Open AccessArticle
Credit Rating and Pricing: Poles Apart
J. Risk Financial Manag. 2018, 11(2), 27; https://doi.org/10.3390/jrfm11020027 -
Abstract
Corporate credit ratings remove the information asymmetry between lenders and borrowers to find an equilibrium price. Structured finance ratings, however, are informationally insufficient because the systematic risk of equally rated assets can vary substantially. As I demonstrate in a Monte Carlo analysis, highly-rated
[...] Read more.
Corporate credit ratings remove the information asymmetry between lenders and borrowers to find an equilibrium price. Structured finance ratings, however, are informationally insufficient because the systematic risk of equally rated assets can vary substantially. As I demonstrate in a Monte Carlo analysis, highly-rated structured finance bonds can exhibit far higher non-linear systematic risks than lowly-rated corporate bonds. I value credit instruments under a four-moment CAPM, between and within some markets there is no one-to-one relation between expected loss (rating) and credit spread (pricing). The linear CAPM beta is insufficient, buyers and sellers need also the same information on non-linear risk to have an equilibrium. Full article
Figures

Figure 1

Open AccessArticle
The Wolf and the Caribou: Coexistence of Decentralized Economies and Competitive Markets
J. Risk Financial Manag. 2018, 11(2), 26; https://doi.org/10.3390/jrfm11020026 -
Abstract
Starting with BitTorrent and then Bitcoin, decentralized technologies have been on the rise over the last 15+ years, gaining significant momentum in the last 2+ years with the advent of platform ecosystems such as the Blockchain platform Ethereum. New projects have evolved from
[...] Read more.
Starting with BitTorrent and then Bitcoin, decentralized technologies have been on the rise over the last 15+ years, gaining significant momentum in the last 2+ years with the advent of platform ecosystems such as the Blockchain platform Ethereum. New projects have evolved from decentralized games to marketplaces to open funding models to decentralized autonomous organizations. The hype around cryptocurrency and the valuation of innovative projects drove the market cap of cryptocurrencies to over a trillion dollars at one point in 2017. These high valued technologies are now enabling something new: globally scaled and decentralized business models. Despite their valuation and the hype, these new business ecosystems are frail. This is not only because the underlying technology is rapidly evolving, but also because competitive markets see a profit opportunity in exponential cryptocurrency returns. This extracts value from these ecosystems, which could lead to their collapse, if unchecked. In this paper, we explore novel ways for decentralized economies to protect themselves from, and coexist with, competitive markets at a global scale utilizing decentralized technologies such as Blockchain. Full article
Figures

Figure 1

Open AccessFeature PaperArticle
Mean-Variance Portfolio Selection in a Jump-Diffusion Financial Market with Common Shock Dependence
J. Risk Financial Manag. 2018, 11(2), 25; https://doi.org/10.3390/jrfm11020025 -
Abstract
This paper considers the optimal investment problem in a financial market with one risk-free asset and one jump-diffusion risky asset. It is assumed that the insurance risk process is driven by a compound Poisson process and the two jump number processes are correlated
[...] Read more.
This paper considers the optimal investment problem in a financial market with one risk-free asset and one jump-diffusion risky asset. It is assumed that the insurance risk process is driven by a compound Poisson process and the two jump number processes are correlated by a common shock. A general mean-variance optimization problem is investigated, that is, besides the objective of terminal condition, the quadratic optimization functional includes also a running penalizing cost, which represents the deviations of the insurer’s wealth from a desired profit-solvency goal. By solving the Hamilton-Jacobi-Bellman (HJB) equation, we derive the closed-form expressions for the value function, as well as the optimal strategy. Moreover, under suitable assumption on model parameters, our problem reduces to the classical mean-variance portfolio selection problem and the efficient frontier is obtained. Full article
Figures

Figure 1

Open AccessArticle
Credit Ratings and Liquidity Risk for the Optimization of Debt Maturity Structure
J. Risk Financial Manag. 2018, 11(2), 24; https://doi.org/10.3390/jrfm11020024 -
Abstract
The purpose of this study is to examine the relationship between credit rating scales and debt maturity choices. A liquidity hypothesis is used to formulate the testable proposition and conceptual framework. Generalized linear model (GLM) and pooled ordinary least square (OLS) are utilized
[...] Read more.
The purpose of this study is to examine the relationship between credit rating scales and debt maturity choices. A liquidity hypothesis is used to formulate the testable proposition and conceptual framework. Generalized linear model (GLM) and pooled ordinary least square (OLS) are utilized by SAS programming to test the proposed hypothesis. Other different estimation techniques are also used for robust evidence. Results suggest that companies with high and low ratings have a shorter debt maturity. Companies with medium ratings have longer debt maturity structure. Liquidity shows a negative association with longer debt maturity structure. It is evident that at high rating scale with high liquidity, and at lower rating scales with lower liquidity firms have a shorter debt maturity. Mid rated firms with a low probability of refinancing risk show longer debt maturity structure. Considering refinancing risk by Asian companies make the nonlinear relationship between credit ratings and debt maturity choices. Results suggest the importance of credit ratings for the optimization of debt maturity structure of Asian firms, which was totally overlooked by the past studies. The findings of this study are consistent with the liquidity hypothesis. The findings also motivating financial managers and investors to consider credit ratings as a measure of financial constraints. Full article
Figures

