Matching Items (60)
Description
Given the "New Nine Measures" for capital market reform, a policy document issued by the State Council of China, the development of markets for interest rate derivatives, such as treasury futures, becomes an increasingly important task. Several shortcomings of the existing treasury futures market have been noted: including low market liquidity, singular investor composition, restrict contract terms, and low hedging demand.
This study contributes to a better understanding of the treasury futures market by analyzing changes in China treasury futures market regulations and their impact on market liquidity of treasury futures. Found that compared with the mature market, China treasury futures market exists liquidity shortage, the trading system, market structure and the division of regulatory are factors which influence the liquidity of China treasury futures market.
This study found that reducing transaction costs for further optimization of the width and depth of China treasury futures market are not obvious by using quantitative analysis method, expanding the smallest change price can optimize the market depth, reducing transaction costs and expanding smallest change price can optimize the immediacy, volume and hosting amount. In addition, the bond market will also influence the treasury futures market, the price fluctuations and the morphology of the yield curve of bond market have significant influence on width, depth and holdings of market.
The system of China treasury futures market needs to be optimized by expanding the smallest change price and reducing transaction costs. The market structure needs to be optimized by establishing unified bond market and enriching investor structure.
These findings have significant theoretical and practical implications. The study also provides policy recommendations for the design and establishment of treasury futures market to the regulatory agencies.
This study contributes to a better understanding of the treasury futures market by analyzing changes in China treasury futures market regulations and their impact on market liquidity of treasury futures. Found that compared with the mature market, China treasury futures market exists liquidity shortage, the trading system, market structure and the division of regulatory are factors which influence the liquidity of China treasury futures market.
This study found that reducing transaction costs for further optimization of the width and depth of China treasury futures market are not obvious by using quantitative analysis method, expanding the smallest change price can optimize the market depth, reducing transaction costs and expanding smallest change price can optimize the immediacy, volume and hosting amount. In addition, the bond market will also influence the treasury futures market, the price fluctuations and the morphology of the yield curve of bond market have significant influence on width, depth and holdings of market.
The system of China treasury futures market needs to be optimized by expanding the smallest change price and reducing transaction costs. The market structure needs to be optimized by establishing unified bond market and enriching investor structure.
These findings have significant theoretical and practical implications. The study also provides policy recommendations for the design and establishment of treasury futures market to the regulatory agencies.
ContributorsMa, Jun (Author) / Gu, Bin (Thesis advisor) / Chen, Hong (Thesis advisor) / Wang, Tan (Committee member) / Arizona State University (Publisher)
Created2016
Description
The recent changes in the software markets gave users an unprecedented number
of alternatives for any given task. In such a competitive environment, it is imperative
to understand what drives user behavior. To that end, the research presented in
this dissertation, tries to uncover the impact of business strategies often used in the
software markets.
The dissertation is organized into three distinct studies into user choice and post
choice use of software. First using social judgment theory as foundation, zero price
strategies effects on user choice is investigated, with respect to product features,
consumer characteristics, and context effects. Second, role of social features in
moderating network effects on user choice is studied. And finally, the role of social
features on the effectiveness of add-on content strategy on continued user engagement
is investigated.
The findings of this dissertation highlight the alignments between popular business
strategies and broad software context. The dissertation contributes to the litera-
ture by uncovering hitherto overlooked complementarities between business strategy
and product features: (1) zero price strategy enhances utilitarian features but not
non-utilitarian features in software choice, (2) social features only enhance network
externalities but not social influence in user choice, (3) social features enhance the
effect of add-on content strategy in extending software engagement.
of alternatives for any given task. In such a competitive environment, it is imperative
to understand what drives user behavior. To that end, the research presented in
this dissertation, tries to uncover the impact of business strategies often used in the
software markets.
The dissertation is organized into three distinct studies into user choice and post
choice use of software. First using social judgment theory as foundation, zero price
strategies effects on user choice is investigated, with respect to product features,
consumer characteristics, and context effects. Second, role of social features in
moderating network effects on user choice is studied. And finally, the role of social
features on the effectiveness of add-on content strategy on continued user engagement
is investigated.
The findings of this dissertation highlight the alignments between popular business
strategies and broad software context. The dissertation contributes to the litera-
ture by uncovering hitherto overlooked complementarities between business strategy
and product features: (1) zero price strategy enhances utilitarian features but not
non-utilitarian features in software choice, (2) social features only enhance network
externalities but not social influence in user choice, (3) social features enhance the
effect of add-on content strategy in extending software engagement.
