Trading Strategy Based on Hull Moving Average and WT Cross

This strategy mainly combines the Hull Moving Average and WT cross signals to leverage the advantages of each indicator for more accurate trend judgment and entry timing.

Pine ScriptTrend following EMA SMA

Author: ChaoZhang
Complexity: Intermediate · 143 lines
Parameters: 22
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy mainly combines the Hull Moving Average and WT cross signals to leverage the advantages of each indicator for more accurate trend judgment and entry timing.

Strategy Logic

The strategy consists of the Hull Moving Average and WT cross signals.

The Hull Moving Average part calculates short-term and long-term Hull MAs and fills color to determine the trend direction. The formulas are:

Short Hull MA = WMA(2*WMA(n/2) - WMA(n), sqrt(n))

Long Hull MA = WMA(WMA(n/3)*3 - WMA(n/2), n/2)

Where WMA is the Weighted Moving Average. When the short MA crosses over the long MA, it is a bullish signal, otherwise a bearish signal.

The WT part calculates the WT lines and observes their crossings to determine entries. The formulas are:

TCI = (Close - EMA(Close,n1)) / (k * STD(Close - EMA(Close,n1),n1))

WT1 = EMA(TCI,n2)

WT2 = SMA(WT1,m)

Where TCI is the Trend Composite Index, reflecting the deviation of price from the EMA; WT1 is the EMA of TCI, WT2 is the SMA of WT1, m is usually 4. The crossing of WT1 over WT2 indicates a bullish signal, while the crossing of WT1 under WT2 indicates a bearish signal.

By combining the Hull MA trend judgment and the WT crossing signals, we can enter the market in the right direction.

Advantage Analysis

The advantages of this strategy are:

Hull MA captures price changes faster by modifying the calculation, and filters out market noise effectively for reliable trend judgment.
WT uses the price fluctuation within the channel to capture turning points quickly and generate relatively accurate trading signals.
The combination considers both trend and crossing for better risk control when trend aligns.
The Hull MA and WT parameters are customizable for adjustment and optimization based on symbol characteristics and trading preferences.
Hull MA and WT signals can be used alone or together for both trend following and crossing validation.
Stop loss and take profit can be set to effectively control single trade risks.

Risk Analysis

The main risks of this strategy are:

Both Hull MA and WT smooth out prices to some extent, which may cause lagging entry signals.
WT may generate false bullish/bearish divergence signals without a clear trend.
Inappropriate parameter settings may impact trading performance and require ongoing optimization.
Stop loss may be triggered frequently during trend consolidations, causing some loss.

The risks can be addressed and optimized as follows:

Adjust Hull MA and WT parameters to find the optimal balance. Other indicators may also be tested with Hull MA.
Add trend validation mechanisms to avoid false WT signals without a confirmed trend.
Optimize parameters through backtesting and demo trading, and set reasonable stop loss ranges.
Reduce position sizes or stop trading when trend is unclear.

Optimization Directions

The strategy can be further optimized from the following aspects:

Test different moving averages combined with WT, to find better balance, e.g. KAMA, TEMA etc.
Add other indicators such as oscillators, Bollinger Bands to improve decision accuracy.
Optimize parameters through backtesting and demo trading. Build parameter optimization programs for fast tuning.
Optimize stop loss strategies e.g. trailing stop, volatility-based stop, moving from near to far etc., to reduce unwanted triggering.
Optimize position sizing strategies, reduce sizes and frequencies in unclear trends to lower risks.
Introduce machine learning and other advanced techniques for smarter trading decisions and adaptive parameters.

Summary

This strategy combines the Hull MA smoothing and WT crossing strengths for both trend judgment and validation. Trading with confirmed direction helps control risks. Further improvements can be made on parameter optimization, stop loss strategies, position sizing etc. Integrating other indicators and intelligent techniques are also future optimization directions. Overall, this is a practical trend following strategy with simplicity, reliability and ease of optimization.

