TSI CCI Hull Moving Average Trading Strategy

This strategy combines the TSI, CCI indicators and Hull Moving Average to determine and trade trends. TSI and CCI identify price waves while Hull MA confirms trend direction. Profit targets are set when long/short…

Pine ScriptBreakout Mean reversion Trend following EMA CCI

Author: ChaoZhang
Complexity: Intermediate · 95 lines
Parameters: 17
Backtest bar: 3h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

The TSI curve and signal line are calculated. Long signal when curve crosses above line, short on downward crossover. CCI indicates overbought/oversold levels. Price crossing above Hull MA suggests bull market, and below for bear market. Long/short trades are taken when TSI, CCI and Hull MA breakout conditions align. Profit targets are set to exit positions when reached.

Advantages

TSI strongly identifies trend direction
CCI effectively detects overbought/oversold
Hull MA filters false breakouts improving signals
Profit targets allow exiting at peak profitability
Combining multiple indicators improves robustness

Risks

Lag exists in TSI, CCI and other indicators
Hull MA cannot perfectly determine turning points
Exact price reversal timing cannot be accurately determined
Poor profit target setting risks missing profit potential

Risks can be reduced by tuning indicators, optimizing profit algorithms etc.

Enhancements

Test TSI/CCI combinations to improve sensitivity
Consider dynamic/trailing profit targets
Add other indicators to determine reversals
Test across different products to improve robustness

Conclusion

This multiple indicator strategy with profit targeting shows good backtest results. Further refinements like parameter optimization can make it a stable quant trading system.

Parameters

Name	Default	What it controls
v_input_1	50	Long Length
v_input_2	50	Short Length
v_input_3	25	Signal Length
v_input_4_close	0	Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_5	26	Period
v_input_6	100	Upper Line
v_input_7	-100	Lower Line
v_input_8	true	Start Date
v_input_9	true	Start Month
v_input_10	2018	Start Year
v_input_11	true	End Date
v_input_12	7	End Month
v_input_13	9999	End Year
v_input_14	0.5	LongProfitPercent
v_input_15	0.5	ShortProfitPercent
v_input_16_close	0	profit long source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_17_close	0	profit short source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4

Source Pine Script

/*backtest
start: 2023-08-18 00:00:00
end: 2023-09-17 00:00:00
period: 3h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4

strategy(title="TSI CCI Hull", shorttitle="TSICCIHULL", default_qty_type=strategy.percent_of_equity, default_qty_value=100, calc_on_order_fills= false, calc_on_every_tick=true, pyramiding=0, commission_type=strategy.commission.percent, commission_value=0.018)
long = input(title="Long Length", type=input.integer, defval=50)
short = input(title="Short Length", type=input.integer, defval=50)
signal = input(title="Signal Length", type=input.integer, defval=25)
price=input(title="Source",type=input.source,defval=close)
Period=input(26, minval=1)
lineupper = input(title="Upper Line", type=input.integer, defval=100)
linelower = input(title="Lower Line", type=input.integer, defval=-100)
p=price
length= Period
double_smooth(src, long, short) =>
    fist_smooth = ema(src, long)
    ema(fist_smooth, short)
pc = change(price)
double_smoothed_pc = double_smooth(pc, long, short)
double_smoothed_abs_pc = double_smooth(abs(pc), long, short)
tsi_value = 100 * (double_smoothed_pc / double_smoothed_abs_pc)
keh = tsi_value*5 > linelower ? color.red : color.lime
teh = ema(tsi_value*5, signal*5) > lineupper ? color.red : color.lime
meh = ema(tsi_value*5, signal*5) > tsi_value*5 ? color.red : color.lime
i1=plot(tsi_value*5, title="TSI Value", color=color.black, linewidth=1,transp=100)
i2=plot(ema(tsi_value*5, signal*5), title="TSI Signal", color=color.black, linewidth=1,transp=100)
fill(i1,i2,color=meh,transp=85)
plot(cross(tsi_value*5, ema(tsi_value*5, signal*5)) ? tsi_value*5 : na, style=plot.style_circles, color=color.black, linewidth=10)
plot(cross(tsi_value*5, ema(tsi_value*5, signal*5)) ? tsi_value*5 : na, style=plot.style_circles, color=color.white, linewidth=8,transp=0)
plot(cross(tsi_value*5, ema(tsi_value*5, signal*5)) ? tsi_value*5 : na, style=plot.style_circles, color=meh, linewidth=5)
n2ma = 2 * wma(p, round(length / 2))
nma = wma(p, length)
diff = n2ma - nma
sqn = round(sqrt(length))
n1 = wma(diff, sqn)
cci = (p - n1) / (0.015 * dev(p, length))
c = cci > 0 ? color.lime : color.red
c1 = cci > 20 ? color.lime : color.silver
c2 = cci < -20 ? color.red : color.silver
cc=plot(cci, color=c, title="CCI Line", linewidth=2)
cc2=plot(cci[1], color=color.gray, linewidth=1,transp=100)
fill(cc,cc2,color=c,transp=85)
plot(cross(20, cci) ? 20 : na, style=plot.style_cross,title="CCI cross UP",  color=c1, linewidth=2,transp=100,offset=-2)
plot(cross(-20, cci) ? -20 : na, style=plot.style_cross,title="CCI cross down",  color=c2, linewidth=2,transp=100,offset=-2)

TSI1=ema(tsi_value*5, signal*5)
TSI2=ema(tsi_value*5, signal*5)[2]

hullma_smoothed = wma(2*wma(n1, Period/2)-wma(n1, Period), round(sqrt(Period)))
//plot(hullma_smoothed*200)

// Make input options that configure backtest date range
startDate = input(title="Start Date", type=input.integer,
     defval=1, minval=1, maxval=31)
startMonth = input(title="Start Month", type=input.integer,
     defval=1, minval=1, maxval=12)
startYear = input(title="Start Year", type=input.integer,
     defval=2018, minval=1800, maxval=2100)

endDate = input(title="End Date", type=input.integer,
     defval=1, minval=1, maxval=31)
endMonth = input(title="End Month", type=input.integer,
     defval=7, minval=1, maxval=12)
endYear = input(title="End Year", type=input.integer,
     defval=9999, minval=1800, maxval=2100)
     
// Look if the close time of the current bar
// falls inside the date range
inDateRange = (time >= timestamp(syminfo.timezone, startYear,
         startMonth, startDate, 0, 0)) and
     (time < timestamp(syminfo.timezone, endYear, endMonth, endDate, 0, 0))
     
LongProfitPercent=input(0.5)
ShortProfitPercent=input(0.5)
LP=(LongProfitPercent/100)+1
SP=(ShortProfitPercent/100)+1

LongProfitSource=input(title="profit long source",type=input.source,defval=close)
ShortProfitSource=input(title="profit short source",type=input.source,defval=close)

longCondition = TSI1>TSI2 and hullma_smoothed<price and cci>0
shortCondition = TSI1<TSI2 and hullma_smoothed>price and cci<0

if (longCondition and cci>cci[1] and cci > 0 and n1>n1[1] and inDateRange)
    strategy.entry("buy", strategy.long)
strategy.close("buy", when = shortCondition and cci<cci[1] and cci < 0 and n1<n1[1] or LongProfitSource>strategy.position_avg_price*LP and inDateRange)
if (shortCondition and cci<cci[1] and cci < 0 and n1<n1[1] and inDateRange)
    strategy.entry("sell", strategy.short)
strategy.close("sell", when = longCondition and cci>cci[1] and cci > 0 and n1>n1[1] or ShortProfitSource<strategy.position_avg_price/SP and inDateRange)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-09-18. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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