ContributorsKanat, Irfan (Author) / Santanam, Raghu (Thesis advisor) / Vinze, Ajay (Thesis advisor) / Gu, Bin (Committee member) / Arizona State University (Publisher)
Created2016
Description
By collecting and analyzing more than two million tweets, U.S. House Representatives’ voting records in 111th and 113th Congress, and data from other resources I study several aspects of adoption and use of Twitter by Representatives. In the first chapter, I study the overall impact of Twitter use by Representatives on their political orientation and their political alignment with their constituents. The findings show that Representatives who adopted Twitter moved closer to their constituents in terms of political orientation.
By using supervised machine learning and text mining techniques, I shift the focus to synthesizing the actual content shared by Representatives on Twitter to evaluate their effects on Representatives’ political polarization in the second chapter. I found support for the effects of repeated expressions and peer influence in Representatives’ political polarization.
Last but not least, by employing a recently developed dynamic network model (separable temporal exponential-family random graph model), I study the effects of homophily on formation and dissolution of Representatives’ Twitter communications in the third chapter. The results signal the presence of demographic homophily and value homophily in Representatives’ Twitter communications networks.
These three studies altogether provide a comprehensive picture about the overall consequences and dynamics of use of online social networking platforms by Representatives.
By using supervised machine learning and text mining techniques, I shift the focus to synthesizing the actual content shared by Representatives on Twitter to evaluate their effects on Representatives’ political polarization in the second chapter. I found support for the effects of repeated expressions and peer influence in Representatives’ political polarization.
Last but not least, by employing a recently developed dynamic network model (separable temporal exponential-family random graph model), I study the effects of homophily on formation and dissolution of Representatives’ Twitter communications in the third chapter. The results signal the presence of demographic homophily and value homophily in Representatives’ Twitter communications networks.
These three studies altogether provide a comprehensive picture about the overall consequences and dynamics of use of online social networking platforms by Representatives.
ContributorsMosuavi, Seyedreza (Author) / Gu, Bin (Thesis advisor) / Vinzé, Ajay S. (Committee member) / Shi, Zhan (Michael) (Committee member) / Arizona State University (Publisher)
Created2016
Description
With the fast development of Chinese capital market, an increasing number of institutions and retail investors invest through professional managers. The key to evaluating investment manager’s skill and performance persistence largely lies in portfolio style research and attribution analysis.
The current dissertation takes advantage of a unique dataset, uncover hidden investment style and trading behavior, understanding their source of excess returns, and establishing a more comprehensive methodology for evaluating portfolio performance and manager skills.
The dissertation focuses on quantitative analysis. Highlights three most important aspects. Investment style determines the systematic returns and risks of any portfolio, and can be assessed ex-ante; Transaction can be observed and modified during the investment process; and return attribution can be implemented to evaluate portfolio (managers), ex-post. Hence, these three elements make up a comprehensive and logical investment process.
Investment style is probably the most important factor in determining portfolio returns. However, Chinese investment managers are under constant pressure to follow the market trend and shift style accordingly. Therefore, accurately identifying and predicting each manager’s investment style proves critically valuable.
In addition, transaction data probably provides the most reliable source of information in observing and evaluating an investment manager’s style and strategy, in the middle of the investment process.
Despite the efficacy of traditional return attribution methodology, there are clear limitations. The current study proposes a novel return attribution methodology, by synthesizing major portfolio strategy components, such as risk exposure adjustment, sector rotation, stock selection, altogether. Our novel methodology reveals that investment managers do not obtain much abnormal returns through risk exposure adjustment or sector rotation. Instead, Chinese investment managers seem to enjoy most of their excess returns through stock selection.
In addition, we find several interesting patterns in Chinese A-share market: 1). There is a negative relationship between asset under management (AUM) and investment performance, beyond certain AUM threshold; 2). There are limited benefits from style switching in the long run; 3). Many investment managers use CSI 300 component stocks as portfolio ballast and speculate with CSI500 and Medium-and-Small board component stocks for excess returns; 4). There is no systematic negative relationship between portfolio turnover and investment performance; despite negative relationship within certain sub-samples and sectors; 5). It is plausible to construct out-performing portfolios with style index funds and ETFs.
The current dissertation takes advantage of a unique dataset, uncover hidden investment style and trading behavior, understanding their source of excess returns, and establishing a more comprehensive methodology for evaluating portfolio performance and manager skills.
The dissertation focuses on quantitative analysis. Highlights three most important aspects. Investment style determines the systematic returns and risks of any portfolio, and can be assessed ex-ante; Transaction can be observed and modified during the investment process; and return attribution can be implemented to evaluate portfolio (managers), ex-post. Hence, these three elements make up a comprehensive and logical investment process.
