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Volume 13
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J. Risk Financial Manag., Volume 13, Issue 2 (February 2020) – 21 articles

Cover Story (view full-size image): We find that variables such as economic policy uncertainty and stock market volatility are among the most important for bitcoin. We also trace strong evidence of bubbly bitcoin behavior, especially in the 2017–2018 period, as well as evidence that internet trends can expedite the creation and the burst of a bubble. We find a minor importance of FX markets and monetary policy, but a higher importance of traditional stock market returns. Commodity markets appear not to play a role, while the opposite holds for government bond yields. View this paper.
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19 pages, 1828 KiB  
Article
Parsimonious Heterogeneous ARCH Models for High Frequency Modeling
by Juan Carlos Ruilova and Pedro Alberto Morettin
J. Risk Financial Manag. 2020, 13(2), 38; https://doi.org/10.3390/jrfm13020038 - 20 Feb 2020
Viewed by 2768
Abstract
In this work we study a variant of the GARCH model when we consider the arrival of heterogeneous information in high-frequency data. This model is known as HARCH(n). We modify the HARCH(n) model when taking into consideration some market [...] Read more.
In this work we study a variant of the GARCH model when we consider the arrival of heterogeneous information in high-frequency data. This model is known as HARCH(n). We modify the HARCH(n) model when taking into consideration some market components that we consider important to the modeling process. This model, called parsimonious HARCH(m,p), takes into account the heterogeneous information present in the financial market and the long memory of volatility. Some theoretical properties of this model are studied. We used maximum likelihood and Griddy-Gibbs sampling to estimate the parameters of the proposed model and apply it to model the Euro-Dollar exchange rate series. Full article
(This article belongs to the Special Issue Financial Statistics and Data Analytics)
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35 pages, 5218 KiB  
Article
An Ensemble Classifier-Based Scoring Model for Predicting Bankruptcy of Polish Companies in the Podkarpackie Voivodeship
by Tomasz Pisula
J. Risk Financial Manag. 2020, 13(2), 37; https://doi.org/10.3390/jrfm13020037 - 19 Feb 2020
Cited by 18 | Viewed by 5030
Abstract
This publication presents the methodological aspects of designing of a scoring model for an early prediction of bankruptcy by using ensemble classifiers. The main goal of the research was to develop a scoring model (with good classification properties) that can be applied in [...] Read more.
This publication presents the methodological aspects of designing of a scoring model for an early prediction of bankruptcy by using ensemble classifiers. The main goal of the research was to develop a scoring model (with good classification properties) that can be applied in practice to assess the risk of bankruptcy of enterprises in various sectors. For the data sample, which included 1739 Polish businesses (of which 865 were bankrupt and 875 had no risk of bankruptcy), a genetic algorithm was applied to select the optimum set of 19 bankruptcy indicators, on the basis of which the classification accuracy of a number of ensemble classifier model variants (boosting, bagging and stacking) was estimated and verified. The classification effectiveness of ensemble models was compared with eight classical individual models which made use of single classifiers. A GBM-based ensemble classifier model offering superior classification capabilities was used in practice to design a scoring model, which was applied in comparative evaluation and bankruptcy risk analysis for businesses from various sectors and of different sizes from the Podkarpackie Voivodeship in 2018 (over a time horizon of up to two years). The approach applied can also be used to assess credit risk for corporate borrowers. Full article
(This article belongs to the Special Issue Modern Methods of Bankruptcy Prediction)
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6 pages, 188 KiB  
Editorial
Risk Management of COVID-19 by Universities in China
by Chuanyi Wang, Zhe Cheng, Xiao-Guang Yue and Michael McAleer
J. Risk Financial Manag. 2020, 13(2), 36; https://doi.org/10.3390/jrfm13020036 - 19 Feb 2020
Cited by 292 | Viewed by 49740
Abstract
The rapid spread of new coronaviruses throughout China and the world in 2019–2020 has had a great impact on China’s economic and social development. As the backbone of Chinese society, Chinese universities have made significant contributions to emergency risk management. Such contributions have [...] Read more.
