Safe Haven Demand IndexSafe Haven Demand Index
Stocks are riskier than bonds. But the reward for investing in stocks over the long haul is greater. Still, bonds can outperform stocks over short periods. Safe Haven Demand shows the difference between Treasury bond and stock returns over the past 20 trading days. Bonds do better when investors are scared. The Fear & Greed Index uses increasing safe haven demand as a signal for Fear.
Indicateurs et stratégies
Gold Price APIGold_mammad sends live chart on this api.i want to test it.just testing and nothing more
Help my PMCC/CSP Debug Versionfor indicating when to sell CC or CSP, needs something to be less indicating? Try the 4h
EMA (3) MA (5) BB by Ismael R📈 Moving Averages & Bollinger Bands Indicator - SMA & EMA MultiFrame
🔹 Description:
This indicator combines Simple Moving Averages (SMA), Exponential Moving Averages (EMA), and Bollinger Bands, providing a clear view of market trends and potential volatility zones.
🔹 Features:
✅ Includes 5 configurable SMAs (50, 8, 200, 20, 800 by default).
✅ Incorporates 3 configurable EMAs (45, 9, 200 by default).
✅ Implements Bollinger Bands with different standard deviation levels (2.0, 2.5, and 3.0).
✅ Ability to enable or disable each MA/EMA individually.
✅ Customizable colors for better readability.
🔹 How to use it?
📊 Trend Identification: EMAs and SMAs help recognize market direction.
📈 Dynamic Support & Resistance: Bollinger Bands indicate areas of high and low volatility.
⚡ Entry & Exit Signals: Moving average crossovers can signal potential trade opportunities.
🔹 Recommended Settings:
Short-term traders can use a combination of SMA (8, 20, 50) and EMA (9, 45).
Long-term investors can watch the SMA 200 and EMA 200 as macro trend indicators.
📌 Code available in Pine Script v5
Add it to your TradingView and enhance your technical analysis! 🚀
Triple Moving Averages3 EMAS In one indicator,
EMA 1 IS GOOD
EMA 2 IS GOOD
EMA 3 IS GOOD
I don't know why it says my description is very brief what else is there to say, its just 3 different Emas
lev-multi moving everagethis indicator include 20,50,150 and 200 in one indicator
so good for basic accounts
EMA Strategy with Downward Symbol_siubosiubo_option
This script allows novices to quickly grasp and judge trends
Pegofe Universal Breakout StrategyDescription for TradingView Publication
Title: Pegofe NY Breakout Strategy – EUR/USD (1:2 Risk/Reward)
Description:
The Pegofe NY Breakout Strategy is designed to capture high-probability trading opportunities in EUR/USD at the opening of the New York session (15:30 Spain / 14:30 UTC) on a 5-minute timeframe.
Key Features:
✅ Trend Confirmation: Uses EMA 50 and EMA 9 to filter high-probability trades.
✅ Momentum-Based Entries: Combines RSI (14) and EMA crossovers to detect overbought/oversold conditions.
✅ Risk-Reward Ratio of 1:2: Automatically calculates Stop Loss (SL) and Take Profit (TP) based on ATR (14) for dynamic volatility adjustment.
✅ Clear Trade Signals: Visual buy and sell signals appear when the entry criteria are met.
✅ Stop Loss & Take Profit Labels: Displays SL and TP levels on the chart using label.new() for better visualization.
Entry Conditions:
📈 Long Entry (Buy Signal):
• The price is above EMA 50 (uptrend).
• RSI < 35 (oversold).
• EMA 9 crosses above the price.
• The trade occurs after 14:30 UTC (New York session open).
📉 Short Entry (Sell Signal):
• The price is below EMA 50 (downtrend).
• RSI > 65 (overbought).
• EMA 9 crosses below the price.
• The trade occurs after 14:30 UTC (New York session open).
How It Works:
• When a valid trade setup occurs, the strategy executes an entry order and automatically sets a Stop Loss (1.5x ATR) and Take Profit (2x SL).
• The SL and TP levels are dynamically adjusted based on market volatility.
• The script labels SL and TP directly on the chart for better tracking.
Recommended Settings:
• Market: EUR/USD
• Timeframe: 5 minutes
• Session: After 14:30 UTC (New York open)
🚀 Try it now and optimize your NY session trading!
Heikin Ashi + MACD + RSI + Candlestick + Fibonacci• Heikin Ashi Candles: The script calculates Heikin Ashi values (haOpen, haClose, haHigh, haLow) to identify bullish or bearish candle conditions.
• MACD Signals: Uses a fast and slow EMA on the Heikin Ashi close, along with a signal line, to detect bullish (crossover) or bearish (crossunder) momentum shifts.
• RSI Filter: Applies RSI with adjustable overbought/oversold levels to refine bullish or bearish signals and to detect potential divergences.
• Candlestick Patterns: Checks for bullish/bearish engulfing and three-line strike patterns, integrating them into the overall signal logic.
• RSI Divergence: Identifies bullish or bearish divergence by comparing recent price lows/highs with RSI lows/highs.
• Base Buy/Sell Signals: Combines MACD crosses, RSI overbought/oversold, candlestick patterns, and divergence into single buy or sell triggers.
• Fibonacci for Entry Filtering (Optional): Uses pivot highs/lows to calculate Fibonacci retracement levels; signals only trigger if price is near these retracement zones (when enabled).
• ATR-Based Stops/Targets: Calculates stop-loss and take-profit levels using ATR with user-defined multipliers for risk management.
• Fibonacci-Based Stops/Targets (Optional): Optionally replaces ATR-based stops/targets with Fibonacci extensions for both upside (long) and downside (short) scenarios.
• Strategy Execution & Plotting: Executes trades on buy/sell signals, sets corresponding stops/targets, and plots all relevant lines (signals, pivots, fib levels) for visual reference.
works well on low TF 2-5min. not great on larger time frames. gives a lot of signals.
If you can help me make it better and filter low quality signals please let me know
Pegofe NY Breakout StrategyDescription for TradingView Publication
Title: Pegofe NY Breakout Strategy – EUR/USD (1:2 Risk/Reward)
Description:
The Pegofe NY Breakout Strategy is designed to capture high-probability trading opportunities in EUR/USD at the opening of the New York session (15:30 Spain / 14:30 UTC) on a 5-minute timeframe.
Key Features:
✅ Trend Confirmation: Uses EMA 50 and EMA 9 to filter high-probability trades.
✅ Momentum-Based Entries: Combines RSI (14) and EMA crossovers to detect overbought/oversold conditions.
✅ Risk-Reward Ratio of 1:2: Automatically calculates Stop Loss (SL) and Take Profit (TP) based on ATR (14) for dynamic volatility adjustment.
✅ Clear Trade Signals: Visual buy and sell signals appear when the entry criteria are met.
✅ Stop Loss & Take Profit Labels: Displays SL and TP levels on the chart using label.new() for better visualization.
Entry Conditions:
📈 Long Entry (Buy Signal):
• The price is above EMA 50 (uptrend).
• RSI < 35 (oversold).
• EMA 9 crosses above the price.
• The trade occurs after 14:30 UTC (New York session open).
📉 Short Entry (Sell Signal):
• The price is below EMA 50 (downtrend).
• RSI > 65 (overbought).
• EMA 9 crosses below the price.
• The trade occurs after 14:30 UTC (New York session open).
How It Works:
• When a valid trade setup occurs, the strategy executes an entry order and automatically sets a Stop Loss (1.5x ATR) and Take Profit (2x SL).
• The SL and TP levels are dynamically adjusted based on market volatility.
• The script labels SL and TP directly on the chart for better tracking.
Recommended Settings:
• Market: EUR/USD
• Timeframe: 5 minutes
• Session: After 14:30 UTC (New York open)
🚀 Try it now and optimize your NY session trading!
Stoch RSI Buy and Sell Signal_Hemthis indicator is purely based on default values of stochastic rsi. it will generate buy and sell signall according to default values of stochastic rsi.
[COW] Tripple Backflip Confirmation"Im a simple man just trying to make my way in the galaxy..."
- Spock from the hit movie Spaceballs
An indicator I made to fit the strat that I and Santana_trades uses!
It uses a mix of the daily open/close ranges, daily bias for upside/downside, and the ema's for the 30 min, 60 min, and daily ranges. Configurable as all hell. Have fun!
<3 moo
True Macros ºTweaked version of ICT's Mcros and my personal way to use them.
OG Script and code is made by toodegres all credit to him.
Buy/Sell Reversal SignalsThe Buy/Sell Reversal Signals indicator is designed to identify potential buy and sell opportunities based on price reversals. It uses a moving average crossover strategy to detect changes in trend direction.
RSI+StRSI+RVI+MFI+DMI+CCI+MACDH+OBV+Ichimoku Milky Way// © expert-x
// Created: 2023-12-21
// Last modified: 2025-02-14
// Version 6.0
//@version=6
////////////////////////////////////////////////////////////////////////////////////////////////////
indicator(title = 'RSI+StRSI+RVI+MFI+DMI+CCI+MACDH+OBV+Ichimoku Milky Way', format = format.price, overlay = false, precision = 2, shorttitle = 'Multi+Tool Milky Way X')
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//////////////////////////////////////////// TOOLTIPS //////////////////////////////////////////////
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ENABLE_TOOLTIP = 'Включить/выключить'
ST1_ENABLE_TOOLTIP = 'Стратегия пересечения линией переворота, базовой линии'
ST2_ENABLE_TOOLTIP = 'Стратегия пересечения верховой линией 1, верховой линии 2'
TR_RT_ENABLE_TOOLTIP = 'Отключает отображенине ярлыков UP/Down Trend текущего таймфрейма'
TR_MTF_ENABLE_TOOLTIP = 'Отключает отображенине ярлыков UP/Down Trend дополнительных таймфреймов'
LAST_ENABLE_TOOLTIP = 'Удалит все ярлыки, кроме последних, по-каждому тайм-фрейму.'
TIMEFRAME_TOOLTIP = 'Выбор и активация дополнительного таймфрейма'
STYLE_TOOLTIP = 'Настройки цвета'
CCI_TOOLTIP = 'Как большинство осцилляторов, CCI был разработан, чтобы определять уровни перекупленности и перепроданности. Индикатор CCI делает это, измеряя отношение между ценой и Скользящей средней, или, если быть более точным, нормальные отклонения от этой Скользящей средней. Иными словами, CCI измеряет отклонение цены инструмента от ее среднестатистической цены. Индикатор CCI показывает, насколько текущая стоимость отклонилась от своего среднего значения. Высокие показатели говорят, что она намного выше стандартной. Низкие ― актив недооценен и вскоре станет дороже. Таким образом определяются зоны перекупленности и перепроданности, что является характерной чертой осцилляторов. CCI работает на всех таймфреймах и активах. Алгоритм прогнозирует разворот текущего тренда.'
