Chapter 3. Forecasting Volume
Price formation on stock exchanges has been the center of attention of many researchers for several decades now. As a result, there is an abundance of theories, models, and empirical evidence on the price, and although there are always new aspects to discover, we believe that the financial knowledge is fairly comprehensive on the subject. We understand the dynamics of the price reasonably well, and most of us agree that it is rather difficult to forecast.
In contrast, the trading volume, which is another fundamental measure of the trading process on stock exchanges, has been much less researched. The most common equilibrium models on price do not even include volume in their framework of explaining trading activities. It is only recently that researchers appear to be paying increasing attention to volume, and they have already found that its stylized facts allow for much better forecasts compared to price.
This chapter aims to introduce an intra-day forecasting model selected from the available literature, and to provide its implementation in R.
- jQuery Mobile Web Development Essentials(Third Edition)
- Software Defined Networking with OpenFlow
- Effective C#:改善C#代碼的50個(gè)有效方法(原書(shū)第3版)
- Clojure for Domain:specific Languages
- 零基礎(chǔ)學(xué)Java(第4版)
- 微信小程序開(kāi)發(fā)解析
- Node.js:來(lái)一打 C++ 擴(kuò)展
- Arduino可穿戴設(shè)備開(kāi)發(fā)
- Java多線程并發(fā)體系實(shí)戰(zhàn)(微課視頻版)
- C#網(wǎng)絡(luò)編程高級(jí)篇之網(wǎng)頁(yè)游戲輔助程序設(shè)計(jì)
- Cinder:Begin Creative Coding
- R語(yǔ)言:邁向大數(shù)據(jù)之路
- Cloud Development andDeployment with CloudBees
- Java網(wǎng)絡(luò)編程實(shí)用精解
- Swift 2 Blueprints