The rapid spread of new coronaviruses throughout China and the world in 2019–2020 has had a great impact on China’s economic and social development. As the backbone of Chinese society, Chinese universities have made significant contributions to emergency risk management. Such contributions have been made primarily in the following areas: alumni resource collection, medical rescue and emergency management, mental health maintenance, control of staff mobility, and innovation in online education models. Through the support of these methods, Chinese universities have played a positive role in the prevention and control of the epidemic situation. However, they also face the problems of alumni’s economic development difficulties, the risk of deadly infection to medical rescue teams and health workers, infection of teachers and students, and the unsatisfactory application of information technology in resolving the crisis. In response to these risks and emergency problems, we propose some corresponding solutions for public dissemination, including issues related to medical security, emergency research, professional assistance, positive communication, and hierarchical information-based teaching. Full article
(This article belongs to the Special Issue COVID-19’s Risk Management and Its Impact on the Economy)
20 pages, 364 KiB  
Review
A Comprehensive Review of Corporate Bankruptcy Prediction in Hungary
by Tamás Kristóf and Miklós Virág
J. Risk Financial Manag. 2020, 13(2), 35; https://doi.org/10.3390/jrfm13020035 - 19 Feb 2020
Cited by 23 | Viewed by 5496
Abstract
The article provides a comprehensive review regarding the theoretical approaches, methodologies and empirical researches of corporate bankruptcy prediction, laying emphasis on the 30-year development history of Hungarian empirical results. In ex-socialist countries corporate bankruptcy prediction became possible more than 20 years later compared [...] Read more.
The article provides a comprehensive review regarding the theoretical approaches, methodologies and empirical researches of corporate bankruptcy prediction, laying emphasis on the 30-year development history of Hungarian empirical results. In ex-socialist countries corporate bankruptcy prediction became possible more than 20 years later compared to the western countries, however, based on the historical development of corporate bankruptcy prediction after the political system change it can be argued that it has already caught up to the level of international best practice. Throughout the development history of Hungarian bankruptcy prediction, it can be tracked how the initial, small, cross-sectional sample and classic methodology-based bankruptcy prediction has evolved to today’s corporate rating systems meeting the requirements of the dynamic, through-the-cycle economic capital calculation models. Contemporary methodological development is characterized by the domination of artificial intelligence, data mining, machine learning, and hybrid modelling. On the basis of empirical results, the article draws several normative proposals how to assemble a bankruptcy prediction database and select the right classification method(s) to accomplish efficient corporate bankruptcy prediction. Full article
(This article belongs to the Special Issue Modern Methods of Bankruptcy Prediction)
10 pages, 274 KiB  
Article
Cross-Country Application of Manufacturing Failure Models
by Sebastian Klaudiusz Tomczak and Piotr Staszkiewicz
J. Risk Financial Manag. 2020, 13(2), 34; https://doi.org/10.3390/jrfm13020034 - 18 Feb 2020
Cited by 6 | Viewed by 2654
Abstract
The post-Altman models suffer from moral amortization. This paper asks whether models developed in one country can be applied in other economies. One of the characteristics of the prediction model is that a date drives the estimation. Thus, the estimated model based on [...] Read more.
The post-Altman models suffer from moral amortization. This paper asks whether models developed in one country can be applied in other economies. One of the characteristics of the prediction model is that a date drives the estimation. Thus, the estimated model based on one economy is not necessarily applicable to other economies. To verify such a statement, we carried out a literature review to identify the manufacturing models constructed during the last 30 years that were reported in reputable scientific journals. Our literature comprised 75 papers, and with the application of the citation count and citation mining, we selected a sample and traced the selected papers to the cross-country application. Our results indicated an existing gap in the cross-economy validation of existing manufacturing models. Our study has implications for policy, as the application of the prediction models to cross-economies’ consolidated financial statements is biased. Full article
(This article belongs to the Special Issue Modern Methods of Bankruptcy Prediction)
10 pages, 913 KiB  
Article
A Principal Component-Guided Sparse Regression Approach for the Determination of Bitcoin Returns
by Theodore Panagiotidis, Thanasis Stengos and Orestis Vravosinos
J. Risk Financial Manag. 2020, 13(2), 33; https://doi.org/10.3390/jrfm13020033 - 13 Feb 2020
Cited by 15 | Viewed by 4286
Abstract
We examine the significance of fourty-one potential covariates of bitcoin returns for the period 2010–2018 (2872 daily observations). The recently introduced principal component-guided sparse regression is employed. We reveal that economic policy uncertainty and stock market volatility are among the most important variables [...] Read more.