RSI_TOOLTIP = 'RSI — это импульсный индикатор для технического трейдинга, который измеряет скорость изменения цены или данных. Увеличение импульса и рост цены указывают на активные покупки акций на рынке. При этом снижение импульса свидетельствует об увеличении давления продавцов. Кроме того, RSI позволяет трейдерам обнаружить признаки перепроданности и перекупленности рынка. Для этого цена актива оценивается по шкале от 0 до 100 за 14 периодов.'
STOCHASTIC_TOOLTIP = 'Стохастический RSI, или просто StochRSI - это индикатор технического анализа, используемый для определения того, перекуплен актив или перепродан, а также для определения текущих рыночных тенденций. Как следует из названия, StochRSI является производной от стандартного Индекса Относительной Силы (RSI) и как таковой, считается индикатором индикатора. Это тип осциллятора, означающий, что он колеблется выше и ниже центральной линии. ' + 'Впервые StochRSI был описан в 1994 году, в книге Новый Технический Трейдер Стэнли Кролла и Тушар Чанде. Она часто используется биржевыми трейдерами, но также может применяться и в других торговых аспектах, к примеру для торгов на Forex или криптовалютой. ' + 'Как работает StochRSI? Индикатор StochRSI генерируется из обычного RSI путем применения формулы Стохастического Осциллятора. Результатом является единый числовой рейтинг, который колеблется вокруг центральной линии (0,5) в диапазоне от 0 до 1. Однако существуют модифицированные версии StochRSI, которые умножают результаты на 100, поэтому значение находятся в диапазоне от 0 до 100 вместо 0 и 1. Также часто встречается 3-дневная простая скользящая средняя (SMA) вместе с линией StochRSI, которая выступает в качестве сигнала и предназначена для снижения торговых рисков. ' + 'Стандартная формула Стохастического Осциллятора учитывает цену закрытия актива, а также его самые высокие и самые низкие точки в течение определенного периода. Однако когда формула используется для расчета StochRSI, она непосредственно применяется к данным от RSI (цены не учитываются). ' + 'Stoch RSI = (Текущий RSI - Наименьший RSI)/(Наибольший RSI - Наименьший RSI) Как и в стандартном RSI, для StochRSI чаще всего используется настройка 14 периодов. 14 периодов, участвующих в расчете StochRSI, основаны на временных рамках графика. Таким образом, в то время как дневной график будет учитывать последние 14 дней (свечи), часовой график будет генерировать StochRSI на основе последних 14 часов. ' + 'Периоды могут быть установлены в днях, часах или даже минутах, и их использование значительно варьируется от трейдера к трейдеру (в зависимости от их стратегии). Количество периодов также может быть скорректировано вверх или вниз, чтобы определить долгосрочные или краткосрочные тренды. 20-периодная настройка, это еще один довольно популярный параметр для StochRSI. ' + 'Как уже упоминалось, некоторые графические шаблоны StochRSI присваивают значения в диапазоне от 0 до 100 вместо 0 до 1. На этих графиках центральная линия находится на уровне 50 вместо 0,5. Следовательно, сигнал перекупленности, который обычно возникает на уровне 0,8, будет обозначаться как 80, а сигнал перепроданности, на уровне 20, а не 0,2. Графики с настройкой от 0 до 100 могут выглядеть немного иначе, но практическая интерпретация по сути одна и та же. ' + 'Как использовать StochRSI? Индикатор StochRSI приобретает наибольшее значение вблизи верхних и нижних границ своего диапазона. Поэтому основное использование индикатора заключается в определении потенциальных точек входа и выхода, а также разворотов цен. Таким образом, значение 0,2 или ниже, указывает на то, что актив вероятнее всего перепродан, а значение 0,8 или выше предполагает, что он может быть перекуплен. ' + 'Кроме того, нахождение линий ближе к центру, также может предоставить полезную информацию относительно рыночных тенденций. Например, когда центральная линия выступает в качестве поддержки, а линии StochRSI постоянно движутся выше отметки 0,5, это может указывать на продолжение бычьего или восходящего тренда, особенно если линии начинают двигаться в направлении 0,8. Аналогично, последовательные колебания ниже 0,5 и отклонения к 0,2 указывают на нисходящий или медвежий тренд.'
MF_INDEX_TOOLTIP = 'Индикатор Money Flow Index (MFI) — это инструмент, используемый в техническом анализе для измерения давления покупки и продажи. Это делается путем анализа как цены, так и объёма. Расчет MFI генерирует значение, которое затем отображается как линия, которая перемещается в диапазоне 0-100, что делает его осциллятором. Когда MFI повышается, это указывает на увеличение покупательского давления.'
DMI_TOOLTIP = 'Что такое DMI: Индекс направленного движения (DMI) — это технический индикатор, используемый трейдерами для определения силы восходящего или нисходящего тренда на рынке. ' + 'Индекс направленного движения (DMI) — это технический индикатор, используемый трейдерами для определения силы восходящего или нисходящего тренда на рынке. Он включает в себя два индекса направления и обычно используется в тандеме с индексом среднего направления движения (ADX). Таким образом, DMI отображается в виде трех линий выше или ниже свечного графика. ' + 'Что такое DMI индикатор? DMI – индекс направленного движения – состоит из двух индексов направления: Plus Direction Indicator (также называемого индикатором положительного направления), обозначаемого DI+, и Minus Direction Indicator (также называемого индикатором отрицательного направления), обозначаемого DI-. Когда линия DI+ находится выше линии DI-, рынки находятся в бычьем тренде. И наоборот, когда линия DI- выше линии DI+, рынки находятся в медвежьем тренде. Когда линии показывают повторяющиеся пересечения — рынки находятся в нерешительности, и цены торгуются относительно стабильно. ' + 'Сами по себе индексы DMI не скажут вам слишком многого, чего вы не смогли бы понять, взглянув на стандартный свечной график. Некоторые трейдеры используют точки пересечения в качестве торгового сигнала, поскольку они указывают на разворот тренда. Однако индексы DMI также включают третью строку, называемую индексом среднего направления движения (ADX).'
ADX_TOOLTIP = 'Что такое ADX: Индекс среднего направления движения (ADX) представляет собой индикатор относительной силы направленного тренда, обозначенного DI+ и DI-. ' + 'Что такое ADX индикатор?ADX – индекс среднего направления движения – представляет собой индикатор относительной силы направленного тренда, обозначенного DI+ и DI-. Чтобы прочитать его, обратитесь к оси на диаграмме, которая показывает значение. В целом, значение ADX выше 25 указывает на то, что тренд относительно силен. Значение ниже 20 указывает на то, что тренд слабый или что рынки торгуются в боковом тренде. Также может случиться так, что рынки переживают период волатильности, и ADX не может определить четкий тренд ни в одном направлении. ' + 'Значения DMI и ADX определяются на основе диапазона ценовых движений за последние 14 торговых периодов. Существуют математические формулы, которые позволят вам самостоятельно рассчитать значения; однако это сложно и в значительной степени не нужно для большинства трейдеров. Все, что вам нужно знать, это как интерпретировать значения DMI и ADX на графике и использовать их в своих торговых сигналах. ' + 'Как использовать DMI и ADX в торговле. Вы можете видеть, что DMI и ADX представляются как один индикатор или как два отдельных индикатора, в зависимости от того, какие инструменты построения графиков вы используете. В Trading View при выборе среднего индекса направления отображается только график с линией ADX, тогда как при выборе индекса направленного движения отображается график как с линиями DI, так и с линией ADX. ' + 'Индикаторы положительного (DI+) и отрицательного (DI-) направления. Если вы планируете использовать DMI и ADX в торговле, вам понадобятся два важных индикатора. Первый — это точка, когда линии DI+ и DI- пересекаются друг с другом, что указывает на разворот тренда. ' + 'Тем не менее, вы должны быть осторожны, если линии DI+ и DI- уже пересекались несколько раз в предыдущие торговые периоды или проходят очень близко друг к другу, так как это указывает на то, что рынки не определились и ни быки, ни медведи не контролируют ситуацию. Чем дальше друг от друга находятся линии DI+ и DI-, тем сильнее индикатор тренда. ' + 'Откуда взялись DMI и ADX? Индикаторы DMI и ADX были разработаны в 1970-х годах американским техническим аналитиком Дж. Уэллсом Уайлдером, автором книги «Новые концепции технических торговых систем». Он изобрел несколько технических индикаторов, которые сейчас используются трейдерами по всему миру, в том числе индекс относительной силы и Parabolic SAR.'
RVI_TOOLTIP = 'Индекс относительной волатильности - RVI. Технический индикатор RVI был разработан Дональдом Дорси в 1993 году, а затем описан в журнале Technical Analysis of Stocks and Commodities. В 1995 году индикатор был преобразован автором, и его обновленная версия была использована для анализа. По словам Дорси, индикатор RVI не является независимым инструментом технического анализа и может использоваться либо в качестве фильтра для других индикаторов, либо в качестве инструмента для указания на намерения, но не на возможности реализации ценовых моделей. ' + 'Торговое использование. ' + 'Главное преимущество RVI заключается в том, что он основан на индексе RSI и учитывает все уровни диверсификации, которые могут быть опущены RSI. Тем не менее, RVI является изменчивым индикатором, но не классическим осциллятором, поэтому неразумно использовать его независимо. Как следствие, лучше сочетать сигналы RVI с осцилляторными сигналами технического анализа, например, индикатором RSI. ' + 'В случае, если индикатор RSI попадет в зону перепроданности, преодолевая 70% вместе с RVI, мы получаем мощный сигнал о том, что повышение цен скоро закончится и начнется снижение. ' + 'Кроме того, если и индикаторы RSI, и RVI опадают ниже уровня 30%, другими словами, попадают в зону перекупленности, необходимо быть готовым к росту цен. В соответствии с этим лучше использовать комбинацию этих двух показателей, чем применять их самостоятельно. ' + 'Когда RSI составляет более 70% или менее 30%, но RVI не подтверждает эти сигналы, лучше подождать, пока оба из них не покажут похожую картину, прежде чем открыть позицию. ' + 'Другим вариантом применения RVI является выявление расхождений и конвергенции с ценой. Если цена идет вверх, пока индекс падает, это указывает на то, что цена скоро снизится (случай расхождения). ' + 'Противоположная ситуация также верна для жизни: индекс падает, в то время как цена растет, что свидетельствует об ускорении цены (случай конвергенции). ' + 'Формирование этих сигналов более актуально, когда RVI находится в зоне перекупленной или перепроданной. Но даже если индекс RVI попадет в нейтральную зону (между 30%-70%), сигналы расхождения/конвергенции также будут показательными. ' + 'Учитывая, что RVI рассматривает больший масштаб параметров, чем индекс RSI, сигналы, полученные с помощью RVI, будут намного лучше.'
