ChaoZhang
Overview
This strategy uses the Chande Momentum Oscillator (CMO) to determine overbought and oversold levels for trading signals. The absolute CMO values over 3 periods are averaged to smooth the oscillator for identifying extremes. A typical mean reversion oscillator trading strategy.
Strategy Logic
The key logic includes:
- Calculating absolute CMO values over 3 different periods
- Taking the average of 3-period absolute CMO values
- Going short when average value exceeds upper threshold
- Going long when average value drops below lower threshold
- Closing positions when CMO returns to normal range
The CMO reflects the momentum of price changes. High absolute values represent price divergence entering overbought/oversold zones. The strategy utilizes this characteristic of CMO, using a multi-period average to smooth the curve for identifying extremes.
Advantages
- Uses CMO to identify overbought/oversold regions
- Multi-period averaging smooths curve and avoids false signals
- Sound theoretical basis for overbought/oversold detection
- Customizable parameter thresholds to adapt
- Simple mean reversion implementation
Risks and Mitigations
- Potential for false CMO signals
- Requires ongoing threshold optimization
- Sustained extremes during trends can cause losses
Mitigations:
- Adding trend filter to avoid counter-trend trades
- Parameter optimization for better CMO sensitivity
- Using stops to limit losses
Enhancement Opportunities
The strategy can be enhanced through:
- Volume confirmation to avoid false breakouts
- Incorporating trailing stops for better risk management
- Auto-optimization of parameters via machine learning
- Volatility-based position sizing
- Combining with other strategies to diversify and improve returns
Conclusion
This strategy uses CMO to identify overbought/oversold for mean reversion trading. Multi-period averaging helps avoid false signals. CMO itself has sound theoretical basis for gauging divergence. Enhancements through better parameters, stops, and filters can make it a stable oscillator trading strategy.
/*backtest
start: 2023-09-11 00:00:00
end: 2023-09-14 07:00:00
period: 30m
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=2
////////////////////////////////////////////////7////////////
// Copyright by HPotter v1.0 21/02/2017
// This indicator plots the absolute value of CMO averaged over three
// different lengths. This indicator plots a classical-looking oscillator,
// which is really an averaged value based on three different periods.
//
// You can change long to short in the Input Settings
// Please, use it only for learning or paper trading. Do not for real trading.
////////////////////////////////////////////////////////////
strategy(title="CMOabsav", shorttitle="CMOabsav")
Length1 = input(5, minval=1)
Length2 = input(10, minval=1)
Length3 = input(20, minval=1)
TopBand = input(58, minval=1)
LowBand = input(5, minval=0)
reverse = input(false, title="Trade reverse")
hline(0, color=green, linestyle=hline.style_dashed)
hline(TopBand, color=purple, linestyle=hline.style_solid)
hline(LowBand, color=red, linestyle=hline.style_solid)
xMom = close - close[1]
xMomabs = abs(close - close[1])
nSum1 = sum(xMom, Length1)
nSumAbs1 = sum(xMomabs, Length1)
nSum2 = sum(xMom, Length2)
nSumAbs2 = sum(xMomabs, Length2)
nSum3 = sum(xMom, Length3)
nSumAbs3 = sum(xMomabs, Length3)
nRes = abs(100 * (nSum1 / nSumAbs1 + nSum2 / nSumAbs2 + nSum3 / nSumAbs3 ) / 3)
pos = iff(nRes > TopBand, 1,
iff(nRes < LowBand, -1, nz(pos[1], 0)))
possig = iff(reverse and pos == 1, -1,
iff(reverse and pos == -1, 1, pos))
if (possig == 1)
strategy.entry("Long", strategy.long)
if (possig == -1)
strategy.entry("Short", strategy.short)
barcolor(possig == -1 ? red: possig == 1 ? green : blue )
plot(nRes, color=blue, title="CMOabsav")