Figure 1

Open AccessArticle
Long- and Short-Term Cryptocurrency Volatility Components: A GARCH-MIDAS Analysis
J. Risk Financial Manag. 2018, 11(2), 23; https://doi.org/10.3390/jrfm11020023 -
Abstract
We use the GARCH-MIDAS model to extract the long- and short-term volatility components of cryptocurrencies. As potential drivers of Bitcoin volatility, we consider measures of volatility and risk in the US stock market as well as a measure of global economic activity. We
[...] Read more.
We use the GARCH-MIDAS model to extract the long- and short-term volatility components of cryptocurrencies. As potential drivers of Bitcoin volatility, we consider measures of volatility and risk in the US stock market as well as a measure of global economic activity. We find that S&P 500 realized volatility has a negative and highly significant effect on long-term Bitcoin volatility. The finding is atypical for volatility co-movements across financial markets. Moreover, we find that the S&P 500 volatility risk premium has a significantly positive effect on long-term Bitcoin volatility. Finally, we find a strong positive association between the Baltic dry index and long-term Bitcoin volatility. This result shows that Bitcoin volatility is closely linked to global economic activity. Overall, our findings can be used to construct improved forecasts of long-term Bitcoin volatility. Full article
Figures

Figure 1

Open AccessArticle
Investigation of the Financial Stability of S&P 500 Using Realized Volatility and Stock Returns Distribution
J. Risk Financial Manag. 2018, 11(2), 22; https://doi.org/10.3390/jrfm11020022 -
Abstract
In this work, the financial data of 377 stocks of Standard & Poor’s 500 Index (S&P 500) from the years 1998–2012 with a 250-day time window were investigated by measuring realized stock returns and realized volatility. We examined the normal distribution and frequency
[...] Read more.
In this work, the financial data of 377 stocks of Standard & Poor’s 500 Index (S&P 500) from the years 1998–2012 with a 250-day time window were investigated by measuring realized stock returns and realized volatility. We examined the normal distribution and frequency distribution for both daily stock returns and volatility. We also determined the beta-coefficient and correlation among the stocks for 15 years and found that, during the crisis period, the beta-coefficient between the market index and stock’s prices and correlation among stock’s prices increased remarkably and decreased during the non-crisis period. We compared the stock volatility and stock returns for specific time periods i.e., non-crisis, before crisis and during crisis year in detail and found that the distribution behaviors of stock return prices has a better long-term effect that allows predictions of near-future market behavior than realized volatility of stock returns. Our detailed statistical analysis provides a valuable guideline for both researchers and market participants because it provides a significantly clearer comparison of the strengths and weaknesses of the two methods. Full article
Figures

Graphical abstract

Open AccessArticle
Testing for Causality-In-Mean and Variance between the UK Housing and Stock Markets
J. Risk Financial Manag. 2018, 11(2), 21; https://doi.org/10.3390/jrfm11020021 -
Abstract
This paper employs the two-step procedure to analyze the causality-in-mean and causality-in-variance between the housing and stock markets of the UK. The empirical findings make two key contributions. First, although previous studies have indicated a one-way causal relation from the housing market to
[...] Read more.
This paper employs the two-step procedure to analyze the causality-in-mean and causality-in-variance between the housing and stock markets of the UK. The empirical findings make two key contributions. First, although previous studies have indicated a one-way causal relation from the housing market to the stock market in the UK, this paper discovered a two-way causal relation between them. Second, a causality-in-variance as well as a causality-in-mean was detected from the housing market to the stock market. Full article
Figures