forceoverlay_tooltip = 'Данный параметр, отобразит этикетки Лонг/Шорт непосредственно на основном графике'
////////////////////////////////////////////////////////////////////////////////////////////////////
///////////////////////////////////////////// GROUPS ///////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////
cci_set_group = 'CCI setup'
components = 'enable/disable components'
rd_algorithm_1_group = 'Long/Short Algorithm "CCI"'
rd_algorithm_2_group = 'Long/Short Algorithm "DMI & ADX"'
rd_algorithm_3_group = 'Long/Short Algorithm "STRSI"'
rd_algorithm_4_group = 'Long/Short Algorithm "EMA GC/DC"'
rd_algorithm_5_group = 'Long/Short Algorithm "MACD HISTOGRAM"'
rd_algorithm_6_group = 'Long/Short Algorithm "CCI"'
rd_algorithm_7_group = 'Long/Short Algorithm "OBV"'
rd_close_algorithm_group = 'Long/Short Close position algorithm'
rd_long_short_group = 'Long/Short strategy modul'
rd_ma_set = 'MA Settings'
rd_macd_group = 'MACD HISTOGRAM'
rd_mfi_set_group = 'Money Flow Index (MFI) setup'
rvi_group = 'Relative Volatility Index'
trend_group = 'Ichimoku UP/Down Trend'
// Рассчитываем нулевую линию
cci_zero_line = 50
dmiadx_zero_line = 75
macd_zero_line = 0
mfi_zero_line = 100
rsi_zero_line = 50
rvi_zero_line = 50
strsi_zero_line = 100
////////////////////////////////////////////////////////////////////////////////////////////////////
//////////////////////////////////////////// COMPONENTS ////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////
show_trend_01_module_input = input.bool(true, title = 'Show Ichimoku trending strategy 1', group = components, tooltip = ST1_ENABLE_TOOLTIP)
show_trend_02_module_input = input.bool(false, title = 'Show Ichimoku trending strategy 2', group = components, tooltip = ST2_ENABLE_TOOLTIP)
show_rsi_modul_input = input.bool(true, title = 'Show "RSI" modul', group = components, tooltip = RSI_TOOLTIP)
show_rsi_ma_plot_input = input.bool(true, title = 'Show "RSI" smoothing line', group = components, tooltip = RSI_TOOLTIP)
show_rsi_divergence = input.bool(false, title = 'Show Divergence', group = components, tooltip = RSI_TOOLTIP)
show_stoc_rsi_modul_input = input.bool(true, title = 'Show "Stochastic RSI" modul', group = components, tooltip = STOCHASTIC_TOOLTIP)
show_rvi_modul_input = input.bool(false, title = 'Show "RVI" modul', group = components, tooltip = RVI_TOOLTIP)
show_rvi_ma_plot_input = input.bool(false, title = 'Show "RVI" smoothing line', group = components, tooltip = RVI_TOOLTIP)
show_rd_modul_input = input.bool(false, title = 'Show "DMI & ADX" modul', group = components, tooltip = DMI_TOOLTIP)
show_mfi_modul_input = input.bool(false, title = 'Show "MFI" modul', group = components, tooltip = MF_INDEX_TOOLTIP)
show_cci_modul_input = input.bool(true, title = 'Show "CCI" modul', group = components, tooltip = CCI_TOOLTIP)
show_cci_ma_plot_input = input.bool(true, title = 'Show "CCI" smoothing line', group = components, tooltip = CCI_TOOLTIP)
show_macd_histo_modul_input = input.bool(true, title = 'Show "MACD Histogram" modul', group = components, tooltip = ENABLE_TOOLTIP)
show_long_short_modul_input = input.bool(true, title = 'Show "Long/Short" strategy modul', group = components, tooltip = ENABLE_TOOLTIP)
////////////////////////////////////////////////////////////////////////////////////////////////////
///////////////////////////////////////////// Ichimoku Trend X /////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////
conversionPeriods = input.int(13, minval = 1, title = 'Длина линии переворота', group = trend_group)
basePeriods = input.int(60, minval = 1, title = 'Длина линии стандарта', group = trend_group)
laggingSpan2Periods = input.int(60, minval = 1, title = 'Длина верховой линии 2', group = trend_group)
displacement = input.int(21, minval = 1, title = 'Опаздывающая линия', group = trend_group)
donchian(len) =>
math.avg(ta.lowest(len), ta.highest(len))
conversionLine = donchian(conversionPeriods)
baseLine = donchian(basePeriods)
leadLine1 = math.avg(conversionLine, baseLine)
leadLine2 = donchian(laggingSpan2Periods)
base_offset = displacement - 1
contr_offset = -displacement + 1
////////////////////////////////////////////////////////////////////////////////////////////////////
plot(conversionLine, color = color.new(#2962FF, 0), title = 'Conversion Line', linewidth = 3, style = plot.style_line, display = display.none, force_overlay = true)
plot(baseLine, color = color.new(#B71C1C, 0), title = 'Base Line', linewidth = 3, style = plot.style_line, display = display.none, force_overlay = true)
plot(close, offset = contr_offset, color = #43A047, title = 'Lagging Span Line', linewidth = 3, style = plot.style_line, display = display.none, force_overlay = true)
p1 = plot(leadLine1, offset = base_offset, color = #A5D6A7, title = 'Leading Span Line 1', linewidth = 3, style = plot.style_line, display = display.none, force_overlay = true)
p2 = plot(leadLine2, offset = base_offset, color = #EF9A9A, title = 'Leading Span Line 2', linewidth = 3, style = plot.style_line, display = display.none, force_overlay = true)
kumo_cloud_upper_line = leadLine1 > leadLine2 ? leadLine1 : leadLine2
kumo_cloud_lower_line = leadLine1 < leadLine2 ? leadLine1 : leadLine2
plot(kumo_cloud_upper_line, offset = base_offset, title = 'Kumo Cloud Upper Line', force_overlay = true)
plot(kumo_cloud_lower_line, offset = base_offset, title = 'Kumo Cloud Lower Line', force_overlay = true)
fill(p1, p2, color = leadLine1 > leadLine2 ? color.rgb(67, 160, 71, 75) : color.rgb(244, 67, 54, 75))
downtrend_01 = ta.crossover(baseLine, conversionLine)
uptrend_01 = ta.crossunder(baseLine, conversionLine)
downtrend_02 = ta.crossover(leadLine1, leadLine2)
uptrend_02 = ta.crossunder(leadLine1, leadLine2)
uptrend_01_label_color_input = input.color(color.new(#1b5e20, 0), title = 'label uptrend_01', inline = 'trend_color1', group = trend_group, tooltip = STYLE_TOOLTIP)
downtrend_01_label_color_input = input.color(color.new(#e65100, 0), title = 'downtrend_01', inline = 'trend_color1', group = trend_group, tooltip = STYLE_TOOLTIP)
uptrend_02_label_color_input = input.color(color.new(#1b5e20, 0), title = 'label uptrend_02', inline = 'trend_color2', group = trend_group, tooltip = STYLE_TOOLTIP)
downtrend_02_label_color_input = input.color(color.new(#e65100, 0), title = 'downtrend_02', inline = 'trend_color2', group = trend_group, tooltip = STYLE_TOOLTIP)
label_textcolor_input = input.color(color.new(color.white, 5), title = 'label font color ', group = trend_group, tooltip = STYLE_TOOLTIP)
only_last_label = input.bool(false, title = 'Show only last label', group = trend_group, tooltip = LAST_ENABLE_TOOLTIP)
////////////////////////////////////////////////////////////////////////////////////////////////////
if show_trend_01_module_input ? downtrend_01 : bool(na)
label_downtrend_01 = label.new(x = na, y = na, text = '', force_overlay = true)
label.set_xy(label_downtrend_01, x = bar_index, y = low)
label.set_text(label_downtrend_01, text = 'DownTrend1⬇ Ichimoku ' + 'TF' + str.tostring(timeframe.period))
label.set_yloc(label_downtrend_01, yloc = yloc.abovebar)
label.set_color(label_downtrend_01, color = downtrend_01_label_color_input)
label.set_style(label_downtrend_01, style = label.style_label_down)
label.set_textcolor(label_downtrend_01, textcolor = label_textcolor_input)
label.set_size(label_downtrend_01, size = size.small)
label.set_textalign(label_downtrend_01, textalign = text.align_center)
label.set_tooltip(label_downtrend_01, tooltip = 'Down Trend')
if only_last_label
label.delete(label_downtrend_01 )
else
na
if show_trend_01_module_input ? uptrend_01 : bool(na)
label_uptrend_01 = label.new(x = na, y = na, text = '', force_overlay = true)
label.set_xy(label_uptrend_01, x = bar_index, y = low)
label.set_text(label_uptrend_01, text = 'UpTrend1⬆ Ichimoku ' + 'TF' + str.tostring(timeframe.period))
label.set_yloc(label_uptrend_01, yloc = yloc.belowbar)
label.set_color(label_uptrend_01, color = uptrend_01_label_color_input)
label.set_style(label_uptrend_01, style = label.style_label_up)
label.set_textcolor(label_uptrend_01, textcolor = label_textcolor_input)
label.set_size(label_uptrend_01, size = size.small)
label.set_textalign(label_uptrend_01, textalign = text.align_center)
label.set_tooltip(label_uptrend_01, tooltip = 'Up Trend')
if only_last_label
label.delete(label_uptrend_01 )
else
na
////////////////////////////////////////////////////////////////////////////////////////////////////
if show_trend_02_module_input ? downtrend_02 : bool(na) // and kumo_cloud_lower_line > open
label_downtrend_02 = label.new(x = na, y = na, text = '', force_overlay = true)
label.set_xy(label_downtrend_02, x = bar_index + base_offset, y = low)
label.set_text(label_downtrend_02, text = 'DownTrend2⬇ Ichimoku ' + 'TF' + str.tostring(timeframe.period))
label.set_yloc(label_downtrend_02, yloc = yloc.abovebar)
