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Re: Time Series Prediction Competition

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  • shanemcdonaldryan
    Hey Colin, Or anyone else who is interested. Does anyone have any recommendations for papers on intraday financial time series analysis? I have quite a library
    Message 1 of 3 , Apr 2, 2007
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      Hey Colin,

      Or anyone else who is interested. Does anyone have any recommendations
      for papers on intraday financial time series analysis? I have quite a
      library of papers if anyone want to trade notes. Yes I am very
      familiar with Sidhant Dash's excellent paper on the subject.

      Also as I mentioned a couple of weeks ago. I will be putting up my
      time-series specific NEAT implementation (based on Mat Buckland's
      code) on Sourceforge soon. I am just waiting to get my project
      approved. It works on windows and linux. Is relatively easy to use for
      TS prediction. Has a couple of nice features like using a uniform
      random number generator.

      Anyone interested in chatting about NEAT TS or more specifically NEAT
      TS for intraday financial prediction. Please drop me a line.

      Thanks,

      Shane

      --- In neat@yahoogroups.com, Colin Green <cgreen@...> wrote:
      >
      > Thanks Ken.
      >
      > My initial thought is to try using my waveform generator experiment to
      > find an approximation of the underlying function that generates the
      > competition data, as at first glance some of the datasets appear to be
      > very cyclical. Under the 'Instructions' tab on the web page it says
      that
      > the submitted results will be compared to "established statistical
      > forecasting methods" and then it lists the following techniques:
      >
      > * Naïve
      > * Single, Linear, Seasonal & Dampened Trend Exponential Smoothing
      > * ARIMA-Methods
      >
      > So does anyone know off-hand what types of data sets these techniques
      > can perform [good] predictions for, and therefore what type of data
      > source is likely being used for these competition data sets? E.g. is it
      > more likely to be, say, environmental readings such as temperature,
      > river flow rates, water oxygen levels, population levels, etc. where we
      > can expect some cyclic behaviour (through the seasons)?
      >
      > The reason I ask is that my investigations into financial time series
      > data have lead me to believe you really need additional information to
      > predict stock and indices price series with any sort of success, e.g.
      > Price/Earnings ratios, and even then such series will possess a large
      > amount of unpredictability caused by random events. I'll give it a try
      > anyway but I think the chances of getting anything like good results
      > with my existing waveform generator experiment are much greater with
      > something like cyclical environmental data rather than financial data
      > that, although cyclical in the very long term (like in decade
      > timescales), tends to be largely chaotic IMHO.
      >
      > Cheers,
      >
      > Colin
      >
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