Special Issue Contemporary Issues in Business and Economics)

19 pages, 713 KiB

Open AccessArticle

The Effects of Environmental Regulation on the Singapore Stock Market

by Huy Pham, Van Nguyen, Vikash Ramiah, Priyantha Mudalige and Imad Moosa

J. Risk Financial Manag. 2019, 12(4), 175; https://doi.org/10.3390/jrfm12040175 - 24 Nov 2019

Cited by 13 | Viewed by 4426

Abstract

This study examines the impact of environmental regulation on the Singapore stock market using the event study methodology. Several asset pricing models are used to estimate sectoral abnormal returns. Additionally, we estimate the change in systematic risk after the introduction of the carbon [...] Read more.

This study examines the impact of environmental regulation on the Singapore stock market using the event study methodology. Several asset pricing models are used to estimate sectoral abnormal returns. Additionally, we estimate the change in systematic risk after the introduction of the carbon tax and related regulation. We conduct various robustness tests, including the Corrado non-parametric ranking test, the Chesney non-parametric conditional distribution approach, a representation of market integration, and Fama–French five-factor model. We find evidence showing that the environmental regulations tend to achieve their desired effects in Singapore in which several big polluters (including industrial metals and mining, forestry and papers, and electrical equipment and services) were negatively affected by the announcements of environmental regulations and carbon tax. In addition, our results indicate that the electricity sector, one of the biggest polluters, was negatively affected by the announcement of environmental regulations and carbon tax. We also find that environmental regulations seem to boost the performance of environmentally-friendly sectors whereby we find the alternative energy industry (focusing on new renewable energy technologies) experienced a sizeable positive reaction following the announcements of these regulations. Full article

(This article belongs to the Special Issue Green and Sustainable Finance)

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14 pages, 346 KiB

Open AccessArticle

Corporate Social Responsibility and SMEs in Vietnam: A Study in the Textile and Garment Industry

by Loan Thi-Hong Van and Phuong Anh Nguyen

J. Risk Financial Manag. 2019, 12(4), 174; https://doi.org/10.3390/jrfm12040174 - 23 Nov 2019

Cited by 13 | Viewed by 7298

Abstract

This study explored the influence of factors on the implementation of corporate social responsibility (CSR) in companies. The study used a quantitative approach in which a survey was conducted. The final 250 among various respondents in the textile and garment industry were used. [...] Read more.

This study explored the influence of factors on the implementation of corporate social responsibility (CSR) in companies. The study used a quantitative approach in which a survey was conducted. The final 250 among various respondents in the textile and garment industry were used. The final respondents were top-, middle-, and low-level managers in 250 small and medium enterprises (SMEs) in Vietnam. The results indicate that competitive context, social influences, the understanding of managers about CSR, and the internal environment of companies are the four drivers of CSR. In the four drivers, competitive context has the strongest impact on adopting CSR. The finding implies that stakeholders’ pressure influences SMEs in this industry because of the high expectations from international stakeholders. Full article

(This article belongs to the Special Issue Contemporary Issues in Business and Economics)

14 pages, 258 KiB

Open AccessArticle

Financial Development and Income Inequality in Emerging Markets: A New Approach

by Thang Cong Nguyen, Tan Ngoc Vu, Duc Hong Vo and Dao Thi-Thieu Ha

J. Risk Financial Manag. 2019, 12(4), 173; https://doi.org/10.3390/jrfm12040173 - 23 Nov 2019

Cited by 25 | Viewed by 5278

Abstract

Financial development has been considered an efficient and effective mechanism for the sustainable economic growth and development of emerging markets in past decades. However, various concerns have emerged in relation to the influences of financial sector development on income inequality. It is the [...] Read more.

Financial development has been considered an efficient and effective mechanism for the sustainable economic growth and development of emerging markets in past decades. However, various concerns have emerged in relation to the influences of financial sector development on income inequality. It is the claim of this paper that findings from the current literature are incomplete. This is because various proxies have been utilized inconsistently for both financial development and income inequality in previous empirical studies. This study extends the current literature on this important finance–inequality nexus by examining a sample of 21 emerging countries for the period of 1961–2017. Various estimation techniques were employed with the aim of ensuring robust findings. Findings from this paper confirm the existence of an inverted U-curve relationship between financial development and income inequality, implying that income inequality may rise at the early stage of financial development and fall after a certain level is achieved. Policy implications have emerged from the findings of this study. Full article

(This article belongs to the Special Issue Contemporary Issues in Business and Economics)

16 pages, 1325 KiB

Open AccessArticle

Double Taxation Treaties as a Catalyst for Trade Developments: A Comparative Study of Vietnam’s Relations with ASEAN and EU Member States

by Anh D. Pham, Ha Pham and Kim Cuong Ly

J. Risk Financial Manag. 2019, 12(4), 172; https://doi.org/10.3390/jrfm12040172 - 23 Nov 2019

Cited by 9 | Viewed by 6851

Abstract

Employing a panel gravity model and Generalized Least Squares (GLS) estimation technique, this study documents the effect of double taxation treaties on the bilateral trade of Vietnam with ASEAN member states, thereby making an extensive comparison with its EU partner countries. Our findings [...] Read more.