label.set_color(label_downtrend_02, color = downtrend_02_label_color_input)
label.set_style(label_downtrend_02, style = label.style_label_down)
label.set_textcolor(label_downtrend_02, textcolor = label_textcolor_input)
label.set_size(label_downtrend_02, size = size.small)
label.set_textalign(label_downtrend_02, textalign = text.align_center)
label.set_tooltip(label_downtrend_02, tooltip = 'Down Trend')
if only_last_label
label.delete(label_downtrend_02 )
else
na
if show_trend_02_module_input ? uptrend_02 : bool(na) // and kumo_cloud_upper_line < open
label_uptrend_02 = label.new(x = na, y = na, text = '', force_overlay = true)
label.set_xy(label_uptrend_02, x = bar_index + base_offset, y = low)
label.set_text(label_uptrend_02, text = 'UpTrend2⬆ Ichimoku ' + 'TF' + str.tostring(timeframe.period))
label.set_yloc(label_uptrend_02, yloc = yloc.belowbar)
label.set_color(label_uptrend_02, color = uptrend_02_label_color_input)
label.set_style(label_uptrend_02, style = label.style_label_up)
label.set_textcolor(label_uptrend_02, textcolor = label_textcolor_input)
label.set_size(label_uptrend_02, size = size.small)
label.set_textalign(label_uptrend_02, textalign = text.align_center)
label.set_tooltip(label_uptrend_02, tooltip = 'Up Trend')
if only_last_label
label.delete(label_uptrend_02 )
else
na
////////////////////////////////////////////////////////////////////////////////////////////////////
highUsePivot = fixnan(ta.pivothigh(15, 15) )
lowUsePivot = fixnan(ta.pivotlow(15, 15) )
volumeThresh = 20
shortVolume = ta.ema(volume, 5)
longVolume = ta.ema(volume, 10)
osc = 100 * (shortVolume - longVolume) / longVolume
////////////////////////////////////////////////////////////////////////////////////////////////////
/////////////////////////////////////////// LONG/SHORT INPUT ///////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////
rd_consider_algo_1_input = input.bool(false, title = 'Activate CCI algorithm', group = rd_algorithm_1_group, tooltip = ENABLE_TOOLTIP)
rd_factor_rsi_open_long_algo_1_input = input.int(42, title = 'Factor RSI open Long', group = rd_algorithm_1_group, minval = 20, maxval = 50)
rd_factor_rsi_open_short_algo_1_input = input.int(58, title = 'Factor RSI open Short', group = rd_algorithm_1_group, minval = 51, maxval = 80)
cci_length = input.int(20, title = 'Length', minval = 1, group = rd_algorithm_1_group)
cci_src = input.source(hlc3, title = 'Source', group = rd_algorithm_1_group)
cci_plot_color_input = input.color(color.new(#4caf50, 0), title = 'CCI line color', group = rd_algorithm_1_group, tooltip = STYLE_TOOLTIP)
cci_smoothing_plot_color_input = input.color(color.new(#3179f5, 0), title = 'CCI smoothing line color', group = rd_algorithm_1_group, tooltip = STYLE_TOOLTIP)
cci_ma = ta.sma(cci_src, cci_length)
cci = (cci_src - cci_ma) / (0.15 * ta.dev(cci_src, cci_length)) // fill(cci_band1, cci_band0, color=color.rgb(33, 150, 243, 90), title="Background")
cci_ma(source, cci_length, type) =>
switch type
'SMA' => ta.sma(source, cci_length)
'EMA' => ta.ema(source, cci_length)
'SMMA (RMA)' => ta.rma(source, cci_length)
'WMA' => ta.wma(source, cci_length)
'VWMA' => ta.vwma(source, cci_length)
cci_typeMA = input.string(defval = 'SMMA (RMA)', title = 'Method', options = , group = rd_algorithm_1_group)
cci_smoothingLength = input.int(5, title = 'Length', minval = 1, maxval = 100, group = rd_algorithm_1_group)
cci_smoothingLine = cci_ma(cci, cci_smoothingLength, cci_typeMA)
cci_cross = ta.cross(cci, cci_smoothingLine)
plot(show_cci_modul_input ? cci + rsi_zero_line - cci_zero_line : na, color = cci_plot_color_input, title = 'CCI', linewidth = 3)
plot(show_cci_modul_input ? show_cci_ma_plot_input ? cci_smoothingLine + rsi_zero_line - cci_zero_line : na : na, color = cci_smoothing_plot_color_input, title = 'CCI Smoothing Line', linewidth = 3) // , display=display.none
////////////////////////////////////////////////////////////////////////////////////////////////////
rd_consider_algo_2_input = input.bool(false, title = 'Activate RSI algorithm', group = rd_algorithm_2_group, tooltip = ENABLE_TOOLTIP)
rd_factor_rsi_open_long_algo_2_input = input.int(30, title = 'Factor RSI open Long (1 - 50)', group = rd_algorithm_2_group, minval = 1, maxval = 50)
rd_factor_rsi_open_short_algo_2_input = input.int(70, title = 'Factor RSI open Short (50 - 100)', group = rd_algorithm_2_group, minval = 50, maxval = 100)
rd_ma(source, length, type) =>
switch type
'SMA' => ta.sma(source, length)
'Bollinger Bands' => ta.sma(source, length)
'EMA' => ta.ema(source, length)
'SMMA (RMA)' => ta.rma(source, length)
'WMA' => ta.wma(source, length)
'VWMA' => ta.vwma(source, length)
rd_rsi_length_input = input.int(19, title = 'RSI Length', group = rd_algorithm_2_group, minval = 1)
rd_rsi_plot_color_input = input.color(color.new(#b2b5be, 65), title = 'RSI plot color', group = rd_algorithm_2_group, tooltip = STYLE_TOOLTIP)
rd_rsi_source_input = input.source(close, title = 'Source', group = rd_algorithm_2_group)
rd_ma_type_input = input.string('Bollinger Bands', title = 'Method', group = rd_algorithm_2_group, options = )
rd_ma_length_input = input.int(5, title = 'MA Length', group = rd_algorithm_2_group)
rd_bb_mult_input = input.float(4.0, title = 'BB StdDev', group = rd_algorithm_2_group, minval = 0.001, maxval = 50)
rd_ma_plot_color_input = input.color(color.new(#787b86, 30), title = 'RSI-based MA plot color', group = rd_algorithm_2_group, tooltip = STYLE_TOOLTIP)
rd_RSI_Highest_Band_color = input.color(color.new(#ff5252, 30), title = 'RSI highest band', group = rd_algorithm_2_group, tooltip = STYLE_TOOLTIP)
rd_RSI_Upper_Band_color = input.color(color.new(color.white, 25), title = 'RSI upper band', group = rd_algorithm_2_group, tooltip = STYLE_TOOLTIP)
rd_MID_line_Band_color = input.color(color.new(color.white, 75), title = 'RSI middle band', group = rd_algorithm_2_group, tooltip = STYLE_TOOLTIP)
rd_RSI_Lower_Band_color = input.color(color.new(color.white, 25), title = 'RSI lower band', group = rd_algorithm_2_group, tooltip = STYLE_TOOLTIP)
rd_RSI_lowest_Band_color = input.color(color.new(color.green, 30), title = 'RSI lowest band', group = rd_algorithm_2_group, tooltip = STYLE_TOOLTIP)
rd_Fill_Color = input.color(color.new(#311b92, 70), title = 'RSI Background Fill', group = rd_algorithm_2_group, tooltip = STYLE_TOOLTIP)
rd_BB_Fill_Color = input.color(color.new(#5b9cf6, 75), title = 'Bollinger Bands Background Fill', group = rd_algorithm_2_group, tooltip = STYLE_TOOLTIP)
////////////////////////////////////////////////////////////////////////////////////////////////////
rd_consider_algo_3_input = input.bool(false, title = 'Activate STRSI algorithm', group = rd_algorithm_3_group, tooltip = ENABLE_TOOLTIP)
rd_factor_strsi_open_long_algo_3_input = input.int(10, title = 'Factor ST RSI open Long (1 - 50)', group = rd_algorithm_3_group, minval = 1, maxval = 100)
rd_factor_strsi_open_short_algo_3_input = input.int(90, title = 'Factor ST RSI open Short(50 - 100)', group = rd_algorithm_3_group, minval = 1, maxval = 100)
rd_strsi_smooth_k_input = input.int(4, title = 'K', group = rd_algorithm_3_group, minval = 1)
rd_strsi_smoot_d_input = input.int(3, title = 'D', group = rd_algorithm_3_group, minval = 1)
//rd_strsi_length_rsi_input = input.int(19, title = 'RSI Length', group = rd_algorithm_3_group, minval = 1)
rd_strsi_length_stoch_input = input.int(15, title = 'Stochastic Length', group = rd_algorithm_3_group, minval = 1)
//rd_strsi_src_input = input(close, title = 'RSI Source', group = rd_algorithm_3_group)
rd_strsi_plot_k_color_input = input.color(color.new(#2962FF, 5), title = 'Stochastic RSI(K) plot color', group = rd_algorithm_3_group, tooltip = STYLE_TOOLTIP)
rd_strsi_plot_d_color_input = input.color(color.new(#FF6D00, 5), title = 'Stochastic RSI(D) plot color', group = rd_algorithm_3_group, tooltip = STYLE_TOOLTIP)
////////////////////////////////////////////////////////////////////////////////////////////////////
rd_consider_algo_4_input = input.bool(false, title = 'Activate DMI & ADX algorithm', group = rd_algorithm_4_group, tooltip = ENABLE_TOOLTIP)
rd_factor_rsi_open_long_algo_4_input = input.int(35, title = 'Factor RSI open Long', group = rd_algorithm_4_group, minval = 1, maxval = 100)
rd_factor_rsi_open_short_algo_4_input = input.int(65, title = 'Factor RSI open Short', group = rd_algorithm_4_group, minval = 1, maxval = 100)
dmi_lensig = 19 //input.int(19, title = 'ADX Smoothing', group = rd_algorithm_4_group, minval = 1, maxval = 50) //14
dmi_len = 15 //input.int(15, minval=1, title = 'DI Length', group = rd_algorithm_4_group) //14
dmi_plot_adx_color_input = input.color(color.new(color.white, 10), title = 'ADX plot color', group = rd_algorithm_4_group, tooltip = STYLE_TOOLTIP) //#d1d4dc
dmi_plot_di_plus_color_input = input.color(color.new(#388e3c, 0), title = 'DI + plot color', group = rd_algorithm_4_group, tooltip = STYLE_TOOLTIP)