Graphical abstract

Open AccessEditorial
Editorial Note: Review Papers for Journal of Risk and Financial Management (JRFM)
J. Risk Financial Manag. 2018, 11(2), 20; https://doi.org/10.3390/jrfm11020020 -
Abstract
The Journal of Risk and Financial Management (JRFM) was inaugurated in 2008 and has continued publishing successfully with Volume 11 in 2018. Since the journal was established, JRFM has published in excess of 110 topical and interesting theoretical and empirical papers in financial
[...] Read more.
The Journal of Risk and Financial Management (JRFM) was inaugurated in 2008 and has continued publishing successfully with Volume 11 in 2018. Since the journal was established, JRFM has published in excess of 110 topical and interesting theoretical and empirical papers in financial economics, financial econometrics, banking, finance, mathematical finance, statistical finance, accounting, decision sciences, information management, tourism economics and finance, international rankings of journals in financial economics, and bibliometric rankings of journals in cognate disciplines. Papers published in the journal range from novel technical and theoretical papers to innovative empirical contributions. The journal wishes to encourage critical review papers on topical subjects in any of the topics mentioned above in financial economics and in cognate disciplines. Full article
Open AccessArticle
Exchange Rate Effects on International Commercial Trade Competitiveness
J. Risk Financial Manag. 2018, 11(2), 19; https://doi.org/10.3390/jrfm11020019 -
Abstract
This study is meant to be an evaluation sustained by theoretical and empirical considerations of the exchange rate impact on international commercial trade competitiveness. In this respect, the study aims to find how the exchange rate influences Romanian competitiveness through assessing the effects
[...] Read more.
This study is meant to be an evaluation sustained by theoretical and empirical considerations of the exchange rate impact on international commercial trade competitiveness. In this respect, the study aims to find how the exchange rate influences Romanian competitiveness through assessing the effects generated on exports and imports. The main purpose of the study is to assess the complex action of the exchange rate on international commercial trade competitiveness in contemporaneity and the connections between these variables. The empirical part contains a regression analysis where exports and imports are dependent variables influenced by a series of determinants. Full article
Figures

Figure 1

Open AccessArticle
Value-at-Risk for South-East Asian Stock Markets: Stochastic Volatility vs. GARCH
J. Risk Financial Manag. 2018, 11(2), 18; https://doi.org/10.3390/jrfm11020018 -
Abstract
This study compares the performance of several methods to calculate the Value-at-Risk of the six main ASEAN stock markets. We use filtered historical simulations, GARCH models, and stochastic volatility models. The out-of-sample performance is analyzed by various backtesting procedures. We find that simpler
[...] Read more.
This study compares the performance of several methods to calculate the Value-at-Risk of the six main ASEAN stock markets. We use filtered historical simulations, GARCH models, and stochastic volatility models. The out-of-sample performance is analyzed by various backtesting procedures. We find that simpler models fail to produce sufficient Value-at-Risk forecasts, which appears to stem from several econometric properties of the return distributions. With stochastic volatility models, we obtain better Value-at-Risk forecasts compared to GARCH. The quality varies over forecasting horizons and across markets. This indicates that, despite a regional proximity and homogeneity of the markets, index volatilities are driven by different factors. Full article
Figures

Figure 1

Open AccessArticle
Equity Options During the Shorting Ban of 2008
J. Risk Financial Manag. 2018, 11(2), 17; https://doi.org/10.3390/jrfm11020017 -
Abstract
The Securities and Exchange Commission’s 2008 emergency order introduced a shorting ban of some 800 financials traded in the US. This paper provides an empirical analysis of the options market around the ban period. Using transaction level data from OPRA (The Options Price
[...] Read more.
The Securities and Exchange Commission’s 2008 emergency order introduced a shorting ban of some 800 financials traded in the US. This paper provides an empirical analysis of the options market around the ban period. Using transaction level data from OPRA (The Options Price Reporting Authority), we study the options volume, spreads, pricing measures and option trade volume informativeness during the ban. We also consider the put–call parity relationship. While mostly statistically significant, economic magnitudes of our results suggest that the impact of the ban on the equity options market was likely not as dramatic as initially thought. Full article
Figures

