Stock Forecast Methods

Stock Market Trading and Investing

Technology Sector Might Do Well During the Next Three Months

The chart below shows the comparative analysis of expected sectors’ performance for the next three months – April, May, and June of 2011. The 11 sectors (no data for Conglomerates) have been composed of selected more than 500 US and Canadian stocks. Apparently, Technology and Financial sectors look the best:

Technology Sector Might Do Well During the Next Three Months

The chart has been calculated using Investment Analyzer InvAn-4. The calculation is based on a rank of stocks. Sector ranks distribution allows making comparative analysis of sectors’ ratings (sectors are formed from the stocks recorded in InvAn-4 internal database). The highest ranked stocks are expected to be the most probable best performers within the next three-month period. Stocks are ranked on the basis of the composite rating which is a combination of fundamental, technical, and timing ratings. Such combination allows realistic modeling the quality of a company and its stock in the market.

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April 11, 2011 Posted by | Stock Market Forecast, Stock Market Software | , , , , , , , , , , , , , , , | Leave a comment

The Best Technical Indicators of 2010

Is it possible to find the best technical indicators that are the best for all cases? The best way to find the answer is to collect and analyze data and make a comparative analysis for many years. In fact, statistics shows that depending on different time-frame, market conditions, industry specifics, type of stock or ETF, and other factors, some indicators might be best but other worst, and vice versa. The major conclusion – it is better to select the best indicators for a particular case.

In general, the question can be answered if an average is calculated (although it might be not so helpful). Specifically, concerning average forecasting success based on the statistics during 2010, the five of top winning indicators are:

  1. Relative Strength Index
  2. Money Flow Index
  3. Twiggs Money Flow
  4. On Balance Volume
  5. Directional Movement System

Another problem is that there are not only many technical indicators but also many different interpretations of their signals. Some traders use particular favorite indicators and insist that their interpretations are right. A computer program could decide using back-testing which indicator should be trusted more and another less for particular market conditions and a specific stock. It could compose the forecast with weights accordingly to predictive ability of each technical indicator. The example of such program is Investment Analyzer (10-day forecast using Neural Network).

March 30, 2011 Posted by | Stock Market Forecast, Stock Market Software | , , , , , , , , , , | Leave a comment

S&P-500 Index Cycle Analysis Forecast for the Next Several Years

There is a simple forecast that is built on assumption that the stock market has a cyclical nature. The cycles may not be stable all the time but the probability of repeating cycles can be high enough to use the cycles by stock traders and investors for their benefits. The cyclical nature of the market can be masked by more powerful factors (fundamental data, bad/good news, global events, etc.) that over-drive the market time-from-time. Many technical analysts use cycle predictions in their comprehensive analysis.

One of the result-sensitive parameters in the cycle analysis prediction is a historical period that used to extract the cycles from a curve. The prediction can be very different depending on the historical period that is chosen. One of the stable cycles that is observed for the recent decade is a seven-year period. The chart below shows S&P-500 index forecast for the next several years. The calculation has been performed using Stock Market Predictor SMAP-3. According to this forecast the stock market might continue its uptrend with natural short-term small-amplitude sub-cycles until 2012-2013.

S&P-500 Index Cycle Analysis Forecast for the Next Several Years

December 29, 2010 Posted by | Stock Market Forecast, Stock Market Software | , , , , , , , | Leave a comment

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

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

S&P-500 Forecast for the First Two Weeks of August on the Basis of Technical Indicators Signals

There are many technical indicators. And there are many interpretations of each indicator’s signal. Some stock investors and traders use particular favorite indicators and insist on own interpretation. Who is right? What if to allow a computer program to decide using back-testing which indicator should be trusted more and another less for particular market conditions and a specific stock?

One of computer programs that enables to compose the forecast with weights accordingly to predictive ability of each technical indicator is Investment Analyzer InvAn-4. It performs a short-term (10 trading days) forecast using Neural Network. The chart below shows an example of such forecast. It is S&P-500 forecast for the first two weeks of August, 2010.

S&P-500 Forecast for the First Two Weeks of August on the Basis of Technical Indicators Signals

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

August 3, 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

Sectors Comparative Analysis for Summer 2010

Each stock belongs to a general market, a particular sector and industry. An individual stock performance depends on the general stock market performance, as well as, on the sector performance. History evidences that different sectors perform differently in different periods. Therefore, choosing a right sector at the moment of investing can increase the chances of successful outcome.

The chart below shows the comparative analysis of expected sectors’ performance for the three months of 2010 summer. These 12 sectors composed of more than 500 US and Canadian stocks. Financial and Healthcare sectors look the best, the Energy – the worst. The question still remains if the stock market is going to be bullish this summer.

