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Article
Publication date: 5 November 2019

Yi Sun, Quan Jin, Qing Cheng and Kun Guo

The purpose of this paper is to propose a new tool for stock investment risk management through studying stocks with what kind of characteristics can be predicted by…

Abstract

Purpose

The purpose of this paper is to propose a new tool for stock investment risk management through studying stocks with what kind of characteristics can be predicted by individual investor behavior.

Design/methodology/approach

Based on comment data of individual stock from the Snowball, a thermal optimal path method is employed to analyze the lead–lag relationship between investor attention (IA) and the stock price. And machine learning algorithms, including SVM and BP neural network, are used to predict the prices of certain kind of stock.

Findings

It turns out that the lead–lag relationships between IA and the stock price change dynamically. Forecasting based on investor behavior is more accurate only when the IA of the stock is stably leading its price change most of the time.

Research limitations/implications

One limitation of this paper is that it studies China’s stock market only; however, different conclusions could be drawn for other financial markets or mature stock markets.

Practical implications

As for the implications, the new tool could improve the prediction accuracy of the model, thus have practical significance for stock selection and dynamic portfolio management.

Originality/value

This paper is one of the first few research works that introduce individual investor data into portfolio risk management. The new tool put forward in this study can capture the dynamic interplay between IA and stock price change, which help investors identify and control the risk of their portfolios.

Details

Industrial Management & Data Systems, vol. 120 no. 2
Type: Research Article
ISSN: 0263-5577

Keywords

Content available
Article
Publication date: 26 August 2014

Abstract

Details

Asian Review of Accounting, vol. 22 no. 3
Type: Research Article
ISSN: 1321-7348

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Article
Publication date: 9 August 2013

Pan Ji and W. Wayne Fu

This study aims to examine how information and social gratifications sought by Internet users affect their affinity for the Internet or for particular types of online content.

Abstract

Purpose

This study aims to examine how information and social gratifications sought by Internet users affect their affinity for the Internet or for particular types of online content.

Design/methodology/approach

A survey was administered in Singapore to collect data. A correlation analysis, a paired‐sample t test, and hierarchical regression analyses are conducted to address the research questions and hypotheses.

Findings

Affinity for the Internet and affinity for particular types of online content are correlated and distinct. Both relate positively to social gratifications. The passive social gratification of Internet access and the active pursuit of interactions exert similar impact on both types of affinity. Information affects neither after social gratifications are controlled.

Practical implications

Constant access to online contacts or quality online interaction may facilitate social gratifications, thereby boosting user affinity for the Internet or for particular types of online content. Online information should be presented interactively to attract and retain users. The selection of online content and applications should also be made easier to cultivate a loyal user market.

Originality/value

This study contributes to U&G theory by adapting a television‐based proposition to cyberspace, and examining the attitudinal effect of online social gratifications involving different levels of user activity.

Details

Internet Research, vol. 23 no. 4
Type: Research Article
ISSN: 1066-2243

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Article
Publication date: 28 September 2020

Satish Kumar, Riza Demirer and Aviral Kumar Tiwari

This study aims to explore the oil–stock market nexus from a novel angle by examining the predictive role of oil prices over the excess returns associated with the market…

Abstract

Purpose

This study aims to explore the oil–stock market nexus from a novel angle by examining the predictive role of oil prices over the excess returns associated with the market, size, book-to-market and momentum factors via bivariate cross-quantilograms.

Design/methodology/approach

This study makes use of the bivariate cross-quantilogram methodology recently developed by Han et al. (2016) to analyze the predictability patterns across the oil and stock markets by focusing on various quantiles that formally distinguish between normal, bull and bear as well as extreme market states.

Findings

The study analysis of systematic risk premia across the four regions shows that crude oil returns indeed capture predictive information regarding excess factor returns in stock markets, particularly those associated with market, size and momentum factors. However, the predictive power of oil return over excess factor returns is asymmetric and primarily concentrated on extreme quantiles, suggesting that large fluctuations in oil prices capture markedly different predictive information over stock market risk premia during up and down states of the oil market.

Practical implications

The findings have significant implications for the profitability of factor- or style-based active portfolio strategies and suggest that the predictive information contained in oil market fluctuations could be used to enhance returns via conditional strategies based on these predictability patterns.

Originality/value

This study contributes to the vast literature on the oil–stock market nexus from a novel perspective by exploring the effect of oil price fluctuations on the risk premia associated with the systematic risk factors including market, size, value and momentum.

