Supertrend and Fast and Slow EMA StrategyThis strategy combines Exponential Moving Averages (EMAs) and Average True Range (ATR) to create a simple, yet effective, trend-following approach. The strategy filters out fake or sideways signals by incorporating the ATR as a volatility filter, ensuring that trades are only taken during trending conditions. The key idea is to buy when the short-term trend (Fast EMA) aligns with the long-term trend (Slow EMA), and to avoid trades during low volatility periods.
How It Works:
EMA Crossover:
1). Buy Signal: When the Fast EMA (shorter-term, e.g., 20-period) crosses above the Slow EMA (longer-term, e.g., 50-period), this indicates a potential uptrend.
2). Sell Signal: When the Fast EMA crosses below the Slow EMA, this indicates a potential downtrend.
ATR Filter:
1). The ATR (Average True Range) is used to measure market volatility.
2). Trending Market: If the ATR is above a certain threshold, it indicates high volatility and a trending market. Only when ATR is above the threshold will the strategy generate buy/sell signals.
3). Sideways Market: If ATR is low (sideways or choppy market), the strategy will suppress signals to avoid entering during non-trending conditions.
When to Buy:
1). Condition 1: The Fast EMA crosses above the Slow EMA.
2). Condition 2: The ATR is above the defined threshold, indicating that the market is trending (not sideways or choppy).
When to Sell:
1). Condition 1: The Fast EMA crosses below the Slow EMA.
2). Condition 2: The ATR is above the defined threshold, confirming that the market is in a downtrend.
When Not to Enter the Trade:
1). Sideways Market: If the ATR is below the threshold, signaling low volatility and sideways or choppy market conditions, the strategy will not trigger any buy or sell signals.
2). False Crossovers: In low volatility conditions, price action tends to be noisy, which could lead to false signals. Therefore, avoiding trades during these periods reduces the risk of false breakouts.
Additional Factors to Consider Adding:
=> RSI (Relative Strength Index): Adding an RSI filter can help confirm overbought or oversold conditions to avoid buying into overextended moves or selling too low.
1). RSI Buy Filter: Only take buy signals when RSI is below 70 (avoiding overbought conditions).
2). RSI Sell Filter: Only take sell signals when RSI is above 30 (avoiding oversold conditions).
=> MACD (Moving Average Convergence Divergence): Using MACD can help validate the strength of the trend.
1). Buy when the MACD histogram is above the zero line and the Fast EMA crosses above the Slow EMA.
2). Sell when the MACD histogram is below the zero line and the Fast EMA crosses below the Slow EMA.
=> Support/Resistance Levels: Adding support and resistance levels can help you understand market structure and decide whether to enter or exit a trade.
1). Buy when price breaks above a significant resistance level (after a valid buy signal).
2). Sell when price breaks below a major support level (after a valid sell signal).
=> Volume: Consider adding a volume filter to ensure that buy/sell signals are supported by strong market participation. You could only take signals if the volume is above the moving average of volume over a certain period.
=> Trailing Stop Loss: Instead of a fixed stop loss, use a trailing stop based on a percentage or ATR to lock in profits as the trade moves in your favor.
=> Exit Signals: Besides the EMA crossover, consider adding Take Profit or Stop Loss levels, or even using a secondary indicator like RSI to signal an overbought/oversold condition and exit the trade.
Example Usage:
=> Buy Example:
1). Fast EMA (20-period) crosses above the Slow EMA (50-period).
2). The ATR is above the threshold, confirming that the market is trending.
3). Optionally, if RSI is below 70, the buy signal is further confirmed as not being overbought.
=> Sell Example:
1). Fast EMA (20-period) crosses below the Slow EMA (50-period).
2). The ATR is above the threshold, confirming that the market is trending.
3). Optionally, if RSI is above 30, the sell signal is further confirmed as not being oversold.
Conclusion:
This strategy helps to identify trending markets and filters out sideways or choppy market conditions. By using Fast and Slow EMAs combined with the ATR volatility filter, it provides a reliable approach to catching trending moves while avoiding false signals during low-volatility, sideways markets.