Figure 1a

Open AccessArticle
Contagion Effect of Natural Disaster and Financial Crisis Events on International Stock Markets
J. Risk Financial Manag. 2018, 11(2), 16; https://doi.org/10.3390/jrfm11020016 -
Abstract
In the contemporary world bustling with global trade, a natural disaster or financial crisis in one country (or region) can cause substantial economic losses and turbulence in the local financial markets, which may then affect the economic activities and financial assets of other
[...] Read more.
In the contemporary world bustling with global trade, a natural disaster or financial crisis in one country (or region) can cause substantial economic losses and turbulence in the local financial markets, which may then affect the economic activities and financial assets of other countries (or regions). This study focuses on the major natural disasters that occurred worldwide during the last decade, especially those in the Asia–Pacific region, and the economic effects of global financial crises. The heteroscedasticity bias correlation coefficient method and exponential general autoregressive conditional heteroscedasticity model are employed to compare the contagion effect in the stock markets of the initiating country on other countries, determining whether economically devastating factors have contagion or spillover effects on other countries. The empirical results indicate that among all the natural disasters considered, the 2008 Sichuan Earthquake in China caused the most substantial contagion effect in the stock markets of neighboring Asian countries. Regarding financial crises, the financial tsunami triggered by the secondary mortgage fallout in the United States generated the strongest contagion effect on the stock markets of developing and emerging economies. When building a diversified global investment portfolio, investors should be aware of the risks of major natural disasters and financial incidents. Full article
Open AccessFeature PaperReview
Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology: Connections
J. Risk Financial Manag. 2018, 11(1), 15; https://doi.org/10.3390/jrfm11010015 -
Abstract
The paper provides a review of the literature that connects Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology, and discusses research issues that are related to the various disciplines. Academics could develop theoretical models and subsequent econometric and statistical models to
[...] Read more.
The paper provides a review of the literature that connects Big Data, Computational Science, Economics, Finance, Marketing, Management, and Psychology, and discusses research issues that are related to the various disciplines. Academics could develop theoretical models and subsequent econometric and statistical models to estimate the parameters in the associated models, as well as conduct simulation to examine whether the estimators in their theories on estimation and hypothesis testing have good size and high power. Thereafter, academics and practitioners could apply theory to analyse some interesting issues in the seven disciplines and cognate areas. Full article
Open AccessFeature PaperArticle
Groups, Pricing, and Cost of Debt: Evidence from Turkey
J. Risk Financial Manag. 2018, 11(1), 14; https://doi.org/10.3390/jrfm11010014 -
Abstract
The paper examines the impact of business group affiliation on cost of loans in an emerging market setting. It focuses on operational strategy, organizational structure and internationalization policies of business group firms and their impact on borrowing cost of affiliated firms. Bank loans
[...] Read more.
The paper examines the impact of business group affiliation on cost of loans in an emerging market setting. It focuses on operational strategy, organizational structure and internationalization policies of business group firms and their impact on borrowing cost of affiliated firms. Bank loans are a dominant source of corporate funding in emerging markets, in which business groups exist as leading economic entities. Yet, the impact of belonging to a group on the firm’s cost of debt has not been studied in depth. Our results reveal that the extent of group affiliation, government ownership, and diversification increase the cost of loans. However, a group bank is advantageous in terms of borrowing, and decreases the cost of loans. While foreign ownership is beneficial in terms of pricing, being affiliated with a foreign group is not. Being a financial firm and being cross-listed are not significantly associated with bank loan terms. Borrowing costs are thus influenced in various ways by organizational structure, operational strategies, and global policies of business groups and affiliates. Therefore, business groups may benefit from strategically implementing policies and selecting loan applicant firms. Full article
Open AccessArticle
Hierarchical Transmuted Log-Logistic Model: A Subjective Bayesian Analysis
J. Risk Financial Manag. 2018, 11(1), 13; https://doi.org/10.3390/jrfm11010013 -
Abstract
In this study, we propose to apply the transmuted log-logistic (TLL) model which is a generalization of log-logistic model, in a Bayesian context. The log-logistic model has been used it is simple and has a unimodal hazard rate, important characteristic in survival analysis.
[...] Read more.
In this study, we propose to apply the transmuted log-logistic (TLL) model which is a generalization of log-logistic model, in a Bayesian context. The log-logistic model has been used it is simple and has a unimodal hazard rate, important characteristic in survival analysis. Also, the TLL model was formulated by using the quadratic transmutation map, that is a simple way of derivating new distributions, and it adds a new parameter λ, which one introduces a skewness in the new distribution and preserves the moments of the baseline model. The Bayesian model was formulated by using the half-Cauchy prior which is an alternative prior to a inverse Gamma distribution. In order to fit the model, a real data set, which consist of the time up to first calving of polled Tabapua race, was used. Finally, after the model was fitted, an influential analysis was made and excluding only 0.1% of observations (influential points), the reestimated model can fit the data better. Full article
Figures

