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Super Ichi Strategy

Author: ChaoZhang, Date: 2023-11-06 16:32:11
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Overview

The Super Ichi strategy is a trend trading strategy that makes trading decisions based on the Super Ichi indicator. It uses the relationships between the Tenkan line, Kijun line and the Ichimoku Cloud of the Super Ichi indicator to determine the current trend direction, and enters on price pullbacks.

The Super Ichi strategy is mainly suitable for medium-to-long term trend trading and aims to profit from major trends. It also has strong trend identification capabilities.

Strategy Logic

The Super Ichi strategy mainly judges the following elements to determine the trading direction:

  1. Tenkan and Kijun Relationship: Bullish when Tenkan is on top, bearish when below

  2. Cloud Color: Bullish when cloud is green, bearish when red

  3. Price Pullback: Requires a pullback from the lines before entry

Specifically, the trading signals are:

Long Signal:

  • Tenkan above Kijun
  • Price above Tenkan and Kijun
  • Tenkan and Kijun above Cloud
  • Price pulls back below Tenkan and Kijun

Short Signal:

  • Tenkan below Kijun
  • Price below Tenkan and Kijun
  • Tenkan and Kijun below Cloud
  • Price pulls back above Tenkan and Kijun

When the long/short signal is triggered, a position will be opened based on the current position.

Advantage Analysis

The Super Ichi strategy has the following advantages:

  1. Uses Ichimoku combination to determine trends accurately

  2. Tenkan/Kijun shows short-term, Cloud shows long-term trends

  3. Pullback requirement avoids false breakouts

  4. Risk management uses recent swing high/low for stop loss to limit losses

  5. Reasonable risk-reward ratio for steady gains

  6. Applicable to different timeframes for medium-to-long term trend trading

  7. Clear logic and large optimization space

  8. Performs well across various market conditions

Risk Analysis

The Super Ichi strategy also has the following risks:

  1. Stop loss may be triggered frequently during ranging markets, impacting profitability

  2. Failure to quickly reverse positions when trend changes swiftly could lead to losses

  3. Default risk-reward ratios may not suit all instruments, fine tuning required

  4. Limited upside potential when Cloud breakout has limited follow-through

  5. Indicator parameters need extensive testing and optimization for active instruments

Risks can be reduced through:

  1. Optimizing parameters for different timeframes and instruments

  2. Adding filters to avoid false breakout entries during ranging market

  3. Using dynamic stop loss to reduce being stopped out

  4. Testing different risk-reward ratio settings

  5. Confirming signal strength using chart patterns etc.

Optimization Directions

The Super Ichi strategy can be optimized in the following aspects:

  1. Optimize Tenkan/Kijun parameters to better suit the traded instrument

  2. Optimize Cloud parameters for better long-term trend assessment

  3. Enhance stop loss algorithm, e.g. ATR-based or trailing stops

  4. Add filters using other indicators to reduce false entries

  5. Fine-tune risk-reward ratios for different instruments and timeframes

  6. Use martingale position sizing to accommodate varying market volatility

  7. Utilize machine learning for parameter optimization and robustness

  8. Set separate parameters for day vs overnight sessions

Summary

The Super Ichi strategy is well-suited for medium-to-long term trend trading overall. It excels at determining trend direction using Ichimoku, while the pullback requirement avoids false entries. With parameter optimization, it can achieve steady profits across more instruments and timeframes. Easy to understand yet highly optimizable, the Super Ichi strategy serves as an excellent basic trend following strategy for research and learning.


/*backtest
start: 2022-11-05 00:00:00
end: 2023-11-05 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// Strategy based on the the SuperIchi indicator.
//
// Strategy was designed for the purpose of back testing. 
// See strategy documentation for info on trade entry logic.
// 
// Credits:
//  - SuperIchi [LUX]: LuxAlgo (https://www.tradingview.com/script/vDGd9X9y-SuperIchi-LUX/)

//@version=5
strategy("SuperIchi Strategy", overlay=true, initial_capital=1000, currency=currency.NONE, max_labels_count=500, default_qty_type=strategy.cash, commission_type=strategy.commission.percent, commission_value=0.01)

// =============================================================================
// STRATEGY INPUT SETTINGS
// =============================================================================