אינדיקטורים ואסטרטגיות
Smart Scalping Momentum StrategyThe Smart Scalping Momentum Strategy is a powerful and well-optimized trading strategy designed for Forex, Crypto, and XAU/USD (Gold) markets. It focuses on high-probability entries based on price momentum, trend confirmation, and volatility adjustments. The strategy aims to maximize daily profits while maintaining a low-risk exposure by utilizing multiple technical indicators and strict risk management rules.
Seasonality Monthly v2.0//@version=6
indicator("Seasonality Monthly v2.0", overlay=false)
if not (timeframe.ismonthly or timeframe.isdaily)
alert("Switch to Daily or Monthly timeframe", alert.freq_once_per_bar)
// Input Settings
i_year_start = input(2000, "Start Year")
i_text_size = input.string(size.auto, "Text Size", )
// Function for calculating statistics
f_array_stats(array_) =>
count_pos_ = 0
count_neg_ = 0
count_ = 0
sum_ = 0.0
if not na(array_) and array.size(array_) > 0
for i_ = 0 to array.size(array_) - 1
elem_ = array.get(array_, i_)
if not na(elem_)
sum_ += elem_
count_ += 1
count_pos_ += elem_ > 0 ? 1 : 0
count_neg_ += elem_ < 0 ? 1 : 0
avg_ = count_ > 0 ? sum_ / count_ : 0.0
// Request historical data
year_ = request.security(syminfo.tickerid, "M", year(time_close), gaps = barmerge.gaps_on, lookahead = barmerge.lookahead_on)
month_ = request.security(syminfo.tickerid, "M", month(time_close), gaps = barmerge.gaps_on, lookahead = barmerge.lookahead_on)
chg_pct_ = request.security(syminfo.tickerid, "M", nz(close / close - 1), gaps = barmerge.gaps_on, lookahead = barmerge.lookahead_on)
// Initialize variables
var year_start_ = math.max(year_, i_year_start)
var no_years_ = year(timenow) - year_start_ + 1
var matrix data_ = matrix.new(no_years_, 13, na)
var table table_ = na
var text_color_ = color.white
var bg_color_ = color.gray
if year_ >= year_start_
cur_val_ = nz(matrix.get(data_, year_ - year_start_, month_ - 1))
matrix.set(data_, year_ - year_start_, month_ - 1, cur_val_ + chg_pct_)
if barstate.islast
table_ := table.new(position.middle_center, 13, no_years_ + 7, border_width = 1)
table.cell(table_, 0, 0, str.format("Seasonality Monthly Performance - {0}:{1}", syminfo.prefix, syminfo.ticker), text_color = text_color_, bgcolor = color.blue, text_size = i_text_size)
table.merge_cells(table_, 0, 0, 12, 0)
row = 1
// Header row
months_ ="Year", "Jan", "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"
for col = 0 to 12
table.cell(table_, col, row, months_ , text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size)
// Data rows
for row_ = 0 to no_years_ - 1
table.cell(table_, 0, 2 + row_, str.tostring(row_ + year_start_), text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size)
for col_ = 0 to 11
val_ = nz(matrix.get(data_, row_, col_), 0.0)
val_color_ = val_ > 0.0 ? color.green : val_ < 0.0 ? color.red : color.gray
table.cell(table_, col_ + 1, 2 + row_, str.format("{0,number,###.##%}", val_), bgcolor = color.new(val_color_, 80), text_color = val_color_, text_size = i_text_size)
// Aggregates
row_ = no_years_ + 2
labels = "AVG", "SUM", "+ive", "WR"
for i = 0 to 3
table.cell(table_, 0, row_ + i, labels , text_color = text_color_, bgcolor = bg_color_, text_size = i_text_size)
for col_ = 0 to 11
arr_ = matrix.col(data_, col_)
= f_array_stats(arr_)
val_color_ = sum_ > 0 ? color.green : sum_ < 0 ? color.red : color.gray
table.cell(table_, col_ + 1, row_, str.format("{0,number,###.##%}", avg_), bgcolor = color.new(val_color_, 50), text_color = val_color_, text_size = i_text_size)
table.cell(table_, col_ + 1, row_ + 1, str.format("{0,number,###.##%}", sum_), bgcolor = color.new(val_color_, 50), text_color = val_color_, text_size = i_text_size)
table.cell(table_, col_ + 1, row_ + 2, str.format("{0}/{1}", count_pos_, count_), bgcolor = color.new(val_color_, 50), text_color = color.new(color.white, 50), text_size = i_text_size)
table.cell(table_, col_ + 1, row_ + 3, str.format("{0,number,#.##%}", count_pos_ / count_), bgcolor = color.new(val_color_, 50), text_color = color.new(color.white, 50), text_size = i_text_size)
is_strategyCorrection-Adaptive Trend Strategy (Open-Source)
Core Advantage: Designed specifically for the is_correction indicator, with full transparency and customization options.
