Joint dynamic modeling and option pricing in incomplete derivative-security market

In this study, we evaluate the option prices on two assets under stochastic interest rates when the stochastic process that underlying asset prices follow is depending on a correlated bivariate Markov-modulated geometric Brownian motion model with jump risks. More specifically, we conduct the joint dynamic modeling by identifying two independent compound Poisson processes with the log-normal jump sizes to describe both individual jumps and systematic cojumps. Facilitating the cojumping behavior this way with the time-inhomogeneity of the volatility, option pricing expressions are readily obtainable since the Gerber–Siu’s approach is employed to determine a pricing kernel. The empirical results and numerical illustrations are provided to show the impact of cojumps and stochastic volatilities on option prices.     

Exploring customer sentiment regarding online retail services: A topic-based approach

User-generated content is a valuable source for understanding online shoppers' emotions. Using text-mining techniques, this study identifies seven topics regarding online retail services in online posts: product, retailer promotion, delivery, payment, communication, return/refund, and price. The topics are associated with the sentiment polarity of online shoppers' posts. This study further explores whether the emotional responses from domestic and cross-border online shoppers differ with regard to these topics. The results show that differences exist in these two groups' sentiments concerning product and payment. Furthermore, there are differences in the two groups’ respective negative emotions (i.e., anger, sadness, and fear) concerning delivery, communication, and return/refund. The findings of this study provide online retailers with important managerial implications.     

What Are You Saying? Using topic to Detect Financial Misreporting

We use a machine learning technique to assess whether the thematic content of financial statement disclosures (labeled topic) is incrementally informative in predicting intentional misreporting. Using a Bayesian topic modeling algorithm, we determine and empirically quantify the topic content of a large collection of 10-K narratives spanning 1994 to 2012. We find that the algorithm produces a valid set of semantically meaningful topics that predict financial misreporting, based on samples of Securities and Exchange Commission (SEC) enforcement actions (Accounting and Auditing Enforcement Releases [AAERs]) and irregularities identified from financial restatements and 10-K filing amendments. Our out-of-sample tests indicate that topic significantly improves the detection of financial misreporting by as much as 59% when added to models based on commonly used financial and textual style variables. Furthermore, models that incorporate topic significantly outperform traditional models when detecting serious revenue recognition and core expense errors. Taken together, our results suggest that the topics discussed in annual report filings and the attention devoted to each topic are useful signals in detecting financial misreporting.     

Does financial development stimulate environmental sustainability? Evidence from a panel study of 115 countries

This paper investigates the moderation effect of financial development (FD) on the environmental Kuznets curve (EKC). Using comprehensive panel data of 115 countries spanning the 1990–2016 period and dividing the countries into different income groups, the researcher found systematic differences in the relationship between significant indicators of environmental degradation and economic growth. More specifically, the interaction effect of FD on the relationship between gross domestic product (GDP) growth and CO₂ emissions are positive; nevertheless, the interaction effect of FD on the relationship between GDP squared and CO₂ emissions become negative for all income groups and therefore supports the EKC. Moreover, the interaction effect of FD is negative on the relationship of GDP with both CH₄ and PM_2.5 emissions in the middle‐income groups, whereas the interaction effect of FD on the relationship between GDP squared and PM_2.5 emissions are negative for the high‐income group. Our results suggest that FD can reduce environmental degradation without adversely impacting on growth.     

The effects of management inertia on the supply chain performance of produce-to-stock firms

This article examines the impact of inertia on the management of the firm's supply chain operations and the effects it can have on a produce-to-stock firm's ability to respond to external market pressure and develop corrective strategies. The research methodology used is based on earlier Catastrophe Modeling that looked at inertia in organizational design, competitive pressure, and competitive response. The model demonstrates how latent variables, such as customer pressure and supply chain inertia can influence a finished goods supply chain management's response under various conditions. The model was tested and validated using questionnaire data gathered from a sample of members of the Council of Logistics Management. The model was used to estimate individual finished goods firm inertia response estimates. We incorporate these estimates in a brief examination of three produce-to-stock firms from the sample to give readers an idea of the usefulness of the approach in examining supply chain inertia.     

Resident attitudes toward sustainable community tourism

This study examined, using social exchange theory, a range of variables involved in determining resident attitudes toward tourism development and the adoption of sustainable tourism. After a comprehensive review of the literature on the role of residents in tourism development, and of the use of social exchange theory, 430 completed questionnaires obtained in a Texas town involved in tourism were analyzed. A structural equation model was utilized to understand the effects of selected components of sustainability on the attitudes of the respondents about future tourism development and to test hypothesized causal relationships among the variables. The findings revealed that three major components of sustainable tourism, namely long-term planning, full community participation and environmental sustainability within tourism, are critically related to support for tourism and to the positive and negative impacts of tourism. The paper uses the findings to suggest critical implications that local governments need to consider when developing tourism.     

Wine attributes,perceived risk and online wine repurchase intention: The cross-level interaction effects of website quality

It is vital for the successful web-based wine business to reduce perceived risk associated with online wine purchasing because it negatively affects repurchase intention. Randomly obtained data from 457 U.S. consumers identified as having purchased wine online was analyzed using hierarchical linear modeling (HLM) to determine the relationships between key wine attributes, perceived risk and online wine repurchase intention. Results confirmed that sensory and origin-related attributes positively influence perceived risk. The cross-level interaction role that wine website quality plays upon the relationship between wine attributes and perceived risk was also examined. Results revealed that information quality and service quality moderate the impact of the origin attribute, which in turn reduces perceived risk with online wine shopping. These findings offer useful implications for online wine website managers to develop more effective website frameworks.     

Market size,scale economies,and tourism market structure: A case of historic water town tourism in China

The historic water towns in the Tai Lake Basin are representative of tourism products featuring a unique cultural heritage landscape and the local way of life in eastern China. Since the 1980s, this market has experienced phenomenal growth in both the quantity of water towns and the scale of tourist arrivals. Drawing from industrial economics theory and an agent-based modeling approach, we examine the structural evolution of this market. Simulation results show that scale economies and market size are a pair of opposite forces driving the evolution of the historic water town tourism market structure, where scale economies play a role as a barrier to deter potential entrants and ensure superprofits for existing water towns, while an expanding market size creates opportunities for entry. Theoretical and practical implications are discussed, and management recommendations are made for tourism destinations competing with identical products and services.     

Spatial Complementarity of Forests and Farms: Accounting for Ecosystem Services

Our article considers the economic contributions of forest ecosystem services, using a case study from Flores, Indonesia, in which forest protection in upstream watersheds stabilize soil and hydrological flows in downstream farms. We focus on the demand for a weak complement to the ecosystem services—farm labor—and account for spatial dependence due to economic interactions, ecosystem processes, and data integration. The estimated models have theoretically expected properties across eight different specifications. We find strong evidence that forest ecosystem services provide economically substantive benefits to local people and that these services would be substantially undervalued if spatial dependence is ignored.     

On estimating true change interrelationships with other variables

This article is concerned with the estimation of indexes of interrelationship between true change in repeatedly assessed latent constructs and other variables. In the social and behavioral sciences this theoretically and empirically important issue arises commonly in research aimed at studying correlates and predictors of growth or decline in a context of a longitudinal research design. A structural equation modeling approach is described that is useful in empirical situations where identifying variables correlated with change in longitudinally followed latent constructs is of interest. The issue of discerning between correlates and predictors of change using the structural equation modeling methodology is discussed. The described approach is used to study correlative aspects of ability growth in a cognitive intervention study (Balteset al., 1986).