SMFT-2 is a New Stock Market Prediction Software

SMFT-2 (Stock Market Forecast Tools) is a new integrated system by Addaptron Software. It is the next generation of the software that intended to replace older SMFT-1 version. As a result of a few recent development projects, the new version is based on new advanced methods, provides more accurate prediction, and is easier to use.

Prediction modules is built with back-test calculation to estimate the accuracy of forecast within the recent performance periods. Additionally, the back-testing computations is important if more than one method is used. It allows estimating the weight of each method in a composed result; the weights that are proportional to the ability of the methods to predict the price.

SMFT-2 currently includes five major modules:

TA Predictor - prediction for day or week period based on Technical Analysis, pattern recognition and Neural Networks (generates composite result). Back-analysis models optimization and batch calculation for comparative analysis included.

Waves - Elliott Wave model: back-test optimization, up to 10 waves forecast.

Cycles - prediction based on cycle analysis.

Week day - search for maximum performance using price behavior depending on week day. It allows discovering the best entry/exit days of week; batch calculation included.

Month day - search for maximum performance using price behavior depending on month day. It allows discovering the best entry/exit days of month; batch calculation included.

The implemented methods are statistically proven and widely used. All modules share the same EOD (end-of-day) input data. The software is provided with a free Downloader that allows downloading EOD historical quotes files from the Internet for free. A fully-functional software SMFT-2 is free during initial 30-day period. The software and associated documentation are delivered via download links over the Internet. For technical requirements, installation instruction, and download link, visit SMFT-2 download page.

SP-500 Index Cycle Analysis Forecast for Spring and Summer of 2012

There is a simple predictive model that is built on an assumption that the stock market has a semi-cyclical nature. Many technical analysts use cycle analysis in their comprehensive research. The cycles may not be stable all the time but the probability of repeating patterns can be big enough to get a consistent trading profit.

Cycle analysis can be made using charts. However, the distinctive cycles in pattern can be masked by more powerful factors (fundamental data, bad/good news, global events, etc.) that over-drive the market time-from-time. Therefore, a special software can be very useful for extracting hidden cycles.

The chart below shows S&P-500 index forecast for April-May and summer months of 2012. The calculation has been performed using Stock Market Predictor SMAP-3. According to this forecast the stock market might continue its uptrend until the end of May, then have some correction in June and top in July.

S&P-500 Index May Drop Soon

There are several negative fundamental factors that can cause stock market downtrend: GDP growth slowed to 2.4% in the second quarter compared with 3.7% in the first quarter; jobless rate is at high level (9.5%); individuals and companies save cash at near record levels; consumer spending shows no signs of picking up; state budget deficit poses an additional risk to the US economy.

Despite a weak current conditions of the US economy and pessimistic investors' expectations, the stock market would continue to move sideways above some supportive level. However, technically S&P-500 Index is ready to start a downtrend cycle. The probability may increase with approaching September-October traditional low performance season.

Additionally, there is a natural stock market fluctuation. The following chart represents S&P-500 forecast for September 2010 using cycle analysis. The calculation has been performed using SMAP-3 computer program:




A possible prediction is a cycle with minimum in September. However, as always - technical prediction may be different if something fundamental happens.

Nothing in this piece or blog should be construed as investment advice in any way. Always do your 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

Stock Market Ups and Downs for the Next Three Months

S&P-500 has increased around 5% during the first decade of July. Evidently, the stock market was uplifted by investors' optimism. One of the most important fundamental factors that causes this uptrend was strong second-quarter earnings reports. Also other positive news factors stopped sliding down S&P-500 index.

From the technical point of view, downs and ups follow each other. Any action normally results a reaction. To discover periods and amplitudes of this natural market fluctuations, some investors use a cycle analysis. The cycle analysis also can be used to predict the further fluctuations. The following chart represents S&P-500 forecast for August-September-October, 2010. The calculation has been performed using Stock Market Predictor SMAP-3.



Possible prediction from the current 1078 value of S&P-500 is the following. It can increase in about 3-5% in the middle of August and then decrease below 1000 level in September. Then it can reverse to an uptrend again. However, as always - such technical prediction may change if something fundamental happens.

Nothing in this piece or blog should be construed as investment advice in any way. Always do your 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

Return on Investment Built on Expectations: Time Factor Is Critical in Stock Investing

Since all stock market buy-sell rush built on expectations, today's prices strongly depend on prices that even expected to be in several months. For example, if you are the first who know that today's $20 share would cost $30 in six months, you would rather to buy immediately. What can happen if others have the same prediction? They can do the same - buy immediately and that buying power can push prices higher very fast. Therefore, the price can jump in a few days due to a perspective of several months.

