KST EMA Momentum Trend Following Strategy

Pine ScriptMomentum Trend following Breakout RSI MACD EMA SMA ATR Volume

Author: ChaoZhang
Complexity: Intermediate · 78 lines
Parameters: 14
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

The core idea of this strategy is to combine the KST indicator and EMA lines to identify and follow trends. It generates buy signals when the KST indicator crosses above 0 and closes above the EMA line, and sell signals when it crosses below 0 and closes below the EMA line. This simple and practical strategy can automatically track trends and is suitable for medium to long term holdings.

Strategy Logic

Calculate the KST indicator: Compute the ROC of 10, 15, 20 and 30 periods, take a weighted sum, and smooth it with a 9-period SMA to derive the KST indicator.
Calculate the EMA line: Compute a 50-period EMA line.
Generate buy signal: When the fast KST line crosses above the slow KST line (golden cross) and is below 0, while the close is above the EMA line, a buy signal is triggered.
Generate sell signal: When the fast KST line crosses below the slow KST line (dead cross) and is above 0, while the close is below the EMA line, a sell signal is triggered.
Set trailing stop loss: The stop loss tracks 1% of account value to realize automatic stop loss.

Advantages

KST identifies trend changes, EMA confirms direction. Combining both accurately detects entry timing.
Using fast/slow crossovers and 0-line avoids unnecessary trades.
EMA as support/resistance further filters fake signals. Only enter on EMA breakouts.
Auto trailing stop loss controls risk and allows profits to run.
Simple parameters make implementation and optimization easy.

Risks

KST has lag in detecting trend changes, may miss some chances. Can shorten periods or optimize weighting.
EMA has lag around trend reversals. Other indicators or MA combos may work better.
Stop loss too wide increases losses, too tight gets stopped out by spikes. Careful testing needed to optimize.
Frequent signals may increase transaction costs. Can tighten entry rules to reduce trades.

Optimization Directions

Optimize KST periods for sensitivity to specific instruments.
Test other moving averages like MA, WMA to see which combines best with KST.
Experiment dynamic stops based on volatility metrics like ATR.
Add filters like volume spikes to avoid traps.
Consider combining with indicators like RSI, MACD for more dimensions.
Test parameters across instruments to optimize for each.

Conclusion

This strategy has clear, reliable logic that is easy to implement. KST identifies trend turns, EMA filters further, and stops control risk. It automatically tracks medium to long term trends. Reasonable parameters provide large optimization space. Users can tweak for different instruments. Applicable for beginners to learn and professionals to build on. With further optimization it shows promise as a robust trend following system.

Parameters

Name	Default	What it controls
v_input_1	10	ROC Length #1
v_input_2	15	ROC Length #2
v_input_3	20	ROC Length #3
v_input_4	30	ROC Length #4
v_input_5	10	SMA Length #1
v_input_6	10	SMA Length #2
v_input_7	10	SMA Length #3
v_input_8	15	SMA Length #4
v_input_9	9	Signal Line Length
v_input_10	50	Length EMA
v_input_11_close	0	Source EMA: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_12	false	Offset
v_input_13	true	Trail Long Loss (%)
v_input_14	true	Trail Short Loss (%)

Source Pine Script

/*backtest
start: 2022-10-31 00:00:00
end: 2023-11-06 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
strategy(title="Know Sure Thing and EMA Strategy by JLX", shorttitle="KST EMA JLX", format=format.price, precision=4, initial_capital = 1000, default_qty_type=strategy.percent_of_equity, default_qty_value = 100)
roclen1 = input(10, minval=1, title = "ROC Length #1")
roclen2 = input(15, minval=1, title = "ROC Length #2")
roclen3 = input(20, minval=1, title = "ROC Length #3")
roclen4 = input(30, minval=1, title = "ROC Length #4")
smalen1 = input(10, minval=1, title = "SMA Length #1")
smalen2 = input(10, minval=1, title = "SMA Length #2")
smalen3 = input(10, minval=1, title = "SMA Length #3")
smalen4 = input(15, minval=1, title = "SMA Length #4")
siglen = input(9, minval=1, title = "Signal Line Length")
smaroc(roclen, smalen) => sma(roc(close, roclen), smalen)
kst = smaroc(roclen1, smalen1) + 2 * smaroc(roclen2, smalen2) + 3 * smaroc(roclen3, smalen3) + 4 * smaroc(roclen4, smalen4)
sig = sma(kst, siglen)
plot(kst, color=color.green, title="KST")
plot(sig, color=color.red, title="Signal")
hline(0, title="Zero")

len = input(50, minval=1, title="Length EMA")
src = input(close, title="Source EMA")
offset = input(title="Offset", type=input.integer, defval=0, minval=-500, maxval=500)
fastEMA = ema(src, len)

delta = kst - sig

buySignal = crossover(delta, 0) and kst < 0 and close > fastEMA
sellSignal = crossunder(delta, 0) and kst > 0 and close < fastEMA

longTrailPerc = input(title="Trail Long Loss (%)", type=input.float, minval=0.0, step=0.1, defval=1) * 0.01
shortTrailPerc = input(title="Trail Short Loss (%)",type=input.float, minval=0.0, step=0.1, defval=1) * 0.01

// STEP 2:
// Determine trail stop loss prices
longStopPrice = 0.0, shortStopPrice = 0.0

longStopPrice := if (strategy.position_size > 0)
    stopValue = close * (1 - longTrailPerc)
    max(stopValue, longStopPrice[1])
else
    0
shortStopPrice := if (strategy.position_size < 0)
    stopValue = close * (1 + shortTrailPerc)
    min(stopValue, shortStopPrice[1])
else
    999999

// Submit entry orders
if (buySignal)
    strategy.entry(id="EL", long=true)

if (sellSignal)
    strategy.entry(id="ES", long=false)

// STEP 3:
// Submit exit orders for trail stop loss price
if (strategy.position_size > 0)
    strategy.exit(id="XL TRL STP", stop=longStopPrice)

if (strategy.position_size < 0)
    strategy.exit(id="XS TRL STP", stop=shortStopPrice)



alertcondition(crossover(delta, 0) and kst < 0 and close > fastEMA,'Long alert', 'You should buy')

alertcondition(crossunder(delta, 0) and kst > 0 and close < fastEMA, 'Short alert', 'You should sell')

Published by ChaoZhang on the FMZ strategy square · last modified 2023-11-07. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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