June 2011: SP-500 Might Not Touch 1250, At Least For Now

One of the popular ideas now is that until S&P-500 index touch 1250 number, it is too early to buy or sell. However, on the assumption that currently many market participants are looking at charts and use technical analysis to make their buy-sell decisions, the index might not move down too much, at least for now.

If almost everyone is considering that it is not good time yet to sell (or go short) and waiting for this magic number, this move might not happen. The reason is that there will be no sellers but mostly holders that are waiting. It can be a typical situation when an expectation affects the market. The index might stall for a while and then move up. Also a statistical cycle analysis method based on action-reaction idea indicate that such reverse will happen after June 15-17 and before reaching 1250 value:

Chart has been calculated using cycles predictor

Are Technical Indicators Useful?

Yes and No. Evidently, there are periods when technical analysis works and the periods when it does not. The reasons can be many – fundamental changes, revised expectations, unexpected news, etc. During the periods when a majority of market participants make their decisions based on past market performance, as a rule, there would be some technical indicators that relatively work well.

Are there best ones? During some periods, some indicators might be the best winners, others – the worst losers. But all things are subject to change. Besides, indicators and markets are often a two-way system, i.e., markets can be affected when a huge number of investors use the same indicator(s). For example, the indicator predicts flat 2 days and then an uptrend for 3 days. If everybody follows, the forecast fails because price would be driven up first 2 days by buying volume and then 3 days flat or down-trending due to taking profit.

Other technical methods. In many cases, due to a semi-stochastic nature of the market, probabilistic statistical methods are able to predict well. Some of the systems that employed such methods is Neural Network (NN). NN often suffers from “over-fitting”. It is bad because over-fitting gives an exact but sometimes wrong result more often than an approximate but correct one. Cycle analysis, as another statistical method, has other advantages and disadvantages.

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

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.

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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.

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.