اطلاعات متن باز، توجه سرمایه گذار و قیمت گذاری دارایی ها
|کد مقاله||سال انتشار||تعداد صفحات مقاله انگلیسی||ترجمه فارسی|
|13068||2013||7 صفحه PDF||سفارش دهید|
نسخه انگلیسی مقاله همین الان قابل دانلود است.
هزینه ترجمه مقاله بر اساس تعداد کلمات مقاله انگلیسی محاسبه می شود.
این مقاله تقریباً شامل 3990 کلمه می باشد.
هزینه ترجمه مقاله توسط مترجمان با تجربه، طبق جدول زیر محاسبه می شود:
- تولید محتوا با مقالات ISI برای سایت یا وبلاگ شما
- تولید محتوا با مقالات ISI برای کتاب شما
- تولید محتوا با مقالات ISI برای نشریه یا رسانه شما
پیشنهاد می کنیم کیفیت محتوای سایت خود را با استفاده از منابع علمی، افزایش دهید.
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Economic Modelling, Volume 33, July 2013, Pages 613–619
In this paper, we advocate the search frequency of stock name in Baidu Index as a novel and direct proxy for investor attention. Firstly, empirical results show that the quantified investor attention is a desired explanatory variable for abnormal return even trading volume is considered. Secondly, the Main Board is more efficient than the ChiNext and the SME Board in the view of informational efficiency. Thirdly, investor attention exhibits strong contemporary relationship with abnormal return. Fourthly, open source information can enhance the speed of information dissemination and make the market efficient.
Over the past decade and a half, the emergency of the internet has become a mainstream platform for information gathering, processing and interaction. In stock market, the internet has not only enhanced the existing processes (e.g., the electronic system facilitates the broker in sending orders), but also created new processes and interactions (e.g., stock message board, blog and email). The efficiency of stock market is in large attributable to the efficient dissemination of information. Therefore, the internet is undoubtedly playing an increasing role in stock market. Market efficiency has double-meanings in financial economics. Allocative efficiency is concerned with the optimal distribution of scarce resources among individuals in the economy; Informational efficiency refers to how much information is revealed by price process (Brunnermeier, 2001). Infer from these two viewpoints of efficiency, the efficient market is characteristic of prices incorporate all available information and does not have any unexploited gains from trade. Therefore, if prices do not precisely and fully reflect public information, then there would be a profitable trading opportunity for individuals and paying attention to research the opportunity from internet is worthy. Considering these two aspects mentioned above, it's an empirical question to ask whether the open source information has some impacts on information dissemination, investor behavior and even explanatory power for stock return.
نتیجه گیری انگلیسی
As the internet becoming the dominant platform for information gathering, processing and interacting, it brings some useful possibilities to academic research. The quantified investor attention enjoys this benefit. In this paper, we advocate a novel and direct measure of investor attention employing the search frequency of stock name in Baidu Index. By focusing on different boards of Chinese Stock Market, we firstly demonstrate that investor attention is a desired variable to predict stock abnormal return. Secondly, investor attention exhibits strong contemporary relationship with abnormal return. Thirdly, granger causality test reveals the bi-directional pattern. Fourthly, the impacts of variations in investor attention illustrate that searching for information can enhance the speed of information dissemination process from the public to a wider range of investors, making the market more informationally efficient. Since investor attention is a cognitive resource, it must display some heterogeneous behaviors of investor. Due to this attribute, the quantified investor attention could become a new barometer of information dissemination in stock market and provide perspective on investor psychology. We leave this for future research.