Key Features:
Open-Source Code:
✅ Full access to the strategy logic – study how every trade signal is generated.
✅ Freedom to customize – modify entry/exit rules, risk parameters, or add new indicators.
✅ No black boxes – understand and trust every decision the strategy makes.
Built for is_correction:
Filters out false signals during market noise.
Works only in confirmed trends (is_correction = false).
Adaptable for Your Needs:
Change Take Profit/Stop Loss ratios directly in the code.
Add alerts, notifications, or integrate with other tools (e.g., Volume Profile).
For Developers/Traders:
Use the code as a template for your own strategies.
Test modifications risk-free on historical data.
How the Strategy Works:
Main Goal:
Automatically buys when the price starts rising and sells when it starts falling, but only during confirmed trends (ignoring temporary pullbacks).
What You See on the Chart:
📈 Up arrows ▼ (below the candle) = Buy signal.
📉 Down arrows ▲ (above the candle) = Sell signal.
Gray background = Market is in a correction (no trades).
Key Mechanics:
Buy Condition:
Price closes higher than the previous candle + is_correction confirms the main trend (not a pullback).
Example: Red candle → green candle → ▼ arrow → buy.
Sell Condition:
Price closes lower than the previous candle + is_correction confirms the trend (optional: turn off short-selling in settings).
Exit Rules:
Closes trades automatically at:
+0.5% profit (adjustable in settings).
-0.5% loss (adjustable).
Or if a reverse signal appears (e.g., sell signal after a buy).
User-Friendly Settings:
Sell – On (default: ON):
ON → Allows short-selling (selling when price falls).
OFF → Strategy only buys and closes positions.
Revers (default: OFF):
ON → Inverts signals (▼ = sell, ▲ = buy).
%Profit & %Loss:
Adjust these values (0-30%) to increase/decrease profit targets and risk.
Example Scenario:
Buy Signal:
Price rises for 3 days → green ▼ arrow → strategy buys.
Stop loss set 0.5% below entry price.
If price keeps rising → trade closes at +0.5% profit.
Correction Phase:
After a rally, price drops for 1 day → gray background → strategy ignores the drop (no action).
Stop Loss Trigger:
If price drops 0.5% from entry → trade closes automatically.
Key Features:
Correction Filter (is_correction):
Acts as a “noise filter” → avoids trades during temporary pullbacks.
Flexibility:
Disable short-selling, flip signals, or tweak profit/loss levels in seconds.
Transparency:
Open-source code → see exactly how every signal is generated (click “Source” in TradingView).
Tips for Beginners:
Test First:
Run the strategy on historical data (click the “Chart” icon in TradingView).
See how it performed in the past.
Customize It:
Increase %Profit to 2-3% for volatile assets like crypto.
Turn off Sell – On if short-selling confuses you.
Trust the Stop Loss:
Even if you think the price will rebound, the strategy will close at -0.5% to protect your capital.
Where to Find Settings:
Click the strategy name on the top-left of your chart → adjust sliders/toggles in the menu.
Русская Версия
Трендовая стратегия с открытым кодом
Главное преимущество: Полная прозрачность логики и адаптация под ваши нужды.