Parameters

Name	Default	What it controls
v_input_1	false	───────── SP/TP SETTINGS ─────────
v_input_2	true	Stop Loss On/Off?
v_input_float_1	5	Stop Loss
v_input_3	true	Take Profit On/Off?
v_input_float_2	10	Take Profit
v_input_4	false	──────── WT CROSS SETTINGS ────────
v_input_5	true	WT Cross On/Off?
v_input_6	false	Change WT Cross Method ( If WT Cross ON )
v_input_7	10	Channel Length
v_input_8	21	Average Length
v_input_9	false	──────── HULLMA SETTINGS ────────
v_input_10_hl2	0	Source: hl2 \| high \| low \| open \| close \| hlc3 \| hlcc4 \| ohlc4
v_input_11	24	Lookback
v_input_12	10000	Gain
v_input_13	true	Use Kahlman
v_input_14	false	───────── DATE SETTINGS ─────────
v_input_int_1	true	From Month
v_input_int_2	true	From Day
v_input_int_3	999	From Year
v_input_int_4	true	To Month
v_input_int_5	true	To Day
v_input_int_6	9999	To Year

Source Pine Script

/*backtest
start: 2023-08-26 00:00:00
end: 2023-09-25 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// WT CROSS @author [© LazyBear]
// © pigsq
// @version=5

strategy("Kahlman HullMA / WT Cross Strategy", overlay=true, default_qty_type=strategy.percent_of_equity, default_qty_value=100, initial_capital=100)

_1 = input(false, '───────── SP/TP SETTINGS ─────────')

stoploss1 = input(title='Stop Loss On/Off?', defval=true)
stoploss = input.float(5, "Stop Loss", minval = 1, step = 1)/100
takeprofit1 = input(title='Take Profit On/Off?', defval=true)
takeprofit = input.float(10, "Take Profit", minval = 1, step = 1)/100

_2 = input(false, '──────── WT CROSS SETTINGS ────────')

wtcross = input(title='WT Cross On/Off?', defval=true)
wtcross2 = input(title='Change WT Cross Method ( If WT Cross ON )', defval=false)

/// WT CROSS ///

n1 = input(10, 'Channel Length')
n2 = input(21, 'Average Length')

ap = hlc3
esa = ta.ema(ap, n1)
r = ta.ema(math.abs(ap - esa), n1)
ci = (ap - esa) / (0.015 * r)
tci = ta.ema(ci, n2)

wt1 = tci
wt2 = ta.sma(wt1, 4)

/// WT CROSS ///

/// HULL TREND WITH KAHLMAN ///

_3 = input(false, '──────── HULLMA SETTINGS ────────')

srchull = input(hl2, 'Source')
lengthhull = input(24, 'Lookback')
gain = input(10000, 'Gain')
kh = input(true, 'Use Kahlman')

hma(_srchull, _lengthhull) =>
    ta.wma((2 * ta.wma(_srchull, _lengthhull / 2)) - ta.wma(_srchull, _lengthhull), math.round(math.sqrt(_lengthhull)))

hma3(_srchull, _lengthhull) =>
    p = lengthhull / 2
    ta.wma(ta.wma(close, p / 3) * 3 - ta.wma(close, p / 2) - ta.wma(close, p), p)

kahlman(x, g) =>
    kf = 0.0
    dk = x - nz(kf[1], x)
    smooth = nz(kf[1], x) + dk * math.sqrt(g / 10000 * 2)
    velo = 0.0
    velo := nz(velo[1], 0) + g / 10000 * dk
    kf := smooth + velo
    kf

a = kh ? kahlman(hma(srchull, lengthhull), gain) : hma(srchull, lengthhull)
b = kh ? kahlman(hma3(srchull, lengthhull), gain) : hma3(srchull, lengthhull)
c = b > a ? color.lime : color.red
crossdn = a > b and a[1] < b[1]
crossup = b > a and b[1] < a[1]

p1hma = plot(a, color=c, linewidth=1, title='Long Plot', transp=75)
p2hma = plot(b, color=c, linewidth=1, title='Short Plot', transp=75)
fill(p1hma, p2hma, color=c, title='Fill', transp=55)

