Stock Forecast Methods

Stock Market Trading and Investing

Transforming Moving Average From Lagging To Leading Indicator

Traditionally in technical analysis, chartists consider moving average indicators as lagging ones. In other words, these indicators are able only to confirm long-term trends that already started but not to predict in advance. The difference between simple moving average (SMA) and exponential moving average (EMA) is not so big in that respect although exponential one assigns more weights to the latest points and, therefore, EMA is more sensitive to the latest changes.

A more “predictive” signal can provide a combination of EMA with crossing price curve. Normally, it is used as an affirmation of increase in momentum but, still, the disadvantage of using this combination is that a significant move may have already happened. Therefore, if the trend is not going to last long, traders risk to enter a position too late.

Recent research showed that the predictive abilities of some well-known indicators can be improved by an additional transformation. Briefly, if an indicator is trend-differentially coupled with price – it demonstrates better predictive abilities than a simple indicator. As experiments showed – a similar improvement occurred when EMA indicator has been transformed to a slope of line and differentially-coupled with a price line slope.

The image below shows EMA divergence indicator forecast by Technical Analyzer TA-1. This interface represents one of three major modules of TA-1. The module provides with more than 50 popular technical indicators. Except chart analysis, indicators can be used as input for Neural Network to build 10-day price forecast. There is an option to compose forecast from all indicators – each indicator’s forecast is added with the weight proportionally to the current ability of the indicator to predict prices.

Transforming Moving Average From Lagging To Leading Indicator

Advertisements

August 6, 2011 Posted by | Stock Market Forecast, Stock Market Software | , , , , , | Leave a comment

Model To Predict Stock Market Using Butterfly Effect

As it was reported in the research “The Technical Indicator to Watch Rapid Sell-off“, one of the ways to predict a steep downtrend could be to monitor the speed and acceleration of prices (high-order derivatives). As statistics showed, a typical picture is that specific stock market short-term changes are coupled to big long-term negative changes in the future. Evidently, the same idea can be applied to long-term positive changes.

Considering the impact of short-term changes on longer periods can look revolutionary since normally analysts use a longer period to predict a shorter one. For example, to predict one-day price change, chartists consider up to 12 previous candlesticks in patterns. If we assume that markets are partly obeyed general natural laws, a similarity when a small seed is able to grow into a huge tree might look less surprising.

There is a hypothesis that many dynamic processes including financial markets can be described by Chaos theory. One of the theory’s ideas is “Butterfly Effect” (BE). According to this effect, the slightest disturbance of input parameters can cause a huge change in the outcome (a high sensitivity to initial conditions – link to video).

There is another explanation why BE might be applied to financial markets. Big market participants (BMP) have powerful resources to get important information before it becomes known to others. They also deal with a much bigger volume of funds and, therefore, are able to affect the market by changing supply-demand equilibrium. Also BMP have resources to react quickly and due a huge volume of money inflow or outflow, the market equilibrium can be changed very fast.

One of simple conclusions is that fast market movements might signal a high probability of changing long-term expectations. Except fast moves, BMP may move prices with different degrees of acceleration. So that in most cases, BMP’s short-term actions should have special pattern signatures and, therefore, some typical short pattern signatures can literally predefine following huge long-term changes.

Creating Model To Predict Stock Market Using Butterfly Effect

July 10, 2011 Posted by | Stock Market Forecast | , , | Leave a comment

New Trading Decision Support Systems Group on LinkedIn

New Trading Decision Support Systems group on LinkedInThe new group Trading Decision Support Systems is intended to be a resource for individual/institutional traders/investors and software developers in stock market area to share ideas, initiate and participate discussions, benefit from the collective intelligence, and to expand network. It will be primarily focused on such topics as:

  • Trading EOD and intraday different asset classes: trading tips, strategies, why, how, and results.
  • Trading systems: algorithms, methods, technologies, human factor, and statistics.
  • Software tools to support traders decisions: forecast methods, simulations, back-testing, and optimization.
  • Technical Analysis: indicators and chart patterns.
  • Fundamental Analysis: financial ratios and predictive models.
  • News: analysis and formalization by converting to measurable variables to automate systems with contributing news factor.
  • Numerical methods, data processing, artificial intelligence, and modeling in stock market areas.

Many things remain unchangeable in a trading world – supply-demand price balance, greed-fear driven mistakes, as well as, ability to think, make right decisions, and find the best solutions. When once winning approaches, strategies, or methods failed, many traders are prone to analyze the reasons why it happened. Then they create new approaches and develop new successful systems. If systems are automated, it is easy and fast to test them, collect and analyze back-testing and live statistics, and then make necessary improvements. That is why it is important to implement the best ideas in software applications that can be also used by others.

