Name
多时间框架趋势猎手策略Multitimeframe-Trend-Hunter-Strategy
Author
ChaoZhang
Strategy Description
多时间框架趋势猎手策略(Multitimeframe Trend Hunter Strategy)是一个利用多种指标配合实现自动化交易信号的策略。该策略综合利用移动平均线、超级趋势指标和一云图指标等,在多个时间框架内判断趋势方向,以发现潜在的交易机会。
该策略的核心原理是同时在高时间框架和低时间框架判断趋势方向。策略首先在高时间框架计算出关键的移动平均线、超级趋势线和一云图的转换线、基准线等。然后在低时间框架计算出超级趋势线。当高低时间框架的超级趋势线方向一致时,即确认当前整体趋势方向。此外,该策略还要判断价格是否突破移动平均线或一云图的云,以进一步验证趋势的可靠性。
在满足一定条件后,该策略会产生买入或卖出的交易信号。用户可以根据自己的需要选择是否只交易长单、短单或都交易。此外,用户还可以配置移动平均线参数、超级趋势参数、一云图参数等,对策略的表现进行优化。
该策略最大的优势在于多时间框架和多指标的结合,这可以大大提高判断趋势方向的准确性,并及时发现反转机会。具体优势如下:
- 利用高低时间框架确认趋势,避免被市场噪音误导
- 移动平均线作为中长线指标,判断主要趋势方向
- 超级趋势线作为短期指标,及时捕捉趋势反转
- 一云图判断支持阻力区域,发现潜在机会
该策略的主要风险在于参数设置不当可能导致过于频繁交易或漏失机会。此外,指标发出错误信号也会造成损失。具体风险及解决方法如下:
- 参数设置风险:多进行回测和优化,找到最佳参数组合
- 信号错误风险:结合更多指标进行验证,避免错误信号
- 回撤风险:适当调整仓位管理,控制单笔损失
该策略还有进一步优化的空间:
- 增加更多指标结合,如布林带、RSI等,提高判断准确性
- 集成机器学习模型,实现更智能化的交易策略
- 结合量化技术,如高频交易、arly bird等,进一步提升策略表现
- 优化仓位管理策略,通过动态调整仓位,降低回撤风险
综上所述,多时间框架趋势猎手策略利用多指标和多时间框架判断趋势,能及时抓住反转机会,是一种表现较佳的量化交易策略。该策略集成度高、应用广泛,未来仍有很大的优化空间,值得量化交易者继续研究和应用。
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The Multitimeframe Trend Hunter Strategy is a strategy that utilizes multiple indicators to generate automated trading signals. This strategy incorporates moving averages, Supertrend indicator, Ichimoku Cloud and more across multiple timeframes to determine trend direction and discover potential trading opportunities.
The core logic of this strategy is to judge trend direction simultaneously on higher and lower timeframes. The strategy first calculates key moving average, Supertrend lines, Ichimoku conversion and base lines etc. on the higher timeframe. It then calculates the Supertrend lines on the lower timeframe. When Supertrend directions on both timeframes align, the overall trend direction is confirmed. In addition, the strategy also checks if price breaks through moving average or ichimoku cloud to further validate trend reliability.
Once certain criteria are met, the strategy will generate buy or sell signals. Users can choose to only trade longs, shorts or both based on their needs. Users can also optimize parameters like moving average, Supertrend, Ichimoku etc. to improve strategy performance.