Employing a panel gravity model and Generalized Least Squares (GLS) estimation technique, this study documents the effect of double taxation treaties on the bilateral trade of Vietnam with ASEAN member states, thereby making an extensive comparison with its EU partner countries. Our findings indicate the significant contributions of the tax treaties to Vietnam’s trade performance, not exclusively with ASEAN but also with EU partner countries. Nevertheless, under some circumstances, the conclusion of tax treaties seems ineffective in strengthening export capacity or narrowing trade deficits for Vietnam. This is primarily due to the unidirectional movement of trade associated with tax treaty conditions, viz., imports from the advanced economies into Vietnam. Besides, the role of tax treaties as a dynamism of Vietnam’s export growth remains opaque during recent years. Full article

(This article belongs to the Special Issue Contemporary Issues in Business and Economics)

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28 pages, 850 KiB

Open AccessArticle

An Universal, Simple, Circular Statistics-Based Estimator of α for Symmetric Stable Family

by Ashis SenGupta and Moumita Roy

J. Risk Financial Manag. 2019, 12(4), 171; https://doi.org/10.3390/jrfm12040171 - 23 Nov 2019

Cited by 2 | Viewed by 2165

Abstract

The aim of this article is to obtain a simple and efficient estimator of the index parameter of symmetric stable distribution that holds universally, i.e., over the entire range of the parameter. We appeal to directional statistics on the classical result on wrapping [...] Read more.

The aim of this article is to obtain a simple and efficient estimator of the index parameter of symmetric stable distribution that holds universally, i.e., over the entire range of the parameter. We appeal to directional statistics on the classical result on wrapping of a distribution in obtaining the wrapped stable family of distributions. The performance of the estimator obtained is better than the existing estimators in the literature in terms of both consistency and efficiency. The estimator is applied to model some real life financial datasets. A mixture of normal and Cauchy distributions is compared with the stable family of distributions when the estimate of the parameter

α

lies between 1 and 2. A similar approach can be adopted when

α

(or its estimate) belongs to (0.5,1). In this case, one may compare with a mixture of Laplace and Cauchy distributions. A new measure of goodness of fit is proposed for the above family of distributions. Full article

(This article belongs to the Special Issue Financial Statistics and Data Analytics)

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17 pages, 1639 KiB

Open AccessReview

A Survey on Empirical Findings about Spillovers in Cryptocurrency Markets

by Nikolaos A. Kyriazis

J. Risk Financial Manag. 2019, 12(4), 170; https://doi.org/10.3390/jrfm12040170 - 12 Nov 2019

Cited by 55 | Viewed by 8440

Abstract

This paper provides a systematic survey on return and volatility spillovers of cryptocurrencies based on the empirical results of relevant academic literature. Evidence reveals that Bitcoin is the most influential among digital coins mainly as a transmitter toward digital currencies but also as [...] Read more.

This paper provides a systematic survey on return and volatility spillovers of cryptocurrencies based on the empirical results of relevant academic literature. Evidence reveals that Bitcoin is the most influential among digital coins mainly as a transmitter toward digital currencies but also as a receiver of spillovers from virtual currencies and alternative assets. Ethereum, Litecoin, and Ripple present the most significant interlinkages with Bitcoin. Return spillovers are more pronounced but volatility spillovers often present a bi-directional character. Volatility shock transmission is detected among Bitcoin and national currencies, while economic policy uncertainty is not influential. This survey provides useful guidance in the hotly-debated issue of reform and decentralization of financial systems. Full article

(This article belongs to the Special Issue Recent Developments in Cryptocurrency Markets: Co-movements, Spillovers and Forecasting)

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15 pages, 417 KiB

Open AccessArticle

The Dali Model in Risk-Management Practice: The Case of Financial Services Firms

by Rebecca Dalli Gonzi, Simon Grima, Murat Kizilkaya and Jonathan Spiteri

J. Risk Financial Manag. 2019, 12(4), 169; https://doi.org/10.3390/jrfm12040169 - 07 Nov 2019

Cited by 6 | Viewed by 3531

Abstract

Originality/value—this model contributed to the vast literature on models of change and risk management within organisations, but was not validated empirically for reliability of the factors, and on financial services providers within small jurisdictions. Therefore, the significance and importance of such a study [...] Read more.

