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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.