ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- All Subjects: Business Administration
- Creators: Wang, Tan
- Creators: Liang, Bing
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.
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.
通过对市场的观察,能够明显看出在同样办公的使用功能的前提下,科研用地交易价格远低于纯办公土地性质的办公用房,而且不同的科研用地的房产价格也有较为明显差异(即使在地段、硬件相似的前提下)。究其原因,主要存在于科研用地的诸多限制,即和纯粹的商办性质的楼宇相比,政府对于科研用地的楼宇规定了更多的限制条件,从产权的角度而言即产权的不完全因素。本研究通过南京科研用地楼宇产权不完全的现状这一现象,从产权的限制性因素出发,研究整体的产权不完全性对于交易价格的影响,进而拆分各个限制因素(不完全因素)对交易价格产生影响。
为研究调研科研楼宇市场的政策现状交易情况现状、政策中的哪些限制因素会对楼宇的交易价格产生影响、限制因素影响价格背后的传导机制如何等问题,研究者全面收集了政府出台的科研用地相关政策,深度访谈了6个科研项目开发者,并问卷调查了63组科研性质物业的购房客户,并以地段和硬件的可比性作为选择原则精选了五组纯办公土地性质的项目和不同限制条件的科研办公项目进行对比研究,对1023套科研办公、正常办公楼宇的实际成交价格的数据进行分析比较。
通过政策规定、土地出让合同、开发者访谈确定限制性因素,即不完全产权的因素;通过消费者购买认知,确定个因素在购买决策中的影响程度;运用相关性分析和回归分析对所获取的数据进行1023组数据进行分析研究,来探究不同因素对交易价格的影响。
研究发现:是否是科研用地、面积是否可以切分销售对交易价格有显著性的影响。可切分销售面积越小,交易价格越高。金融性和确权的不确定性也能够对价格产生强影响,购买主体限制对价格有弱影响,而交易比例限制和现售限制对价格无显著影响。对于限制因素影响价格背后的理论机制,研究发现科研用地政策中的限制因素首先影响市场流通中的有效需求,供需关系决定价格。
研究应用:1、科研用地政策激励作用是否兑现?从城市更新的角度来讲的的确起到非常大的作用;从产业引导来讲为企业提供了低成本的持有型研发办公的载体,或有补贴的低租金的办公空间;但对于部分科技型企业在没有考虑清楚的前提下,被动的投入了地产项目开发,消耗了资金和精力,未实现激励的初衷反而是适得其反。2、政府调控策略:可以通过间接控制自变量中的因素来实现,如面积可切分的大小、金融性和确权不确定性的改变可以有效调节项目的有效需求。3、开发者需对自己选定的项目的产权的不完全程度即限制条件有明确的结论对应关系的认知;购买者对于项目的不完全性进行适当的研究,以防出现和自身需求的错配关系。4、使用功能为办公的前提下,与纯办公相似的租金价格而更低的交易价格所带来的高回报率。回报率高为使用REITs金融工具解决问题提供了基础,而REITs的定价逻辑也一定会以使用价值实现拉动交易价值提升。这对于有大宗资产经营的持有者来说也许蕴含着巨大的机会。
关键词: 科研用地 不完全产权 市场流通 交易价格
关键词: FOF、因子投资、组合配置、特质因子