Originality/value—this model contributed to the vast literature on models of change and risk management within organisations, but was not validated empirically for reliability of the factors, and on financial services providers within small jurisdictions. Therefore, the significance and importance of such a study lies firstly on the premise that testing on small countries can be deemed as small laboratories for more complex politics, regulations and policies of larger countries and secondly, the importance of financial services as essential for prosperity in a country’s economy. This model will provide an empirically tested proactive model in a specific environment for managing organisational risks to arrive at their objectives with minimal setbacks. Full article

(This article belongs to the Special Issue Mechanisms and Models of Risk Management)

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15 pages, 3616 KiB

Open AccessArticle

Global Asset Allocation Strategy Using a Hidden Markov Model

by Eun-chong Kim, Han-wook Jeong and Nak-young Lee

J. Risk Financial Manag. 2019, 12(4), 168; https://doi.org/10.3390/jrfm12040168 - 06 Nov 2019

Cited by 8 | Viewed by 7661

Abstract

This study uses the hidden Markov model (HMM) to identify the phases of individual assets and proposes an investment strategy using price trends effectively. We conducted empirical analysis for 15 years from January 2004 to December 2018 on universes of global assets divided [...] Read more.

This study uses the hidden Markov model (HMM) to identify the phases of individual assets and proposes an investment strategy using price trends effectively. We conducted empirical analysis for 15 years from January 2004 to December 2018 on universes of global assets divided into 10 classes and the more detailed 22 classes. Both universes have been shown to have superior performance in strategy using HMM in common. By examining the change in the weight of the portfolio, the weight change between the asset classes occurs dynamically. This shows that HMM increases the weight of stocks when stock price rises and increases the weight of bonds when stock price falls. As a result of analyzing the performance, it was shown that the HMM effectively reflects the asset selection effect in Jensen’s alpha, Fama’s Net Selectivity and Treynor-Mazuy model. In addition, the strategy of the HMM has positive gamma value even in the Treynor-Mazuy model. Ultimately, HMM is expected to enable stable management compared to existing momentum strategies by having asset selection effect and market forecasting ability. Full article

(This article belongs to the Special Issue AI and Financial Markets)

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34 pages, 2518 KiB

Open AccessArticle

How Long Does It Last to Systematically Make Bad Decisions? An Agent-Based Application for Dividend Policy

by Victor Dragotă and Camelia Delcea

J. Risk Financial Manag. 2019, 12(4), 167; https://doi.org/10.3390/jrfm12040167 - 05 Nov 2019

Cited by 4 | Viewed by 3371

Abstract

Bad decisions have harmful effects on the quality of human life and an increase of their duration expands these undesirable effects. Systematic bad decisions related to dividend policy can affect the investors’ quality of life in the long-term. We propose an agent-based model [...] Read more.

Bad decisions have harmful effects on the quality of human life and an increase of their duration expands these undesirable effects. Systematic bad decisions related to dividend policy can affect the investors’ quality of life in the long-term. We propose an agent-based model for the estimation of the duration of systematically making bad decisions, with an application on dividend policy. We propose an algorithm that can be used in modelling the interaction between different classes of shareholders and for predicting this duration. We perform numerical simulations based on this model using NetLogo 6.0.4. We prove that, as a result of agents’ interaction, in some conditions, the duration of systematically making bad decisions can be very long: some numerical simulations suggest that, in some circumstances, this duration can significantly exceed the human lifetime. Additionally, in some conditions, the company can fail before the power is switched. This duration can increase dramatically if the shareholders have a great level of trust in the management’s decisions. As an implication, a greater concern for the quality of financial education, and more performant instruments for controlling the power’s decisions are required. Full article

(This article belongs to the Special Issue Corporate Finance)

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15 pages, 704 KiB

Open AccessArticle

Social and Financial Inclusion through Nonbanking Institutions: A Model for Rural Romania

by Xiao-Guang Yue, Yong Cao, Nelson Duarte, Xue-Feng Shao and Otilia Manta

J. Risk Financial Manag. 2019, 12(4), 166; https://doi.org/10.3390/jrfm12040166 - 29 Oct 2019

Cited by 14 | Viewed by 4489

Abstract

The challenges of financial systems have immediate or medium-term social effects. The financial industry is constantly searching for measures to reduce these challenges, especially for those with little or no access to financial services. While current communication technologies make services more accessible through [...] Read more.

