The endo–exo problem in high frequency financial price fluctuations and rejecting criticality

The endo–exo problem lies at the heart of statistical identification in many fields of science, and is often plagued by spurious strong-and-long memory due to improper treatment of trends, shocks and shifts in the data. A class of models that has shown to be useful in discerning exogenous and endogenous activity is the Hawkes process. This class of point processes has enjoyed great recent popularity and rapid development within the quantitative finance literature, with particular focus on the study of market microstructure and high frequency price fluctuations. We show that there are important lessons from older fields like time series and econometrics that should also be applied in financial point process modelling. In particular, we emphasize the importance of appropriately treating trends and shocks for the identification of the strength and length of memory in the system. We exploit the powerful Expectation Maximization algorithm and objective statistical criteria (BIC) to select the flexibility of the deterministic background intensity. With these methods, we strongly reject the hypothesis that the considered financial markets are critical at univariate and bivariate microstructural levels.     

Understanding innovation

While innovation has become a pervasive term, many of today’s organizations still find innovation elusive. One reason may be that much of what is being said about innovation contributes to misunderstanding. To truly manifest innovation and reap its benefits, one must recognize that innovation is three different things: innovation is an outcome, innovation is a process, and innovation is a mindset. Innovation as an outcome emphasizes what output is sought, including product innovation, process innovation, marketing innovation, business model innovation, supply chain innovation, and organizational innovation. Innovation as a process attends to the way in which innovation should be organized so that outcomes can come to fruition; this includes an overall innovation process and a new product development process. Innovation as a mindset addresses the internalization of innovation by individual members of the organization where innovation is instilled and ingrained along with the creation of a supportive organizational culture that allows innovation to flourish. Such an understanding defines necessary elements, considerations, and vernacular surrounding the term so that better decisions can be made, thereby enabling innovation and having a greater propensity to succeed.     

Using methods of Multi-Criteria Decision Making to provide decision support concerning local bioenergy projects

The public sector plays an important role in the German “Energiewende”. Besides energy management in municipal properties the local government can also support the switch to renewable energy sources through a change in energy supply structures within in their region. Methods of Multi-Criteria Decision Making (MCDM) from Operations Research are helpful regarding that challenge, as they are able to assess the sustainability of local energy concepts, since they not only offer stakeholders the opportunity to participate, but also consider multiple conflicting criteria. In that way, the acceptance of local energy projects and the participation of stakeholders in the decision process are supported. The case study presented in this paper illustrates the results of a MCDM process employed to identify a sustainable bioenergy concept in a rural village in Lower Saxony, Germany. Our analysis revealed not only the opportunities and challenges associated with executing an MCDM process to support the realization of local bioenergy projects, but also discusses potential limitations of the methods.     

西北生态山岳旅游健康发展评估

生态山岳的旅游健康发展程度对山地旅游资源的可持续利用具有重要的影响。采用层次分析法和熵权法对2018年西北地区的华山、麦积山和天山天池的旅游生态健康进行了分析。结果表明:三大山岳景区旅游健康发展均处于健康状态;在资源健康方面,天山天池表现为非常健康,华山和麦积山处于健康等级;在环境健康方面,麦积山处于非常健康,华山和天山天池处于健康等级;在经济健康和旅游社会方面,三大景区均表现为健康。     

Risk assessment for public–private partnership projects: using a fuzzy analytic hierarchical process method and expert opinion in China

Public–private partnerships (PPP) have been widely used in China to procure public facilities and services. Complicated problems in PPP projects in China arise because of a variety of risk factors. A proper risk assessment model is needed to identify risks and provide risk response strategies for future Chinese PPP projects. The fuzzy analytic hierarchy process (F-AHP) method provides the ability to solve complex risk assessment of PPP projects. Current risk assessment models are limited to PPP projects in specific countries and do not consider unique risks in China, especially political, economic, social, and legal risks. This paper designed a risk evaluation index system for PPP projects based on the Delphi expert investigation method, and then established an optimized risk evaluation model for PPP projects in China using the F-AHP method. The risks identified are confirmed by interviewing experts from Chinese local government departments, private enterprise, third-party intermediary consulting and regulatory agencies, and academic organizations. The results show that the risks that ranked among the top ten are closely related to China’s political and economic policies and relationships among stakeholders. It can be concluded that government authorities play a critical role in providing a favorable political, social, and economic environment and an effective institutional framework for PPP projects. Furthermore, it is also important to deal with relationships among stakeholders based on the public–private ‘win–win’ principle. This study provides risk response strategies, addressing key issues from eight aspects: an impeccable legal and regulatory framework; a central coordinating and regulating PPP authority; supportive governmental authorities; institutional capacity-building; favorable economic conditions and viability; community, partner, and moral accountability; clear division of responsibilities through contracts; and effective advisory management. These effective measures may be useful in reducing the adverse effects of risk for PPP projects in China.     

