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- 2018.02.12 17:06
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The Stochastic Momentum Index (SMI) was developed by William Blau and was introduced in the January 1993 issue of Technical Analysis of Stocks & Commodities magazine.
It incorporates an interesting twist on the popular Stochastic Oscillator. While the Stochastic Oscillator provides you with a value showing the distance the current close is relative to the recent x-period high/low range, the SMI shows you where the close is relative to the midpoint of the recent x-period high/low range.
This version is doing the calculation in the same way as the original Stochastic Momentum Index, except in one very important part: instead of using EMA (Exponential Moving Average) for calculation, it is using T3. That produces a smoother result without adding any lag.
Stochastic Momentum Index
The Stochastic Momentum Index (SMI) was developed by William Blau and was introduced in the January 1993 issue of Technical Analysis of Stocks & Commodities magazine. It incorporates an interesting twist on the popular Stochastic Oscillator. While the Stochastic Oscillator provides you with a value showing the distance the current close is relative to the recent x-period high/low range, the SMI shows you where the close is relative to the midpoint of the recent x-period high/low range.
Directional Efficiency Ratio
The Efficiency Ratio (ER) was first presented by Perry Kaufman in his 1995 book "Smarter Trading". It is calculated by dividing the price change over a period by the absolute sum of the price movements that occurred to achieve that change. The resulting ratio ranges between 0 and 1 with higher values representing a more efficient or trending market.
Stochastic Extended
This version of Stochastic Oscillator allows you to use any of the 4 basic types of averages (default is SMA, but you can use EMA, SMMA or LWMA too) - some are "faster" then the default version (like EMA and LWMA versions) and SMMA is a bit "slower" but this way you can fine tune the "speed" to signals ratio.
Fisher RVI
This indicator has an addition of Fisher Transform to the RVI. The Fisher Transform enables traders to create a nearly Gaussian probability density function by normalizing prices. In essence, the transformation makes peak swings relatively rare events and unambiguously identifies price reversals on a chart. The technical indicator is commonly used by traders looking for extremely timely signals rather than lagging indicators.