dmi_plot_di_minus_color_input = input.color(color.new(#f23645, 0), title = 'DI - plot color', group = rd_algorithm_4_group, tooltip = STYLE_TOOLTIP)
////////////////////////////////////////////////////////////////////////////////////////////////////
///////////////////////////////////////////// MACD HISTOGRAM ///////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////
rd_consider_algo_5_input = input.bool(true, title = 'Activate MACD HISTOGRAM algorithm', group = rd_algorithm_5_group, tooltip = ENABLE_TOOLTIP)
rd_strsi_smooth_ls_input = input.int(15, title = 'K', group = rd_algorithm_5_group, minval = 1)
rd_factor_strsi_open_long_algo_5_input = input.int(37, title = 'Factor ST RSI open Long (1 - 50)', group = rd_algorithm_5_group, minval = 1, maxval = 100)
rd_factor_strsi_open_short_algo_5_input = input.int(63, title = 'Factor ST RSI open Short(50 - 100)', group = rd_algorithm_5_group, minval = 1, maxval = 100)
macd_fastlength = input.int(12, title = 'MACD fast length', group = rd_algorithm_5_group, minval = 1)
macd_slowlength = input.int(26, title = 'MACD slow length', group = rd_algorithm_5_group, minval = 1)
macd_signallength = input.int(9, title = 'MACD signal length', group = rd_algorithm_5_group, minval = 1)
macd_source = close
macd_histo_color_1 = color.new(color.lime, 70)
macd_histo_color_2 = color.new(color.green, 70)
macd_histo_color_3 = color.new(color.maroon, 70)
macd_histo_color_4 = color.new(color.red, 70)
macd_fastma = ta.ema(macd_source, macd_fastlength)
macd_slowma = ta.ema(macd_source, macd_slowlength)
macd_line = macd_fastma - macd_slowma
macd_signal = ta.ema(macd_line, macd_signallength)
macd_histo = macd_line - macd_signal
macd_plotcolor = if macd_histo > 0
macd_histo > macd_histo ? macd_histo_color_1 : macd_histo_color_2
else
macd_histo < macd_histo ? macd_histo_color_3 : macd_histo_color_4
// Определяем значения для верхней и нижней границы RSI
rsi_upper_bound = 100
rsi_lower_bound = 0
// Рассчитываем значения MACD гистограммы, ограничивая их между границами RSI
macd_histo_bounded = macd_histo
if macd_histo > 0
macd_histo_bounded := math.min(macd_histo, rsi_upper_bound - rsi_zero_line + macd_zero_line)
macd_histo_bounded
else
macd_histo_bounded := math.max(macd_histo, rsi_lower_bound - rsi_zero_line + macd_zero_line)
macd_histo_bounded
plot(show_macd_histo_modul_input ? macd_histo_bounded : na, title = 'MACD', color = macd_plotcolor, style = plot.style_area)
////////////////////////////////////////////////////////////////////////////////////////////////////
///////////////////////////////////////////// OBV INPUTS ///////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////
// obv_plot_color_input = input.color(color.new(#2962FF, 5), title = 'OBV line color', group = rd_algorithm_6_group, tooltip = STYLE_TOOLTIP) //rd_obv_group
// obv_smoothing_plot_color_input = input.color(color.new(#f37f20, 5), title = 'OBV smoothing line color', group = rd_algorithm_6_group, tooltip = STYLE_TOOLTIP)
rd_consider_algo_6_input = input.bool(true, title = 'Activate OBV algorithm', group = rd_algorithm_6_group, tooltip = ENABLE_TOOLTIP)
rd_factor_rsi_open_long_algo_6_input = input.int(42, title = 'Factor RSI open Long', group = rd_algorithm_6_group, minval = 1, maxval = 100)
rd_factor_rsi_open_short_algo_6_input = input.int(58, title = 'Factor RSI open Short', group = rd_algorithm_6_group, minval = 1, maxval = 100)
obv_type_ma = input.string(defval = 'SMMA (RMA)', title = 'OBV smoothing method', options = , group = rd_algorithm_6_group)
obv_smoothing_length = input.int(10, title = 'OBV smoothing Length', group = rd_algorithm_6_group, minval = 1, maxval = 100)
obv_src = input.source(close, title = 'Source', group = rd_algorithm_6_group)
var obv_cumvol = 0.
obv_cumvol := obv_cumvol + nz(volume)
if obv_cumvol == 0
runtime.error('Поставщик данных не предоставляет объем.')
obv = ta.cum(math.sign(ta.change(obv_src)) * volume)
obv_ma(source, length, type) =>
switch type
'SMA' => ta.sma(source, length)
'EMA' => ta.ema(source, length)
'SMMA (RMA)' => ta.rma(source, length)
'WMA' => ta.wma(source, length)
'VWMA' => ta.vwma(source, length)
obv_smoothing_line = obv_ma(obv, obv_smoothing_length, obv_type_ma)
////////////////////////////////////////////////////////////////////////////////////////////////////
rd_OpenLong_label_color_input = input.color(color.new(#1b5e20, 0), title = 'Open Long Label color', group = rd_long_short_group, tooltip = STYLE_TOOLTIP)
rd_OpenShort_label_color_input = input.color(color.new(#e65100, 10), title = 'Open Short Label color', group = rd_long_short_group, tooltip = STYLE_TOOLTIP)
rd_Openlabel_textcolor_input = input.color(color.new(color.white, 10), title = 'Open Label font color', group = rd_long_short_group, tooltip = STYLE_TOOLTIP)
rd_CloseLong_label_color_input = input.color(color.new(#1b5e20, 0), title = 'Close Long Label color', group = rd_long_short_group, tooltip = STYLE_TOOLTIP)
rd_CloseShort_label_color_input = input.color(color.new(#e65100, 0), title = 'Close Short Label color', group = rd_long_short_group, tooltip = STYLE_TOOLTIP)
rd_Closelabel_textcolor_input = input.color(color.new(color.white, 20), title = 'Close Label font color', group = rd_long_short_group, tooltip = STYLE_TOOLTIP)
rd_OpenLong_label_txt = 'LONG'
rd_OpenShort_label_txt = 'SHORT'
rd_CloseLong_label_txt = 'SHORT'
rd_CloseShort_label_txt = 'LONG'
////////////////////////////////////////////////////////////////////////////////////////////////////
///////////////////////////////////////////// MFI INPUTS ///////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////
rd_mfi_length = input.int(19, title = 'MFI Length', group = rd_mfi_set_group, minval = 1, maxval = 2000)
rd_mfi_plot_color = input.color(color.new(#9598a1, 10), title = 'MFI plot color', group = rd_mfi_set_group, tooltip = STYLE_TOOLTIP)
rd_mfi_source_input = input.source(hlc3, title = 'Source', group = rd_mfi_set_group)
rd_mfi_src = hlc3
rd_mfi_mf = ta.mfi(rd_mfi_source_input, rd_mfi_length)
plot(show_mfi_modul_input ? rd_mfi_mf + rsi_zero_line - mfi_zero_line : na, title = 'MFI', color = rd_mfi_plot_color, linewidth = 1, style = plot.style_histogram)
////////////////////////////////////////////////////////////////////////////////////////////////////
///////////////////////////////////////////// RSI //////////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////
rd_up = ta.rma(math.max(ta.change(rd_rsi_source_input), 0), rd_rsi_length_input)
rd_down = ta.rma(-math.min(ta.change(rd_rsi_source_input), 0), rd_rsi_length_input)
rd_rsi = rd_down == 0 ? 100 : rd_up == 0 ? 0 : 100 - 100 / (1 + rd_up / rd_down)
rd_rsi_ma = rd_ma(rd_rsi, rd_ma_length_input, rd_ma_type_input)
rd_is_BB = rd_ma_type_input == 'Bollinger Bands'
rd_rsi_plot = plot(show_rsi_modul_input ? rd_rsi - rsi_zero_line : na, title = 'RSI', color = rd_rsi_plot_color_input, linewidth = 2, style = plot.style_columns) //style = plot.style_cross
rd_MA_Plot = plot(show_rsi_modul_input ? show_rsi_ma_plot_input ? rd_rsi_ma - rsi_zero_line : na : na, title = 'RSI Smoothing Line', color = rd_ma_plot_color_input, linewidth = 2)
rd_RSI_Highest_Band = hline(90 - rsi_zero_line, title = '', color = rd_RSI_Highest_Band_color, linewidth = 1, linestyle = hline.style_solid, editable = false, display = display.none)
rd_RSI_Upper_Band = hline(70 - rsi_zero_line, title = '', color = rd_RSI_Upper_Band_color, linewidth = 1, linestyle = hline.style_dotted, editable = false, display = display.none)
rd_MID_line_Band = hline(50 - rsi_zero_line, title = '', color = rd_MID_line_Band_color, linewidth = 1, linestyle = hline.style_solid, editable = false, display = display.none)
rd_RSI_Lower_Band = hline(30 - rsi_zero_line, title = '', color = rd_RSI_Lower_Band_color, linewidth = 1, linestyle = hline.style_dotted, editable = false, display = display.none)
rd_RSI_lowest_Band = hline(10 - rsi_zero_line, title = '', color = rd_RSI_lowest_Band_color, linewidth = 1, linestyle = hline.style_solid, editable = false, display = display.none)
fill(rd_RSI_Upper_Band, rd_RSI_Lower_Band, color = rd_Fill_Color, title = 'RSI Background Fill', fillgaps = true, editable = false)
rd_BB_Upper_Band = plot(show_rsi_modul_input and rd_is_BB ? show_rsi_ma_plot_input ? rd_rsi_ma - rsi_zero_line + ta.stdev(rd_rsi, rd_ma_length_input) * rd_bb_mult_input : na : na, title = 'RSI Upper Bollinger Band', color = color.new(#90bff9, 0), editable = false)
rd_BB_Lower_Band = plot(show_rsi_modul_input and rd_is_BB ? show_rsi_ma_plot_input ? rd_rsi_ma - rsi_zero_line - ta.stdev(rd_rsi, rd_ma_length_input) * rd_bb_mult_input : na : na, title = 'RSI Lower Bollinger Band', color = color.new(#90bff9, 0), editable = false)
fill(rd_BB_Upper_Band, rd_BB_Lower_Band, color = rd_is_BB ? show_rsi_ma_plot_input ? rd_BB_Fill_Color : na : na, title = 'RSI Bollinger Bands Background Fill', editable = false, fillgaps = true)