The biggest advantage of this strategy is the combination of multiple timeframes and indicators, which greatly improves trend accuracy and timely detects reversal opportunities. Specific advantages are:
- Confirm trend with high/low timeframes, avoid market noise
- Moving average as mid/long-term indicator judges major trend
- Supertrend as short-term indicator timely catches trend reversal
- Ichimoku cloud identifies potential support/resistance levels
The main risks are improper parameter settings leading to over-trading or missing opportunities. Incorrect signal by indicators can also cause losses. Specific risks and solutions:
- Parameter risk: Backtest and optimize to find optimal parameters
- Signal error risk: Add more indicators to verify and avoid wrong signals
- Drawdown risk: Adjust position sizing to limit single trade loss
There is further room to optimize this strategy:
- Add more indicators like Bollinger Bands, RSI to improve accuracy
- Integrate machine learning models for more intelligent strategies
- Incorporate quant techniques like HFT, early bird to further enhance performance
- Optimize position sizing strategy to lower drawdown risk
In conclusion, the Multitimeframe Trend Hunter Strategy leverages multiple indicators across timeframes to determine trend and capture reversals timely. It is an effective quant trading strategy with wide applications and much room for future optimizations, worthwhile for quant traders to continually research and apply. [/trans]
Strategy Arguments
| Argument | Default | Description |
|---|---|---|
| v_input_timeframe_1 | 60 | (?== Timeframe ==)Higher Time Frame |
| v_input_int_1 | 200 | (?== EMA ==)EMA Length |
| v_input_bool_1 | true | Colour EMA |
| v_input_1 | 10 | (?== Supertrend ==)ATR Period |
| v_input_float_1 | 3 | ATR Multiplier |
| v_input_source_1_hl2 | 0 | Source: hl2 |
| v_input_int_2 | 9 | (?== Ichimoku ==)Conversion Line Periods |
| v_input_int_3 | 26 | Base Line Periods |
| v_input_int_4 | 52 | Lagging Span 2 Periods |
| v_input_int_5 | 26 | Displacement |
| v_input_2 | false | Conversion Line |
| v_input_3 | false | Base Line |
| v_input_4 | false | Lagging Span |
| v_input_5 | true | Cloud |
| v_input_bool_2 | true | (?== Strategy Options ==)Trade Table |
| v_input_bool_3 | true | Enter Longs |
| v_input_bool_4 | true | Enter Shorts |
| v_input_bool_5 | true | Price outside cloud |
| v_input_bool_6 | false | Full Body |
| v_input_bool_7 | false | Price above/below EMA |
| v_input_bool_8 | false | Full Body |
| v_input_bool_9 | true | Supertrend transistions |
| v_input_bool_10 | false | LTF/HTF Supertrend alignment |
| v_input_bool_11 | true | EMA Outside Cloud |
| v_input_bool_12 | false | EMA above/below Cloud |
| v_input_bool_13 | true | Super Trend Exits: HTF |
| v_input_bool_14 | true | LTF |
Source (PineScript)
/*backtest
start: 2024-01-01 00:00:00
end: 2024-01-31 23:59:59
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © godzcopilot / blockybears
// Thanks to anthonyf50 for his MTF Ichimoku https://www.tradingview.com/script/Pw9cBFma/
// Thanks to KivancOzbilgic for his SuperTrend https://www.tradingview.com/script/r6dAP7yi/
// Thanks to ZenAndTheArtOfTrading / PineScriptMastery for their Higher Timeframe EMA https://www.tradingview.com/script/Vh3XG9sD-Higher-Timeframe-EMA/
//@version=5
strategy("TrendHunter [Blocky]", overlay=true, default_qty_type=strategy.percent_of_equity, default_qty_value=80, initial_capital=1000, pyramiding=0)
// ================
// Strategy Inputs
// ================
// Defines user inputs for configuring the strategy.
// Higher Time Frame Selection