The challenges of financial systems have immediate or medium-term social effects. The financial industry is constantly searching for measures to reduce these challenges, especially for those with little or no access to financial services. While current communication technologies make services more accessible through digital mobile platforms, there are still difficulties in establishing viable customer arrangements. In addition to the increased investment in financial technologies, nonbanking financial institutions have now expanded to offer more flexible services tailored to individual circumstances, especially those in isolated rural areas. This research outlines the network model of nonbanking financial institutions in Romania, as well as a microfinance model, based on the financial analysis of four national indicators of nonbanking financial institutions. Data used are presented in absolute values, from the annual numerical series for the reference period 2007–2017. The new initiatives and features incorporated in this Romanian model should be applicable elsewhere and will actively contribute to the expansion and sustainability of financial services, with a positive inclusive impact on society. Full article

(This article belongs to the Special Issue AI and Financial Markets)

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26 pages, 518 KiB

Open AccessReview

The Cross Section of Country Equity Returns: A Review of Empirical Literature

by Adam Zaremba

J. Risk Financial Manag. 2019, 12(4), 165; https://doi.org/10.3390/jrfm12040165 - 28 Oct 2019

Cited by 24 | Viewed by 6274

Abstract

The last three decades brought mounting evidence regarding the cross-sectional predictability of country equity returns. The studies not only documented country-level counterparts of well-established stock-level anomalies, such as size, value, or momentum, but also demonstrated some unique return-predicting signals such as fund flows [...] Read more.

The last three decades brought mounting evidence regarding the cross-sectional predictability of country equity returns. The studies not only documented country-level counterparts of well-established stock-level anomalies, such as size, value, or momentum, but also demonstrated some unique return-predicting signals such as fund flows or political regimes. Nonetheless, the different studies vary remarkably in terms of their dataset and methods employed. This study aims to provide a comprehensive review of the current literature on the cross-section of country equity returns. We focus on three particular aspects of the asset pricing literature. First, we study the choice of dataset and sample preparation methods. Second, we survey different aspects of the methodological approaches. Last but not least, we review the country-level equity anomalies discovered so far. The discussed cross-sectional return patterns not only provide new insights into international asset pricing but can also be potentially translated into effective country allocation strategies. Full article

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

26 pages, 510 KiB

Open AccessArticle

Price Discovery of a Speculative Asset: Evidence from a Bitcoin Exchange

by Eric Ghysels and Giang Nguyen

J. Risk Financial Manag. 2019, 12(4), 164; https://doi.org/10.3390/jrfm12040164 - 25 Oct 2019

Cited by 6 | Viewed by 5395

Abstract

We examine price discovery and liquidity provision in the secondary market for bitcoin—an asset with a high level of speculative trading. Based on BTC-e’s full limit order book over the 2013–2014 period, we find that order informativeness increases with order aggressiveness within the [...] Read more.

We examine price discovery and liquidity provision in the secondary market for bitcoin—an asset with a high level of speculative trading. Based on BTC-e’s full limit order book over the 2013–2014 period, we find that order informativeness increases with order aggressiveness within the first 10 tiers, but that this pattern reverses in outer tiers. In a high volatility environment, aggressive orders seem to be more attractive to informed agents, but market liquidity migrates outward in response to the information asymmetry. We also find support to the Markovian learning assumption often made in theoretical models of limit order markets. Full article

(This article belongs to the Section Financial Markets)

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16 pages, 346 KiB

Open AccessArticle

Exploring the Determinants of Financial Structure in the Technology Industry: Panel Data Evidence from the New York Stock Exchange Listed Companies

by Georgeta Vintilă, Ştefan Cristian Gherghina and Diana Alexandra Toader

J. Risk Financial Manag. 2019, 12(4), 163; https://doi.org/10.3390/jrfm12040163 - 22 Oct 2019

Cited by 6 | Viewed by 4296

Abstract

This paper aims to analyze the influencing factors on the financial structure of 51 companies listed on the New York Stock Exchange, in the technology industry, from 2005–2018. The objective is to see the impact of independent company-specific variables such as company size, [...] Read more.

