Stock Forecast Methods

Stock Market Trading and Investing

Stock Market Forecast for August 16-27 by Pattern Similarity

A pattern recognition system is to classify data based on statistical information excerpted from the data. Normally, a pattern recognition system consists of data input, converter, an extraction processor to classify accordingly to descriptive scheme, and output grouped data. The statistical classification of patterns assumes that the patterns are generated by a probabilistic system.

Some patterns can be repeatable in the future, therefore, we can use selected present patterns to predict the future pattern. Investment Analyzer InvAn-4 (IA) by Addaptron Software has an extra feature to predict stock or index prices using pattern similarity. The prediction period can be chosen within a range 1..60 trading days; the period of historical data that used for matching recommended in 4..16 times longer than prediction period. IA searches for the best matches by scanning all historical data from the internal database.

IA ranks all possible matches on the basis of maximum correlation and minimum deviation 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 pattern ranks.

The chart below shows S&P-500 Index forecast for August 16-27, 2010 by Investment Analyzer. The forecast is a small uptrend and then a bigger downtrend:

Stock Market Forecast for August 16-27 by Pattern Similarity

Nothing in this piece or blog should be construed as investment advice in any way. Always do our own research or/and consult a qualified investment advisor. It is wise to analyze data from multiple sources and draw your own conclusions based on the soundest principles. Be aware of the risks involved in stock investments

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August 14, 2010 Posted by | Stock Market Forecast, Stock Market Software | , , , , , , , , , , | Leave a comment

Pattern Similarity S&P-500 Forecast for the Last Two Weeks of July 2010

Pattern similarity method predicts stock market downtrend-uptrend reverse during the last two weeks of July 2010. The chart below was calculated and plotted using Investment Analyzer InvAn-4. 80 historical days are used to predict within next 10 trading days. With settings for 10 best matches, the Analyzer scans among 153990 cases. The chart shows that S&P-500 index may continue a downtrend with fluctuation then gradually reverse to a moderate uptrend. The reverse point is expected on July 21 with a minimum value around 1050.

Pattern Similarity S&P-500 Forecast for the Last Two Weeks of July 2010

InvAn-4 searches for the best match from internal database by scanning all historical data. It ranks all possible matches on the basis of minimum deviation and maximum correlation within given historical period. Pattern matching is performed using open, high, low, and close prices and volume data. When scanning is completed, it composes forecast using several best matched patterns (top ranked). 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.

July 17, 2010 Posted by | Stock Market Forecast, Stock Market Software | , , , , , , , , | 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