J. Risk Financial Manag., Volume 13, Issue 7 (July 2020) – 21 articles

In this paper we introduce a deep learning method for pricing and hedging American-style options. It first computes a candidate optimal stopping policy. From there it derives a lower bound for the price. Then it calculates an upper bound, a point estimate and confidence intervals. Finally, it constructs an approximate dynamic hedging strategy. We test the approach on different specifications of a Bermudan max-call option. In all cases it produces highly accurate prices and dynamic hedging strategies with small replication errors. Full article

An important aspect of liquidity is price risk, i.e., the risk that a small transaction leads to a large price change. This usually happens in a thin market, when trading opportunities are scarce and the time between subsequent trades is long. We rely on an autoregressive conditional duration model to extract the probability of a substantial price event in a particular time interval and, thus, an intraday risk profile. Our findings show that price risk is highest at times when European and U.S. investors do not trade. In a second step, we relate daily aggregates to characteristics of the Bitcoin blockchain and investigate whether investors account for features like confirmation time or fees when timing their orders. Full article

This paper investigates the decoupling and integration between the region-wise (Asia, Europe, Africa and the Americas) developed and emerging market’s equity pairs of Islamic and conventional stock returns with the focus on multi-horizons. In doing so, daily wavelet and ADCC-based stock returns correlations are estimated to capture the dynamics of time-frequency and the time-domain based correlations, respectively. The findings of this study indicate that at the short-term horizon, the all selected emerging and developed Islamic and conventional equity markets across all regions depict a high positive correlation, suggesting a rejection of the decoupling hypothesis. However, it is accepted for some of the developed markets of the Pacific region (Hong Kong and New Zealand), Europe (Ireland, Denmark and Spain) and emerging markets of Asia (China), Europe (Czech Republic) and Americas (Argentina and Peru) at a medium-term horizon. Moreover, in an examination of the comparative behaviors of the wavelet and ADCC-based Islamic-conventional correlations, the observed transitional behavior has been exemplified as the difference between the time-frequency and time-domain analysis. This study provides fruitful insights for investors who opt for cross-asset allocation and seek maximum portfolio diversification benefits. Full article

We propose a portfolio rebalance framework that integrates machine learning models into the mean-risk portfolios in multi-period settings with risk-aversion adjustment. In each period, the risk-aversion coefficient is adjusted automatically according to market trend movements predicted by machine learning models. We employ Gini’s Mean Difference (GMD) to specify the risk of a portfolio and use a set of technical indicators generated from a market index (e.g., S&P 500 index) to feed the machine learning models to predict market movements. Using a rolling-horizon approach, we conduct a series of computational tests with real financial data to evaluate the performance of the machine learning integrated portfolio rebalance framework. The empirical results show that the XGBoost model provides the best prediction of market movement, while the proposed portfolio rebalance strategy generates portfolios with superior out-of-sample performances in terms of average returns, time-series cumulative returns, and annualized returns compared to the benchmarks. Full article

The purpose of this paper is to investigate the effect of corporate governance quality and ownership structure on the relationship between the agency cost and firm performance. Both the fixed-effects model and a more robust dynamic panel generalized method of moment estimation are applied to Chinese A-listed firms for the years 2008 to 2016. The results show that the agency–performance relationship is positively moderated by (1) corporate governance quality, (2) ownership concentration, and (3) non-state ownership. State ownership has a negative effect on the agency–performance relationship. Various robust tests of an alternative measure of agency cost confirm our main conclusions. The analysis adds to the empirical literature on agency theory by providing useful insights into how corporate governance and ownership concentration can help mitigate agency–performance relationship. It also highlights the impact of ownership type on the relationship between agency cost and firm performance. Our study supports the literature that agency cost and firm performance are negatively related to the Chinese listed firms. The investors should keep in mind the proxies of agency cost while choosing a specific stock. Secondly; the abuse of managerial appropriation is higher in state-held firms as compared to non-state firms. Policymakers can use these results to devise the investor protection rules so that managerial appropriation can be minimized. Full article

Big data has become a very frequent research topic, due to the increase in data availability. In this introductory paper, we make the linkage between the use of big data and Econophysics, a research field which uses a large amount of data and deals with complex systems. Different approaches such as power laws and complex networks are discussed, as possible frameworks to analyze complex phenomena that could be studied using Econophysics and resorting to big data. Full article

