TAILIEUCHUNG - Data Mining Historic Stock Quotes in Java

Tetlock, Saar-Tsechansky and Macskassy (2008) describe a news-based automated trading strategy based on relative occurrence of negative words in firm specific financial news in an effort to predict firms’ accounting earnings and stock returns. A simplified bag of words representation was used to interpret textual data according to the relative frequency of negative words defined by the Harvard psychosocial dictionary. Key findings of Tetlock et al. (2008) are that the fraction of negative words in firm-specific news forecasts low firm earnings and stock market prices respond to the information embedded in negative words with a small, one-day delay. They. | Ỵ Journal of Object Technology Online at http . Published by ETH Zurich Chair of Software Engineering JOT 2007 Vol. 6 No. 10 November-December 2007 Data Mining Historic Stock Quotes in Java By Douglas Lyon Abstract This paper describes how to extract historic stock quote data and display it. We show how to chart stock prices using the web as a data source. The methodology for converting the web data source into internal data structures is based on using HTML as input. This type of screen scraping has become a popular means of recording data into programs. Simple string manipulation techniques are shown to be good enough for these types of well-formed data streams. 1 THE PROBLEM Historic stock price data is generally available on the web using a browser to format the HTML data . Given an HTML data source we would like to find a way to create an underlying data structure that is type-safe and well formulated. We are motivated to study these problems for a variety of reasons. Firstly for the purpose of conducting empirical studies entering the data into the computer by hand is both error-prone and tedious. We seek a means to get this data using free data feeds so that we can build dynamically updated displays and perform data mining functions. Secondly we find that easy to parse data enables us to teach our students the basic concepts of data mining. This example is used in a first course in network programming. 2 FINDING THE DATA Finding the data on-line and free is a necessary first step toward this type of data mining. Quotes have been available for years from Yahoo. We can obtain the quotes using comma-separated values CSV by constructing a URL and entering it into a browser. For example http s IBM a 00 b 2 c 1800 d 04 e 8 f 2005 g v ignore .csv Cite this column as follows Douglas A. Lyon Data Mining Historic Stock Quotes in Java in Journal of Object Technology vol. 6. no. 10 November-December 2007 pp. 17-23 http .

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