HTF_TimeFrame = input.timeframe(title='Higher Time Frame', defval='60', group = '== Timeframe ==', tooltip = "Select Chart for standard functionality")
// Inputs for EMA
len = input.int(title="EMA Length", defval=200, group ='== EMA ==')
col = input.bool(title="Colour EMA", defval=true, group ='== EMA ==')
// SuperTrend
Periods = input(title='ATR Period', defval=10, group = '== Supertrend ==')
Multiplier = input.float(title='ATR Multiplier', step=0.1, defval=3.0, group = '== Supertrend ==')
Src = input.source(title='Source', defval=hl2, group = '== Supertrend ==')
// Ichimoku
conversionPeriods = input.int(9, minval=1, title='Conversion Line Periods', group = '== Ichimoku ==')
basePeriods = input.int(26, minval=1, title='Base Line Periods', group = '== Ichimoku ==')
laggingSpan2Periods = input.int(52, minval=1, title='Lagging Span 2 Periods', group = '== Ichimoku ==')
displacement = input.int(26, minval=1, title='Displacement', group = '== Ichimoku ==')
// Ichimoku Display Options
isActiveConversion = input(false, 'Conversion Line', group = '== Ichimoku ==', inline = 'lines1')
isActiveBase = input(false, 'Base Line', group = '== Ichimoku ==', inline = 'lines1')
isActiveLagging = input(false, 'Lagging Span', group = '== Ichimoku ==', inline = 'lines2')
isActiveCloud = input(true, 'Cloud', group = '== Ichimoku ==', inline = 'lines2')
// ================
// Strategy Options
// ================
bTable = input.bool(true, title='Trade Table', group='== Strategy Options ==', tooltip = "Show table that shows current selected options and trade trade entry parameters")
bLong = input.bool(true, title='Enter Longs', group='== Strategy Options ==', inline = 'LongShort')
bShort = input.bool(true, title='Enter Shorts', group='== Strategy Options ==', inline = 'LongShort', tooltip = "Filter long / short trade signals")
bPriceCloud = input.bool(true, title='Price outside cloud', group='== Strategy Options ==', inline='PriceCloud')
bPriceCloudBody = input.bool(false, title='Full Body', group='== Strategy Options ==', inline='PriceCloud', tooltip = 'Only trade when price action outside the cloud.\nLongs when price action above the cloud.\nShort when price action below the cloud')
bPriceEMA = input.bool(false, title='Price above/below EMA', group='== Strategy Options ==', inline='PriceEMA')
bPriceEMABody = input.bool(false, title='Full Body', group='== Strategy Options ==', inline='PriceEMA', tooltip = 'Longs when price action above the EMA.\nShort when price action below the EMA')
bSuper = input.bool(true, title='Supertrend transistions', group='== Strategy Options ==', tooltip = "Trade in direction of the supertrend transitions")
bLTF = input.bool(false, title='LTF/HTF Supertrend alignment', group='== Strategy Options ==', tooltip = "Utilise a dual supertrends, chart and defined higher time frame")
bEMACloud1 = input.bool(true, title='EMA Outside Cloud', group='== Strategy Options ==', tooltip = "EMA must be outside the ichimoku cloud")
bEMACloud2 = input.bool(false, title='EMA above/below Cloud', group='== Strategy Options ==', tooltip = "Longs when EMA above the cloud.\nShort when EMA below the cloud")
bExitHTFTrail = input.bool(true, title='Super Trend Exits: HTF', group='== Strategy Options ==', inline = 'Exits')
bExitLTFTrail = input.bool(true, title='LTF', group='== Strategy Options ==', inline = 'Exits', tooltip = 'Exit trades when price crosses the supertrend line\nIf neither selected trade closes when opposite trade opens\nIf using LTF closes turn on HTF/LTF alignment')
// ===========================
// EMA Functions and Plotting
// ===========================
// Calculate EMA
ema = ta.ema(close, len)
emaSmooth = request.security(syminfo.tickerid, HTF_TimeFrame, ema[barstate.isrealtime ? 1 : 0], gaps=barmerge.gaps_on)[barstate.isrealtime ? 0 : 1]