In order to highlight the extent to which young consumers, or members of Generation Z, are familiar with the sustainability principles implemented by retailers operating in emerging markets, the authors conducted a qualitative empirical research study with the help of a semi-structured in-depth interview guide. Respondents were asked to express their perception of the extent to which their favorite retailers adopted and implemented the social, economic, and environmental dimensions of sustainability. The results show that respondents viewed retailers’ sustainability orientation favorably, specifying concrete measures implemented by their preferred retailers. They seemed to favor those retail networks making a useful and proactive contribution to resource preservation and environmental protection, whilst taking care of employees’ welfare and being involved in their local communities. From a theoretical perspective, the paper makes a clear contribution to enhancing the generational theory-based studies on emerging markets, where market conditions and polyvalent consumer behavior are highly dynamic, and where sustainability principles play a major role in drawing and maintaining their customers. From a management perspective, the paper provides retailers with an overview on the measures, tactics, and actions that allow them to properly target consumers and develop a proper customer approach strategy. Full article

The purpose of this paper is to approach the way investors perceive the risk associated with unexpected environmental disasters. For that reason, we examine certain types of natural and technological disasters, also known as “na-tech”. Based on the existing relevant literature and historical sources, the most common types of such disasters are geophysical and industrial environmental disasters. After providing evidence of the historical evolution of the na-tech events and a brief description of the events included in the sample, we estimate the systematic risk of assets connected to these events. The goal is to capture possible abnormalities as well as to observe investors’ psychology of risk after the occurrence of an unexpected event. Finally, we examine whether macroeconomic factors may affect those abnormalities. The empirical findings indicate that the cases we examined did not cause significant cumulative abnormal returns. Moreover, some events caused an increase in systematic risk while surprisingly some others reduced risk, showing that investors tend to support a country and/or corporation due to their reputation. Full article

The recent financial crisis offered an interesting opportunity to analyze the markets’ behavior in a high-volatility framework. In this paper, we analyzed the price discovery process of the Italian banks’ Credit Default Swap (CDS) spreads through the Merton model, extended with the inclusion of a redenomination risk proxy, as to say, the risk that Italy could leave the eurozone. This paper contributes to the literature by integrating the classic Merton model with a political-sensitive market variable able to explain the greatest variance in the Italian banks’ CDS spreads during the most relevant and commonly recognized periods of socio-political and financial distress. Results show that the redenomination risk is progressively becoming the main driver of the process during crises, in particular for the sovereign debt crisis and in 2018. Full article

Medical disputes that result in medical compensation and losses affect the financial management and sustainable operational risks of enterprises. Employee training plays an important role in the sustainable growth of human resource management and also can help avoid any potential risks to enterprises’ operating revenue. Based on data of a company, this study’s model aims to establish a mathematical model to find the most suitable decision variables in order to provide decision-making analysis and judgment of a company’s individual economic behaviors. From the second-order differential modeling method, where the functional training time of the aesthetic medicine industry (including medical errors/dispute incidences, functional training costs, and medical benefits) links to a specific functional relationship, the optimal decision-making model and evaluation criteria for the proportion of this training time under the concept of sustainable management can be constructed. The method proposed herein reduces medical errors or disputes, strengthens risk and financial management, provides customers with the best service quality, and serves as the basis for decision-making evaluation of the maximum benefits of sustainable operations. Full article

This study uses the BEKK-GARCH model to examine the return-and-volatility spillover between the world-leading markets (USA and China) and four emerging Latin American stock markets over the global financial crisis of 2008 and the crash of the Chinese stock market of 2015. Regarding return spillover, our findings reveal a unidirectional return transmission from Mexico to the US stock market during the global financial crisis. During the crash of the Chinese stock market, the return spillover is found to be unidirectional from the US to the Brazil, Chile, Mexico, and Peru stock markets. Moreover, the results indicate a unidirectional return transmission from China to the Brazil, Chile, Mexico, and Peru stock markets during the global financial crisis and the crash of the Chinese stock market. Regarding volatility spillover, the results show the bidirectional volatility transmission between the US and the stock markets of Chile and Mexico during the global financial crisis. During the Chinese crash, the bidirectional volatility transmission is observed between the US and Mexican stock markets. Furthermore, the volatility spillover is unidirectional from China to the Brazil stock market during the global financial crisis. During the Chinese crash, the volatility spillover is bidirectional between the China and Brazil stock markets. Lastly, a portfolio analysis application has been conducted. Full article

