TAILIEUCHUNG - Intelligent stock trading system by turning point confirming and probabilistic reasoning

Sliding glass doors are easy for a burglar to enter if no remedial action is taken. Often, the door panels can simply be lifted out of the tracks. To solve this problem, open the active door and install a few screws in the track, allowing the screw to project down 3/8" to 1/2". Use a stack of several metal washers to serve as a spacer so the screws can be firmly set. Slide the door closed, making sure the extended screws pass freely over the top rail of the door. Now try to lift the door from the track; upward movement should be stopped by the. | Available online at ScienceDirect Expert Systems with Applications 34 2008 620-627 Expert Systems with Applications locate eswa Intelligent stock trading system by turning point confirming and probabilistic reasoning Depei Bao Zehong Yang State Key Lab of Intelligent Technology and Systems Computer Science Department Tsinghua University Beijing China Abstract Financial engineering such as trading decision is an emerging research area and also has great commercial potentials. A successful stock buying selling generally occurs near price trend turning point. Traditional technical analysis relies on some statistics . technical indicators to predict turning point of the trend. However these indicators can not guarantee the accuracy of prediction in chaotic domain. In this paper we propose an intelligent financial trading system through a new approach learn trading strategy by probabilistic model from high-level representation of time series - turning points and technical indicators. The main contributions of this paper are two-fold. First we utilize high-level representation turning point and technical indicators . High-level representation has several advantages such as insensitive to noise and intuitive to human being. However it is rarely used in past research. Technical indicator is the knowledge from professional investors which can generally characterize the market. Second by combining high-level representation with probabilistic model the randomness and uncertainty of chaotic system is further reduced. In this way we achieve great results comprehensive experiments on S P500 components in a chaotic domain in which the prediction is thought impossible in the past. 2006 Elsevier Ltd. All rights reserved. Keywords Intelligent stock trading system Turning point Technical indicators Markov network 1. Introduction The stock market is a complex and dynamic system with noisy non-stationary and chaotic data series Peters 1994 . .

• Đầu tư Chứng khoán
• evidence is consistent
• block trading
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