Stock Forecast Methods

Stock Market Trading and Investing

Vote To See Stock Market Forecast for the next Week

This is a page “Vote To See Stock Market Forecast for the next Week” where you are invited to build a collective forecast. Please share your opinion by voting and see the result of composite forecast. If you use more than one method, approach, or tool for prediction, it could be reasonable to give a vote for each one. All participants may benefit from building a simple average forecast. However, do not put too much trust in any method alone – make your own conclusion.

The more methods and information are taken into consideration, the more precise an investment-related solution and, consequently, the more profitable is investing.

April 26, 2010 Posted by | Stock Market Forecast | , , , | Leave a comment

Stock Price Forecast by Pattern Similarity

Pattern recognition systems are able to classify data based on statistical information extracted from the patterns. The patterns should be classified in order to extract useful information. Normally, a pattern recognition system consists of the input, data converter, an extraction processor to classify accordingly to descriptive scheme, and output grouped data. The most popular systems are based on statistical pattern recognition, i.e., statistical classification of patterns, assuming that the patterns are generated by a probabilistic system.

If we assume that some patterns are repeatable in the future, we can use selected present patterns to predict the future ones. Investment Analyzer (IA) by Addaptron Software has an extra feature to predict prices of the selected stock (index) using pattern similarity. The prediction period can be chosen from 1 day to around 60 trading days; the period of historical data that used for matching should be in 4..16 times longer than prediction period. IA searches for the best match from the internal database by scanning all historical data.

IA ranks all possible matches on the basis of minimum deviation and maximum correlation within given historical period. IA performs pattern matching using open, high, low, and close prices and volume data. When scanning is completed, IA composes forecast using several best matched patterns (top ranked). Since the statistical regularities of the patterns help to create more stable picture, IA allows adding up many top-rated patterns. The composite result is built as a weighted average with weights proportionally patterns’ ranks. The number of patterns that form composite forecast can be adjusted; the number range is 1..99.

The chart below has been plotted using IA pattern similarity feature. SP-500 index prices have been used as input; the output is predicted prices for two weeks of April 2010:

Stock Price Forecast by Pattern Similarity

© Alex Shmatov. Published with permission of the copyright owner. Further reproduction strictly prohibited without permission.

April 8, 2010 Posted by | Stock Market Forecast, Stock Market Software | , , , , , , , , | Leave a comment