New Software Stock Market Tools SMT1:

discover the power of AI Stock Market forecast and trading simulation
- increase your trading profitability

2010-12-31

2010 Stock Market Strength Might Propagate Into 2011

S&P-500 index has grown 12.78% during 2010 and it is ending on a positive note. The US corporate profits continue improving and companies have a lot of cash that provide opportunities for business optimization, better dividends, and make stocks more attractive. Also during the last several months the stock market became more predictable from the technical analysis point of view.

Many experts believe that the corporate earnings will grow further in 2011. Evidently, the prices of most shares will move in a natural cyclical manner with dynamical responds to unexpected news, as it was before. In average, major indexes are expected to perform around the same as in 2010. Anything can happen but, as always, extremes have less probability than averages.

Wishing You
Happy 20111 New Year!

Hopefully, 2011 will be a better year with many new opportunities for stock investors and traders!

2010-11-13

November 2010: The Stock Market Is Taking Break

The US stock market reached the highest level in two years after a strong two-month rally. However, good news about improving retail results and a four-month low jobless claims rate were unable to push the market higher. Since the current market is driven mostly by news, it was a relatively rare case when technical indicators were able to predict a downtrend. A massive insider selling was another factor that contributed to the decline. If the correction is deep, then a consequent cyclical reaction might send the market up again.

The GDP grew at a 2% pace in the third quarter that is slightly better than the 1.7% growth during the second quarter. The government says that the improvement of GDP-to-deficit ratio is the biggest since fiscal 1987 year. Many analysts expect that the US corporate earnings will aspire higher despite a weakening dollar and a slow-speed recovery will lead eventually to an economic normalization.

2010-10-30

SP-500 Index: the First Two Weeks of November 2010

Although technically there are no many signals for significant advance in any direction, a possible scenario could be a downside move at the end of the first week and then a slight bounce back. As example of technical prediction, see the chart. The chart has been plotted using InvAn-4 pattern recognition forecast for S&P-500 index prices (November 1-12, 2010).

From the summarized point of view, stock market investors may not rely on technical predictions but rather react to the US congressional elections and the Federal Reserve economic stimulus plans. Therefore, news might be a major driving force in the stock market for the first two weeks of November 2010.

2010-10-09

October 2010 Stock Market Overview: Fundamentals Not Improving, Technicals Not Worsening

Due to a growing expectation that the US Federal Reserve will ease a credit environment to help the economy recovery, the US dollar dropped to several-month lows against most foreign currencies. More dollars may stimulate the economical growth. On the other hand, if the Federal Reserve pumps more dollars into the economy, a falling dollar can negatively affect consumers, businesses, and investors.

A dollar weakness together with the news that the US federal deficit for the 2010 budget year was estimated around $1.3 trillion add some fear of the instability of the system, Gold hit a new high that may also evidence a weak hope among investors for a decent stock market performance.

The US unemployment stayed at high 9.6% rate for the last couple of months. Adding jobless people who are not actively seeking work and people who are underemployed result more than 17%. Such statistics may indicate that the stimulus measures failed to create jobs as it was initially expected.

Some of technical indicators signal a lasting momentum that may keep the recent uptrend cycle for several weeks ahead. However, the third quarter earnings reports may not be so optimistic to sustain an existing stock market evaluation. In this case, major stock market indexes may have a correction if more negative news add the pressure.



The chart above shows S&P-500 forecast for the period from October 11 to October 22, 2010. The calculation has been performed using Neural Network Stock Trend Predictor NNSTP-2. The forecast is a slight uptrend.

2010-09-24

SP-500 Forecast for the Next Two Weeks, September 27 – October 8, 2010



The chart shows S&P-500 forecast for the period from September 27 to October 8, 2010. The calculation has been performed using Neural Network Stock Trend Predictor NNSTP-2. The forecast is fluctuations with eventual uptrend. However, technical prediction may be different if something fundamental happens.

2010-09-12

Pattern Prediction for September 13-24, 2010

The patterns of the S&P-500 Index may be repeatable in the future. Pattern recognition systems can help to find similar patterns easier by classifying them. After selecting similar patterns, it is possible to use them to predict the future pattern.

Investment Analyzer (IA) by Addaptron Software has a few extra features for a short term forecast. To predict prices of the selected stock (index) using pattern similarity. IA searches for the pattern from the internal database by scanning all historical data. Depending on degree of similarity, it ranks all possible matches within given historical period and then combine them.