Investment style is probably the most important factor in determining portfolio returns. However, Chinese investment managers are under constant pressure to follow the market trend and shift style accordingly. Therefore, accurately identifying and predicting each manager’s investment style proves critically valuable.
In addition, transaction data probably provides the most reliable source of information in observing and evaluating an investment manager’s style and strategy, in the middle of the investment process.
Despite the efficacy of traditional return attribution methodology, there are clear limitations. The current study proposes a novel return attribution methodology, by synthesizing major portfolio strategy components, such as risk exposure adjustment, sector rotation, stock selection, altogether. Our novel methodology reveals that investment managers do not obtain much abnormal returns through risk exposure adjustment or sector rotation. Instead, Chinese investment managers seem to enjoy most of their excess returns through stock selection.
In addition, we find several interesting patterns in Chinese A-share market: 1). There is a negative relationship between asset under management (AUM) and investment performance, beyond certain AUM threshold; 2). There are limited benefits from style switching in the long run; 3). Many investment managers use CSI 300 component stocks as portfolio ballast and speculate with CSI500 and Medium-and-Small board component stocks for excess returns; 4). There is no systematic negative relationship between portfolio turnover and investment performance; despite negative relationship within certain sub-samples and sectors; 5). It is plausible to construct out-performing portfolios with style index funds and ETFs.
ContributorsZhan, Yuyin (Author) / Gu, Bin (Thesis advisor) / Wang, Jiang (Thesis advisor) / Wang, Tan (Committee member) / Arizona State University (Publisher)
Created2016
Description
In the last two years, China’s booming of Internet Finance Platform made significant impacts on three dimensions. Compared with the conventional market, Internet Finance is asserted to open a revolutionary pathway of lending where by small and mid-sized companies may overcome the financing dilemma on credit accessibility and high cost. In other words, Internet Finance is hyped to be able to reduce information asymmetry, enhance allocation efficiency of resources, and promote product and process innovations for the financial institutions. However, the core essence of Internet Finance rests on risk assessment and control – a fundamental element applies to all forms of financing. Most current practice of internet finance on risk assessment and control remains unchanged from the mindset of traditional banking practices for small and medium sized firms. Hence, the same problems persisted and may only become even worse under the internet finance platform if no innovations take place.
In this thesis, the author proposed and tested a credit risk assessment model using data analytics techniques through an in-depth cases study with actual transaction data. Specifically, based on the 30,000 observations collected from actual transactional data from small and medium size firms of China’s home furnishing industry. The preliminary results are promising in spite of the limitations. The thesis concludes with the findings of relevance to improve the current practices and suggests areas of future research.
In this thesis, the author proposed and tested a credit risk assessment model using data analytics techniques through an in-depth cases study with actual transaction data. Specifically, based on the 30,000 observations collected from actual transactional data from small and medium size firms of China’s home furnishing industry. The preliminary results are promising in spite of the limitations. The thesis concludes with the findings of relevance to improve the current practices and suggests areas of future research.
ContributorsZhang, Qi (Author) / Pei, Ker-Wei (Thesis advisor) / Gu, Bin (Thesis advisor) / Cui, Haitao (Committee member) / Arizona State University (Publisher)
Created2016
Description
The city of Shanghai is set to become an international financial center (IFC) by 2020. To achieve this goal, it is imperative to clearly define the key characteristics of an IFC. In this study I draw from recent research on the ranking of IFCs to develop an index of these key characteristics that can be used to assess a city’s standings as an IFC. Based on a review of prior research, I first put together a comprehensive list of the indicators that have been used to evaluate IFCs, which includes six first-level indicators and 34 second-level indicators. I then collect information on all these indicators from public sources for the following eight cities each year from 2011 to 2013: London, New York, Paris, Hong Kong, Tokyo, Singapore, Beijing and Shanghai. Next, I conduct a principal component analysis (PCA) on my data, and obtain four primary factors that contain most information of the original 34 indicators. The first factor covers 18 of the original indicators and reflects a city’s level of development in general business environment. The second factor covers 10 of the original indicators and reflects a city’s level of development in financial markets. The third factor covers three of the original indicators and reflects a city’s level of economic vitality. The fourth factor covers three of the original indicators and reflects a city’s level of the costs of living. I further calculate the composite scores for the above eight cities along these four factors, and find that these eight cities can be classified into three tiers on the basis of their scores. The first tier consists of New York and London; the second tier consists of Singapore, Hong Kong, Paris and Tokyo; and the third tier consists of Shanghai and Beijing. I also find that Shanghai has been making progress in its scores along these four factors over the last three years, especially regarding financial market development, economic vitality, and cost of living. What Shanghai needs to focus on next is to improve its business environment so that it can move up to the second tier in IFC status.