Особенности:
Открытый исходный код:
✅ Видите всю «кухню» стратегии – как формируются сигналы, когда открываются сделки.
✅ Меняйте правила – корректируйте тейк-профит, стоп-лосс или добавляйте новые условия.
✅ Никаких секретов – вы контролируете каждое правило.
Заточка под is_correction:
Игнорирует ложные сигналы в коррекциях.
Работает только в сильных трендах (is_correction = false).
Гибкая настройка:
Подстройте параметры под свой риск-менеджмент.
Добавьте свои индикаторы или условия для входа.
Для трейдеров и разработчиков:
Используйте код как основу для своих стратегий.
Тестируйте изменения на истории перед реальной торговлей.
Простыми словами:
Почему это удобно:
Открытый код = полный контроль. Вы можете:
Увидеть, как именно стратегия решает купить или продать.
Изменить правила закрытия сделок (например, поставить TP=2% вместо 1.5%).
Добавить новые условия (например, торговать только при высоком объёме).
Примеры кастомизации:
Новички: Меняйте только TP/SL в настройках (без кодинга).
Продвинутые: Добавьте RSI-фильтр, чтобы избегать перекупленности.
Разработчики: Встройте стратегию в свою торговую систему.
Как начать:
Скачайте код из TradingView.
Изучите логику в разделе strategy.entry/exit.
Меняйте параметры в блоке input.* (безопасно!).
Тестируйте изменения и оптимизируйте под свои цели.
Как работает стратегия:
Главная задача:
Автоматически покупает, когда цена начинает расти, и продаёт, когда падает. Но делает это «умно» — только когда рынок в основном тренде, а не во временном откате (коррекции).
Что видно на графике:
📈 Стрелки вверх ▼ (под свечой) — сигнал на покупку.
📉 Стрелки вниз ▲ (над свечой) — сигнал на продажу.
Серый фон — рынок в коррекции (не торгуем).
Как это работает:
Когда покупаем:
Если цена закрылась выше предыдущей и индикатор is_correction показывает «основной тренд» (не коррекция).
Пример: Была красная свеча → стала зелёная → появилась стрелка ▼ → покупаем.
Когда продаём:
Если цена закрылась ниже предыдущей и is_correction подтверждает тренд (опционально, можно отключить в настройках).
Когда закрываем сделку:
Автоматически при достижении:
+0.5% прибыли (можно изменить в настройках).
-0.5% убытка (можно изменить).
Или если появился противоположный сигнал (например, после покупки пришла стрелка продажи).
Настройки для чайников:
«Sell – On» (включено по умолчанию):
Если включено → стратегия будет продавать в шорт.
Если выключено → только покупки и закрытие позиций.
«Revers» (выключено по умолчанию):
Если включить → стратегия будет работать наоборот (стрелки ▼ = продажа, ▲ = покупка).
«%Profit» и «%Loss»:
Меняйте эти цифры (от 0 до 30), чтобы увеличить/уменьшить прибыль и риски.
Пример работы:
Сигнал на покупку:
Цена 3 дня растет → появляется зелёная стрелка ▼ → стратегия покупает.
Стоп-лосс ставится на 0.5% ниже цены входа.
Если цена продолжает расти → сделка закрывается при +0.5% прибыли.
Коррекция:
После роста цена падает на 1 день → фон становится серым → стратегия игнорирует это падение (не закрывает сделку).
Стоп-лосс:
Если цена упала на 0.5% от точки входа → сделка закрывается автоматически.
Важные особенности:
Фильтр коррекций (is_correction):
Это «защита от шума» — стратегия не реагирует на мелкие откаты, работая только в сильных трендах.
Гибкие настройки:
Можно запретить шорты, перевернуть сигналы или изменить уровни прибыли/убытка за 2 клика.
Прозрачность:
Весь код открыт → вы можете увидеть, как формируется каждый сигнал (меню «Исходник» в TradingView).
Советы для новичков:
Начните с теста:
Запустите стратегию на исторических данных (кнопка «Свеча» в окне TradingView).
Посмотрите, как она работала в прошлом.