Graphical abstract

Open AccessArticle
Ensemble Learning or Deep Learning? Application to Default Risk Analysis
J. Risk Financial Manag. 2018, 11(1), 12; https://doi.org/10.3390/jrfm11010012 -
Abstract
Proper credit-risk management is essential for lending institutions, as substantial losses can be incurred when borrowers default. Consequently, statistical methods that can measure and analyze credit risk objectively are becoming increasingly important. This study analyzes default payment data and compares the prediction accuracy
[...] Read more.
Proper credit-risk management is essential for lending institutions, as substantial losses can be incurred when borrowers default. Consequently, statistical methods that can measure and analyze credit risk objectively are becoming increasingly important. This study analyzes default payment data and compares the prediction accuracy and classification ability of three ensemble-learning methods—specifically, bagging, random forest, and boosting—with those of various neural-network methods, each of which has a different activation function. The results obtained indicate that the classification ability of boosting is superior to other machine-learning methods including neural networks. It is also found that the performance of neural-network models depends on the choice of activation function, the number of middle layers, and the inclusion of dropout. Full article
Figures

Figure 1

Open AccessArticle
Variance Swap Replication: Discrete or Continuous?
J. Risk Financial Manag. 2018, 11(1), 11; https://doi.org/10.3390/jrfm11010011 -
Abstract
The popular replication formula to price variance swaps assumes continuity of traded option strikes. In practice, however, there is only a discrete set of option strikes traded on the market. We present here different discrete replication strategies and explain why the continuous replication
[...] Read more.
The popular replication formula to price variance swaps assumes continuity of traded option strikes. In practice, however, there is only a discrete set of option strikes traded on the market. We present here different discrete replication strategies and explain why the continuous replication price is more relevant. Full article
Figures

Figure 1

Open AccessArticle
A New Generalization of the Pareto Distribution and Its Application to Insurance Data
J. Risk Financial Manag. 2018, 11(1), 10; https://doi.org/10.3390/jrfm11010010 -
Abstract
The Pareto classical distribution is one of the most attractive in statistics and particularly in the scenario of actuarial statistics and finance. For example, it is widely used when calculating reinsurance premiums. In the last years, many alternative distributions have been proposed to
[...] Read more.
The Pareto classical distribution is one of the most attractive in statistics and particularly in the scenario of actuarial statistics and finance. For example, it is widely used when calculating reinsurance premiums. In the last years, many alternative distributions have been proposed to obtain better adjustments especially when the tail of the empirical distribution of the data is very long. In this work, an alternative generalization of the Pareto distribution is proposed and its properties are studied. Finally, application of the proposed model to the earthquake insurance data set is presented. Full article
Figures

Graphical abstract

Open AccessArticle
Effectiveness of Interest Rate Policy of the Fed in Management of Subprime Mortgage Crisis
J. Risk Financial Manag. 2018, 11(1), 9; https://doi.org/10.3390/jrfm11010009 -
Abstract
The federal funds rate is one of the most important monetary policy instruments of Federal Reserve Bank of America. In this study, we analyze the effectiveness of Fed interest rate policy on different markets in the period between 1976 and 2016 through Markov
[...] Read more.
The federal funds rate is one of the most important monetary policy instruments of Federal Reserve Bank of America. In this study, we analyze the effectiveness of Fed interest rate policy on different markets in the period between 1976 and 2016 through Markov regime-switching regression analysis. Results indicate that Federal funds’ rate affects labor and housing markets with a few months’ lag. However, the influence of Federal funds rate on inflation rate is quite limited. It is most probable that Fed employs alternative monetary instruments to regulate inflation. The most interesting results are obtained in the domain of personal savings. The interaction of personal savings and Federal funds rate is significant during both expansion and recession regimes. Full article
Figures

Figure 1a

Open AccessFeature PaperArticle
Estimation of Cross-Lingual News Similarities Using Text-Mining Methods
J. Risk Financial Manag. 2018, 11(1), 8; https://doi.org/10.3390/jrfm11010008 -
Abstract
In this research, two estimation algorithms for extracting cross-lingual news pairs based on machine learning from financial news articles have been proposed. Every second, innumerable text data, including all kinds news, reports, messages, reviews, comments, and tweets are generated on the Internet, and
[...] Read more.
In this research, two estimation algorithms for extracting cross-lingual news pairs based on machine learning from financial news articles have been proposed. Every second, innumerable text data, including all kinds news, reports, messages, reviews, comments, and tweets are generated on the Internet, and these are written not only in English but also in other languages such as Chinese, Japanese, French, etc. By taking advantage of multi-lingual text resources provided by Thomson Reuters News, we developed two estimation algorithms for extracting cross-lingual news pairs from multilingual text resources. In our first method, we propose a novel structure that uses the word information and the machine learning method effectively in this task. Simultaneously, we developed a bidirectional Long Short-Term Memory (LSTM) based method to calculate cross-lingual semantic text similarity for long text and short text, respectively. Thus, when an important news article is published, users can read similar news articles that are written in their native language using our method. Full article
Figures

Figure 1