rd_MID_Line_Plot = plot(50 - rsi_zero_line, color = na, title = 'RSI Middle Bollinger Band', editable = false, display = display.none)
fill(rd_rsi_plot, rd_MID_Line_Plot, 100 - rsi_zero_line, 70 - rsi_zero_line, top_color = color.new(color.green, 0), bottom_color = color.new(color.green, 100), title = 'RSI Overbought Gradient Fill')
fill(rd_rsi_plot, rd_MID_Line_Plot, 30 - rsi_zero_line, 0 - rsi_zero_line, top_color = color.new(color.red, 100), bottom_color = color.new(color.red, 0), title = 'RSI Oversold Gradient Fill')
////////////////////////////////////////////////////////////////////////////////////////////////////
///////////////////////////////////////////// STOCHASTIC RSI ///////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////
//rd_rsi = ta.rsi(rd_strsi_src_input, rd_strsi_length_rsi_input)
rd_strsi_k = ta.sma(ta.stoch(rd_rsi, rd_rsi, rd_rsi, rd_strsi_length_stoch_input), rd_strsi_smooth_k_input)
rd_strsi_d = ta.sma(rd_strsi_k, rd_strsi_smoot_d_input)
rd_strsi_macdh = ta.sma(ta.stoch(rd_rsi, rd_rsi, rd_rsi, rd_strsi_length_stoch_input), rd_strsi_smooth_ls_input)
plot(show_stoc_rsi_modul_input ? rd_strsi_k + rsi_zero_line - strsi_zero_line : na, title = 'STRSI K', color = rd_strsi_plot_k_color_input, linewidth = 1)
plot(show_stoc_rsi_modul_input ? rd_strsi_d + rsi_zero_line - strsi_zero_line : na, title = 'STRSI D', color = rd_strsi_plot_d_color_input, linewidth = 1)
////////////////////////////////////////////////////////////////////////////////////////////////////
///////////////////////////////////////////// RELATIVE VOLATILITY INDEX (RVI) INPUTS ///////////////
////////////////////////////////////////////////////////////////////////////////////////////////////
rvi_plot_color_input = input.color(color.new(#b2b5be, 15), title = 'RVI plot color', group = rvi_group, tooltip = STYLE_TOOLTIP)
rvi_ma_plot_color_input = input.color(color.new(#5b9cf6, 15), title = 'RVI Smoothing Line color', group = rvi_group, tooltip = STYLE_TOOLTIP)
rvi_length = input.int(10, minval = 1, group = rvi_group)
rvi_offset = input.int(0, 'Offset', minval = -500, maxval = 500, group = rvi_group)
rvi_matypeinput = input.string('SMA', title = 'MA Type', options = , group = rvi_group)
rvi_marvi_lengthinput = input.int(14, title = 'RVI MA Length', group = rvi_group)
rvi_bbmultinput = input.float(2.0, minval = 0.001, maxval = 50, title = 'BB StdDev', group = rvi_group)
rvi_src = input.source(close, 'Source', group = rvi_group)
rvi_len = input.int(14, title = 'RVI lenght', group = rvi_group)
rvi_stddev = ta.stdev(rvi_src, rvi_length)
rvi_upper = ta.ema(ta.change(rvi_src) <= 0 ? 0 : rvi_stddev, rvi_len)
rvi_lower = ta.ema(ta.change(rvi_src) > 0 ? 0 : rvi_stddev, rvi_len)
rvi = rvi_upper / (rvi_upper + rvi_lower) * 100
ma(source, rvi_length, type) =>
switch type
'SMA' =>
'Bollinger Bands' =>
= ta.bb(source, rvi_length, rvi_bbmultinput)
'EMA' =>
'SMMA (RMA)' =>
'WMA' =>
'VWMA' =>
= ma(rvi, rvi_marvi_lengthinput, rvi_matypeinput)
// rvi_h0 = hline(80, "Upper Band", color=#787B86)
// hline(50, "Middle Band", color=color.new(#787B86, 50))
// rvi_h1 = hline(20, "Lower Band", color=#787B86)
// fill(rvi_h0, rvi_h1, color=color.rgb(126, 87, 194, 90), title="Background")
plot(show_rvi_modul_input ? rvi - rvi_zero_line : na, title = 'RVI', color = rvi_plot_color_input, offset = rvi_offset, linewidth = 1, style = plot.style_stepline)
plot(show_rvi_modul_input ? show_rvi_ma_plot_input ? rviMA - rvi_zero_line : na : na, title = 'RVI Smoothing Line', color = rvi_ma_plot_color_input, offset = rvi_offset, linewidth = 1)
rvi_bbupper = plot(show_rvi_modul_input ? highValue - rvi_zero_line : na, title = 'RVI Upper Bollinger Band', color = color.green)
rvi_bblower = plot(show_rvi_modul_input ? lowValue - rvi_zero_line : na, title = 'RVI Lower Bollinger Band', color = color.green)
fill(rvi_bbupper, rvi_bblower, color = color.new(color.green, 90), title = 'RVI Bollinger Bands Background Fill')
////////////////////////////////////////////////////////////////////////////////////////////////////
///////////////////////////////////////////// DIVERGENCE ///////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////
rd_Lookback_Right = 5
rd_Lookback_Left = 5
rd_Range_Upper = 60
rd_Range_Lower = 5
rd_Bear_Color = color.new(#e65100, 0)
rd_Bull_Color = color.new(#1b5e20, 0)
rd_Text_Color = color.new(color.white, 0)
rd_None_Color = color.new(color.white, 100)
rd_PL_Found = na(ta.pivotlow(rd_rsi, rd_Lookback_Left, rd_Lookback_Right)) ? false : true
rd_PH_Found = na(ta.pivothigh(rd_rsi, rd_Lookback_Left, rd_Lookback_Right)) ? false : true
_inRange(cond) =>
rd_Bars = ta.barssince(cond == true)
rd_Range_Lower <= rd_Bars and rd_Bars <= rd_Range_Upper
/////////////////////////////////////////// REGULAR BULLISH
/////////////////////////////////////////// RSI: HIGHER LOW
rd_RSI_HL = rd_rsi > ta.valuewhen(rd_PL_Found, rd_rsi , 1) and _inRange(rd_PL_Found )
// Price: Lower Low
rd_PriCeLL = low < ta.valuewhen(rd_PL_Found, low , 1)
rd_bull_cond_alert = rd_PriCeLL and rd_RSI_HL and rd_PL_Found
rd_Bull_Cond = show_rsi_divergence and rd_bull_cond_alert
plot(show_rsi_modul_input and rd_PL_Found ? rd_rsi - rsi_zero_line : na, offset = -rd_Lookback_Right, title = 'Regular Bullish', linewidth = 2, force_overlay = true, color = rd_Bull_Cond ? rd_Bull_Color : rd_None_Color)
plotshape(show_rsi_modul_input and rd_Bull_Cond ? rd_rsi - rsi_zero_line : na, offset = -rd_Lookback_Right, title = 'Regular Bullish Label', text = 'BULLS', style = shape.labelup, location = location.belowbar, force_overlay = true, color = rd_Bull_Color, textcolor = rd_Text_Color, display = display.pane)
///////////////////////////////////////////// REGULAR BEARISH
///////////////////////////////////////////// RSI: LOWER HIGH
rd_RSI_LH = rd_rsi < ta.valuewhen(rd_PH_Found, rd_rsi , 1) and _inRange(rd_PH_Found )
//////////////////////////////////////////// PRICE: HIGHER HIGH
priceHH = high > ta.valuewhen(rd_PH_Found, high , 1)
rd_bearcondalert = priceHH and rd_RSI_LH and rd_PH_Found
rd_bearCond = show_rsi_divergence and rd_bearcondalert
plot(show_rsi_modul_input and rd_PH_Found ? rd_rsi - rsi_zero_line : na, offset = -rd_Lookback_Right, title = 'Regular Bearish', linewidth = 2, force_overlay = true, color = rd_bearCond ? rd_Bear_Color : rd_None_Color)
plotshape(show_rsi_modul_input and rd_bearCond ? rd_rsi - rsi_zero_line : na, offset = -rd_Lookback_Right, title = 'Regular Bearish Label', text = 'BEARS', style = shape.labeldown, location = location.abovebar, force_overlay = true, color = rd_Bear_Color, textcolor = rd_Text_Color, display = display.pane)
////////////////////////////////////////////////////////////////////////////////////////////////////
///////////////////////////////////////////// DIRECTIONAL MOVEMENT INDEX /////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////
dmi_up = ta.change(high)
dmi_down = -ta.change(low)
dmi_plusDM = na(dmi_up) ? na : dmi_up > dmi_down and dmi_up > 0 ? dmi_up : 0
dmi_minusDM = na(dmi_down) ? na : dmi_down > dmi_up and dmi_down > 0 ? dmi_down : 0
dmi_trur = ta.rma(ta.tr, dmi_len)
dmi_plus = fixnan(100 * ta.rma(dmi_plusDM, dmi_len) / dmi_trur)
dmi_minus = fixnan(100 * ta.rma(dmi_minusDM, dmi_len) / dmi_trur)
dmi_sum = dmi_plus + dmi_minus
dmi_adx = 100 * ta.rma(math.abs(dmi_plus - dmi_minus) / (dmi_sum == 0 ? 1 : dmi_sum), dmi_lensig)
dmi_gc = dmi_down <= dmi_up
dmi_dc = dmi_down >= dmi_up
dmi_gc_ = ta.crossover(dmi_plus, dmi_adx)
dmi_dc_ = ta.crossunder(dmi_minus, dmi_adx)
plot(show_rd_modul_input ? dmi_adx + rsi_zero_line - dmiadx_zero_line : na, color = dmi_plot_adx_color_input, title = 'DMI ADX', linewidth = 3)
plot(show_rd_modul_input ? dmi_plus + rsi_zero_line - dmiadx_zero_line : na, color = dmi_plot_di_plus_color_input, title = 'DMI DI +', linewidth = 3)
plot(show_rd_modul_input ? dmi_minus + rsi_zero_line - dmiadx_zero_line : na, color = dmi_plot_di_minus_color_input, title = 'DMI DI -', linewidth = 3)
//////////////////////////////////////////////////////////////////////////////////////////////////////
///////////////////////////////////////////// crossover/crossunder ////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////////////////////////
rd_sma = rd_ma(rd_rsi, rd_ma_length_input, rd_ma_type_input)
rd_rsi_sma_gc = ta.crossover(rd_rsi, rd_sma)
rd_rsi_sma_dc = ta.crossunder(rd_rsi, rd_sma)
rd_stoc_rsi_sma_dc = ta.crossover(rd_strsi_k, rd_strsi_d)
rd_stoc_rsi_sma_gc = ta.crossunder(rd_strsi_k, rd_strsi_d)
rd_adx_mfi_gc_ = ta.crossover(rd_mfi_mf, dmi_adx)
rd_adx_mfi_dc_ = ta.crossunder(rd_mfi_mf, dmi_adx)
rd_dmi_plus_adx_gc = ta.crossover(dmi_plus, dmi_adx)
rd_dmi_plus_adx_dc = ta.crossunder(dmi_plus, dmi_adx)
rd_dmi_minus_adx_gc = ta.crossover(dmi_minus, dmi_adx)
rd_dmi_minus_adx_dc = ta.crossunder(dmi_minus, dmi_adx)