Настройте под себя:
Увеличьте %Profit до 2-3%, если торгуете валюты.
Отключите «Sell – On», если не понимаете шорты.
Доверяйте стоп-лоссу:
Даже если кажется, что цена развернётся — стратегия закроет сделку при -0.5%, защитив ваш депозит.
Где найти настройки:
Кликните на название стратегии в верхнем левом углу графика → откроется меню с ползунками и переключателями.
Важно: Стратегия предоставляет «рыбу» – чтобы она стала «уловистой», адаптируйте её под свой стиль торговли!
KDJ Stochastic of MA ModelIndicator Name:
KDJ Stochastic of MA Model
Disclaimer
Various factors can affect changes in the value of financial assets. These include, but are not limited to, geopolitical issues, industry policies, and technological developments within the industry. Other influencing elements include expectations of interest rates, inflation or deflation, unemployment rates, company development strategies, company revenues and liabilities, investor sentiment, and preferences for investor trading strategies. These factors may pose a risk of loss to investors' investment costs. Moreover, the past performance of individual trades does not guarantee future results or returns. Therefore, no a single idea, algorithm, script, indicator, or system content can account for all factors influencing financial asset value fluctuations. Investors are fully responsible for any investment decisions they make, and such decisions should be based entirely on an assessment of their financial situation, investment goals, risk tolerance, and liquidity needs.
The content provided in my ideas, algorithms, scripts, indicators, and systems is intended solely to demonstrate changes in the value of financial assets for educational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. The provider will not accept liability for any loss or damage, including, without limitation, any loss of investment costs, which may arise directly or indirectly from the use of or reliance on such information.
About Coffee
I would be delighted if my ideas, algorithms, scripts, indicators, and code can assist or inspire your pricing model. Should you feel inclined to buy me a cup of coffee, please feel free to contact me on TradingView. I am also more than willing to share my proprietary code indicators with you, along with practical usage tips for the related indicators.
CRYPTOCAP:ETH | CRYPTOCAP:USDT | CRYPTOCAP:USDC
0xE1b33484211595Ba4Dd9d6fEa52D64e873AfDe12
CRYPTOCAP:SOL | CRYPTOCAP:USDT | CRYPTOCAP:USDC
H8P3o2mqsb4u1R3TZa9PXKg5e5weyQFHVFMfZUPjheYE
CRYPTOCAP:USDT | CRYPTOCAP:USDC
TKQQNAZqBLQQMBSE98kEQdg6wRRqykNveh
CRYPTOCAP:BTC
bc1pkylhtk7srdqk6cyk7vfggzkkv8898drnmjpnvv69mp99uswh6rlstq63vr
Introduction to Indicator
KDJ stochastic values generated by various from 7 types of moving averages (WSMA, SMA, EMA, RMA, HMA, WMA, VWMA) pricing models of the same cycles.
Applicable to all time intervals.
Indicator effect display
S&P 500 Index ( SP:SPX )
S&P 500 Index ( SP:SPX )
Tesla, Inc. ( NASDAQ:TSLA )
Tesla, Inc. ( NASDAQ:TSLA )
Bitcoin / U.S. Dollar ( BITSTAMP:BTCUSD )
Bitcoin / U.S. Dollar ( BITSTAMP:BTCUSD )
BXY & DXY Cross (Perfectly Balanced)If you deal with Usd and their pairs and need necssary confirmation You might need this
Bxy and Dxy Index Crossings (GBP Index and Usd Index Crossing)
Asset Valuation ComparisonThis indicator calculates and visualizes z-scores to compare the valuation of an asset (the charted symbol) against gold, bonds, and either its own price or USD (depending on the isCurrency input). A z-score measures how many standard deviations a value is from its mean over a specified lookback period (default: 200 bars).
Horizontal Lines:
0 (Zero Line): The mean value of the z-score.
+1 (Overvalued Threshold): One standard deviation above the mean.
-1 (Undervalued Threshold): One standard deviation below the mean.