The purpose of this paper is to explore how organisational culture, represented by the competing values framework (CVF), and the relationship mechanisms of situational strength and power influence an organisation’s approach to supply chain resilience (SCRES). This is a conceptual paper which uses a multi-theoretical approach to create a framework outlining how organisations which possess different characteristics of culture within the CVF will work to achieve SCRES. Secondary analysis of four case examples as discussed in the supply chain and resilience literature are then used to support the development of propositions from this framework in more detail. The paper suggests that ‘flexibility focused’ cultures will create weaker situational strengths for supply chain partners when managing disruptions, while ‘stability focused’ cultures will create stronger situational strengths in the same scenarios. ‘Internally focused’ cultures may use coercive power with supply chain partners when managing disruptions, while ‘externally focused’ cultures will prefer non-coercive power in the same scenarios. The four case studies from the literature highlight that each type of culture within the CVF can enable an organisation to achieve SCRES. The practical implications of the findings are that managers should take into consideration how their organisation’s culture will influence their relationships with supply chain partners, depending on their application of power and situational strength. However, future research is required to empirically test the propositions. Full article

The study focuses on the effects of imports, exports, financial direct investment inflow and financial direct investment outflow on sustainable economic growth expressed by various macroeconomic indicators (gross domestic product, gross domestic savings, gross domestic capital) using the least squares panel method. Sample data were selected for ten Central and Eastern European (CEE) countries and the time frame considered was 2005–2016. Generally, transitional economies have to incorporate strong savings and a steady capital formation in order to achieve higher economic growth via foreign direct investment. Results showed that the analyzed factors played a major role in the sustainable economic growth of CEE countries. Another important and valuable insight of this study is that the financial sector steers the process of achieving sustainable economic growth across CEE countries. Full article

The field of computational finance is evolving ever faster. This book collects a number of novel contributions on the use of computational methods and techniques for modelling financial asset prices, returns, and volatility, and on the use of numerical methods for pricing, hedging, and risk management of financial instruments. Full article

Socially responsible firms receive more finance and have been well researched in the corporate finance literature. In this paper, we examine the relationship between CSR and trade credit. Using data from the US manufacturing industry, we find that CSR has a significant positive association with the buyer and supplier sides of trade credit. During the 2008–2009 financial crisis, the manufacturing industry trade badly fell. We also argue and find evidence that, during crisis, CSR is negatively associated with trade credit. These findings are robust for alternate proxies of CSR and trade credit, sample selection, and time period. Moreover, the potential endogeneity concerns do not affect our results. Finally, we show that this relationship exists for both domestic and multinational firms’ subsamples. Overall, our results indicate that firms with high social performance use more trade credit to increase their business activity. Full article

This paper examines the current No-Claim Discount (NCD) system used in Ghana’s auto insurance market as inefficient and outmoded and, therefore, proposes an alternative optimal Bonus-Malus System (BMS) intended to meet the present market conditions and demand. It appears that the existing BMS fails to acknowledge the frequency and severity of policyholders’ claims in its design. We minimized the auto insurance portfolios’ risk through Bayesian estimation and found that the risk is well fitted by gamma, with the claim distribution modeled by the negative binomial law with the expected number of claims (a priori) as 14%. The models presented in this paper recognize the longevity of accident-free driving and fully reward higher discounts to policyholders from the second year when the true characteristics of the hidden risks posed to the pool have been ascertained. The BMS finally constructed using the net premium principle is very optimal and has reasonable punishment and rewards for both good and bad drivers, which could also be useful in other developing economies. Full article