The computational technologies are changing. Systems empowered by Artificial Intelligence have self-learning abilities that enable them to adapt to market changes. One of the purposes of this group is to bring together the developers of decision support software and traders-users for mutual benefits: the developers get more ideas about their products’ improvements and make a better progress in developing software for traders, the users arise issues relating to their needs and wants. Hopefully everyone will find something useful participating in this group.

You are welcome to join this newly created networking group. Be the first to start a relevant discussion, promote your product or service. Please join Trading Decision Support Systems group on LinkedIn!

June 22, 2011 Posted by | Stock Market Forecast, Stock Market Software | , , , , , , , , , , , , , , , , , , | 1 Comment

The Stock Market Is Likely Taking Summer Break

The Stock Market Is Likely Taking Summer Break

S&P-500 Index Drop from May 2 to June 8, 2011

Major stock market indexes slowly went down during the last several weeks, from May 2 to June 8, 2011. Since this decline has already broken a few important technical chart levels, many technical analysts believe that the trend might continue with sideways moves for a few weeks ahead.

Except seasonal reason, this May stock market decline was also caused by fundamental factors. The US corporate profits in the first quarter dropped for the first time in more than two years. The US unemployment rate in May increased from 9.0% to 9.1%. It looks likely that investors overreacted to strong corporate earnings at the beginning of this year. Economists believe that the government stimulus money could have artificially inflated the market. Evidently, without additional money injection the US economy would undergo a transition to a self-sustaining recovery.

From the fundamental point of view it is not clear how precisely the ending of stimulus is reflected in the current market evaluation. So that when the bond-buying program ends at the end of June, the US stock market might reach a more accurate equilibrium. Other surprises might be brought by the second quarter reporting season.

June 9, 2011 Posted by | Stock Market Forecast | , , , , , , , | Leave a comment

The Stock Market Is Entering A Slow Summer Season

The Stock Market Is Entering A Slow Summer Season

Not so long ago, S&P warned the US government of consequences if a massive federal deficit is not fixed; as it was estimated, there is a 33% chance it would lower existing triple-A rating. The US trade deficit worsened. More automobiles and other goods were sold abroad but oil imports increased. So that high oil prices is one of the reasons that the trade deficit rose 6% in March from February. The unemployment monthly rate slightly grew, from 8.8% to 9%. The productivity growth slowed in the 1st quarter.

However, long-term fundamentals look strong. During the last several quarters in a row, the US biggest corporations had stronger revenues and better profits. The recent slight correction in commodities prices will help the economy growth. The current market weakness can be partly explained by typical for this time of year assets re-location – many big investors are making summer seasonal adjustments to their portfolios. They are switching to cash and bonds trying to anticipate a statistically known summer market slowdown.

May 25, 2011 Posted by | Stock Market Forecast | , , , , , , | Leave a comment

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.

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

February Is the Month of a Slight Correction

With positive US earnings forecast for this year, 2011 is set to be one of the best years after the recession. Additionally, it is a good stock market timing of the presidential election cycle. According to many experts, this bull market will have more room to run. On the negative side, the US economy still remains too weak to help a high unemployment rate. Although the economy is improving, it is a slow recovery. Besides, this year the US government’s deficit might surge to a record $1.5 trillion.

S&P-500 reached a 2.5-year high level and now there is no much pressure to push the market down. However, bad economic or market-related news might easily cause a short-term correction. Another trigger could be a continuing downtrend of Indian Market that is currently already at a several-month low level. From the technical analysis view, according to the last 10-year S&P-500 statistics, February is the month of a slight correction.

10-year S&P-500 index statistics of monthly performance

Chart shows 10-year S&P-500 index statistics of monthly performance (calculated by Stock Market Predictor SMAP-3)

February 11, 2011 Posted by | Stock Market Forecast | , , , , , , , | 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

Until the Middle of November S&P-500 Might Be Still Good

The stock market during a month ahead might be driven by a few expected fundamental news. Nevertheless, technical factors can give some additional momentum for the market. In October, S&P-500 gained more than 3%. The last four weeks, S&P-500 weekly performance was 1.65%, 0.95%, 0.59%, and 0.02%. The trend does not look optimistic. However, according to a cycle analysis, October’s uptrend cycle can be still intact. The chart shows a possible resumption of uptrend until November 11:

Until the Middle of November S&P-500 Might Be Still Good

The forecast was calculated using software tool SMAP-3. A cycle prediction is based on the hypothesis that statistically revealed cycles may be repeatable in the future and, therefore, they can be used to build the summarized curve of future movements.

October 31, 2010 Posted by | Stock Market Forecast | , , , , , , , | Leave a comment