Stock Forecast Methods

Stock Market Trading and Investing

Unusual Use of Parabolic SAR

Parabolic SAR can be improved and successfully used for predicting stock market prices, especially, in trending markets

Traditionally, Parabolic SAR* is considered as a trend following indicator. Probably, few traders would think about using it for prediction. But after testing, I started to believe that it can be successfully used for prediction in conjunction with other indicators, especially, in a trending market. The explanation why it works can be the following. When a trend reverses, the probability of its continuation is more than 50% in average. The software with Neural Network (NN) is able to catch it statistically and show the result in extrapolated curves. The function of SAR in this method is to provide NN with reversal point signals.

The initial hypothesis was the following. Since SAR is able to give a strong signal when a price trend is reversing, this signal can be used for predicting if a new trend is prone to last. To compare predictive ability of SAR with other indicators, it has been implemented into the technical analysis module of Fundamental-Technical Analyzer FTA-2. SAR calculations have been used to collect statistics based on the forecast simulations for major indexes and ETFs during August-October 2011 period. As a result, SAR’s position was mostly in “top ten” indicators’ list.

Unusual Use of Parabolic SAR
The research and presented chart are made by Fundamental-Technical Analyzer FTA-2, one of the software modules that enables composing Neural Network forecasts of many indicators with weights accordingly to each indicator’s predictive ability.

Omitting logical rules for acceleration factor and reversal conditions, a recurring core formula for Parabolic SAR is the following:

   SAR (current point) = AF * [EP - SAR (previous point)] + SAR (previous point) 

where:
AF – Acceleration Factor (normally starts from 0.02 and increases by 0.02 if each next point reaches a new extreme, saturates until 0.2);
EP – Extreme Point (lowest low or highest high).

Conclusions. SAR is especially effective in a trending market. To make it more effective in a sideways market, it is a good idea to use it in conjunction with other indicators. Parabolic SAR can be enriched and successfully used for predicting stock market prices. Combing it with Neural Network allows extracting more statistically stable patterns and, therefore, providing a better accuracy in the forecast. As simulations showed, improved results can be achieved if SAR is transformed into more sensitive indicator by subtracting it from close price (it indicates the degree of SAR and price convergence).


*) SAR stands for Stop-And-Reverse. It has been used by many traders for decades. Its major application is in trading systems to define a trailing stop, i.e., to protect profit when a price trend changes. The term “parabolic” appeared to characterize the indicator parabola shape that is due to using an accelerating factor in the formula.

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November 26, 2011 Posted by | Stock Market Forecast, Stock Market Software | , , , , , , | 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