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This article is about orthogonal polynomials. Their use can become the basis for a more accurate and effective analysis of market information allowing traders to make more informed decisions.

Trading efficiency largely depends on the methods of analyzing market data. One such method is orthogonal polynomials. These polynomials are mathematical functions that can be used to solve a number of problems related to trading.

The most famous orthogonal polynomials are the Legendre, Chebyshev, Laguerre and Hermite polynomials. Each of these polynomials has unique properties that allow them to be used to solve different problems. Here are some of the main ways to use them:

  • Simulating time series. Orthogonal polynomials can be used to describe time series. Their use can help in identifying trends and other patterns.
  • Regression. Orthogonal polynomials can be applied in regression analysis. Their use allows us to improve the quality of the model and make it more interpretable.
  • Forecasting. Orthogonal polynomials can be used to make predictions about what the price will be if current trends continue.

Let's see how orthogonal polynomials can be applied in practice.



Author: Aleksej Poljakov

 
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The article Polynomial models in trading was published:

Author: Aleksej Poljakov

Thank you. As always, a lot of food for thought.
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