SMAP-3 2009.10

Addaptron Software
0.3 MB
Operating System
Windows All
Stock Trading software

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The stock market has different cycles, such as, four-year presidential
cycle, fiscal reporting cycles. In addition, some cycles are defined by
intrinsic characteristic properties of the system. The stock market
performance curve can be considered as a sum of the cyclical functions
with different periods and amplitudes. It is not easy to analyze the
repetition of typical patterns using a simple chart analysis because
cycles mask themselves – sometimes they overlap to form an abnormal
extremum or offset to form a flat period. Stock Market
Analyzer-Predictor SMAP-3 is able to extract basic cycles of the stock
market (indexes, sectors, or well-traded shares) and to predict an
optimal timing to buy or sell stocks. Its calculation mainly based on
extracting basic cyclical functions with different periods, amplitudes,
and phases from historical quote curve. To detect correctly major
cycles, the historical price data are transformed from time domain to
frequency domain (spectrum). At the beginning SMAP-3 does a simulation
(back testing) of forecast on relevant past data in order to estimate
the accuracy of prediction with certain parameters. Then it calculates
the prediction for the time period forward using internal optimized
parameters. Using back testing also allows user to find an optimal time
frame. By selecting data with different historical periods, user can
identify the major cycles, which have a dominant effect in a particular
time frame. To build an extrapolation (predicted curve), 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. SMAP-3 also enables finding
optimal timing to buy/sell by analyzing month of year, day of month,
and day of week (the calculation is based on statistical analysis).
SMAP-3 has a user-friendly easy-to-use interface. This software is
intended for investors with a basic knowledge in stock investing.


  • Any index as an equivalent of the overall stock
    market, sector, industry, or well-traded shares can be used to find an
    optimal timing.
  • SMAP forecasts performance for 1/4 of historical period. For example,
    if the period of historical quote data entered as input is equal 16
    years, prediction is calculated for the next 4 years; for 4 months of
    history, prediction is one month.
  • Using back testing helps to find an optimal time frame for better predictability.
  • Annual return is calculated on a decompounded basis, i.e., for
    example, 20% displayed annual return means 44% total for two-year
  • SMAP is packaged with an initial set of data for ^GSPC with different periods.
  • Historical quote data files are downloaded from publicly available
    data source for free (US and worldwide stock exchanges).
  • SMAP can be used also for intraday trading.


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