Details

Studies in Economics and Finance, vol. 37 no. 4
Type: Research Article
ISSN: 1086-7376

Keywords

Content available
Article
Publication date: 6 November 2018

Candace Borders, Frank Hsu, Alexander J. Sweidan, Emily S. Matei and Robert G. Bota

Studies suggest deep brain stimulation (DBS) as a treatment modality for the refractory obsessive-compulsive disorder (OCD). It is unclear where to place the DBS. Various…

Abstract

Studies suggest deep brain stimulation (DBS) as a treatment modality for the refractory obsessive-compulsive disorder (OCD). It is unclear where to place the DBS. Various sites are proposed for placement with the ventral capsule/ventral striatum (VC/VS) among the most studied. Herein, we aim to summarize both quantitative Yale-Brown Obsessive-Compulsive Scale (YBOCS) data and qualitative descriptions of the participants' symptoms when given. A literature search conducted via PubMed yielded 32 articles. We sought to apply a standard based on the utilization of YBOCS. This yielded 153 distinct patients. The outcome measure we focused on in this review is the latest YBOCS score reported for each patient/cohort in comparison to the location of the DBS. A total of 32 articles were found in the search results. In total, 153 distinct patients' results were reported in these studies. Across this collection of papers, a total of 9 anatomic structures were targeted. The majority of studies showed a better response at the last time point as compared to the first time point. Most patients had DBS at nucleus accumbens followed by VC/VS and the least patients had DBS at the bilateral superolateral branch of the median forebrain bundle and the bilateral basolateral amygdala. The average YBOCS improvement did not seem to directly correlate with the percentile of patients responding to the intervention.

Well-controlled, randomized studies with larger sample sizes with close follow up are needed to provide a more accurate determination for placement of DBS for OCD.

Details

Mental Illness, vol. 10 no. 2
Type: Research Article
ISSN: 2036-7465

Keywords

Content available
Article
Publication date: 6 September 2021

Gerd Hübscher, Verena Geist, Dagmar Auer, Nicole Hübscher and Josef Küng

Knowledge- and communication-intensive domains still long for a better support of creativity that considers legal requirements, compliance rules and administrative tasks…

Abstract

Purpose

Knowledge- and communication-intensive domains still long for a better support of creativity that considers legal requirements, compliance rules and administrative tasks as well, because current systems focus either on knowledge representation or business process management. The purpose of this paper is to discuss our model of integrated knowledge and business process representation and its presentation to users.

Design/methodology/approach

The authors follow a design science approach in the environment of patent prosecution, which is characterized by a highly standardized, legally prescribed process and individual knowledge study. Thus, the research is based on knowledge study, BPM, graph-based knowledge representation and user interface design. The authors iteratively designed and built a model and a prototype. To evaluate the approach, the authors used analytical proof of concept, real-world test scenarios and case studies in real-world settings, where the authors conducted observations and open interviews.

Findings

The authors designed a model and implemented a prototype for evolving and storing static and dynamic aspects of knowledge. The proposed solution leverages the flexibility of a graph-based model to enable open and not only continuously developing user-centered processes but also pre-defined ones. The authors further propose a user interface concept which supports users to benefit from the richness of the model but provides sufficient guidance.

Originality/value

The balanced integration of the data and task perspectives distinguishes the model significantly from other approaches such as BPM or knowledge graphs. The authors further provide a sophisticated user interface design, which allows the users to effectively and efficiently use the graph-based knowledge representation in their daily study.

Details

International Journal of Web Information Systems, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1744-0084

Keywords

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Article
Publication date: 31 May 2013

Behzad Taheri and Edmond Richer

Autonomous Underwater Vehicles (AUVs) play a crucial role in marine biology research and oceanic natural resources exploration. Since most AUVs are underactuated they…

Abstract

Purpose

Autonomous Underwater Vehicles (AUVs) play a crucial role in marine biology research and oceanic natural resources exploration. Since most AUVs are underactuated they require sophisticated trajectory planning and tracking algorithms. The purpose of this paper is to develop a new method that allows an underactuated AUV to track a moving object while constraining the approach to a direction tangent to the path of the target. Furthermore, the distance at which the AUV follows the target is constrained, reducing the probability of detection and unwanted behavior change of the target.

Design/methodology/approach

First, a kinematic controller that generates a trajectory tangent to the path of the moving target is designed such that the AUV maintains a prescribed distance and approaches the target from behind. Using a Lyapunov based method the stability of the kinematic controller is proven. Second, a dynamic sliding mode controller is employed to drive the vehicle on the trajectory computed in the first step.

Findings

The kinematic and dynamic controllers are shown to be stable and robust against parameter uncertainty in the dynamic model of the vehicle. Results of numerical simulations for equidistant tracking of a target on both smooth and discontinuous derivatives trajectories for a variety of relative initial positions and orientations are shown.

Originality/value

The contribution of this research is development of a new method for path planning and tracking of moving targets for underactuated AUVs in the horizontal plane. The method allows control of both the direction of approach and the distance from a moving object.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 6 no. 2
Type: Research Article
ISSN: 1756-378X

Keywords

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Article
Publication date: 30 April 2021

Shaofei Wang and Depeng Dang

Previous knowledge base question answering (KBQA) models only consider the monolingual scenario and cannot be directly extended to the cross-lingual scenario, in which the…

Abstract

Purpose

Previous knowledge base question answering (KBQA) models only consider the monolingual scenario and cannot be directly extended to the cross-lingual scenario, in which the language of questions and that of knowledge base (KB) are different. Although a machine translation (MT) model can bridge the gap through translating questions to the language of KB, the noises of translated questions could accumulate and further sharply impair the final performance. Therefore, the authors propose a method to improve the robustness of KBQA models in the cross-lingual scenario.

