[blackcat] L3 KAMA Trend Trading System
Level: 3
Background
Kaufman’s Adaptive Moving Average ( KAMA ) was developed by American quantitative financial theorist Perry J. Kaufman in 1998.
Function
This is an improved KAMA trading system with my customized algorithm.You can use KAMA like any other trend-following indicator, such as a moving average. You can look for price crosses, directional changes and filtered signals. First, a cross above or below KAMA indicates directional changes in prices. As with any moving average, a simple crossover system will generate lots of signals and lots of whipsaws. Second, You can use the direction of KAMA to define the overall trend for a security. This may require a parameter adjustment to smooth the indicator further. You can change the fastline and slowline parameters to smooth KAMA and look for directional changes. The trend is down as long as KAMA is falling and forging lower lows. The trend is up as long as KAMA is rising and forging higher highs. Finally, You can combine signals and techniques. You can use a longer-term KAMA to define the bigger trend and a shorter-term KAMA for trading signals.
I have included in the indicator an input named "EnableSmooth" that allows you to determine if the KAMA line should be smoothed or not. A "True" as the input value smoothes the calculation. An "False" simply plots the raw KAMA line. When market volatility is low, Kaufman’s Adaptive Moving Average remains near the current market price, but when volatility increases, it will lag behind. What the KAMA indicator aims to do is filter out “market noise” – insignificant, temporary surges in price action. One of the primary weaknesses of traditional moving averages is that when used for trading signals, they tend to generate many false signals. The KAMA indicator seeks to lessen this tendency – generate fewer false signals – by not responding to short-term, insignificant price movements. Traders generally use the moving average indicator to identify market trends and reversals.
Remarks
Feedbacks are appreciated.
Background
Kaufman’s Adaptive Moving Average ( KAMA ) was developed by American quantitative financial theorist Perry J. Kaufman in 1998.
Function
This is an improved KAMA trading system with my customized algorithm.You can use KAMA like any other trend-following indicator, such as a moving average. You can look for price crosses, directional changes and filtered signals. First, a cross above or below KAMA indicates directional changes in prices. As with any moving average, a simple crossover system will generate lots of signals and lots of whipsaws. Second, You can use the direction of KAMA to define the overall trend for a security. This may require a parameter adjustment to smooth the indicator further. You can change the fastline and slowline parameters to smooth KAMA and look for directional changes. The trend is down as long as KAMA is falling and forging lower lows. The trend is up as long as KAMA is rising and forging higher highs. Finally, You can combine signals and techniques. You can use a longer-term KAMA to define the bigger trend and a shorter-term KAMA for trading signals.
I have included in the indicator an input named "EnableSmooth" that allows you to determine if the KAMA line should be smoothed or not. A "True" as the input value smoothes the calculation. An "False" simply plots the raw KAMA line. When market volatility is low, Kaufman’s Adaptive Moving Average remains near the current market price, but when volatility increases, it will lag behind. What the KAMA indicator aims to do is filter out “market noise” – insignificant, temporary surges in price action. One of the primary weaknesses of traditional moving averages is that when used for trading signals, they tend to generate many false signals. The KAMA indicator seeks to lessen this tendency – generate fewer false signals – by not responding to short-term, insignificant price movements. Traders generally use the moving average indicator to identify market trends and reversals.
Remarks
Feedbacks are appreciated.
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