| In 2015, the ups and downs of the stock market makes the investors groups large and complicated. In the new situation, the stock quote system also produced a number of new needs. Users need not only the stock quote system can realize real-time rendering of various specifications but also system can support them in analyzing some commonly used technical specifications and system can recommend some stocks meet their individual requirements.The Design and Implementation of this system was born for those requirements. Based on Candlestick chart and fuzzy time series, we model the stock price movements by mathematics. Then we use this model and sequence comparison algorithms, assisting users performing an analysis of Candlestick chart from history by querying the history similar Candlestick chart sequence. What needs to be explained is that the Candlestick chart is be widely used by investors in technical analysis. In addition, by using similarity calculation of candlestick charts, decision tree algorithms, collaborative filtering algorithm we build three different recommendations algorithms, and finally gives a personalized recommendation algorithm by combining them.In addition, this paper presents the design of the database from an engineering point of view, and presents database core tables. Because the quotes system is essentially a quotes utilization system which is composed of decoding, communication, showing user interaction, stability and efficiency of communication directly influences the quality of system, this paper presents a new and practical framework for communications. At last we use MVC pattern in the level of UI on Android client showing the whole system. So far we built a complete system of stock quotes from algorithms, databases, communications, client which meet the needs of investor groups under the new situation. |
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