The chart below has been plotted using IA pattern similarity feature. S&P-500 index prices have been used as input; the output is prediction for September 13-24. A possible prediction is a slight uptrend and then more downtrend. However, 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 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

2010-08-27

S&P-500 Forecast for the First 10 Days of September on the Basis of Technical Indicators Signals

There is a lot of technical indicators, as well as, multiple interpretations of each indicator's signal. Many stock investors and traders use own favorite indicators and insist on specific interpretations. How to make sure that it is right? What if to allow a computer to decide using back-testing which indicator should be trusted more at current market conditions?

One of computer tools that enables to compose the price 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 index forecast for the first 10 days of September, 2010




It indicates that the index may rise until September 3 and then follow some downtrend.


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

2010-08-09

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


2010-07-26

Downloading Data for Investment Analyzer InvAn-3/4

Investment Analyzer InvAn-3/4 uses free data sources to update stock prices and financial data for technical and fundamental analyses. In some rare cases, it can be difficult to download the data from the Internet. The reasons can be different - an interrupting or slow Internet connection, unstable availability of the source, or the absence of requested data (for example, some company can go out of business and its data may be erased from databases).

Despite the fact that InvAn-3/4 built with the optimization to process such kind of errors, in some critical situations, for example, after several attempts to read the fundamental (financial) data with no success, the following error message can appear in a pop-up window:






The solution for this problem is the following:

  1. Click "Continue" to close the pop-up window and then click "Save".
  2. Since it stops on a particular symbol (company), check if this symbol name still exists by visiting Yahoo! Finance or Google. If data are not available anymore, consider deleting the problematic symbol record.
  3. If company data are available, you may try to download data again starting from the number where it stopped using button "From - To" at the bottom of the form (in our example above, go to two boxes besides the button "From - To" and enter in boxes numbers 379 and 525).
  4. If company data are unavailable, try to download data again starting from the number after where it stopped using button "From - To" at the bottom of the form (in our example above, go to two boxes besides the button "From - To" and enter in boxes numbers 380 and 525). Later consider deleting the symbol record.
  5. If two above steps were unsuccessful, check the Internet connection or try to download later.

2010-07-09

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


2010-06-27

Multi-input Improvement of One-day Performance Indicator

Stock market forecast can be built using different technical indicators. The relative change between the closing prices of two consequent days can be called one-day performance indicator (ODP indicator). The interpretation of ODP indicator chart is very simple - an uptrend starts after a big positive value of ODP indicator (the chart has been presented in the recent post). It works by a simple scheme: input1 → output.

However, a closer look at ODP indicator chart reveals also a typical pattern before starting uptrend - it fluctuates while moving down and then it has a big positive value. So that the more informative scheme would be in case of using n days of ODP indicator signals: (input1, input2, . . inputn) → output. It reminds candlesticks pattern chart. A candlestick figure consists of Real Body and Upper and Lower Shadows. The Real Body size is proportional to the difference between opening and closing prices of one day. Since it is no a big difference between closing prices of previous day and opening price of the next day, there is a similarity between Real Body and ODP indicator.



Considering this uptrend case, it is important to notice that there could be many other ODP indicator patterns. Investors could analyze these multi-day patterns on charts (in the same way as candlesticks pattern is used as a tool to predict future prices) or by using an automatic statistical method to map the correlation (input1, input2, . . inputn) → output. Evidently, one of the simple and powerful statistical methods that could be used for this purpose is Neural Network.

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


2010-06-09

One-day Stock Market Performance Can Be an Indicator

According to Efficient Markets approach, news and other publicly available information are incorporated into the price of a stock. One of the available news factors is a state of the stock market itself - bullish, bearish, or neutral. The state can be the same or it can evolve. A state change results the re-evaluation of price with a certain time delay. So any stock market movement causes a certain reaction of investors. If the market suddenly plunges, investors may start panicking, selling, and dragging the market even faster. If stock market prices are increasing without fluctuations for long, investors become confident to invest. As a result, if more money inflows, demand pushes prices up.

In the same way, one-day stock market performance can impact the emotions of investors. Therefore, it can be considered as a kind of indicator. The chart below shows how a big one-day positive performance can push the market up (callout 1..5):




The chart represents the curve of S&P-500 index values for period from October 2008 to April 2009 (blue line) and the curve of one-day performance (red line). The performance calculated using formula:


P1 = 100% * (C2 - C1) / C1



where C2 - current day closing price, C1 - previous day closing price.