Design/methodology/approach

The authors propose a knowledge distillation-based robustness enhancement (KDRE) method. Specifically, first a monolingual model (teacher) is trained by ground truth (GT) data. Then to imitate the practical noises, a noise-generating model is designed to inject two types of noise into questions: general noise and translation-aware noise. Finally, the noisy questions are input into the student model. Meanwhile, the student model is jointly trained by GT data and distilled data, which are derived from the teacher when feeding GT questions.

Findings

The experimental results demonstrate that KDRE can improve the performance of models in the cross-lingual scenario. The performance of each module in KBQA model is improved by KDRE. The knowledge distillation (KD) and noise-generating model in the method can complementarily boost the robustness of models.

Originality/value

The authors first extend KBQA models from monolingual to cross-lingual scenario. Also, the authors first implement KD for KBQA to develop robust cross-lingual models.

Details

Data Technologies and Applications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9288

Keywords

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Article
Publication date: 22 July 2021

Han Liu, Ying Liu, Gang Li and Long Wen

This study aims to examine whether and when real-time updated online search engine data such as the daily Baidu Index can be useful for improving the accuracy of tourism…

Abstract

Purpose

This study aims to examine whether and when real-time updated online search engine data such as the daily Baidu Index can be useful for improving the accuracy of tourism demand nowcasting once monthly official statistical data, including historical visitor arrival data and macroeconomic variables, become available.

Design/methodology/approach

This study is the first attempt to use the LASSO-MIDAS model proposed by Marsilli (2014) to field of the tourism demand forecasting to deal with the inconsistency in the frequency of data and the curse problem caused by the high dimensionality of search engine data.

Findings

The empirical results in the context of visitor arrivals in Hong Kong show that the application of a combination of daily Baidu Index data and monthly official statistical data produces more accurate nowcasting results when MIDAS-type models are used. The effectiveness of the LASSO-MIDAS model for tourism demand nowcasting indicates that such penalty-based MIDAS model is a useful option when using high-dimensional mixed-frequency data.

Originality/value

This study represents the first attempt to progressively compare whether there are any differences between using daily search engine data, monthly official statistical data and a combination of the aforementioned two types of data with different frequencies to nowcast tourism demand. This study also contributes to the tourism forecasting literature by presenting the first attempt to evaluate the applicability and effectiveness of the LASSO-MIDAS model in tourism demand nowcasting.

Details

International Journal of Contemporary Hospitality Management, vol. 33 no. 6
Type: Research Article
ISSN: 0959-6119

Keywords

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Article
Publication date: 25 November 2020

Yi Liu, Fanhua Wu, Xinwei Tian, Xiaoyang Hu, Yongfeng Liu, Xiandong Zhao, Rongjun Qu, Chunnuan Ji and Yuzhong Niu

This paper aims to focus on the preparation of Kevlar fiber (KF) and alkaline hydrolyzed KF (KF-H) to improve the dispersed condition of polyaniline (PAn), as the…

Abstract

Purpose

This paper aims to focus on the preparation of Kevlar fiber (KF) and alkaline hydrolyzed KF (KF-H) to improve the dispersed condition of polyaniline (PAn), as the aggregation of PAn would lead to some adsorption sites buried. And then the materials were used to enrich anionic dye Congo red (CR) from aqueous solution.

Design/methodology/approach

The materials (KF@PAn and KF-H@PAn) were designed by means of “diffusion-interfacial-polymerization” under mild condition as high affinity due to the structural properties of PAn, KF and KF-H. The dispersed degree of PAn on the surface of KF and KF-H was validated according to adsorption efficiency for CR.

Findings

The content of PAn introduced was not beyond 20 wt.%, while adsorption capacity for CR was significantly enhanced by 4–8 times (on the basis of kinetic data) according to the calculation only by the content of PAn due to KF and alkaline hydrolyzed KF exhibited almost no adsorption for CR, indicating dispersed situation of PAn coating was greatly enhanced and more active sites exposed, which was favorable for the adsorption process. Presence of NaCl would exhibit a more or less positive effect on CR uptake, suggesting the materials could be used for high salt environment.

Research limitations/implications

The investigated means of dispersed degree of PAn on the surface of KF and KF-H are the further and future investigation.

Practical implications

This study will provide a method to improve the dispersed situation of PAn and a theoretical support to treat anionic dyes from aqueous solution especially for salt environment.

Originality/value

The results showed that the dispersed condition of PAn on the surface of KF and KF-H was greatly improved. According to the adsorption capacities for CR, it can be concluded that part of adsorption sites were buried due to the aggregation of PAn, and introduction of KF and KF-H, buried adsorption sites decreased greatly. This study will provide a method to decrease buried adsorption sites of PAn and a contribution for their convenient application in wastewater treatment especially for high salt environment.

Details

Pigment & Resin Technology, vol. 50 no. 4
Type: Research Article
ISSN: 0369-9420

Keywords

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