// ---------------
// Risk Management
// ---------------
swingLength = input.int(15, "Swing High/Low Lookback Length", group='Strategy: Risk Management', tooltip='Stop Loss is calculated by the swing high or low over the previous X candles')
accountRiskPercent = input.float(2, "Account percent loss per trade", step=0.1, group='Strategy: Risk Management', tooltip='Each trade will risk X% of the account balance')
profitFactor = input.float(2, "Profit Factor (R:R Ratio)", step = 0.1, group='Strategy: Risk Management')
useAtrOverride = input.bool(true, "Use Swing High/Low ATR Override", group='Strategy: Risk Management', tooltip='In some cases price may not have a large enough (if any) swing withing previous X candles. Turn this on to use an ATR value when swing high/low is lower than the given ATR value')
atrMultiplier = input.int(1, "Swing High/Low ATR Override Multiplier", group='Strategy: Risk Management')
atrLength = input.int(14, "Swing High/Low ATR Override Length", group='Strategy: Risk Management')

// -----------------
// Strategy Settings
// -----------------
pullbackLength = input.int(5, "Pullback Lookback Length", group='Strategy: Settings', tooltip='Number of candles to consider for a pullback into the moving averages (prerequisite for trade entry)')

// ----------
// Date Range
// ----------
start_year = input.int(title='Start Date', defval=2022, minval=2010, maxval=3000, group='Strategy: Date Range', inline='1')
start_month = input.int(title='', defval=1, group='Strategy: Date Range', inline='1', options = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
start_date = input.int(title='', defval=1, group='Strategy: Date Range', inline='1', options = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31])
end_year = input.int(title='End Date', defval=2023, minval=1800, maxval=3000, group='Strategy: Date Range', inline='2')
end_month = input.int(title='', defval=1, group='Strategy: Date Range', inline='2', options = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12])
end_date = input.int(title='', defval=1, group='Strategy: Date Range', inline='2', options = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31])
in_date_range = time >= timestamp(syminfo.timezone, start_year, start_month, start_date, 0, 0) and time < timestamp(syminfo.timezone, end_year, end_month, end_date, 0, 0)

// =============================================================================
// INDICATORS
// =============================================================================

// ---------------
// SuperIchi [LUX]
// ---------------
tenkan_len  = input(9,'Tenkan          ',inline='SuperIchi', group='Indicator: SuperIchi Settings')
tenkan_mult = input(2.,'',inline='SuperIchi', group='Indicator: SuperIchi Settings')

kijun_len   = input(26,'Kijun             ',inline='SuperIchi', group='Indicator: SuperIchi Settings')
kijun_mult  = input(4.,'',inline='SuperIchi', group='Indicator: SuperIchi Settings')

spanB_len   = input(52,'Senkou Span B ',inline='SuperIchi', group='Indicator: SuperIchi Settings')
spanB_mult  = input(6.,'',inline='SuperIchi', group='Indicator: SuperIchi Settings')

offset      = input(26,'Displacement', inline='SuperIchi', group='Indicator: SuperIchi Settings')
//------------------------------------------------------------------------------
avg(src,length,mult)=>
    atr = ta.atr(length)*mult
    up = hl2 + atr
    dn = hl2 - atr
    upper = 0.,lower = 0.
    upper := src[1] < upper[1] ? math.min(up,upper[1]) : up
    lower := src[1] > lower[1] ? math.max(dn,lower[1]) : dn
    
    os = 0,max = 0.,min = 0.
    os := src > upper ? 1 : src < lower ? 0 : os[1]
    spt = os == 1 ? lower : upper
    max := ta.cross(src,spt) ? math.max(src,max[1]) : os == 1 ? math.max(src,max[1]) : spt
    min := ta.cross(src,spt) ? math.min(src,min[1]) : os == 0 ? math.min(src,min[1]) : spt
    math.avg(max,min)
//------------------------------------------------------------------------------
tenkan = avg(close,tenkan_len,tenkan_mult)
kijun = avg(close,kijun_len,kijun_mult)

senkouA = math.avg(kijun,tenkan)
senkouB = avg(close,spanB_len,spanB_mult)
//------------------------------------------------------------------------------
tenkan_css = #2157f3 //blue
kijun_css = #ff5d00 //red

cloud_a = color.new(color.teal,80)
cloud_b = color.new(color.red,80)

chikou_css = #7b1fa2

plot(tenkan,'Tenkan-Sen',tenkan_css)
plot(kijun,'Kijun-Sen',kijun_css)

plot(ta.crossover(tenkan,kijun) ? kijun : na,'Crossover',#2157f3,3,plot.style_circles)
plot(ta.crossunder(tenkan,kijun) ? kijun : na,'Crossunder',#ff5d00,3,plot.style_circles)