rd_cci_gc = ta.crossover(cci, cci_smoothingLine)
rd_cci_dc = ta.crossunder(cci, cci_smoothingLine)
rd_obv_gc = ta.crossover(obv, obv_smoothing_line)
rd_obv_dc = ta.crossunder(obv, obv_smoothing_line)
///////////////////////////////////////////////////////////////////////////////////////////////////
///////////////////////////////////////////// ПАРАМЕТРЫ ВХОД/ВЫХОД ////////////////////////////////
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OpenLong_1 = bool(na)
OpenShort_1 = bool(na)
OpenLong_2 = bool(na)
OpenShort_2 = bool(na)
OpenLong_3 = bool(na)
OpenShort_3 = bool(na)
OpenLong_4 = bool(na)
OpenShort_4 = bool(na)
OpenLong_5 = bool(na)
OpenShort_5 = bool(na)
OpenLong_6 = bool(na)
OpenShort_6 = bool(na)
OpenLong_1 := rd_consider_algo_1_input ? rd_cci_gc and 25 < rd_rsi and rd_rsi < rd_factor_rsi_open_long_algo_1_input or rd_cci_gc and rd_rsi > 75 and ta.crossover(close, highUsePivot) and not(open - low > close - open) and osc > volumeThresh : bool(na)
OpenShort_1 := rd_consider_algo_1_input ? rd_cci_dc and 75 > rd_rsi and rd_rsi > rd_factor_rsi_open_short_algo_1_input or rd_cci_dc and rd_rsi < 25 and ta.crossunder(close, lowUsePivot) and not(open - close < high - open) and osc > volumeThresh : bool(na)
OpenLong_2 := rd_consider_algo_2_input ? rd_bull_cond_alert or rd_rsi_sma_gc and rd_rsi_ma < rd_factor_rsi_open_long_algo_2_input : bool(na)
OpenShort_2 := rd_consider_algo_2_input ? rd_bearcondalert or rd_rsi_sma_dc and rd_rsi_ma > rd_factor_rsi_open_short_algo_2_input : bool(na)
OpenLong_3 := rd_consider_algo_3_input ? rd_stoc_rsi_sma_gc and rd_strsi_k < rd_factor_strsi_open_long_algo_3_input : false
OpenShort_3 := rd_consider_algo_3_input ? rd_stoc_rsi_sma_dc and rd_strsi_k > rd_factor_strsi_open_short_algo_3_input : false
OpenLong_4 := rd_consider_algo_4_input ? rd_dmi_plus_adx_gc and 30 < rd_rsi and rd_rsi < rd_factor_rsi_open_long_algo_4_input or rd_dmi_minus_adx_dc and 30 < rd_rsi and rd_rsi < rd_factor_rsi_open_long_algo_4_input or rd_dmi_plus_adx_gc and rd_rsi > 70 : false
OpenShort_4 := rd_consider_algo_4_input ? rd_dmi_minus_adx_gc and 70 > rd_rsi and rd_rsi > rd_factor_rsi_open_short_algo_4_input or rd_dmi_plus_adx_dc and 70 > rd_rsi and rd_rsi > rd_factor_rsi_open_short_algo_4_input or rd_dmi_minus_adx_gc and rd_rsi < 30 : false
OpenLong_5 := rd_consider_algo_5_input ? macd_histo > 0 and macd_histo < 0 and 30 < rd_rsi and rd_rsi < rd_factor_strsi_open_long_algo_5_input or macd_histo > 0 and macd_histo < 0 and rd_rsi > 70 : false
OpenShort_5 := rd_consider_algo_5_input ? macd_histo < 0 and macd_histo > 0 and 70 > rd_rsi and rd_rsi > rd_factor_strsi_open_short_algo_5_input or macd_histo < 0 and macd_histo > 0 and rd_rsi < 30 : false
OpenLong_5 := rd_consider_algo_5_input ? macd_histo > 0 and macd_histo < 0 and 30 < rd_rsi and rd_rsi < rd_factor_strsi_open_long_algo_5_input or macd_histo > 0 and macd_histo < 0 and rd_rsi > 70 : false
OpenShort_5 := rd_consider_algo_5_input ? macd_histo < 0 and macd_histo > 0 and 70 > rd_rsi and rd_rsi > rd_factor_strsi_open_short_algo_5_input or macd_histo < 0 and macd_histo > 0 and rd_rsi < 30 : false
OpenLong_6 := rd_consider_algo_6_input ? rd_obv_gc and 20 < rd_rsi and rd_rsi < rd_factor_rsi_open_long_algo_6_input or rd_obv_gc and rd_rsi > 80 : bool(na)
OpenShort_6 := rd_consider_algo_6_input ? rd_obv_dc and 80 > rd_rsi and rd_rsi > rd_factor_rsi_open_short_algo_6_input or rd_obv_dc and rd_rsi < 20 : bool(na)
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rd_OpenLong = OpenLong_1 or OpenLong_2 or OpenLong_3 or OpenLong_4 or OpenLong_5 or OpenLong_6
rd_OpenShort = OpenShort_1 or OpenShort_2 or OpenShort_3 or OpenShort_4 or OpenShort_5 or OpenShort_6
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///////////////////////////////////////////// LABELS LONG/SHORT //////////////////////////////////
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plotshape(show_long_short_modul_input ? rd_OpenLong : bool(na), force_overlay = true, color = rd_OpenLong_label_color_input, title = 'Open Long Label', text = rd_OpenLong_label_txt, textcolor = rd_Openlabel_textcolor_input, location = location.belowbar, style = shape.labelup, display = display.pane)
plotshape(show_long_short_modul_input ? rd_OpenShort : bool(na), force_overlay = true, color = rd_OpenShort_label_color_input, title = 'Open Short Label', text = rd_OpenShort_label_txt, textcolor = rd_Openlabel_textcolor_input, location = location.abovebar, style = shape.labeldown, display = display.pane)
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///////////////////////////////////////////// ALERTS LONG/SHORT ////////////////////////////////////
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alertcondition(rd_OpenLong, title = '$ Open long', message = 'Open long {{exchange}}:{{ticker}}, price = {{close}}, volume = {{volume}}')
alertcondition(rd_OpenShort, title = '$ Open short', message = 'Open short {{exchange}}:{{ticker}}, price = {{close}}, volume = {{volume}}')
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A EMA- und RSI-Hetzenauer Trendfollow Strategy. tmThe Ema&Rsi Hetzenauer Trendfollower is a trend-following indicator that combines three key elements to help traders identify profitable Trend moves.It uses the 200 EMA to confirm the overall trend direction, the 50 EMA for spotting pullbacks,and the RSI above 50 for confirming momentum and enter on a better Position.
How it Works:
* 200 EMA: Confirms the overall trend (bullish or bearish).
*50 EMA: identifies pullbacks in the direction of the trend, creating ideal entry points.
*RSI: Filters out weak signals by confirming momentum (RSI above 50 for buying, below for selling).
MACD Killer Indicator with SuperTrend and RSIThe "MACD Killer Indicator with SuperTrend and RSI" is a comprehensive trading tool designed for technical analysis on TradingView. This script incorporates three powerful indicators: the MACD (Moving Average Convergence Divergence), SuperTrend, and RSI (Relative Strength Index) to generate buy and sell signals.
MACD is used to determine the momentum of the asset, signaling entry points when the MACD line crosses above the signal line.
The SuperTrend adds a layer of trend detection, ensuring that trades are executed in the direction of the prevailing trend, indicated by the SuperTrend line's color (green for uptrend, red for downtrend).
RSI is employed to filter out overbought conditions, limiting buy signals when RSI is below 73.
This indicator effectively mitigates consecutive signals of the same type, helping traders avoid false entries and exits. The visual elements, including clearly marked buy and sell signals and background color changes, enhance the user experience, making it easier to spot actionable trade opportunities on the charts.
AO/AC Trading Zones Strategy [Skyrexio] Overview
AO/AC Trading Zones Strategy leverages the combination of Awesome Oscillator (AO), Acceleration/Deceleration Indicator (AC), Williams Fractals, Williams Alligator and Exponential Moving Average (EMA) to obtain the high probability long setups. Moreover, strategy uses multi trades system, adding funds to long position if it considered that current trend has likely became stronger. Combination of AO and AC is used for creating so-called trading zones to create the signals, while Alligator and Fractal are used in conjunction as an approximation of short-term trend to filter them. At the same time EMA (default EMA's period = 100) is used as high probability long-term trend filter to open long trades only if it considers current price action as an uptrend. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator to identify when current uptrend is likely to be over. In some special cases strategy uses AO and AC combination to trail profit (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Multilayer trades opening system: strategy uses only 10% of capital in every trade and open up to 5 trades at the same time if script consider current trend as strong one.
Short and long term trend trade filters: strategy uses EMA as high probability long-term trend filter and Alligator and Fractal combination as a short-term one.
Methodology
The strategy opens long trade when the following price met the conditions:
1. Price closed above EMA (by default, period = 100). Crossover is not obligatory.
2. Combination of Alligator and Williams Fractals shall consider current trend as an upward (all details in "Justification of Methodology" paragraph)
3. Both AC and AO shall print two consecutive increasing values. At the price candle close which corresponds to this condition algorithm opens the first long trade with 10% of capital.
4. If combination of Alligator and Williams Fractals shall consider current trend has been changed from up to downtrend, all long trades will be closed, no matter how many trades has been opened.