Pearson OscillatorThe Pearson Oscillator is a custom TradingView indicator that leverages statistical correlation analysis to gauge the trend strength of a given price series. By calculating the Pearson correlation coefficient between time (as an index) and price over a user-defined period, the indicator provides traders with an insight into how strongly the market is trending or oscillating.
──────────────────────────────
Key Features
- User-Defined Parameters:
– Set the calculation length, price source, and smoothing period.
– Adjust upper and lower threshold levels to suit your trading strategy.
– Customize color settings for increasing, decreasing, and neutral conditions.
- Dynamic Trend Analysis:
– Computes the Pearson correlation coefficient to measure the relationship between time and price.
– Applies a simple moving average to smooth out fluctuations in the coefficient, offering a more stable reading.
- Visual Representation:
– Plots the smoothed Pearson coefficient as a continuous line.
– Displays a histogram showing the variation (first derivative) of the coefficient to highlight changes in trend strength.
– Draws horizontal reference lines at the specified upper and lower thresholds as well as at the zero level for quick visual assessment.
- Alerts and Dynamic Labeling:
– Automatically triggers alerts when the smoothed Pearson coefficient crosses the predefined threshold levels, so you never miss a potential market turning point.
– Generates a dynamic label on the last bar that displays important statistical information, including:
- The current Pearson coefficient (rounded to three decimals).
- A classification of correlation strength (e.g., STRONG, MEDIUM, WEAK, NEUTRAL) based on the absolute value of the coefficient.
- The trend direction (Upward, Downward, or Stable).
- The delta of the coefficient, offering insight into how quickly the trend is evolving.
──────────────────────────────
How It Works
1. Calculation of the Pearson Coefficient:
- A custom function iterates over a specified number of price bars, summing time indices, price values, and their squared and cross-products.
- Using the Pearson correlation formula, it computes a coefficient that ranges between -1 and 1—values close to ±1 indicate a strong trend or linear relationship, while values near 0 suggest a weak or non-existent trend.
2. Smoothing Process:
- The raw Pearson coefficient is then smoothed using a simple moving average (SMA) to reduce noise and provide a clearer view of the underlying trend.
3. Delta (Variation) Computation:
- The script calculates the change (delta) between the current smoothed coefficient and its value on the previous bar.
- This derivative is plotted as a histogram, signaling the speed at which the correlation (and thus the trend) is changing.
4. Visual and Alert Mechanisms:
- The smoothed coefficient and its delta are plotted with colors that dynamically update to reflect increasing or decreasing trends.
- Horizontal lines set at user-defined thresholds help to quickly identify overbought or oversold (or extreme correlation) scenarios.
- Alerts are defined to notify you when the smoothed coefficient crosses these key levels, ensuring timely trade decisions.
5. Dynamic Label:
- At the last bar, a dynamic label is created displaying the current Pearson value, its strength, the direction of the trend, and the delta.
- This quick snapshot helps traders assess the market condition at a glance without diving into detailed analysis.
──────────────────────────────
Why Use the Pearson Oscillator?
This indicator is particularly useful for traders who need a quantitative measure of trend strength that goes beyond traditional moving averages. By integrating statistical correlation directly into market analysis, the Pearson Oscillator helps you:
- Identify periods of strong trending behavior or potential reversals.
- Enhance your risk management through early alerts.
- Visualize the rate of change in market sentiment, enabling more informed entry and exit decisions.
Whether you are a technical analyst or a systematic trader, this indicator provides a robust tool to complement your existing trading toolkit.
──────────────────────────────
The Pearson Oscillator merges statistical insights with technical charting, creating an intuitive yet powerful tool for market analysis. With its adjustable parameters, visual cues, dynamic labeling, and automated alerts, it assists traders in monitoring and responding to evolving market conditions efficiently. This makes it a valuable addition to any TradingView chart, particularly for those looking to quantify the strength and evolution of market trends.
Feel free to adapt the parameters and visual settings to best align the indicator with your trading strategy. Happy trading!