We examine the significance of fourty-one potential covariates of bitcoin returns for the period 2010–2018 (2872 daily observations). The recently introduced principal component-guided sparse regression is employed. We reveal that economic policy uncertainty and stock market volatility are among the most important variables for bitcoin. We also trace strong evidence of bubbly bitcoin behavior in the 2017–2018 period. Full article
(This article belongs to the Special Issue Recent Developments in Cryptocurrency Markets: Co-movements, Spillovers and Forecasting)
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3 pages, 172 KiB  
Editorial
Extreme Values and Financial Risk
by Stephen Chan and Saralees Nadarajah
J. Risk Financial Manag. 2020, 13(2), 32; https://doi.org/10.3390/jrfm13020032 - 11 Feb 2020
Cited by 1 | Viewed by 2349
Abstract
Since the 2008 financial crisis, modelling of the extreme values of financial risk has become important [...] Full article
(This article belongs to the Special Issue Extreme Values and Financial Risk)
14 pages, 1812 KiB  
Article
Pricing Defaulted Italian Mortgages
by Michela Pelizza and Klaus R. Schenk-Hoppé
J. Risk Financial Manag. 2020, 13(2), 31; https://doi.org/10.3390/jrfm13020031 - 10 Feb 2020
Cited by 4 | Viewed by 2968
Abstract
Our paper forecasts the expected recovery rates of defaulted Italian mortgage loans backed by either residential or commercial real estate. We apply an exponential Ornstein–Uhlenbeck process to model the price dynamics at the provincial and regional level, and two haircut models to estimate [...] Read more.
Our paper forecasts the expected recovery rates of defaulted Italian mortgage loans backed by either residential or commercial real estate. We apply an exponential Ornstein–Uhlenbeck process to model the price dynamics at the provincial and regional level, and two haircut models to estimate the liquidation value. Compared to our findings, rating agencies such as Moody’s, which use geometric Brownian motion to model the price dynamics, paint a rosier picture with higher recovery rates. As a consequence, non-performing mortgage loans held by Italian banks might be overvalued. Full article
(This article belongs to the Special Issue Real Estate Economics and Finance)
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15 pages, 254 KiB  
Article
How Do Corporate Social Responsibility and Corporate Governance Affect Stock Price Crash Risk?
by Ahmed Imran Hunjra, Rashid Mehmood and Tahar Tayachi
J. Risk Financial Manag. 2020, 13(2), 30; https://doi.org/10.3390/jrfm13020030 - 7 Feb 2020
Cited by 31 | Viewed by 9323
Abstract
We investigate the impact of corporate social responsibility (CSR) and corporate governance on stock price crash risk in manufacturing sector of India and Pakistan. We collect data of nine years from 2010 to 2018 from DataStream of 353 manufacturing firms. We apply the [...] Read more.
We investigate the impact of corporate social responsibility (CSR) and corporate governance on stock price crash risk in manufacturing sector of India and Pakistan. We collect data of nine years from 2010 to 2018 from DataStream of 353 manufacturing firms. We apply the Generalized Method of Moments (GMM) to the analysis of the data. We find that when firms actively engage in CSR activities, they lead to reduced stock price crash risk. We further find that managerial ownership has a significant positive impact on stock price crash risk, while board size and CEO duality show a significant and negative impact on stock price crash risk. Full article
(This article belongs to the Special Issue Green and Sustainable Finance)
13 pages, 239 KiB  
Article
Exploring Compliance of AAOIFI Shariah Standard on Ijarah Financing: Analysis on the Practices of Islamic Banks in Malaysia
by Shujaat Saleem and Fadillah Mansor
J. Risk Financial Manag. 2020, 13(2), 29; https://doi.org/10.3390/jrfm13020029 - 5 Feb 2020
Cited by 5 | Viewed by 6868
Abstract
This paper aims to explore whether the practices of Ijarah financing by Islamic banks in Malaysia are in line with the Accounting and Auditing Organization for Islamic Financial Institutions (AAOIFI) Shariah Standard No: (9) on Ijarah financing. Semi- structured interviews based on open-ended [...] Read more.