The chart below shows how short-term price behavior can depend on future expectation. Long-term forecast-1 was positive that pushed price up in short-term. Then when new negative information became available, the long term forecast-2 dragged the price down in short-term.




According to Efficient Markets approach, news and other public information are incorporated into the price of a stock with a certain time delay (price is supposed to reach and keep a stable equilibrium that change only each time a relevant new information is known). Since big money cannot flow very fast, individual investors have some advantage to react quickly. To do this efficiently it is important to watch informational resources, monitor companies' news and macroeconomic trends.

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

Contributing Factors in Forecasting: Stocks vs. Stock Market and Sectors

Each company belongs to a particular industry, sector, national stock market, as well as, global stock market. If system conditions change, company and its stocks respond to this changes. Indeed, a general stock market exerts a significant influence on the behavior of an individual company stocks. That is why experienced investors always carefully watch the stock market, sectors, and industries conditions.

On the other hand, a company is a part of subsystems and global system. It means each company performance is a contributing factor in a whole system performance. So that we could analyze a single company and try to predict the behavior of the stock market. However, it is only partially possible. As example, the recent financial crisis caused by a system failure showed that system itself may have a significantly bigger risk-factor.

Since all structure and all levels of sub-structures depend mutually, it would be unwise to ignore either predictions of big, medium, or small parts or a whole system. Evidently it is possible to build a more accurate forecast by combining predictions for system, sub-systems, and elements of sub-system.

As example, let's consider a three-month forecast for stock market (515 stocks from different sectors):




stocks from different sectors:




and individual company stocks from a leading sector:




In conclusion, we could assume that there is a certain probability that the stock market will have a correction (downtrend around 8-12%) after May 6.

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

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Nothing in this piece or in this blog should be construed as investment advice in any way. Always do your 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.

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

Predicting Stock Market Using Expert Method

The more methods and information are taken into consideration, the more precise an investment-related solution and, consequently, the more profitable is investing. One of the forecasting methods that uses a collective wisdom is an expert method. This method can be explained by following. As example, an experimentalist shows a pen and asks about 40 people to write down their estimate of the length. Then he collects notes and calculates the average number - normally it is almost 100% accurate. Why it works? Everyone makes errors in different directions so that averaging gives a precise result.

An example of simplified expert method forecast in stock forecasting can be analysts' opinions that collected and averaged. Such information can be found, for instance, on Yahoo Finance webpage "Analyst Opinion" for each stock, it is called "Recommendation Summary". If mean recommendation is equal or close to 1, experts predict strong performance because "1" means "strong buy". If mean recommendation is equal or close to 5, experts predict stock decline because "5" means "sell". It is natural to assume that the more experts express their opinions, the better should be the result of prediction.

Another example of expert forecast could be using your own research of different factors that can contribute certain "opinions" in composed forecast. You can assign different weight for each factor and build an estimation based on weighted averaging. For instance, fundamental analysis may be one the most influential factors, then news factor, technical analysis prediction factor, seasonal price fluctuation factor, etc. All these factors should be added with different weight coefficients. Then the result should be divided by total amount of all weights.

One more idea is to read different current news, analytical articles, blogs, investor forums and draw a summarized conclusion from all opinions, positive and negative predictions. To make this process more automatic, it can be possible to participate on-line polls. There are some websites where you can participate in building a collective forecast for S&P-500 index. You can 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.

Link to: useful resources

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

Neural Network vs. Cycle Analysis to Predict the Stock Market

Many stock market experts consider that the last several years show the increasing of general market influence on the behavior of an individual stock. You could find the number around 40% for stock market risk-factor in old books. But now the general market influence is considered almost 85%. That is why it is very important to look at the stock market first and try to predict it before investing in any stock nowadays.

The stock market can be presented by S&P-500 index. It is possible to build its different statistical forecasts using historical data. The purpose of the research was to compare two statistical methods: one that based on Cycle Analysis, another - on Neural Network. We used price and volume data to train this particular Neural Network.

A picture below shows how actual 5-day performance (yellow line) differ from predicted performances by these two methods. The top half is the comparison of Neural Network prediction, bottom half - Cycle Analysis. Green bars mean buy signals, red - sell.



Three major conclusions:
1. Cycle Analysis prediction gives signals too early, Neural Network prediction - too late.
2. In average, Cycle Analysis prediction showed slightly better accuracy than Neural Network prediction for the last six months (from June 2009 to January 2010).
3. It it possible to get a superior prediction by combining these two methods.

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The links where the models' descriptions can be found:
Cycle Analysis
Neural Network

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