Trend Following Strategy Using KST Indicator
This article explains in detail a quantitative trend following strategy using the KST indicator. It generates trading signals by calculating the crossover between the KST line and signal line.
I. Strategy Logic
The main steps for signal generation are:
Calculate values of multiple ROC indicators with different periods.
Apply moving averages to the ROC values separately and take the sum to derive the KST line.
Further smooth the KST line using moving average to get the signal line.
A buy signal is generated when the KST line crosses above the signal line, and vice versa for sell signals.
Appropriate position sizing can be selected.
By taking the sum of multiple ROC values, the KST line reflects both short-term and long-term price trends. Its crossover with the signal line can determine trend direction.
II. Advantages of the Strategy
The biggest advantage is the comprehensive indicator calculation, which incorporates trend information across timeframes.
Another advantage is the simple and intuitive indicator usage with a clear signal line.
Lastly, adjustable position sizing helps control overall risk exposure.
III. Potential Weaknesses
However, some issues exist:
Firstly, the indicator itself has some lag in reacting to price changes.
Secondly, reliance on just the KST makes it susceptible to reversals.
Also, extensive optimization is required to avoid overfitting.
IV. Summary
In summary, this article has explained a quantitative trend following strategy using KST crossover signals. It reflects price trends through the indicator for trade signals, but requires managing indicator lag and proper parameter tuning. Overall it provides a simple trend tracking approach.
/*backtest
start: 2023-08-15 00:00:00
end: 2023-09-14 00:00:00
period: 3h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=5
// strategy(title="KST Alert", shorttitle="KST Alert", format=format.price, precision=4)
roclen1 = input.int(10, minval=1, title = "ROC Length #1")
roclen2 = input.int(15, minval=1, title = "ROC Length #2")
roclen3 = input.int(20, minval=1, title = "ROC Length #3")
roclen4 = input.int(30, minval=1, title = "ROC Length #4")
smalen1 = input.int(10, minval=1, title = "SMA Length #1")
smalen2 = input.int(10, minval=1, title = "SMA Length #2")
smalen3 = input.int(10, minval=1, title = "SMA Length #3")
smalen4 = input.int(15, minval=1, title = "SMA Length #4")
siglen = input.int(9, minval=1, title = "Signal Line Length")
smaroc(roclen, smalen) => ta.sma(ta.roc(close, roclen), smalen)
kst = smaroc(roclen1, smalen1) + 2 * smaroc(roclen2, smalen2) + 3 * smaroc(roclen3, smalen3) + 4 * smaroc(roclen4, smalen4)
sig = ta.sma(kst, siglen)
plot(kst, color=#009688, title="KST")
plot(sig, color=#F44336, title="Signal")
hline(0, title="Zero", color = #787B86)
eL1=ta.crossover(kst,sig)
eS1=ta.crossunder(kst,sig)
ch = 0
t = year(time('D'))
ch := ta.change(t) != 0 ? 1 : 0
T1 = time(timeframe.period, "0915-1520")
session_open = na(t) ? false : true
newDay = ta.change(time("15m")) != 0
strategy.entry("Long1", strategy.long, when = eL1)
strategy.entry("Short1", strategy.short, when = eS1)