This paper aims to explore whether the practices of Ijarah financing by Islamic banks in Malaysia are in line with the Accounting and Auditing Organization for Islamic Financial Institutions (AAOIFI) Shariah Standard No: (9) on Ijarah financing. Semi- structured interviews based on open-ended questionnaires were conducted, recorded verbatim, and transcribed for content analysis. Our study revealed flaws in the contemporary practice of Ijarah financing and indicated that it was slightly out of line with the AAOIFI Shariah standard. The study will not only help the Islamic banking industry of Malaysia to reduce, if not eliminate the gap between the practices of Bank Negara Malaysia (BNM) and AAOIFI Shariah standards pertaining to Ijarah financing but also create novel literature due to the fact that, no study has been undertaken to date, which analyzes the practices of Ijarah financing by Malaysian Islamic banks in the light of the AAOIFI Shariah standards. Full article
(This article belongs to the Special Issue Islamic Finance)
14 pages, 239 KiB  
Article
Banking Finance Experts Consensus on Compliance in US Bank Holding Companies: An e-Delphi Study
by Sophia Velez, Michael Neubert and Daphne Halkias
J. Risk Financial Manag. 2020, 13(2), 28; https://doi.org/10.3390/jrfm13020028 - 5 Feb 2020
Cited by 5 | Viewed by 3650
Abstract
Compliance measures emphasized in the Dodd-Frank Bill 2010, Section 165 is a response to the 2008 financial crisis, that requires large banks to maintain a minimum capital ratio. The Federal Reserve Bank (Fed) regulates capital of Bank Holding Companies (BHC) through compliance Supervisory [...] Read more.
Compliance measures emphasized in the Dodd-Frank Bill 2010, Section 165 is a response to the 2008 financial crisis, that requires large banks to maintain a minimum capital ratio. The Federal Reserve Bank (Fed) regulates capital of Bank Holding Companies (BHC) through compliance Supervisory Capital Assessment Program (SCAP) 2009 and Comprehensive Capital Adequacy Review (CCAR) 2011 annual stress test of capital. The Fed imposed a minimum capital ratio of 8% that has derailed the risk management objective of capital adequacy, as bank managers are forced to take on more risk to meet the capital ratio. This study concerns senior manager practices that can be effective in meeting compliance requirements posed by the Fed for BHCs. Through a qualitative e-Delphi study, 10 banking finance experts were convened to build consensus on senior manager’s practices that can be effective in meeting compliance requirements. Data were collected from three electronic questionnaires submitted through Qualtrics. Data were analyzed using theoretical triangulation, coding, and thematic analysis. Four important considerations were identified that could bolster compliance measures effectiveness: (a) emphasis placed on understanding regulatory consultant compliance, (b) maintenance of effective and independent compliance align to organizational objectives, (c) clear definition of data source for compliance analytics. These considerations of compliance practices may help senior bank managers reduce risky behaviors and investments that cause significant bank losses. Full article
(This article belongs to the Section Banking and Finance)
19 pages, 1384 KiB  
Article
The Distribution of Cross Sectional Momentum Returns When Underlying Asset Returns Are Student’s t Distributed
by Oh Kang Kwon and Stephen Satchell
J. Risk Financial Manag. 2020, 13(2), 27; https://doi.org/10.3390/jrfm13020027 - 5 Feb 2020
Cited by 4 | Viewed by 2525
Abstract
In Kwon and Satchell (2018), a theoretical framework was introduced to investigate the distributional properties of the cross-sectional momentum returns under the assumption that the vector of asset returns over the ranking and holding periods were multivariate normal. In this paper, the framework [...] Read more.