/// HULL TREND WITH KAHLMAN ///

/// DATE ///

_4 = input(false, '───────── DATE SETTINGS ─────────')

FromMonth = input.int(defval=1, title='From Month', minval=1, maxval=12)
FromDay = input.int(defval=1, title='From Day', minval=1, maxval=31)
FromYear = input.int(defval=999, title='From Year', minval=999)
ToMonth = input.int(defval=1, title='To Month', minval=1, maxval=12)
ToDay = input.int(defval=1, title='To Day', minval=1, maxval=31)
ToYear = input.int(defval=9999, title='To Year', minval=999)
start = timestamp(FromYear, FromMonth, FromDay, 00, 00)
finish = timestamp(ToYear, ToMonth, ToDay, 23, 59)
window() =>
    time >= start and time <= finish ? true : false

/// DATE ///

/// LONG/SHORT CONDITION ///

longCondition = crossup and ta.crossover(wt1,wt2)
longCondition1 = crossup
longCondition2 = crossup and wt1 > wt2

if (wtcross == true ? longCondition : wtcross == false ? longCondition1:na)
    strategy.entry("LONG", strategy.long, when=window(), comment="Enter Long")
else if (wtcross2 == true ? longCondition2 : wtcross2 == false ? longCondition:na)
    strategy.entry("LONG", strategy.long, when=window(), comment="Enter Long")
    
shortCondition = crossdn and ta.crossunder(wt1,wt2)
shortCondition1 = crossdn
shortCondition2 = crossdn and wt1 < wt2

if (wtcross == true ? shortCondition : wtcross == false ? shortCondition1:na)
    strategy.entry("SHORT", strategy.short, when=window(), comment="Enter Short")
else if (wtcross2 == true ? shortCondition2 : wtcross2 == false ? shortCondition:na)
    strategy.entry("LONG", strategy.long, when=window(), comment="Enter Short")

/// LONG/SHORT CONDITION ///

/// CLOSE STRATEGY ///

strategy.close("LONG", when=wtcross == true ? shortCondition : wtcross == false ? shortCondition1:na, comment = "Close Long")
strategy.close("SHORT", when=wtcross == true ? longCondition : wtcross == false ? longCondition1:na, comment = "Close Short")

/// EXIT STRATEGY ///

strategy.exit("LONG", when=strategy.position_size > 0, stop=stoploss1 == true ? strategy.position_avg_price * (1 - stoploss):na, limit=takeprofit1 == true ? strategy.position_avg_price * (1 + takeprofit):na, comment="Exit Long")
strategy.exit("SHORT", when=strategy.position_size < 0, stop=stoploss1 == true ? strategy.position_avg_price * (1 + stoploss):na, limit=takeprofit1 == true ? strategy.position_avg_price * (1 - takeprofit):na, comment ="Exit Short")

/// LONG SL/TP LINE ///

plot(strategy.position_size > 0 ? strategy.position_avg_price * (1 - stoploss) : na, title='Long Stop Loss', color=stoploss1 == true ? color.new(color.red, 0):na, style=plot.style_linebr)
plot(strategy.position_size > 0 ? strategy.position_avg_price * (1 + takeprofit) : na, title='Long Take Profit', color=takeprofit1 == true ? color.new(color.green, 0):na, style=plot.style_linebr)

/// LONG SL/TP LINE ///

/// SHORT SL/TP LINE ///

plot(strategy.position_size < 0 ? strategy.position_avg_price * (1 + stoploss) : na, title='Short Stop Loss', color=stoploss1 == true ? color.new(color.red, 0):na, style=plot.style_linebr)
plot(strategy.position_size < 0 ? strategy.position_avg_price * (1 - takeprofit) : na, title='Short Take Profit', color=takeprofit1 == true ? color.new(color.green, 0):na, style=plot.style_linebr)

/// SHORT SL/TP LINE ///

Published by ChaoZhang on the FMZ strategy square · last modified 2023-09-26. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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