ContributorsWang, Weiren, Ph.D (Author) / Yao, David (Thesis advisor) / Gu, Bin (Thesis advisor) / Chen, Hong (Committee member) / Arizona State University (Publisher)
Created2015
Description冷链物流主要是指食品在生产到消费者食用前始终处于适宜的温度环境，以保障食品品质、降低流通过程中的损耗。冷链物流相比于传统物流而言是一项更复杂的系统性工程，受到政策和市场需求的影响呈现迅猛发展态势。但是，冷链物流企业长期以来因规模小、固定资产少、服务范围窄、服务规范性弱而发展困难重重，核心问题是资金的问题。政府引导和鼓励打造冷链物流产业园，推动产业园投资和建设主体打造平台，实现对园区内冷链企业的聚集效应并通过金融服务解决企业发展的资金问题。通过产融结合助力冷链物流企业发展，成为目前冷链物流行业发展的主要方式和未来趋势。
本研究聚焦冷链物流产业园金融服务助力冷链物流企业发展问题，主要研究内容包括：第一，基于产融结合理论，梳理冷链物流企业与产业园之间关系，从供需两侧探索冷链物流企业和产业园的金融服务的范围、类型和特点。第二，基于平台理论，构建冷链物流企业采纳产业园金融服务的研究模型，探索金融服务影响冷链物流企业的经营因素，分析冷链物流企业采纳产业园金融服务的因素和途径。第三，基于信息不对称理论，关切信息技术支持和知识分享在冷链物流企业采纳产业园提供金融服务过程中的调节作用。同时，梳理产业园提供金融服务可能面临哪些风险，制订冷链物流企业入驻园区的标准，防范风险。
本文运用实证研究方法，通过对国内18家冷链物流相关的产业园、物流园、冷链物流、商贸流通、金融等企业实地考察和专家访谈基础上，拟定问卷并对268家企业进行调查收集数据，使用结构方程模型进行假设检验。研究发现：金融服务的有形性、可靠性、移情性、经济性对冷链物流企业采纳产业园金融服务影响显著，而响应性的影响不显著。同时
信息技术支持和知识共享的调节作用不显著。最后，针对产业园吸引冷链物流企业提供金融服务、冷链物流企业采纳产业园金融服务的风险，提出防范策略措施。
本研究聚焦冷链物流产业园金融服务助力冷链物流企业发展问题，主要研究内容包括：第一，基于产融结合理论，梳理冷链物流企业与产业园之间关系，从供需两侧探索冷链物流企业和产业园的金融服务的范围、类型和特点。第二，基于平台理论，构建冷链物流企业采纳产业园金融服务的研究模型，探索金融服务影响冷链物流企业的经营因素，分析冷链物流企业采纳产业园金融服务的因素和途径。第三，基于信息不对称理论，关切信息技术支持和知识分享在冷链物流企业采纳产业园提供金融服务过程中的调节作用。同时，梳理产业园提供金融服务可能面临哪些风险，制订冷链物流企业入驻园区的标准，防范风险。
本文运用实证研究方法，通过对国内18家冷链物流相关的产业园、物流园、冷链物流、商贸流通、金融等企业实地考察和专家访谈基础上，拟定问卷并对268家企业进行调查收集数据，使用结构方程模型进行假设检验。研究发现：金融服务的有形性、可靠性、移情性、经济性对冷链物流企业采纳产业园金融服务影响显著，而响应性的影响不显著。同时
信息技术支持和知识共享的调节作用不显著。最后，针对产业园吸引冷链物流企业提供金融服务、冷链物流企业采纳产业园金融服务的风险，提出防范策略措施。
ContributorsYang, Su (Author) / Shen, Wei (Thesis advisor) / Chen, Xinlei (Thesis advisor) / Gu, Bin (Committee member) / Arizona State University (Publisher)
Created2019
Description
Health is among the most basic needs of the people and driving force of social and economic development. The health nutrition & wellness industry is gradually becoming a global sunrise industry . However, the industry is faced many problems and challenges including weaknesses in the industry structure, fragmentations of supply chain, low
efficiency in resources allocation, and lacking in quality on personnel training. To achieve core competitiveness and value creation, it is important that the health nutrition & wellness industry must meet the needs of Chinese market and its customers with a customer centric perspective to design a firm’s organization strucrture and management processes. This thesis is based on an analysis of the competitive landscape faced by the nutrition & wellness industry as exemplified by By-Health.Ltd. The investigation begins with an analysis and synthsis of the common industry practices on sales & distribution channels for their underlying similarities and differences in product strategies, branding strategies, and agency models on incentive design and profit sharing mechanisms. Through an empirical survey, this thesis also investigate customer’s demand for nutritious and healthy products. The results through factor analysis reveal that such demands are driven by individual factor, product factor, enterprise factor and environmental factor. The study concludes with a proposed framework to link customer value through three innovative designs in sales and distribution: community marketing model, sharing marketing model and Internet factory marketing model.