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


2010-05-24

Informational Resources Available

The Research and Development web-page on Addaptron Software website has been updated. The page has been enriched by the latest headlines form different stock investing blogs. It still includes the links to stock investing articles (some articles can be useful for investors-beginners):  
* How to Become a Successful Investor 
* How to Understand the Stock Market Nowadays 
* Optimal Investing Timing  
* Predicting Stock Market Using Expert Method 

2010-05-19

Predicting Stock Market Using Cycle Analysis

Many 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.

One of the 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. The stock market cycles can be a good opportunity to maximize return on investments.

However, 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.

Any predictive method has own limit. The major obstacle in using cycle analysis 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 cannot guarantee 100% accuracy of prediction.

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 (and then adjust these parameters).

To discover different patterns in the market movement, including cycles, investors use different software tools. One of the tool 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.

As example, the chart below shows S&P-500 forecast for May 17 - June 2, 2010. The calculation has been performed using SMAP-3. The forecast is the following: downtrend may continue until May 21, then a reversal to uptrend until June 02.



Computational details: regular mode (auto); number of line for spectrum analysis - 48; used historical data period - 4 months (from December 17, 2009 to May 14, 2010); back-test deviation - 1.11%; spectrum lines and fitting charts -



In 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." Also, stock market software tools help investors and traders to research, analyze, and predict the stock market.




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



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


2010-05-07

Recent Panic Selling Could Be Caused by Computer-generated Plunge

Traders, exchanges, and regulators try to define what prompted Dow Jones Industrial Average near 1,000-point drop on May 6, 2010. One of the theories is that it was a mistake triggered when a trader accidentally sold billions of shares instead of millions. However, it may be not a case this time.

Firstly this correction was supposed to happen as it was predicted by many. Our cycle analysis calculation even predicted the exact date - May 6, 2010 (see our blog post "Contributing Factors in Forecasting: Stocks vs. Stock Market and Sectors"). Secondly it coincides with a bad news from Greece. The last question is why it was so sharp. Could it be a some kind of high-frequency trading effect? Maybe.

A more simple explanation is the following. Buy or sell order executes very fast if meets certain conditions. This is a modern technologies world. There is a very popular loss-protective strategy in stock investing nowadays – to use a stop-loss order if price drops below 8-10%. Now, let's imagine that more and more orders start executing if prices go down and down. It drags major market indexes down. And this is when traders and investors start to panic and post more selling orders. The prices go down reaching 8-10% threshold faster and faster. It becomes like a loop and results an avalanche.

In conclusion, the question is if stock market regulators will be able to prevent such computer-generated plunges. Probably not. Computers, software, the Internet become faster every year. On the other hand, any artificial restrictions can cause stock market liquidity to suffer. Since the liquidity is a very basic thing for free market to function normally, there is no way to avoid such stock market volatility in the future.

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


2010-05-03

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.


2010-04-23

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.



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



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.


2010-04-17

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.


2010-04-05

April 2010 Stock Market Outlook

Increase in US employment in March is the biggest increase in the last three years. Bloomberg estimates that the economy probably grew by 2.8% in the first quarter of 2010. Some economists believe that the deepest US recession since the 1930s has ended now.

The recent news about strong improvements in demand at services businesses and in the housing market added to an optimistic mood. White House economic adviser Larry Summers said in a newspaper interview with the Financial Times that the US economy is on the path to achieving self-sustaining growth - read more about this optimistic opinion...

Also read why US stocks look better and better, at least in the short run.

From the technical analysis side, the expectations are also positive, at least in a short run. The chart below represents SP-500 forecast for April calculated by Neural Network Stock Trend Predictor NNSTP-2. Neural Network forecast shows uptrend for April 2010:



The next chart shows Cycle Analysis forecast by Stock Market Analyzer-Predictor SMAP-3. It indicates a small uptrend until the middle of the April. Although it does not look so optimistic as previous one but after some correction at the end of May, the bigger uptrend is predicted again:



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.

2010-03-26

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.



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




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


2010-03-15

Spring 2010: A Short-term Outlook for Stock Market Is Positive

Retailers and consumer discretionary stocks demonstrate a strong performance. Retail sales posted a surprising increase in February (sales rose 0.3%). Although some analysts doubt that the spending gains can be sustained since the unemployment rate still remains high (9.7% in February), fundamentals of many companies gradually started showing improvements.

If the overall US national debt over the next few years rises to 100% of the gross domestic product, it will be alarming signal for the International Monetary Fund and international markets. However, many economists believe that US will be able at least keep the national debt stable relative to the size of the economy.

More positive news:
Recovery hope
It is still manageable at the current level of US federal budget deficit

...and negative ones:
Congressional estimates
Dead Cat
Death of American Capitalism
Wall Street Loses
US debt will keep growing even with recovery


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.