5. If AO and AC both continue printing the rising values strategy opens the long trade on each candle close with 10% of capital while number of opened trades reaches 5.
6. If AO and AC both has printed 5 rising values in a row algorithm close all trades if candle's low below the low of the 5-th candle with rising AO and AC values in a row.
Script also has additional visuals. If second long trade has been opened simultaneously the Alligator's teeth line is plotted with the green color. Also for every trade in a row from 2 to 5 the label "Buy More" is also plotted just below the teeth line. With every next simultaneously opened trade the green color of the space between teeth and price became less transparent.
Strategy settings
In the inputs window user can setup strategy setting:
EMA Length (by default = 100, period of EMA, used for long-term trend filtering EMA calculation).
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Let's explore the key concepts of this strategy and understand how they work together. We'll begin with the simplest: the EMA.
The Exponential Moving Average (EMA) is a type of moving average that assigns greater weight to recent price data, making it more responsive to current market changes compared to the Simple Moving Average (SMA). This tool is widely used in technical analysis to identify trends and generate buy or sell signals. The EMA is calculated as follows:
1.Calculate the Smoothing Multiplier:
Multiplier = 2 / (n + 1), Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
In this strategy, the EMA acts as a long-term trend filter. For instance, long trades are considered only when the price closes above the EMA (default: 100-period). This increases the likelihood of entering trades aligned with the prevailing trend.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
Fractals, another tool by Bill Williams, help identify potential reversal points on a price chart. A fractal forms over at least five consecutive bars, with the middle bar showing either:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often use fractals alongside other indicators to confirm trends or reversals, enhancing decision-making accuracy.
How do these tools work together in this strategy? Let’s consider an example of an uptrend.
When the price breaks above an up fractal, it signals a potential bullish trend. This occurs because the up fractal represents a shift in market behavior, where a temporary high was formed due to selling pressure. If the price revisits this level and breaks through, it suggests the market sentiment has turned bullish.
The breakout must occur above the Alligator’s teeth line to confirm the trend. A breakout below the teeth is considered invalid, and the downtrend might still persist. Conversely, in a downtrend, the same logic applies with down fractals.
In this strategy if the most recent up fractal breakout occurs above the Alligator's teeth and follows the last down fractal breakout below the teeth, the algorithm identifies an uptrend. Long trades can be opened during this phase if a signal aligns. If the price breaks a down fractal below the teeth line during an uptrend, the strategy assumes the uptrend has ended and closes all open long trades.
By combining the EMA as a long-term trend filter with the Alligator and fractals as short-term filters, this approach increases the likelihood of opening profitable trades while staying aligned with market dynamics.
Now let's talk about the trading zones concept and its signals. To understand this we need to briefly introduce what is AO and AC. The Awesome Oscillator (AO), developed by Bill Williams, is a momentum indicator designed to measure market momentum by contrasting recent price movements with a longer-term historical perspective. It helps traders detect potential trend reversals and assess the strength of ongoing trends.
The formula for AO is as follows:
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
The Acceleration/Deceleration (AC) Indicator, introduced by Bill Williams, measures the rate of change in market momentum. It highlights shifts in the driving force of price movements and helps traders spot early signs of trend changes. The AC Indicator is particularly useful for identifying whether the current momentum is accelerating or decelerating, which can indicate potential reversals or continuations. For AC calculation we shall use the AO calculated above is the following formula:
AC = AO − SMA5(AO) , where SMA5(AO)is the 5-period Simple Moving Average of the Awesome Oscillator
When the AC is above the zero line and rising, it suggests accelerating upward momentum.
When the AC is below the zero line and falling, it indicates accelerating downward momentum.
When the AC is below zero line and rising it suggests the decelerating the downtrend momentum. When AC is above the zero line and falling, it suggests the decelerating the uptrend momentum.
Now let's discuss the trading zones concept and how it can create the signal. Zones are created by the combination of AO and AC. We can divide three zone types:
Greed zone: when the AO and AC both are rising
Red zone: when the AO and AC both are decreasing
Gray zone: when one of AO or AC is rising, the other is falling
Gray zone is considered as uncertainty. AC and AO are moving in the opposite direction. Strategy skip such price action to decrease the chance to stuck in the losing trade during potential sideways. Red zone is also not interesting for the algorithm because both indicators consider the trend as bearish, but strategy opens only long trades. It is waiting for the green zone to increase the chance to open trade in the direction of the potential uptrend. When we have 2 candles in a row in the green zone script executes a long trade with 10% of capital.
Two green zone candles in a row is considered by algorithm as a bullish trend, but now so strong, that's the reason why trade is going to be closed when the combination of Alligator and Fractals will consider the the trend change from bullish to bearish. If id did not happens, algorithm starts to count the green zone candles in a row. When we have 5 in a row script change the trade closing condition. Such situation is considered is a high probability strong bull market and all trades will be closed if candle's low will be lower than fifth green zone candle's low. This is used to increase probability to secure the profit. If long trades are initiated, the strategy continues utilizing subsequent signals until the total number of trades reaches a maximum of 5. Each trade uses 10% of capital.
Why we use trading zones signals? If currently strategy algorithm considers the high probability of the short-term uptrend with the Alligator and Fractals combination pointed out above and the long-term trend is also suggested by the EMA filter as bullish. Rising AC and AO values in the direction of the most likely main trend signaling that we have the high probability of the fastest bullish phase on the market. The main idea is to take part in such rapid moves and add trades if this move continues its acceleration according to indicators.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.12.31. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 10%
Maximum Single Position Loss: -9.49%
Maximum Single Profit: +24.33%
Net Profit: +4374.70 USDT (+43.75%)
Total Trades: 278 (39.57% win rate)
Profit Factor: 2.203
Maximum Accumulated Loss: 668.16 USDT (-5.43%)
Average Profit per Trade: 15.74 USDT (+1.37%)
Average Trade Duration: 60 hours
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
Normalized RSI Oscillator with DivergencesNormalized RSI with Divergences {A Next-Level Trading Tool}
The Normalized RSI with Divergences indicator is a powerful and innovative tool designed to enhance your trading precision. By normalizing the Relative Strength Index (RSI) and detecting divergences between the standard and normalized RSI, this script helps traders identify potential trend reversals and continuations with remarkable clarity.
Key Features
🔹 Advanced RSI Normalization
• Transforms the traditional RSI into a normalized range of , making overbought and oversold conditions more intuitive.
• Utilizes a dynamic lookback period to adapt to market conditions.
🔹 Divergence Detection for Smarter Trading
• Identifies Bullish, Hidden Bullish, Bearish, and Hidden Bearish divergences by analyzing RSI pivot points.
• Provides early signals of trend reversals and continuations for better trade execution.
🔹 Clear & Visual Trade Signals
• Divergences are automatically labeled on the chart:
o Bullish Divergence: 🟢 “Bull” (Green) – Possible upward reversal.
o Hidden Bullish Divergence: 🟢 “Hid.” (Lime) – Continuation of an uptrend.
o Bearish Divergence: 🔴 “Bear” (Red) – Possible downward reversal.
o Hidden Bearish Divergence: 🟠 “Hid.” (Orange) – Continuation of a downtrend.
🔹 Fully Customizable Inputs
• Adjust RSI period, normalization lookback, and divergence parameters to fit your strategy.
• Tailor the indicator to your preferred trading style and market conditions.
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How It Works
🔹 RSI Normalization Formula:
Norm=2×(RSI−MinMax−Min)−1\text{Norm} = 2 \times \left(\frac{\text{RSI} - \text{Min}}{\text{Max} - \text{Min}}\right) - 1Norm=2×(Max−MinRSI−Min)−1
• Min & Max represent the lowest and highest RSI values over the selected lookback period.
🔹 Divergence Detection Process:
• Identifies pivot points in both the normalized RSI and the standard RSI.
• Compares their directions to detect potential trading signals.
🔹 Real-Time Chart Labeling:
• Uses label.new to visually highlight divergence points for quick and efficient decision-making.
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Input Parameters
• Source: Price source for RSI calculation (Default: hlc3).
• Signal Period: RSI calculation period (Default: 50).
• Lookback Range: Normalization period (Default: 200, Max: 5000).
• Trend Length: Smoothing period for normalized RSI (Default: 5).
• Band Width: Center line & bands calculation period (Default: 34).
• Divergence Range: Lookback period for divergence detection (Default: 5).
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How to Use
1. Add the script to your trading chart.
2. Customize the settings to match your trading approach.
3. Watch for divergence labels to identify potential market moves:
o 🟢 Bullish Divergence: Possible upward reversal.
o 🟢 Hidden Bullish Divergence: Continuation of an uptrend.
o 🔴 Bearish Divergence: Possible downward reversal.
o 🟠 Hidden Bearish Divergence: Continuation of a downtrend.
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Why Use This Indicator?
✅ Enhanced RSI Analysis: Normalization simplifies overbought/oversold conditions.
✅ Crystal-Clear Divergence Signals: Instantly spot key trend shifts.
✅ Fully Customizable: Adjust settings for your specific strategy.
✅ Improve Trade Accuracy: Gain an edge with precise divergence detection.
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⚠️ Disclaimer
This script is for educational and informational purposes only. It does not constitute financial advice. Always conduct thorough research and backtesting before using it in live trading.
📜 License
This script is released under the Mozilla Public License 2.0.
Enjoy the Normalized RSI with Divergences indicator, and happy trading! 🚀📈
— Kerem Ertem
Plot Closed Candles OnlyWhat It Does:
This indicator helps you see candlesticks on your chart only after they are fully closed. It colors the candles based on whether they are bullish (green), bearish (red), or neutral (black/Doji). This way, you can focus on confirmed price movements without the distraction of candles that are still forming.
Key Features:
Plots Confirmed Candles: Only shows candles after they are fully formed.
Custom Colors:
Green: Bullish candles (close > open).
Red: Bearish candles (close < open).
Black: Doji candles (close = open).
Easy to Use: Simply add the indicator to your chart.
How to Use:
Add the indicator to your chart.
Turn off the default candles by:
Right-clicking on the chart.
Going to Style > Candles.
Disabling borders, bodies, and wicks for the default candles.
Enjoy a cleaner view of confirmed candles with clear color coding!
Why Use It?:
Helps you focus on confirmed price action.
Makes it easier to spot bullish, bearish, and neutral candles.
Great for traders who want to avoid the noise of incomplete candles.
Dan BollingerThis Strategy is using a 3 different Bollinger bands
It gives a signal when the candlestick is outside the bands