// Draw EMA
plot(emaSmooth, color=col ? (close > emaSmooth ? color.rgb(76, 163, 175) : color.rgb(6, 23, 173)) : color.black, linewidth=2, title="HTF EMA")
// ==================================
// Supertrend Functions and Plotting
// ==================================
// Function to calculate SuperTrend
calcSuperTrend(src, atrPeriods, multiplier) =>
atr = ta.atr(atrPeriods)
up = src - multiplier * atr
up1 = nz(up[1], up)
up := close[1] > up1 ? math.max(up, up1) : up
dn = src + multiplier * atr
dn1 = nz(dn[1], dn)
dn := close[1] < dn1 ? math.min(dn, dn1) : dn
trend = 1
trend := nz(trend[1], trend)
trend := trend == -1 and close > dn1 ? 1 : trend == 1 and close < up1 ? -1 : trend
[up, dn, trend]
// Calculate SuperTrend for the current time frame
[up, dn, trend] = calcSuperTrend(Src, Periods, Multiplier)
// Plotting for the current time frame
plot(trend == 1 ? up : dn, title='LTF Supertrend', color=trend == 1 ?color.green : color.red, linewidth=1, style = plot.style_stepline)
// Fetching the higher time frame data
[HTF_up, HTF_dn, HTF_trend] = request.security(syminfo.tickerid, HTF_TimeFrame, calcSuperTrend(hl2, Periods, Multiplier), lookahead=barmerge.lookahead_on)
// Plotting for the higher time frame
plot(HTF_trend == 1 ? HTF_up : HTF_dn, title='HTF Up Trend', color= HTF_trend == 1 ? color.green : color.red, linewidth=4)
// ===============================
// Ichimoku Functions and Plotting
// ===============================
// Function to convert timeframe to hours
f_convertTimeframeToHours(tf) =>
val = 0.0
if tf == "1S" or tf == "S"
val := 1.0 / 3600.0
else if str.contains(tf, "S")
val := str.tonumber(str.replace(tf, "S", "")) / 3600.0
else if tf == "1D" or tf == "D"
val := 24.0
else if str.contains(tf, "D")
val := str.tonumber(str.replace(tf, "D", "")) * 24.0
else if tf == "1W" or tf == "W"
val := 24.0 * 7.0
else if str.contains(tf, "W")
val := str.tonumber(str.replace(tf, "W", "")) * 24.0 * 7.0
else if tf == "1M" or tf == "M"
val := 24.0 * 30.0 // Approximation for a month
else if str.contains(tf, "M")
val := str.tonumber(str.replace(tf, "M", "")) * 24.0 * 30.0 // Approximation for months
else
// Default to minutes
val := str.tonumber(tf) / 60.0
val
// Time
timeOffset = time - time[1]
// Returns the displacement based on the chart / HTF resolution
f_getDisplacement(_res) =>
_res == '' ? displacement : math.round(f_convertTimeframeToHours(_res) / f_convertTimeframeToHours(timeframe.period) * displacement)
//f_avgDilationOf(_res) * displacement
// Returns average value between lowest and highest
f_avgLH(_len) =>
math.avg(ta.lowest(_len), ta.highest(_len))
// Returns f_donchian data
f_donchian(_tf, _src) =>
request.security(syminfo.tickerid, _tf, _src, barmerge.gaps_off, barmerge.lookahead_on)
// Returns ichimoku data
f_ichimokuData(_tf) =>
_isShow = _tf == '' or f_convertTimeframeToHours(_tf) >= f_convertTimeframeToHours(timeframe.period)
_displacement = _isShow ? f_getDisplacement(_tf) : na
_Conversion = _isShow ? f_donchian(_tf, f_avgLH(conversionPeriods)) : na
_Base = _isShow ? f_donchian(_tf, f_avgLH(basePeriods)) : na
_Lagging = _isShow ? f_donchian(_tf, close) : na
_SSA = _isShow ? math.avg(_Conversion, _Base) : na
_SSB = _isShow ? f_donchian(_tf, f_avgLH(laggingSpan2Periods)) : na
_middleCloud = _isShow ? _SSA[0] > _SSB[0] ? _SSA[0] - math.abs(_SSA[0] - _SSB[0]) / 2 : _SSA[0] + math.abs(_SSA[0] - _SSB[0]) / 2 : na
[_displacement, _Conversion, _Base, _Lagging, _SSA, _SSB, _middleCloud]
// Plotting ichimoku data
[Displacement, Conversion, Base, Lagging, SSA, SSB, fisrtMiddleCloud] = f_ichimokuData(HTF_TimeFrame)
// ————— Conversion