In Kwon and Satchell (2018), a theoretical framework was introduced to investigate the distributional properties of the cross-sectional momentum returns under the assumption that the vector of asset returns over the ranking and holding periods were multivariate normal. In this paper, the framework is extended to derive the corresponding results when the asset returns are multivariate Student’s t. In particular, we derive the probability density function and the moments of the cross-sectional momentum returns and examine in detail the special case of two underlying assets to demonstrate that many of the salient features reported in the empirical literature are consistent with the theoretical implications. Full article
(This article belongs to the Special Issue Modern Portfolio Theory)
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13 pages, 311 KiB  
Article
The Impact of Economic Freedom on Economic Growth? New European Dynamic Panel Evidence
by Ivana Brkić, Nikola Gradojević and Svetlana Ignjatijević
J. Risk Financial Manag. 2020, 13(2), 26; https://doi.org/10.3390/jrfm13020026 - 4 Feb 2020
Cited by 38 | Viewed by 11371
Abstract
This paper analyzes the impact of economic freedom along with traditional economic factors on economic growth for a panel of European countries. The growth of the gross domestic product was observed over a twenty-year time period on a sample of 43 developing and [...] Read more.
This paper analyzes the impact of economic freedom along with traditional economic factors on economic growth for a panel of European countries. The growth of the gross domestic product was observed over a twenty-year time period on a sample of 43 developing and developed countries. Based on a robust dynamic panel setting, we conclude that increases in economic freedom as expressed by the Index of Economic Freedom/Heritage Foundation (but not its levels) are related to economic growth. The EU membership status either had no effect or it curbed the effect of the economic freedom on growth. We also find that the subprime economic crisis of 2008–2009 exerted a negative impact on the growth of European economies. Full article
(This article belongs to the Special Issue Feature Papers on Applied Economics and Finance)
21 pages, 509 KiB  
Article
Corporate Green Bond Issuances: An International Evidence
by Martin Lebelle, Souad Lajili Jarjir and Syrine Sassi
J. Risk Financial Manag. 2020, 13(2), 25; https://doi.org/10.3390/jrfm13020025 - 4 Feb 2020
Cited by 55 | Viewed by 15556
Abstract
Using an international sample of corporate Green bond issuances over the recent period, this paper highlights the potential consequences of the issuance of a Green bond on the issuer’s financial performance. Starting with a first sample of 2079 Green bond issuances of 190 [...] Read more.
Using an international sample of corporate Green bond issuances over the recent period, this paper highlights the potential consequences of the issuance of a Green bond on the issuer’s financial performance. Starting with a first sample of 2079 Green bond issuances of 190 unique issuers from 2009 to 2018, we investigate only corporate green bond issuances. Our final sample contains 475 green bonds issued by 145 unique firms. We find that the market reacts negatively to the announcement of green bond issuances. In particular, results show that the stock market reacts on the day of the green bond announcement date and the day after, and that the cumulative abnormal return is between −0.5% and −0.2%, depending on the asset pricing model (CAPM, the 3-factor Fama and French models, and the 4-factor Carhart models). This effect is mainly noticeable at the first Green Bond issuance and in developed markets. Our results provide evidence that the investors react in the same manner for Green bonds as for conventional or convertible bonds. This evidence suggests that green debt offerings convey unfavorable information about the issuing firms. Full article
(This article belongs to the Special Issue Green and Sustainable Finance)
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29 pages, 395 KiB  
Article
Optimal Contracting of Pension Incentive: Evidence of Currency Risk Management in Multinational Companies
by Jeffrey (Jun) Chen, Yun Guan and Ivy Tang
J. Risk Financial Manag. 2020, 13(2), 24; https://doi.org/10.3390/jrfm13020024 - 3 Feb 2020
Cited by 1 | Viewed by 2823
Abstract
Using a large sample of multinational companies (MNCs), this paper intends to explore whether executives’ pension incentives will function as a mechanism of optimal contracting in motivating firm risk management. We find that granting more pension to executives is significantly related to the [...] Read more.
