OPEN-SOURCE SCRIPT

Fisher Transform Revisited

Fisher Transform developped by Ehlers is used mostly to detect peaks and troughs, which it does with little lag, but there are many false signals. Looking at its formula and construction, we can revisit it for the purpose of detecting trends and flat market.

How do we want to do that? There are 3 different actions:

  1. Increase the default value from usual 9 or 10 to 30
  2. Show the indicator as seen from upper time frame with synthetic rolling candles
  3. Change the weights in first formula in order to saturate the input signal, push the trend data to the limits, so therefore leaving a good view when market is flat

As can be seen from the chart above, the revisited Fisher is above 2 for uptrend markets, below -2 for downtrending markets and in-between when the market is flat.

Notes
  1. Weights for Fisher transform formula can be changed as parameters. Recommended valeus are 0.6 and 0.6 to saturate signal. You may come back to original formula by setting 0.33 and 0.66.
  2. Parameter n allows view from upper time, a multiple of current time frame. n = 1 for current chart, n = 5 for 5 minutes view on the 1 min chart


Usage
Of course, it should be not be used in standalone mode. Indicator is for trend traders who can stay away when market is flat. Trend start when indicator goes above 2 but like all trade indicators, it will be late; it is therefore a good idea to change n back to 1 to get a timely entry, to be confirmed of course with other elements of technical analysis.

Fisher TransformOscillatorsTrend Analysis

Скрипт с открытым кодом

В истинном духе TradingView автор этого скрипта опубликовал его с открытым исходным кодом, чтобы трейдеры могли понять, как он работает, и проверить на практике. Вы можете воспользоваться им бесплатно, но повторное использование этого кода в публикации регулируется Правилами поведения. Вы можете добавить этот скрипт в избранное и использовать его на графике.

Хотите использовать этот скрипт на графике?

Отказ от ответственности