Option pricing based on hybrid GARCH-type models with improved ensemble empirical mode decomposition

The exploration of option pricing is of great significance to risk management and investments. One important challenge to existing research is how to describe the underlying asset price process and fluctuation features accurately. Considering the benefits of ensemble empirical mode decomposition (EEMD) in depicting the fluctuation features of financial time series, we construct an option pricing model based on the new hybrid generalized autoregressive conditional heteroskedastic (hybrid GARCH)-type functions with improved EEMD by decomposing the original return series into the high frequency, low frequency and trend terms. Using the locally risk-neutral valuation relationship (LRNVR), we obtain an equivalent martingale measure and option prices with different maturities based on Monte Carlo simulations. The empirical results indicate that this novel model can substantially capture volatility features and it performs much better than the M-GARCH and Black–Scholes models. In particular, the decomposition is consistently helpful in reducing option pricing errors, thereby proving the innovativeness and effectiveness of the hybrid GARCH option pricing model.     

Tracing VARDI coefficients: a proposal

ABSTRACT

We propose a new approach for tracing the so-called ‘value-added-(re)distribution-important coefficients’ (in short the VARDI coefficients) in a world input–output model. From the perspective of a selected group of economies, VARDI coefficients may be defined as those elements in world input–output matrix in the case of which a small change in their levels leads to the maximization of a share of this group of economies in value added in global value chains. Due to the rapid development of the World Input Output Database, this approach may be easily applied in empirical research to different groups of countries and sectors in world IO models. In an illustrative empirical case study, we use the new approach in order to answer a question regarding what the main directions of the future macroeconomic policy of the U.S. could be in order to ensure the maximization of the country’s share in global value added.     

GIS-based fuzzy multi-criteria approach for optimal site selection of fire stations in Istanbul,Turkey

Fire stations play a central role in protection and response activities as part of emergency management services in cases of fire incidences. With the rising urban populations and city expansions, the demand for more fire services resultantly increases. It then becomes critical to effectively plan the location of emergency facilities to adequately service the population and ensure the protection of lives and infrastructure. This study, therefore proposes the use of the fuzzy extension of the Multi-Criteria Decision-Making (MCDM) method of Analytical Hierarchical Process (AHP), hence called fuzzy AHP, integrated with Geographic Information Systems (GIS) approach to optimally site new fire stations for the case of Istanbul region. This proposed fuzzy approach simulates the subjective expert judgements for the preferences of the six criteria assessed for fire station suitability mapping and thereby accounted for the uncertainty of crisp comparison values via triangular fuzzy numbers (TFNs). The criteria weights evaluated from this procedure were used in a weighted overlay analysis of the reclassified criteria map layers in ArcGIS to generate a fire station suitability map. These resultant fuzzy AHP criteria weights were validated using another MCDM technique, called Best-Worst Method (BWM) and found to be comparable and consistent. The criteria that had the strongest influence on the selection of sites for fire stations were identified to be: the density of hazardous material facilities (DHM), a high population density (HPD) and proximity to main roads (PMR) with associated weights of 33.3%, 24.4% and 15.2%, respectively. Based on a thorough assessment within the areas represented by class values ranging from 3 to 5 on the suitability map, a total of 34 new fire station sites were selected complementing the existing 121 fire stations. Further, a prioritization analysis from low, medium to high, was performed to plan the phases for the construction of new fire stations in view of competing budgetary needs and resource constraints. The methodology to achieve this was proposed and modelled for enhancing the decision-making process in urban fire station site selection studies.     

Optimizing a portfolio of mean-reverting assets with transaction costs via a feedforward neural network

Optimizing a portfolio of mean-reverting assets under transaction costs and a finite horizon is severely constrained by the curse of high dimensionality. To overcome the exponential barrier, we develop an efficient, scalable algorithm by employing a feedforward neural network. A novel concept is to apply HJB equations as an advanced start for the neural network. Empirical tests with several practical examples, including a portfolio of 48 correlated pair trades over 50 time steps, show the advantages of the approach in a high-dimensional setting. We conjecture that other financial optimization problems are amenable to similar approaches.     

Cognitive foundations of firm internationalization: A systematic review and agenda for future research

Managerial cognition has a fundamental role in the internationalization of firms. However, there exists no coherent understanding of how prior research has examined and captured the cognitive foundations of internationalization. This paper provides a systematic review of this body of literature. The review identifies three main streams of research that, overall, consists of nine more specific research areas. We show that especially the areas addressing (1) managerial learning, (2) characteristics of upper echelons, (3) intra-organizational perceptions, and (4) external actors’ perceptions provide opportunities for the further advancement of internationalization literature. For harnessing these opportunities, we find that the microfoundational approach could support the empirical examination of the cognitive foundations and would notably contribute to the Uppsala model-based theorization of the firm internationalization process.