Using a large sample of multinational companies (MNCs), this paper intends to explore whether executives’ pension incentives will function as a mechanism of optimal contracting in motivating firm risk management. We find that granting more pension to executives is significantly related to the higher likelihood and intensity of currency hedging strategies in MNCs. This suggests that pension incentive should promote executives to more actively manage firms’ risk. Such a positive relationship is robust to endogeneity and is more prominent in firms with strong shareholder power. We further explore the contribution of currency hedging induced by pension incentives to shareholder value. Supporting the hypothesis of optimal contracting, our results indicate that pension incentives play an important role in reconciling managerial risk preference and shareholder value creation. Full article
(This article belongs to the Special Issue Corporate Finance)
16 pages, 3130 KiB  
Article
A Gated Recurrent Unit Approach to Bitcoin Price Prediction
by Aniruddha Dutta, Saket Kumar and Meheli Basu
J. Risk Financial Manag. 2020, 13(2), 23; https://doi.org/10.3390/jrfm13020023 - 3 Feb 2020
Cited by 125 | Viewed by 15225
Abstract
In today’s era of big data, deep learning and artificial intelligence have formed the backbone for cryptocurrency portfolio optimization. Researchers have investigated various state of the art machine learning models to predict Bitcoin price and volatility. Machine learning models like recurrent neural network [...] Read more.
In today’s era of big data, deep learning and artificial intelligence have formed the backbone for cryptocurrency portfolio optimization. Researchers have investigated various state of the art machine learning models to predict Bitcoin price and volatility. Machine learning models like recurrent neural network (RNN) and long short-term memory (LSTM) have been shown to perform better than traditional time series models in cryptocurrency price prediction. However, very few studies have applied sequence models with robust feature engineering to predict future pricing. In this study, we investigate a framework with a set of advanced machine learning forecasting methods with a fixed set of exogenous and endogenous factors to predict daily Bitcoin prices. We study and compare different approaches using the root mean squared error (RMSE). Experimental results show that the gated recurring unit (GRU) model with recurrent dropout performs better than popular existing models. We also show that simple trading strategies, when implemented with our proposed GRU model and with proper learning, can lead to financial gain. Full article
(This article belongs to the Special Issue Machine Learning Applications in Finance)
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6 pages, 177 KiB  
Editorial
Risk Management Analysis for Novel Coronavirus in Wuhan, China
by Xiao-Guang Yue, Xue-Feng Shao, Rita Yi Man Li, M. James C. Crabbe, Lili Mi, Siyan Hu, Julien S. Baker and Gang Liang
J. Risk Financial Manag. 2020, 13(2), 22; https://doi.org/10.3390/jrfm13020022 - 3 Feb 2020
Cited by 48 | Viewed by 16947
Abstract
Recently, a novel coronavirus pneumonia (2019–nCoV) outbreak occurred in Wuhan, China, rapidly spreading first to the whole country, and then globally, causing widespread concern. From the perspectives of early warning and identification of risk, risk monitoring, and analysis, as well as risk management [...] Read more.
Recently, a novel coronavirus pneumonia (2019–nCoV) outbreak occurred in Wuhan, China, rapidly spreading first to the whole country, and then globally, causing widespread concern. From the perspectives of early warning and identification of risk, risk monitoring, and analysis, as well as risk management and handling, we propose corresponding solutions and recommendations, which include institutional cooperation, and to inform national and international policy-makers. Full article
(This article belongs to the Special Issue COVID-19’s Risk Management and Its Impact on the Economy)
17 pages, 637 KiB  
Article
How to Explain When the ES Is Lower Than One? A Bayesian Nonlinear Mixed-Effects Approach
by Nguyen Ngoc Thach
J. Risk Financial Manag. 2020, 13(2), 21; https://doi.org/10.3390/jrfm13020021 - 1 Feb 2020
Cited by 38 | Viewed by 3783
Abstract
Most studies in Vietnam use the Cobb-Douglas production function and its modifications for economic analysis. Extremely rigid presumptions are a main weak point of this functional form, particularly if the elasticity of factor substitution (ES) is equal to one, which hides the role [...] Read more.