A = plot(senkouA,'Senkou Span A',na,offset=offset-1)
B = plot(senkouB,'Senkou Span B',na,offset=offset-1)
fill(A,B,senkouA > senkouB ? cloud_a : cloud_b)

plot(close,'Chikou',chikou_css,offset=-offset+1,display=display.none)


// =============================================================================
// STRATEGY LOGIC
// =============================================================================
plotchar(kijun, "kijun", "", location = location.top)
plotchar(senkouA[offset-1], "senkouA", "", location = location.top)


plotchar(tenkan > kijun, "line above", "", location = location.top)
plotchar(close > tenkan, "price above", "", location = location.top)
plotchar(kijun > senkouA[offset-1], "above cloud", "", location = location.top)
// blue line above red line + price above both lines + both lines above cloud
longSen = tenkan > kijun and close > tenkan and kijun > senkouA[offset-1]
// red line below blue line + price below both lines + both lines below cloud
shortSen = tenkan < kijun and close < tenkan and kijun < senkouA[offset-1]

plotchar(longSen, "longSen", "", location = location.top)
plotchar(shortSen, "shortSen", "", location = location.top)

// Cloud is green
longSenkou = senkouA[offset-1] > senkouB[offset-1]
// Cloud is red
shortSenkou = senkouA[offset-1] < senkouB[offset-1]

// price must have pulled back below sen lines before entry
barsSinceLongPullback = ta.barssince(close < kijun and close < tenkan)
longPullback = barsSinceLongPullback <= pullbackLength
// price must have pulled back above sen lines before entry
barsSinceShortPullback = ta.barssince(close > kijun and close > tenkan)
shortPullback = barsSinceShortPullback <= pullbackLength

// plotchar(lowestClose, "lowestClose", "", location = location.top)
// plotchar(highestClose, "highestClose", "", location = location.top)

inLong = strategy.position_size > 0
inShort = strategy.position_size < 0

longCondition = longSen and longSenkou and longPullback and in_date_range
shortCondition = shortSen and shortSenkou and shortPullback and in_date_range

swingLow = ta.lowest(source=low, length=swingLength)
swingHigh = ta.highest(source=high, length=swingLength)

atr = useAtrOverride ? ta.atr(atrLength) * atrMultiplier : 0
longSl = math.min(close - atr, swingLow)
shortSl = math.max(close + atr, swingHigh)

longStopPercent = math.abs((1 - (longSl / close)) * 100)
shortStopPercent = math.abs((1 - (shortSl / close)) * 100)

longTpPercent = longStopPercent * profitFactor
shortTpPercent = shortStopPercent * profitFactor
longTp = close + (close * (longTpPercent / 100))
shortTp = close - (close * (shortTpPercent / 100))

// Position sizing (default risk 2% per trade)
riskAmt = strategy.equity * accountRiskPercent / 100
longQty = math.abs(riskAmt / longStopPercent * 100) / close
shortQty = math.abs(riskAmt / shortStopPercent * 100) / close

if (longCondition and not inLong)
    strategy.entry("Long", strategy.long, qty=longQty)
    strategy.exit("Long  SL/TP", from_entry="Long", stop=longSl, limit=longTp, alert_message='Long SL Hit')
    buyLabel = label.new(x=bar_index, y=high[1], color=color.green, style=label.style_label_up)
    label.set_y(id=buyLabel, y=low)
    label.set_tooltip(id=buyLabel, tooltip="Risk Amt: " + str.tostring(riskAmt) + "\nQty: " + str.tostring(longQty) + "\nSwing low: " + str.tostring(swingLow) + "\nStop Percent: " + str.tostring(longStopPercent) + "\nTP Percent: " + str.tostring(longTpPercent))

if (shortCondition and not inShort)
    strategy.entry("Short", strategy.short, qty=shortQty)
    strategy.exit("Short  SL/TP", from_entry="Short", stop=shortSl, limit=shortTp, alert_message='Short SL Hit')
    sellLabel = label.new(x=bar_index, y=high[1], color=color.red, style=label.style_label_up)
    label.set_y(id=sellLabel, y=low)
    label.set_tooltip(id=sellLabel, tooltip="Risk Amt: " + str.tostring(riskAmt) + "\nQty: " + str.tostring(shortQty) + "\nSwing high: " + str.tostring(swingHigh) + "\nStop Percent: " + str.tostring(shortStopPercent) + "\nTP Percent: " + str.tostring(shortTpPercent))

template: strategy.tpl:40:21: executing "strategy.tpl" at <.api.GetStrategyListByName>: wrong number of args for GetStrategyListByName: want 7 got 6