Chande Momentum Oscillator

Chande Momentum Oscillator
See also
Osma Bull flag Uptrend Overbought oversold indicator Bullish divergence Trading channel Bear flag Bearish divergence Dragonfly Doji

Chande Momentum Oscillator(CMO) is an index named after its inventor Dr. Tushar Chande, author of The New Technical Trader and Beyond Technical Analysis (1994, Wiley), has probably done more tinkering with momentum indicators than anyone else. According to the author of the index is it a pure momentum oscillator that plots momentum on a bounded scale. It helps to spot extremes in market momentum, and it has many uses in technical analysis. "It is a variation on the RSI, yet is uniquely different."(Pring J. M. 2014, p.289) It has three characteristics:

1. The calculations are based on data that have not been smoothed. This means that extreme short-term movements are not hidden, so the indicator reaches overbought/oversold extremes more often, but not enough to result in too many signals.
2. The scale is confined within the –100 to +100 range. This means that the zero level becomes the equilibrium point. With the RSI, the 50 level is the equilibrium point, and is not always readily identifiable. With zero as the pivotal point, it is easier to see those periods when momentum is positive and those when it is negative. The zero equilibrium, therefore, makes comparisons between different securities that much easier as well.
3. The formula uses both up and down days in the calculation.

Formula

$CMO=100\cdot \left[{\frac {\left(S_{u}-S_{d}\right)}{\left(S_{u}+S_{d}\right)}}\right]$,

where:

S_u = sum of the (close-to-close) up-day momentum for n days,

S_d = sum of the (close-to-close) down-day momentum for n days.

The CMO ranges from -100 to 100 with default overbought and oversold levels of +50 and -50, representing 3:1 and 1:3 up momentum/down momentum ratios, respectively.

CMO and RSI relationship

The CMO differs from The Relative Strength Index (RSI) in that:

• it has no internal smoothing calculation, making short-lived momentum extremes more apparent(probably the most important difference)
• it includes both up and down momentum in the numerator (the RSI has only up momentum in its numerator). In effect, the CMO is related to the RSI by the following formula:

$CMO=2\cdot (unsmoothedRSI)-100$ "Unlike for the RSI, the calculations for the CMO are based on unsmoothed data—meaning major short-term movements are visible and not concealed. "(Thomann A. 2019, p. 9) "The CMO does exaggerate some of the more minor price fluctuations and registers more extreme zone penetrations than RSI, the usefulness of which will depend on the user's need for a more responsive indicator.(Chande and Kroll suggest smoothing the oscillator after calculation if the trader desires.)"(Etzkorn M. 1997, p. 78)

Advantages of Chande Momentum Oscillator

The Chande Momentum Oscillator (CMO) is a technical indicator developed by Dr. Tushar Chande and is used to measure the strength of price movement. The following are some of the advantages of using CMO:

• CMO is an indicator that can be used to identify and measure the momentum of a security or market.
• CMO is useful in determining if the current trend is strong or weak, and can be used to identify potential entry and exit points.
• CMO is relatively straightforward to interpret, as it is based on the difference between two moving averages.
• CMO is not as prone to false signals as other momentum indicators, as it is based on a longer time period.
• CMO is a great tool for traders who are looking to identify potential turning points in the market.
• CMO can be used in conjunction with other technical indicators for a more comprehensive analysis.

Limitations of Chande Momentum Oscillator

CMO has been found to be a valuable tool for traders in the analysis of stock trends, but like any technical indicator, it has its own set of limitations. These limitations include:

• It works best in a trending market and can be less effective in a sideways or choppy market.
• Since it is a momentum indicator, it does not predict price reversals and can lead to false signals when the market is not trending.
• It is lagging, meaning it's based on past prices and can't predict future movements in the stock.
• It is also prone to whipsaws, where short-term swings in the market will cause it to give false signals.
• CMO can be difficult to interpret, since it is a complex indicator and requires a deep understanding of technical analysis to be used effectively.

Other approaches related to Chande Momentum Oscillator

Other approaches related to Chande Momentum Oscillator include:

• Rate of Change - This indicator compares the current price to the price from a period ago. It is calculated as a percentage change and is used to measure the momentum of a stock.
• Momentum Indicator - This indicator measures the rate of change in the price of a stock over a given period of time. It is calculated as the current price minus the price of the same period from a previous period.
• Relative Strength Index - This indicator compares the magnitude of recent gains to recent losses in order to determine overbought and oversold conditions. It is calculated by dividing the average of recent gains by the average of recent losses.

In summary, Chande Momentum Oscillator is an index invented by Dr. Tushar Chande which is used to measure the momentum of a stock. Other approaches related to Chande Momentum Oscillator include Rate of Change, Momentum Indicator, and Relative Strength Index.

References

• Chande, T. S. and S. Kroll (1994), The New Technical Trader: Boost Your Profitby Plugging into the Latest Indicators, John Wiley & Sons, p. 95
• Etzkorn M. (1997), Trading with Oscillators: Pinpointing Market Extremes -- Theory and Practice, John Wiley & Sons, Canada, pp. 77-78
• Pring J. M. (2014), Technical Analysis Explained, Fifth Edition: The Successful Investor's Guide to Spotting Investment Trends and Turning Points, McGraw Hill Professional, p. 289
• Rockefeller B. (2014), Technical Analysis For Dummies, John Wiley & Sons, Hoboken, p. 235
• Thomann, A. (2019), Appendix to'Is Trading Indicator Performance Robust? Evidence from Semi-Parametric Scenario Building'. Evidence from Semi-Parametric Scenario Building, p. 9

Author: Katarzyna Kraj