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    • A Simple, Efficient and Convenient Universal System
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    • Stock Trend Forecaster: online backtesting, Excel template
    • Data Shaping offers proprietary E-commerce solutions
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U p f r o n t

Data Shaping Solutions will soon co-brand its proprietary stock market forecaster on popular financial portals. Our forecaster provides real daily performance of the associated strategy for any stock over the last 365 days, in just a few clicks on our member page.

This innovative technology, performing online computation of real historical return in a snap, brings a new dimension in trading intelligence.

F e a t u r e d

A Simple, Efficient and Convenient Universal System

We propose an original system that provides reliable daily index and stock trending signals. The non-parametric statistical techniques described in this article have several advantages: simplicity, efficiency, convenience and universality.

  • Simplicity:
    There are no advanced mathematics involved, only basic algebra. The algorithms do not require sophisticated programming techniques. They rely on data that is easy to obtain.

  • Efficiency:
    Daily predictions were correct 60% of the time in our tests. This good performance can be improved using techniques described in this article.

  • Convenience:
    The non-parametric system does not require parameter estimation. It automatically adapts to new market conditions. Additionally, the algorithms are very light in terms of computation, providing forecasts in a snap even on very slow machines.

  • Universality:
    The system works with any stock or index with a large enough volume, at any given time, in the absence of major events impacting the price. The same algorithm applies to all stocks and indices.

The algorithm computes the probability, for a particular stock or index, that tomorrow's close will be higher than tomorrow's open by at least a specified percentage. The algorithm can easily be adapted to compare today's close with tomorrow's close instead. The estimated probabilities are based on at most the last 100 days of historical data for the stock (or index) in question.

The first step consists of selecting a few price cross-ratios that have an average value of 1. The variables in the ratios can be selected so as to optimize the forecasts. In one of our applications, we have chosen the following three cross-ratios:

  1. Ratio A = ( today's high / today's low ) / ( yesterday's high / yesterday's low )
  2. Ratio B = ( today's close / today's open ) / ( yesterday's close / yesterday's open )
  3. Ratio C = today's volume / yesterday's volume
Then each day in the historical data set is assigned to one of eight possible price configurations. The configurations are defined as follows:
  1. Ratio A > 1, Ratio B > 1, Ratio C > 1
  2. Ratio A > 1, Ratio B > 1, Ratio C <= 1
  3. Ratio A > 1, Ratio B <= 1, Ratio C > 1
  4. Ratio A > 1, Ratio B <= 1, Ratio C <= 1
  5. Ratio A <= 1, Ratio B > 1, Ratio C > 1
  6. Ratio A <= 1, Ratio B > 1, Ratio C <= 1
  7. Ratio A <= 1, Ratio B <= 1, Ratio C > 1
  8. Ratio A <= 1, Ratio B <= 1, Ratio C <= 1
Now, to compute the probability that close tomorrow will be at least 1.25% higher than tomorrow open, we first compute today's price configuration. Then we check all past days in our historical dataset that have that configuration. We count these days. Let N be the number of such days. Then, let M be the number of such days further satisfying the following:

Next day close is at least 1.25% higher than next day open.

The probability that we want to compute is simply M/N. This is the probability, based on past data, that close tomorrow will be at least 1.25% higher than tomorrow's open. Of course, the 1.25 figure can be substituted by any arbitrary percentage.


There are different ways of assessing the performance of our stock trend predictor. We have investigated two approaches:

  1. computing the proportion of successful daily predictions, using a threshold of 0% instead of 1.25%, over a period of at least 200 trading days

  2. using the predicted trends (with threshold set to 0% as above) in a strategy: buy at open, sell at close or the other way around based on the prediction
Our tests showed a success rate between 54% and 65% in predicting the Nasdaq trend. The strategy associated with the forecaster has been analysed on our web site. Check our section on universal keys.

Even with a 56% success rate in predicting the trend, the long-term (non compound) yearly return before costs is above 40% in many instances. Note that we provide similar strategies that do not rely on the open price to interested clients. As with many trading strategies, the system sometimes exhibits oscillations in performance. It is possible to substantially attenuate these oscillations, using a technique described on our website.

In its simplest form, the technique consists of using the same system tomorrow if it worked today. If the system fails to correctly predict today's trend, then use the reverse system for tomorrow.

Universal Forecaster

Universal Trend Forecaster is the full name of our implementation of this system. It is available online.

You can check out the real past performance (last 365 days) online, for any stock or index, by entering the stock symbol in the trading box and clicking on the submit button. Additionally, we provide an Excel template containing all the formulas to perform the required computations.

A n n o u n c e m e n t s

  • Stock Trend Forecaster: Past Performance, Excel Template
    The universal stock trend forecaster described in our featured article is already available on our web site as an online application. It has been considerably upgraded recently: now you can check online the real day-to-day performance (last 365 days) of the system.

    You will soon also be able to download an Excel spreadsheet containing all the formulas. Eventually, access to the system will be restricted. We plan on designing paid universal trading keys by the time of this writing. High performing strategies will regularly be published in our newsletter.

  • Data Shaping offers proprietary E-commerce solutions
    We are currently developing an application that generates credit card encryption software, automatically creating a different algorithm for each webmaster. The application, relying on the modulo theory applied to random permutations, will soon be available online.
A d v e r t i s e m e n t s


    Daily stock picks for short term traders using Japanese Candlestick Patterns. Free Play of the Day picks; Glossary of candlestick terms and definitions; Traders Forum; Extensive list of stock picks based on daily patterns; 30 day free trial.

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Vincent Granville, Ph.D., Editor
Data Shaping Solutions

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