Period RSI

Reverse transform FISHER

The purpose of technical indicators to help with your timing decisions on buying or selling. We hope that the signals are clear and unambiguous. However, more of your decision to pull the trigger is associated with crossing your fingers. Even if you put just a few trades you know exercise.

In this article I will show you a way to make your vibrator-type indicators make clear black-and-white indicating the time to buy or sell. I will do this by using the inverse Fisher transformation to change the probability distribution function (PDF) of your indicators. In the past I note that the PDF price and indicators do not Gaussian, or normal, probability distribution. A Gaussian PDF format is the famous bell-shaped curve, where long "tails" which means wide deviations from the mean occur with relatively low probability. Fisher transformation can be applied to almost all data normalized to make the resulting PDF nearly Gaussian, in that the turning points are sharply peaked and easy to identify. Fisher transformation is defined by the equation

1) Whereas the Fisher transformation is expansive, the inverse transformation is compressive Fischer. Reverse Fisher Transform is found by solving equation 1 for x in terms of Y. Reverse Fisher transformation is:


The transfer response Inverse Fisher transformation is shown in Figure 1. If the input falls between -0.5 and 0.5, the output is almost the same as the input. For larger absolute values ​​(say, larger than

2), the output is compressed to be no greater than unity. The result of using the inverse transformation of Fisher is that the output has a very high probability to be either 1 or -1. This bipolar probability distribution rights Inverse Fisher transformation ideal for generating an indicator that gives clear buy and sell signals.


One of the popular technical indicators is the Stochastic RSI. This indicator starts by taking the cost of RSI. Then, the Stochastic RSI have been adopted to limit the output to be between 0 and 100. Translation and scaling, this is mathematically the same as varying between -1 and +1.

Now that you know the Inverse Fisher transformation, there is no reason to bludgeon the RSI with a blunt instrument as Stochastic. Instead of raising the observation length that is guaranteed to drive the Stochastic of saturation, you can finesse indicator PDF using the inverse Fisher transformation. EasyLanguage code to do this is given in Figure 2. 5-bar RSI ranges from a minimum 0 and maximum 100th 5-bar length of the RSI was selected to provide good thing when applied to many price series. Period RSI is certainly available for optimization. With the seizure of 50, the RSI indicator is available in a range from -50 to +50. Then, multiplying with 0.1 reduces the range to be between -5 and +5 to Value1. This is just a kind of maximum uplift responsible for Inverse Fisher transformation. I counted employs 9 bar moving average to calculate Value2 Value1 to align and eventually eliminate some false trading signals. There is no magic in this average. It could have less bars have less lag or it may be an exponential moving average. Its function is just to be annoying. The transformation is calculated as IFish variable and then plotted. The code and plots out reference lines of -0.5 and 0.5.


Transformed RSI is applied to the Exchange Traded Fund (ETF) QQQ in Figure 3. I show the inverse Fisher transformation using ETFs, because they can buy or sell a long short with equal facility - just like the future. The trading rules are simple. Buy when the indicator crosses over -0.5 or spends more than 0,5 if not previously crossed -0.5 and short sell when indicators crosses crosses below 0.5 or below -0.5 if not previously crossed below 0 , 5. You can see that the trading signals are not only clear and unambiguous, but they are also profitable.

Using Inverse Fisher transformation is not limited to just change the RSI PDF format. It can be applied to almost every type of vibrator indicator. For example, my simplified model of the market consists of a trend component and a cycle component. The cycle component can be isolated by filtering. I call it Cyber ​​cycle. Like RSI, Cyber ​​cycle oscillator type indicator. Unlike the RSI, Cyber ​​cycle is cyclical swings with variable amplitudes. Providing the cyclical swings of the cycle Cyber ​​enough to allow the amplitude of the inverse transformation of Fisher to invoke its compression, an excellent indicator can result.


Cyber ​​Clean Cycle indicator Spy ETF is shown in the first subgraph in Figure 5. Variable amplitude of cyclical swings are evident. One can trade the use of Cyber ​​Cycle crossing indicator and the indicator for a delayed tape. Transformed result is shown in the second subgraph in Figure 5. As with RSI Transformed, buy and sell signals are clear and unambiguous. Reverse Fisher transformation can be applied with equal success on almost all oscillator type indicators.


Reverse Fisher transformation has even wider potential applications. By transforming the waves is limited to range between -1 and +1, the total energy in the wave is limited. I am particularly intrigued that convergence is guaranteed in some linear predictive algorithms when wave energy is limited. So research can reveal many exciting new results for traders.

More importantly, for the present, I have shown how using the inverse transformation of Fisher may have greater confidence (and maybe uncross your fingers) when you place your trades.