Most studies in Vietnam use the Cobb-Douglas production function and its modifications for economic analysis. Extremely rigid presumptions are a main weak point of this functional form, particularly if the elasticity of factor substitution (ES) is equal to one, which hides the role of the ES for economic growth. The CES (constant elasticity of substitution) production function with more flexible presumptions, concretely its ES, is not unitary, and has been used more and more widely in economic investigations. So, this study is conducted to estimate the average ES through the specification of an aggregate CES function for the Vietnamese nonfinancial enterprises. By performing Bayesian nonlinear mixed-effects regression via Random-walk Metropolis Hastings (MH) algorithm, based on the data set of the listed nonfinancial enterprises of Vietnam, the author found that the CES function estimated for the researched enterprises has an ES lower than one, i.e., capital and labor are complimentary. This finding shows that Vietnamese nonfinancial enterprises can confront a downward trend of output growth. Full article
(This article belongs to the Special Issue Bayesian Econometrics)
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34 pages, 1416 KiB  
Article
Credit Spreads, Business Conditions, and Expected Corporate Bond Returns
by Hai Lin, Xinyuan Tao, Junbo Wang and Chunchi Wu
J. Risk Financial Manag. 2020, 13(2), 20; https://doi.org/10.3390/jrfm13020020 - 21 Jan 2020
Cited by 3 | Viewed by 4726
Abstract
Using an aggregate credit spread index, we find that it has substantial predictive power for corporate bond returns over short and long horizons. The return predictability is economically and statistically significant and robust to various controls. The credit spread index and its components [...] Read more.
Using an aggregate credit spread index, we find that it has substantial predictive power for corporate bond returns over short and long horizons. The return predictability is economically and statistically significant and robust to various controls. The credit spread index and its components have more predictive power for bond returns than conventional default and term spreads. When decomposing the credit spread index into investment- and speculative-grade components, the latter has more predictive power for future bond returns. The source of the index’s predictive power is from its ability to forecast future economic conditions. Full article
(This article belongs to the Special Issue Corporate Debt)
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16 pages, 874 KiB  
Article
The Equity Curve and Its Relation to Future Stock Returns
by Olaf Stotz
J. Risk Financial Manag. 2020, 13(2), 19; https://doi.org/10.3390/jrfm13020019 - 21 Jan 2020
Cited by 3 | Viewed by 3237
Abstract
Using option prices, a new method for estimating the term structure of expected stock returns (equity curve) is proposed. We analyse how the equity curve relates to future stock returns and obtain three main results. First, a higher level of the equity curve [...] Read more.
Using option prices, a new method for estimating the term structure of expected stock returns (equity curve) is proposed. We analyse how the equity curve relates to future stock returns and obtain three main results. First, a higher level of the equity curve is associated with higher future stock returns. Second, a positive slope is followed by future realized returns which are lower in the short term (1 month) than in the long term (1 quarter or 1 year). Third, a steeper slope (either positive or negative) is associated with a larger absolute difference between short-term and long-term returns. Therefore, the equity curve is consistent with theoretical predictions. We also analyse an investment strategy that uses the slope of the equity curve to determine the allocation to stocks. This strategy earns an outperformance of up to 200 basis points per annum. Full article
(This article belongs to the Special Issue Modern Portfolio Theory)
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3 pages, 621 KiB  
Editorial
Editorial Statement for Mathematical Finance
by Wing-Keung Wong
J. Risk Financial Manag. 2020, 13(2), 18; https://doi.org/10.3390/jrfm13020018 - 21 Jan 2020
Cited by 1 | Viewed by 2036
Abstract
Mathematics plays a vital role in many areas of finance and provides the theories and tools that have been widely used in all areas of finance. In this editorial, we tell authors the ideas on what types of papers we will accept for [...] Read more.
Mathematics plays a vital role in many areas of finance and provides the theories and tools that have been widely used in all areas of finance. In this editorial, we tell authors the ideas on what types of papers we will accept for publication in the area of mathematical finance. We will discuss some well-cited papers of mathematical finance. Full article
(This article belongs to the Special Issue Mathematical Finance with Applications)
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