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The article discusses the application of Grey models to forecasting financial time series. We will consider the operating principles of Grey models and the specifics of their application to financial series. We will also discuss the advantages and limitations of using these models in trading.

Grey models can be used to solve a wide variety of problems. With the help of GM we can analyze a time series, smooth it or identify the main trends in price movement. But this model can also be used for forecasting. The main advantage of using GM is that this model does not impose any restrictions on the stationarity of the time series. For example, SMA will show all its best qualities if the time series is stationary and its values are normally distributed. If the time series is non-stationary (in other words, there is a trend), then SMA will be hopelessly lagging. For GM, these requirements are not important and it can cope with any time series. Or at least it should. The requirements for GM are simple and easy to fulfill:

• the length of the time series should be at least 4;
• the values of the time series should be strictly positive and occur at equal time intervals, without gaps.

Author: Aleksej Poljakov