2010-03-01

Neural Network Forecast for March 2010 Stock Market Performance

According to neural network forecast, SP-500 price behavior for March 2010 expected to be fluctuating without significant advances. The chart below has been calculated using Neural Network Stock Trend Predictor NNSTP-2.



Neural networks can discover patterns in data that humans might not notice and successfully predict the future trend. Addaptron Software has developed NNSTP-2, neural network computer tool, to help stock traders in predicting stock prices for short terms. NNSTP-2 predicts future share prices or their percentage changes (can be chosen in settings menu) using Fuzzy Neural Network (FNN). Input data are weighted closing price of the stock and the volume traded (EOD csv-files). It operates automatically when creating the FNN, training it, and mapping to classify a new input vector. NNSTP-2 has a user-friendly easy-to-use interface. Historical stock price data are downloaded automatically from the Internet free-of-charge (US and worldwide stock exchanges). The software is intended for traders with a basic knowledge in stock analysis.

See also:
Weekly stock market forecast
Tools to predict stock market



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.

2010-02-27

Cycle Analysis Forecast Gives Clues for March 2010 Stock Market Performance

According to cycle analysis forecast, SP-500 performance for March 2010 expected to be negative. The chart below has been plotted using Stock Market Analyzer-Predictor SMAP-3.



The stock market performance curve can be considered as a sum of the cyclical functions with different periods and amplitudes. It is not easy to analyze the repetition of typical patterns in stock market performance because cycles mask themselves - sometimes they overlap to form an abnormal extremum or offset to form a flat period. A simple chart analysis has a certain limit in identifying cycles.

Addaptron Software has developed Stock Market Analyzer-Predictor (SMAP), computer program, which is able not only to extract basic cycles of the stock market (indexes, sectors, or well-traded shares) but also to predict an optimal timing to buy or sell stocks. SMAP calculation mainly based on extracting basic cyclical functions with different periods, amplitudes, and phases from historical quote curve. To detect correctly major cycles, the historical price data are transformed from time domain to frequency domain (spectrum).

See also:
Weekly stock market forecast
Tools to predict stock market



Nothing in this piece or on 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.


2010-02-13

Stock Market Forecast 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. There is 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.


There is a webpage where you are invited to build a collective forecast for S&P-500 index. 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.


Link to S&P-500 index weekly forecast


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


2010-02-11

SMAP-2/3 Update

Stock Market Analyzer-Predictor SMAP-2/3 has been added an option to specify the type of input data - adjusted quotes (it is useful when a stock splits) or actual quotes without adjusting. Also now SMAP-3 allows managing the list of symbols and performing a forecast comparative analysis. A user can edit, delete, add symbols on the list, and download all files. The processed symbols output is sorted according to expected performance. To update your tools, visit Addaptron Software download page or use Update interface button.





2010-01-29

Addaptron Software Updated Stock Market Analyzer-Predictor

The stock market has powerful and consistent cycles. They can be as a bad surprise for some investors but others know how to take advantage of the market cycles. By identifying the cycles it is possible to anticipate tops and bottoms and to determine trends. The stock market cycles can be a good opportunity to maximize return on investments. "The stock market cycles known by investors for long," says Alex Shmatov, president and founder of Addaptron Software. "The stock market is an alive system - around can be joy or fear but its pulse always exists. And many investors benefit from a fluctuating nature of the market."

The presence of multiple cycles of different periods and magnitudes in conjunction with linear trends, can form a complex pattern of the stock market performance curve. Often cycles mask themselves - sometimes they overlap to form an abnormal extremum or offset to form a flat period. It is clear that a simple chart analysis has a certain limit in identifying cycles parameters and using them for predicting. SMAP-2 is able to extract basic cycles of the stock market (indexes, sectors, or well-traded shares). To build an extrapolation, SMAP-2 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. SMAP-2 also enables finding optimal timing to buy/sell by analyzing month of year, day of month, and day of week (the calculation is based on statistical analysis). The investors who empowered by using SMAP-2 are less likely to get fooled into buying at the worst time. SMAP-2 is one the most popular among investors software tools.

Addaptron Software develops and provides advanced data processing software tools to businesses and individuals who choose to improve efficiency of their decision-making. The company specialized in developing software that enables comprehensive data processing to extract meaningful and useful information in areas of investment, management, and marketing. One of the main approaches is to reflect precisely system's quality using mathematical modeling. Currently, the company provides software tools to investors to help them more effectively manage their investments.