plot(isActiveConversion ? Conversion : na, color=color.new(color.blue, 0), title=' Conversion', linewidth=1)
// ————— Base
plot(isActiveBase ? Base : na, color=color.new(color.fuchsia, 0), title=' Base', linewidth=2)
// ————— Lagging
plot(isActiveLagging ? Lagging : na, offset=-Displacement, color=color.new(color.green, 0), title=' Lagging')
// ————— SSA + SSB
ssa = plot(isActiveCloud ? SSA : na, offset=Displacement, color=color.new(color.green, 0), title=' SSA', linewidth=1)
ssb = plot(isActiveCloud ? SSB : na, offset=Displacement, color=color.new(color.red, 0), title=' SSB', linewidth=1)
fill(ssa, ssb, color=color.new(SSA > SSB ? color.green : color.red , 80), title=' Cloud')
// ===============================
// Strategy Entries
// ===============================
// Checks whether price is inside the Ichimoku cloud
f_PriceCloud(dir) =>
_enter = false
if bPriceCloud
if bLong and dir == 1
if bPriceCloudBody
_enter := close > math.max(SSA[Displacement], SSB[Displacement]) and open > math.max(SSA[Displacement], SSB[Displacement])
else
_enter := close > math.max(SSA[Displacement], SSB[Displacement])
if bShort and dir == 2
if bPriceCloudBody
_enter := close < math.min(SSA[Displacement], SSB[Displacement]) and open < math.min(SSA[Displacement], SSB[Displacement])
else
_enter := close < math.min(SSA[Displacement], SSB[Displacement])
else
_enter := na
_enter
// Checks whether price is above / below the ema
f_PriceEMA(dir) =>
_enter = false
if bPriceEMA
if bLong and dir == 1
if bPriceEMABody
_enter := close > emaSmooth and open > emaSmooth
else
_enter := close > emaSmooth
if bShort and dir == 2
if bPriceEMABody
_enter := close < emaSmooth and open < emaSmooth
else
_enter := close < emaSmooth
else
_enter := na
_enter
// Checks HTF supertrend direction
f_Super(dir) =>
_enter = false
if bSuper
if bLong and dir == 1
_enter := HTF_trend == 1
if bShort and dir == 2
_enter := HTF_trend == -1
else
_enter := na
_enter
// Checks LTF supertrend direction
f_LTF(dir) =>
_enter = false
if bLTF
if bLong and dir == 1
_enter := trend == 1 and HTF_trend == 1
if bShort and dir == 2
_enter := trend == -1 and HTF_trend == -1
else
_enter := na
_enter
// Checks whether ema is inside the Ichimoku cloud
f_EMACloud1(dir) =>
_enter = false
if bEMACloud1
if bLong and dir == 1
_enter := (emaSmooth > math.max(SSA[Displacement], SSB[Displacement])) or (emaSmooth < math.min(SSA[Displacement], SSB[Displacement]))
if bShort and dir == 2
_enter := (emaSmooth > math.max(SSA[Displacement], SSB[Displacement])) or (emaSmooth < math.min(SSA[Displacement], SSB[Displacement]))
else
_enter := na
_enter
// Checks whether ema is above/below Ichimoku cloud
f_EMACloud2(dir) =>
_enter = false
if bEMACloud2
if bLong and dir == 1
_enter := emaSmooth > math.max(SSA[Displacement], SSB[Displacement])
if bShort and dir == 2
_enter := emaSmooth < math.min(SSA[Displacement], SSB[Displacement])
else
_enter := na
_enter
// Check if a value is 'na' or true.
f_NATrue(val) =>
_enter = false
if na(val)
_enter := true
if val
_enter := true
_enter
// Consolidates entry conditions.
f_checkCondition(dir) =>
_enter = false
if na(f_PriceCloud(dir)) and na(f_PriceEMA(dir)) and na(f_Super(dir)) and na(f_LTF(dir)) and na(f_EMACloud1(dir)) and na(f_EMACloud2(dir))
_enter := false
else if f_NATrue(f_PriceCloud(dir)) and f_NATrue(f_PriceEMA(dir)) and f_NATrue(f_Super(dir)) and f_NATrue(f_LTF(dir)) and f_NATrue(f_EMACloud1(dir)) and f_NATrue(f_EMACloud2(dir))
_enter := true
_enter
// Execute long trade entries
longCondition = bLong and f_checkCondition(1)
if (longCondition)
strategy.entry("Long", strategy.long)
// Execute short trade entries
shortCondition = bShort and f_checkCondition(2)
if (shortCondition)
strategy.entry("Short", strategy.short)