This paper aims to analyze the influencing factors on the financial structure of 51 companies listed on the New York Stock Exchange, in the technology industry, from 2005–2018. The objective is to see the impact of independent company-specific variables such as company size, tangibility of assets, growth opportunity, effective tax rate, current liquidity, depreciation, stock rotation, financial return, working capital, price to book value, price to earnings ratio, as well as the impact of governance variables and macroeconomic variables such as inflation rate, interest rate, market size, gross domestic product per capita. Using panel data and multiple linear regressions, we analyze the relationship between the independent variables listed above and the dependent variables, namely the total debt ratio, the long-term debt ratio and the short-term debt ratio. The results of the analysis showed that variables such as size, tangibility, liquidity, profitability have a significant influence on the dependent variables in accordance with the theories regarding the capital structure. Full article

(This article belongs to the Special Issue Corporate Finance)

79 pages, 8288 KiB

Open AccessArticle

An Exploratory Study Based on a Questionnaire Concerning Green and Sustainable Finance, Corporate Social Responsibility, and Performance: Evidence from the Romanian Business Environment

by Cristina Raluca Gh. Popescu and Gheorghe N. Popescu

J. Risk Financial Manag. 2019, 12(4), 162; https://doi.org/10.3390/jrfm12040162 - 18 Oct 2019

Cited by 88 | Viewed by 17979

Abstract

Green and sustainable finance, corporate social responsibility and financial and non-financial performance are attracting widespread interest due to the challenging times that the business environment is currently facing. Moreover, green and sustainable finance, corporate social responsibility, and intellectual and human capital have become [...] Read more.

Green and sustainable finance, corporate social responsibility and financial and non-financial performance are attracting widespread interest due to the challenging times that the business environment is currently facing. Moreover, green and sustainable finance, corporate social responsibility, and intellectual and human capital have become central issues in measuring organizations’ success, competitive advantage and influence on the marketplace. This scientific paper seeks to address the relationship between corporate social responsibility, intellectual capital and performance, providing valuable insights and relevant evidence from a Romanian business environment. The questionnaire method was used for the targeted research objectives, which referred to: (a) Romanian organizations and local community understanding of green and sustainable finance, corporate social responsibility and intellectual capital; (b) corporate social responsibility actions taken by Romanian organizations and the local community; (c) main drivers of corporate social responsibility and intellectual capital in Romanian organizations; and (d) ways to enhance financial and non-financial performance of Romanian organizations with the aid of corporate social responsibility and intellectual capital. The findings support the idea of a strong relationship between corporate social responsibility, intellectual capital and performance in the Romanian business environment. Our work shows that, broadly speaking, Romanian entities operate on a socially responsible level, being aware of the importance and the advantages brought by both corporate social responsibility and intellectual capital when it comes to enhancing profit, productivity and performance. Our results are highly encouraging and may be validated by a larger sample size. Full article

(This article belongs to the Section Sustainability and Finance)

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20 pages, 11686 KiB

Open AccessArticle

ISA 701 and Materiality Disclosure as Methods to Minimize the Audit Expectation Gap

by Tomasz Iwanowicz and Bartłomiej Iwanowicz

J. Risk Financial Manag. 2019, 12(4), 161; https://doi.org/10.3390/jrfm12040161 - 16 Oct 2019

Cited by 3 | Viewed by 6340

Abstract

Purpose: The main purpose of this paper is to determine how particular audit firms deal with ISA 701 requirements and the society expectations towards reporting the materiality levels. Additionally, the aim of this paper is to range the assertions in terms of the [...] Read more.

Purpose: The main purpose of this paper is to determine how particular audit firms deal with ISA 701 requirements and the society expectations towards reporting the materiality levels. Additionally, the aim of this paper is to range the assertions in terms of the frequency of their occurrence. Design/methodology/approach: The tested sample consisted of 317 companies listed on Warsaw (158 companies) or London (159 companies) stock exchange. The analysis was divided into companies from the following ten market indexes (WIGs): construction, IT, real estate, food, media, oil and gas, mining, energy, automotive and chemicals. The research was executed based on the analysis of annual consolidated financial statements (annual reports) and independent auditor reports that were published by in-scope entities for the latest twelve-months period available as at the date of the research (mostly periods ended on 31 December 2017 and 31 March 2018). All values were denominated to euro (EUR) with use of average exchange rates published by the National Bank of Poland. All performed analyses and developed charts were supported by Microsoft Power BI data analysis tool. Findings: The general conclusion, which may be drawn from this research, is that implementation of ISA 701 and materiality disclosure limited the audit expectation gap. Detailed observations are described throughout the paper and summarized in the conclusions section. Originality/value: This study extends the prior research by providing various dimensions of the analysed matters. It contributes to understanding of the audit expectation gap and investigates on methods of minimizing it. Full article

(This article belongs to the Special Issue Modern Methods of Bankruptcy Prediction)

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J. Risk Financial Manag., Volume 12, Issue 4 (December 2019) – 37 articles

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