efficiency in resources allocation, and lacking in quality on personnel training. To achieve core competitiveness and value creation, it is important that the health nutrition & wellness industry must meet the needs of Chinese market and its customers with a customer centric perspective to design a firm’s organization strucrture and management processes. This thesis is based on an analysis of the competitive landscape faced by the nutrition & wellness industry as exemplified by By-Health.Ltd. The investigation begins with an analysis and synthsis of the common industry practices on sales & distribution channels for their underlying similarities and differences in product strategies, branding strategies, and agency models on incentive design and profit sharing mechanisms. Through an empirical survey, this thesis also investigate customer’s demand for nutritious and healthy products. The results through factor analysis reveal that such demands are driven by individual factor, product factor, enterprise factor and environmental factor. The study concludes with a proposed framework to link customer value through three innovative designs in sales and distribution: community marketing model, sharing marketing model and Internet factory marketing model.
ContributorsGong, Binghui (Author) / Pei, Ker-Wei (Thesis advisor) / Cui, Haitao (Thesis advisor) / Gu, Bin (Committee member) / Arizona State University (Publisher)
Created2018
Description
Due to the growing popularity of the Internet and smart mobile devices, massive data has been produced every day, particularly, more and more users’ online behavior and activities have been digitalized. Making a better usage of the massive data and a better understanding of the user behavior become at the very heart of industrial firms as well as the academia. However, due to the large size and unstructured format of user behavioral data, as well as the heterogeneous nature of individuals, it leveled up the difficulty to identify the SPECIFIC behavior that researchers are looking at, HOW to distinguish, and WHAT is resulting from the behavior. The difference in user behavior comes from different causes; in my dissertation, I am studying three circumstances of behavior that potentially bring in turbulent or detrimental effects, from precursory culture to preparatory strategy and delusory fraudulence. Meanwhile, I have access to the versatile toolkit of analysis: econometrics, quasi-experiment, together with machine learning techniques such as text mining, sentiment analysis, and predictive analytics etc. This study creatively leverages the power of the combined methodologies, and apply it beyond individual level data and network data. This dissertation makes a first step to discover user behavior in the newly boosting contexts. My study conceptualize theoretically and test empirically the effect of cultural values on rating and I find that an individualist cultural background are more likely to lead to deviation and more expression in review behaviors. I also find evidence of strategic behavior that users tend to leverage the reporting to increase the likelihood to maximize the benefits. Moreover, it proposes the features that moderate the preparation behavior. Finally, it introduces a unified and scalable framework for delusory behavior detection that meets the current needs to fully utilize multiple data sources.
ContributorsLi, Chunxiao (Author) / Gu, Bin (Thesis advisor) / Chen, Pei-Yu (Committee member) / Xiong, Hui (Committee member) / Arizona State University (Publisher)
Created2019
Description
Two-sided online platforms are typically plagued by hidden information (adverse selection) and hidden actions (moral hazard), limiting market efficiency. Under the context of the increasingly popular online labor contracting platforms, this dissertation investigates whether and how IT-enabled monitoring systems can mitigate moral hazard and reshape the labor demand and supply by providing detailed information about workers’ effort. In the first chapter, I propose and demonstrate that monitoring records can substitute for reputation signals such that they attract more qualified inexperienced workers to enter the marketplace. Specifically, only the effort-related reputation information is substituted by monitoring but the capability-related reputation information. In line with this, monitoring can lower the entry barrier for inexperienced workers on platforms. In the second chapter, I investigate if there is home bias for local workers when employers make the hiring decisions. I further show the existence of home bias from employers and it is primarily driven by statistical inference instead of personal “taste”. In the last chapter, I examine if females tend to have a stronger avoidance of monitoring than males. With the combination of the observational data and experimental data, I find that there is a gender difference in avoidance of monitoring and the introduction of the monitoring system increases the gender wage gap due to genders differences in such willingness-to-pay for the avoidance of monitoring. These three studies jointly contribute to the literature on the online platforms, gig economy and agency theory by elucidating the critical role of IT-enabled monitoring.
ContributorsLiang, Chen, Ph.D (Author) / Gu, Bin (Thesis advisor) / Hong, Yili (Thesis advisor) / Chen, Peiyu (Committee member) / Arizona State University (Publisher)
Created2019