// Excute trade exits
exitLong = (bExitHTFTrail and (close < HTF_up or HTF_trend == -1)) or (bExitLTFTrail and (close < up or trend == -1))
exitShort = (bExitHTFTrail and (close > HTF_dn or HTF_trend == 1)) or (bExitLTFTrail and (close > dn or trend == 1))
if exitLong
strategy.close("Long")
if exitShort
strategy.close("Short")
// Creates a table shoing all the user options and their current status for entering a trade
if bTable
// Create a table
tbl = table.new(position = position.bottom_right, columns = 4, rows = 9, bgcolor=color.new(color.white, 50), border_width = 1)
table.cell(tbl, 1, 0, "Selected")
table.cell(tbl, 2, 0, "Long", bgcolor=na(bLong) ? color.gray : bShort ? color.rgb(4, 112, 8) : color.rgb(100, 7, 7))
table.cell(tbl, 3, 0, "Short", bgcolor=na(bShort) ? color.gray : bShort ? color.rgb(4, 112, 8) : color.rgb(100, 7, 7))
table.cell(tbl, 0, 1, "Entry")
table.cell(tbl, 2, 1, str.tostring(longCondition), bgcolor=longCondition ? color.green : color.red)
table.cell(tbl, 3, 1, str.tostring(shortCondition), bgcolor=shortCondition ? color.green : color.red)
table.cell(tbl, 0, 3, "Price Cloud")
table.cell(tbl, 1, 3, str.tostring(bPriceCloud), bgcolor=na(bPriceCloud) ? color.gray : bPriceCloud ? color.green : color.red)
table.cell(tbl, 2, 3, str.tostring(f_PriceCloud(1)), bgcolor=na(f_PriceCloud(1)) ? color.gray : f_PriceCloud(1) ? color.green : color.red)
table.cell(tbl, 3, 3, str.tostring(f_PriceCloud(2)), bgcolor=na(f_PriceCloud(2)) ? color.gray : f_PriceCloud(2) ? color.green : color.red)
table.cell(tbl, 0, 4, "Price EMA")
table.cell(tbl, 1, 4, str.tostring(bPriceEMA), bgcolor=na(bPriceEMA) ? color.gray : bPriceEMA ? color.green : color.red)
table.cell(tbl, 2, 4, str.tostring(f_PriceEMA(1)), bgcolor=na(f_PriceEMA(1)) ? color.gray : f_PriceEMA(1) ? color.green : color.red)
table.cell(tbl, 3, 4, str.tostring(f_PriceEMA(2)), bgcolor=na(f_PriceEMA(2)) ? color.gray : f_PriceEMA(2) ? color.green : color.red)
table.cell(tbl, 0, 5, "SuperTrend")
table.cell(tbl, 1, 5, str.tostring(bSuper), bgcolor=na(bSuper) ? color.gray : bSuper ? color.green : color.red)
table.cell(tbl, 2, 5, str.tostring(f_Super(1)), bgcolor=na(f_Super(1)) ? color.gray : f_Super(1) ? color.green : color.red)
table.cell(tbl, 3, 5, str.tostring(f_Super(2)), bgcolor=na(f_Super(2)) ? color.gray : f_Super(2) ? color.green : color.red)
table.cell(tbl, 0, 6, "HTF/LTF")
table.cell(tbl, 1, 6, str.tostring(bLTF), bgcolor=na(bLTF) ? color.gray : bLTF ? color.green : color.red)
table.cell(tbl, 2, 6, str.tostring(f_LTF(1)), bgcolor=na(f_LTF(1)) ? color.gray : f_LTF(1) ? color.green : color.red)
table.cell(tbl, 3, 6, str.tostring(f_LTF(2)), bgcolor=na(f_LTF(2)) ? color.gray : f_LTF(2) ? color.green : color.red)
table.cell(tbl, 0, 7, "EMA Outside Cloud")
table.cell(tbl, 1, 7, str.tostring(bEMACloud1), bgcolor=na(bEMACloud1) ? color.gray : bEMACloud1 ? color.green : color.red)
table.cell(tbl, 2, 7, str.tostring(f_EMACloud1(1)), bgcolor=na(f_EMACloud1(1)) ? color.gray : f_EMACloud1(1) ? color.green : color.red)
table.cell(tbl, 3, 7, str.tostring(f_EMACloud1(2)), bgcolor=na(f_EMACloud1(2)) ? color.gray : f_EMACloud1(2) ? color.green : color.red)
table.cell(tbl, 0, 8, "EMA Above/Below Cloud")
table.cell(tbl, 1, 8, str.tostring(bEMACloud2), bgcolor=na(bEMACloud2) ? color.gray : bEMACloud2 ? color.green : color.red)
table.cell(tbl, 2, 8, str.tostring(f_EMACloud2(1)), bgcolor=na(f_EMACloud2(1)) ? color.gray : f_EMACloud2(1) ? color.green : color.red)
table.cell(tbl, 3, 8, str.tostring(f_EMACloud2(2)), bgcolor=na(f_EMACloud2(2)) ? color.gray : f_EMACloud2(2) ? color.green : color.red)
Detail
https://www.fmz.com/strategy/441963
Last Modified
2024-02-18 10:17:06