Sectors Comparative Analysis for Summer 2010

The chart has been calculated and plotted using Investment Analyzer InvAn-4. Its calculation based on a rank of stocks. The highest ranked stocks are expected to be the most probable best performers within the next three-month period. Stocks are ranked on the basis of the composite rating which is a combination of fundamental, technical, and timing ratings. The combination allows modeling quality of company and its stock very realistically.

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

June 7, 2010 Posted by | Stock Market Forecast, Stock Market Software | , , , , , , , , , , , , | 2 Comments

Predicting Stock Market Using Cycle Analysis and Synthesis

Investors could benefit from a fluctuating nature of the stock market. A semi-cyclical nature of the market is a bad surprise for some investors but others know how to take advantage of the cycles. To discover cyclical patterns in the market movement, investors use different software tools.

Stock market cycles may help to maximize ROI.
One of the stock market characters is that it has powerful and pretty consistent cycles. Its performance curve can be considered as a sum of the cyclical functions with different periods and amplitudes. Some cycles known by investors for long, for example, four-year presidential cycle or annual and quarterly fiscal reporting cycles. By identifying the cycles it is possible to anticipate tops and bottoms, as well as, to determine trends. So that the stock market cycles can be a good opportunity to maximize return on investments.

It is hard to identify cycles using a simple chart analysis.
It is not easy to analyze the repetition of typical patterns in stock market performance because often cycles mask themselves; sometimes they overlap to form an abnormal extremum or offset to form a flat period. The presence of multiple cycles of different periods and magnitudes in conjunction with linear and non-linear trends can form a complex pattern of the curve. Evidently, a simple chart analysis has a certain limit in identifying cycles parameters and using them for predicting. Therefore, a mathematical statistical model implemented in a computer program could be a solution.

Be aware: no predictive model guarantees 100% precision.
Unfortunately, any predictive model has own limit. The major obstacle in using cycle analysis for the stock market prediction is a cycle instability. Due to a probabilistic nature of the stock market cycles, the cycles sometimes repeat, sometimes not. In order to avoid excessive confidence and, therefore, losses it is important to remember about a semi-cyclical nature of the stock market. In other words, the prediction based on cycle analysis, as well as, any other technique cannot guarantee 100% accuracy of prediction.

Back-testing helps to improve prediction accuracy.
One of the techniques to improve a prediction accuracy is back-testing. It is the process of testing prediction on prior time periods. At the beginning, instead of calculating the prediction for the time period forward, we could simulate the forecast on relevant past data in order to estimate the accuracy of prediction with certain parameters. Then the optimization of these parameters could help to reach a better precision in forecast.

Stock Market Predictor SMAP-3 is a computer program that is based on cycle analysis.
To discover different patterns in the market movement, including cycles, investors use different software tools. One of the them is Stock Market Predictor SMAP-3. It is able to extract basic cycles of the stock market (indexes, sectors, or well-traded shares). To build an extrapolation, SMAP-3 uses the following two-step approach: (1) applying spectral (time series) analysis to decompose the curve into basic functions, (2) composing these functions beyond the historical data.

Predicting Stock Market Using Cycle Analysis

Conclusion
The stock market is an alive system – around can be joy or fear but its buy-sell pulse always exists. To discover different patterns in the market movement, including cycles, investors use different software tools. Sometimes, these computer tools are called “stock market software.” The stock market software tools help investors and traders to research, analyze, and predict the stock market.

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

May 22, 2010 Posted by | Stock Market Forecast, Stock Market Software | , , , , , , , , , , , , , , , , , | Leave a comment

The Technical Indicator to Watch Rapid Sell-off

One of the best technical indicators to watch a rapid sell-off is a high-order derivative. In mathematics, the derivative is a measure of how a function changes as its argument (input) changes. In stock investing, the derivative can be used to measure how fast the price of a stock changes for a shortest measured period, for example, in case of EOD, one trading day. The following formula can be used for calculation of the first order derivative:

Δ1 = p2 – p1

where p2 – current day closing price, p1 – previous day closing price

In other words, Δ1 is a speed of changing price. If we apply the same formula to two derivatives – current and previous , we get the second order derivative (or acceleration):

Δ2 = Δ12 – Δ11

where Δ12 – current day first order derivative, Δ11 – previous day first order derivative

We can calculate respectfully the third order derivative Δ3, which can be described as speed of changing acceleration. It can be considered as an indicator of panics in the stock market – the more its absolute value is, the more nervous investors behavior in stock market is.

The chart below shows the result of SP-500 index forecast built by Neural Network (trained by the third order derivative). Forecast horizon is two-week period (May 10-21) after May 6 stock market plunge:

The Technical Indicator to Watch Rapid Sell-off


The charts have been calculated and plotted by Investment Analyzer Inv-An-4.

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

May 8, 2010 Posted by | Stock Market Forecast, Stock Market Software | , , , , , | 1 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