Despite the fact that a comprehensive analysis of digitalization processes in the EU member states has been carried out, the impact of a country’s digitalization level on the risks of poverty and social exclusion requires further investigation. The purpose of the paper is to verify a hypothesis that a higher level of national digitalization provides positive trends in reducing the risks of poverty and social exclusion for the population. The Digital Economy and Society Index (DESI) was used to evaluate the digitalization levels of the EU countries. The indicator “People at risk of poverty or social exclusion” (AROPE) was applied to estimate the poverty level. As the main research methods, the authors used a comparative and correlation analysis with respect to the above-mentioned indicators, as well as the Monte Carlo method in order to evaluate the probability of a change in the indicator “population at risk of poverty or social exclusion” in 2021. The EU countries with higher digitalization levels have a lower percentage of the population at risk of poverty and social exclusion. However, a higher digitalization level of the EU member states does not provide an accelerated risk reduction of poverty and social exclusion. Statistical calculations with respect to the entire population of these countries mainly indicate reverse processes. At the same time, a further reduction of poverty and social exclusion level is less probable in the countries with a higher level of digitalization. For relatively poor segments of the population (the 1st and 2nd quintiles by income) in the EU member states, the level of digitalization does not play a significant role. For relatively wealthy segments of the population (the 3rd and 4th quintiles by income) the authors noticed a pattern: the higher the level of digitalization is, the lower the risk of poverty and social exclusion becomes. A pairwise comparison of countries with initially similar AROPE values showed that in most cases (3 out of 5), the countries with higher levels of digitalization showed a more significant reduction in poverty and social exclusion. However, the probability of further positive changes in this area is higher for the countries with a lower level of digitalization. Full article

This paper investigates the clustering or dependency of extremes in financial returns by estimating the extremal index value, in which smaller values of the extremal index correspond to more clustering. We apply the interval estimator method to determine the extremal index for a range of threshold values in the developed and emerging markets from 2007–2017. The indices we used to represent developed markets are from France, Germany, Italy, Japan, USA, UK, Spain, and Sweden. For the emerging markets, we use indices from China, Brazil, India, Malaysia, Russia, Saudi Arabia, and Portugal. The results show that clustering occurs in the emerging and developed markets under several threshold values. This study will shed light on the dependency structure of financial returns data and the proprieties of the extremes returns. Moreover, understanding clustering of extremes in these markets can help investors reduce the exposure to extreme financial events, such as the financial crisis. Full article

The purpose of this paper is to assess the impact of ambiguity on financial analyst forecast incentives and the associated abnormal stock returns. I present a model incorporating ambiguity aversion into a two-period Lucas tree model. The resulting model confirms the role of ambiguity in the determination of asset returns. In particular, the model with ambiguity aversion generates a lower price and a higher required rate of returns compared to the classical model without ambiguity concern. I construct a measure of ambiguity and provide empirical evidence showing that the incentive of analysts to misrepresent information is a function of ambiguity. Analysts are more likely to bias their forecasts when it is more difficult for investors to detect their misrepresentation. Under ambiguity, analysts’ optimistic forecasts for good/bad news tend to deteriorate. Moreover, stock returns are positively related with ambiguity. Under ambiguity neither good nor bad news is credible. Investors systematically underreact to good news forecast and overreact to bad news forecast when ambiguity exists. Full article

The aim of this study is to determine if capital flows can account for the international effects on domestic monetary policy, using an augmented Taylor rule model. In addition to the standard determinants of nominal interest rates, we include capital flow measures to show how central banks consider this important factor when deciding on the most appropriate monetary policy. Using a panel of inflation targeting economies and the dynamic panel approach, this study finds that capital inflows and outflows are an important determinant of nominal interest rates. Full article

Presently, one of the most critical challenges for e-government and e-banking is the accurate and correct realization of factors that have a significant impact on customer behavior. Without appropriate knowledge of these factors, it would be impossible to predict the level of welcoming toward new services, acquire a competitive advantage, and coordinate marketing programs with the needs of customers. On the other hand, in today’s competitive world, banks are obliged to implement new services to retain current customers and attract new ones. This research has been conducted with the goal of identifying influential factors that have an impact on the development of user intentions. The theoretical research model has been designed based on the technology acceptance model (TAM), as well as technology adoption theory, technology dissemination theory, and planned behavior theory. This study adopted an empirical approach to investigate key acceptance factors in a case organization. The statistical population of this research consists of customers and employees in different branches of a financial institution called Mehr bank in Iran. The data was collected by means of questionnaires that were completed by 200 customers and employees who work at Mehr bank or have business relationships with it. Data analysis in descriptive and inferential statistics domains had been done in SPSS and AMOS software, respectively. This paper presents first-hand data analysis of a case study on technology adoption in banking systems in Iran. In addition, structural equations have been used for inferential analysis. The findings of this study confirm the direct impact of “perceived usefulness” and “perceived ease of use” towards user attitudes. In addition, results show that “attitude” and “perceived usefulness” have a direct impact on the development of usage intention in customers. However, the results do not confirm the role of subjective norms on the development of user intent. This study is limited to a selected organization, and the proposed model should be examined by applying it in different contexts. Full article