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摘要: The deep liquidity at equity markets’ open and close auctions typically provides price discovery and facilitation of block order executions. Trading at these centralized, large-scale liquidity events permits institutional investors to establish sizeable positions without undue complexity [1]. To participate effectively in auctions, we need to understand how an order can potentially affect the auction price, namely the market impact. While market participants have a relatively good understanding of the market impact in continuous trading sessions, there is much less knowledge about auction market impact in the public domain.

 

The content in the work section is from parts of our research reports on market crashes, bubbles and market sentiment, and the projects were funded by the Ministry of Science and Technology and the Taiwan Stock Exchange.

We share here the method used to construct the market and individual stock sentiment index, as well as the visualization of stock return network on a daily basis from 2014

Some key concepts are also presented in this section. The research team is led by Professor Tai Ma (Email住址會使用灌水程式保護機制。你需要啟動Javascript才能觀看它) at the Department of Finance, National Sun Yat-sen University, Taiwan.


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維修公告:個股高頻情緒目前僅更新至2016年6月30日,小編會盡快修改更新,此段期間造成使用者的不便深感抱歉,請使用者見諒。

 

維修公告:個股低頻情緒目前僅更新至2016年6月30日,小編會盡快修改更新,此段期間造成使用者的不便深感抱歉,請使用者見諒。

 

摘要: 毫無疑問,神經網絡和機器學習在過去幾年一直是高科技領域最熱門的話題之一。這一點很容易看出,因為它們解決了很多真正有趣的用例,如語音識別、圖像識別、甚至是樂曲譜寫。因此,在這篇文章,我決定編制一份囊括一些很好的Python機器學習庫的清單,並將其張貼在下面。......

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