Applying Market Profile and Clustering Analysis to Discover the Investment Value of Low Price Stock

• Main Authors: Wang, Jen, 王雪珍
• Other Authors: Chen, An-Pin
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/50788853847495570472

碩士 === 國立交通大學 === 管理學院資訊管理學程 === 102 === Many investment theories suggest investor to buy blue chip stocks, and suggest buying the stocks based on the fundamentals and financial analysis; such as evaluating company’s balance sheet, profitability of the income statement, and last but not least, share placement situation analysis of the discount model. The price of a stock reflects the buyers and sellers future expectation toward the company. Therefore, it is too late to invest if investors wait for the financial reports of the company because it is the result of both buyers and sellers future expectation. In fact, real-time stock price performance is often quite different than we expected. According to the Market Profile Theory by Steidlmayer, the price fluctuates as a result of the buying and selling force of market participants. The price fluctuation diminished as both sellers and buyers reached a majority consensus price resulting in relatively stable stock price. Market Profile Theory stated that market price auctions in two ways: downward bidding and upward bidding; downward when sellers dominate the market, upward when buyers dominate the market. Value Area is the range of price where participants are more likely to trade in. This thesis implements Market Profile and Self-Organizing Map Neural Network Clustering technique to discover the investment value of low price stock.