Stochastic Momentum Index

Commonly abbreviated to SMI, Stochastic Momentum Index is advancement in the Stochastic Oscillator. Stochastic Oscillator is primarily used to calculate the distance between the Current Close and Recent High/Low Range for n-period. Stochastic Momentum Index shows the distance of Current Close relative to the center of High/Low Range. William Blau originated SMI in January 1993 publication of “Technical Analysis of Stocks & Commodities” Magazine. SMI is reasonably less unpredictable than Stochastic Oscillator over a single period. SMI normally ranges in between +100 and -100. Stochastic Momentum Oscillator is used in conjunction with the Tushar Chande Momentum Oscillator.

Study Type: Stand-alone

Description

In SMI, When Current Close is greater than the Midpoint of High/Low Range, the outcome is above zero. Similarly, when the Current Close is less than the Midpoint of High/Low Range, than SMI is below zero. The output of SMI is interpreted as Short Term Extreme Position i.e. Overbought or Oversold Market. The basic difference between SMI and previous Stochastic Indicators is that SMI uses a wide range that can vary from a negative value of -100 to a positive value of +100. In order to smooth the results of SMI, a Moving Average is determined, commonly termed as Stochastic %D. Traders commonly use SMI Indicator to predict the trend prevailing in the market i.e. either bullish or bearish. Traders believe that a market is bearish if its SMI Output is below 40. On the other hand, an SMI Output of above 40 for a particular market conceives a bullish trend.

The output of SMI varies between -100 and +100. In order to interpret the outcome of SMI, traders have developed specific trade points. Like, when SMI rises above the value of +40, a sell signal is indicated. Similarly, if SMI falls below -40, a Purchase signal is indicated. Another common trading sign is that, when SMI passes moving average from below, a purchase signal is generated. Similarly, when SMI falls below Moving Average, a sell signal is generated. The following chart shows the bullish entry trade signal generated by the Stochastic Momentum Index.

Trading cannot be based on short term extreme positions only. There must be a mechanism to check the trendiness of market. R-Squared Indicator is commonly used by traders to determine the trendiness of market. If the outcome of Indicator like R-Squared is a non-trending market then outcome of SMI is reliable and gives effective results. Chande Momentum Oscillator is also frequently used in place of R-Squared Indicator to determine Trendiness. Contrarily, if a trending market is predicted by Trendiness Indicators then traders can use Oscillators to determine the direction of trend. In this way, traders can base their transactions in the direction of market trend predicted by Oscillator.

William Blau found 1-day SMI with large smoothing periods to be more sensitive to the current close rather than the high and low of the day. Having high sensitivity to Closing Value makes SMI an ideal Indicator for Trend Identification. As explained earlier, there isn’t much difference between the interpretation of Stochastic Momentum Index and Stochastic Oscillator. Short term extreme positions are indicated by outcome of SMI. If SMI rises above +40, an overbought condition holds. Traders prefer not to trade in the direction of trendiness anymore. Similarly, when SMI falls below -40, an oversold condition holds. Even before trend reversal, traders start taking their positions to take benefit of the oversold condition. Traders anticipate a significant trend reversal at Extreme Positions. Divergences must be taken into account. A divergence can indicate end of a prevailing trend or signal a false trend. %K cutting %D can also signal crossovers.

Advantages of Stochastic Momentum Index

  1. Majority of technicians believe that SMI is less unpredictable than Stochastic Oscillator Outcome for the same period.
  2. SMI indicates an advance indication of possible shifts in momentum (Price) close to critical points. This allows traders to time their moves in the market.
  3. Entry and Exit with maximum Profits is no longer an issue due to the predictability of Stochastic Momentum Index.

Disadvantages of Stochastic Momentum Index

  1. Stochastic Momentum Index is unable to predict trendiness. This makes a lot of confusion in the mind of traders. Traders often get trapped by seeing the Extreme Positions indicated by SMI.
  2. Traders must use Trendiness indicators like CMO (Chande Momentum Oscillator) or R-Squared Indicator to predict future trends along with SMI which only predicts short term extreme positions.
  3. SMI cannot generate trade signals in trending markets. Oscillators have to be used to generate direction of trend. Traders can then make decisions on the basis of direction of trend in the future.

 

Formula

In order to calculate SMI, start from “N”. Lets suppose N=10. After choosing a Period, determine the Center of High and Low Range during the period. In order to do so, use the following formula:

Lets suppose “C” is the center of High and Low, then:

C = (High MAX + Low MIN) / 2

Where

High MAX = The Highest Figure in the Range.
Low MIN = The Lowest Figure in the Range.

After calculating a center point of the range, subtract distance of Current Close from the Center of the Range.

H = CC TODAY – C

Where

CC TODAY = Current Closing Price.
C = Center of High/Low Range.

In order to smooth the output of “H”, use a 3-period Exponential Moving Average. Following will be the procedure of smoothing “H”.

HS1 = (H) * (3) * Exponential Moving Average
HS2 = (HS1) * (3) * Exponential Moving Average

After smoothing “H”, smooth the difference of High and Low Price during the period using same 3-Period Exponential Moving Average. Divide the results of Second Smoothing by 2:

DHL1 = (High MAX – Low MIN) * (3) * Exponential Moving Average 
DHL2 = (High MAX – Low MIN) * (3) * Exponential Moving Average / 2

In order to Calculate SMI, divide HS2 by DHL2. Multiplying the output by 100 will provide results in the form of a percentage. 

SMI TODAY = (HS2 / DHL2) * 100

Parameters

  • Period 1: (10)
  • Period 2: (3)
  • First Level: (-40)
  • Second Level (40)

 

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