IDEAS home Printed from https://ideas.repec.org/p/hal/wpaper/hal-02145175.html
   My bibliography  Save this paper

A New Adaptive Moving Average (Vama) Technical Indicator For Financial Data Smoothing

Author

Listed:
  • Alex Pierrefeu

    (UNATI - Unité Analyse et Traitement de l'Information - NEUROSPIN - Service NEUROSPIN - Université Paris-Saclay - JOLIOT - Institut des Sciences du Vivant Frédéric JOLIOT - CEA - Commissariat à l'énergie atomique et aux énergies alternatives)

Abstract

The separation of the trend from random fluctuations (noise) is a major objective in technical analysis and for a long time two commons filters, the simple moving average and the exponential moving average have been used to achieve this goal, those two filters use one parameter to control this degree of separation, higher degree of separation involve smoother results but also more lag. Lag is defined as the effect of a moving average to show past trends instead of new ones, this effect his unavoidable with causal filters and is a major drawback in decision timing. In this article I will introduce a new adaptive moving average technical indicator (VAMA) who aim to provide smooth results as well as providing fast decision timing. This new method will be used for the construction of a simple MA crossover strategy in EURUSD, the results of this strategy will then be compared to the results of the same strategy using other adaptive moving averages to provide a comparison of the profitability of this indicator.

Suggested Citation

  • Alex Pierrefeu, 2019. "A New Adaptive Moving Average (Vama) Technical Indicator For Financial Data Smoothing," Working Papers hal-02145175, HAL.
    • Handle: RePEc:hal:wpaper:hal-02145175
    Note: View the original document on HAL open archive server: https://hal.science/hal-02145175
    as

    Download full text from publisher

    File URL: https://hal.science/hal-02145175/document
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:wpaper:hal-02145175. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.