EXY & DXY Cross (Perfectly Balanced)If you deal with Usd and their pairs and need necssary confirmation You might need this
Exy and Dxy Index Crossings
pr_functionsLibrary "pr_functions"
TODO: add library description here
sema(src, length)
TODO: add function description here
Parameters:
src (float)
length (simple int)
Returns: TODO: add what function returns
Utility function for smooth EMA calculation
update_array(arr, value)
Parameters:
arr (array)
value (float)
is_uptrend(arr)
Parameters:
arr (array)
is_downtrend(arr)
Parameters:
arr (array)
is_ema_valid(ema)
Parameters:
ema (float)
Double Bottom & Breakout Strategy (With Alerts)trategy helps traders identify potential bullish breakouts based on multiple technical indicators. It detects a double bottom pattern, higher highs & higher lows, and an EMA crossover before confirming a breakout with increasing volume.
📊 Key Components
1️⃣ 📉 Double Bottom Formation
Detects a double bottom pattern by identifying two lows within a set period (10 & 20 bars).
If the second low is slightly higher than the first, it suggests potential accumulation before a breakout.
2️⃣ 📈 Higher High & Higher Low Confirmation
Checks if the current high is greater than the previous highest high (past 2 bars).
Confirms a higher low to ensure price is forming a bullish structure.
3️⃣ 📊 EMA Crossover for Trend Confirmation
Uses 4 Exponential Moving Averages (EMAs):
✅ 200 EMA (Long-term Trend) – Key support/resistance level.
✅ 189 EMA (Support Level) – Close to 200 EMA for additional confirmation.
✅ 20 EMA (Short-term Trend) – Captures early bullish momentum.
✅ 9 EMA (Fastest EMA) – Confirms rapid trend shifts.
A bullish EMA crossover happens when 9 EMA & 20 EMA cross above the 189 EMA, signaling trend strength.
4️⃣ 📊 Breakout with Rising Volume
Confirms breakout only if the price breaks above the highest high of the last 5 bars.
Volume must be 1.5x greater than the 20-bar moving average of volume (sma(volume, 20) * 1.5).
This ensures strong buyer participation.
5️⃣ 🔔 Buy Signal + Alerts
If all conditions are met, a BUY signal is plotted on the chart.
Sound alert triggered using alertcondition() so traders receive notifications.
Williams %RIndicator Name:
Williams %R
Disclaimer
Various factors can affect changes in the value of financial assets. These include, but are not limited to, geopolitical issues, industry policies, and technological developments within the industry. Other influencing elements include expectations of interest rates, inflation or deflation, unemployment rates, company development strategies, company revenues and liabilities, investor sentiment, and preferences for investor trading strategies. These factors may pose a risk of loss to investors' investment costs. Moreover, the past performance of individual trades does not guarantee future results or returns. Therefore, no a single idea, algorithm, script, indicator, or system content can account for all factors influencing financial asset value fluctuations. Investors are fully responsible for any investment decisions they make, and such decisions should be based entirely on an assessment of their financial situation, investment goals, risk tolerance, and liquidity needs.
The content provided in my ideas, algorithms, scripts, indicators, and systems is intended solely to demonstrate changes in the value of financial assets for educational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. The provider will not accept liability for any loss or damage, including, without limitation, any loss of investment costs, which may arise directly or indirectly from the use of or reliance on such information.
About Coffee
I would be delighted if my ideas, algorithms, scripts, indicators, and code can assist or inspire your pricing model. Should you feel inclined to buy me a cup of coffee, please feel free to contact me on TradingView. I am also more than willing to share my proprietary code indicators with you, along with practical usage tips for the related indicators.
CRYPTOCAP:ETH | CRYPTOCAP:USDT | CRYPTOCAP:USDC
0xE1b33484211595Ba4Dd9d6fEa52D64e873AfDe12
CRYPTOCAP:SOL | CRYPTOCAP:USDT | CRYPTOCAP:USDC
H8P3o2mqsb4u1R3TZa9PXKg5e5weyQFHVFMfZUPjheYE
CRYPTOCAP:USDT | CRYPTOCAP:USDC
TKQQNAZqBLQQMBSE98kEQdg6wRRqykNveh
CRYPTOCAP:BTC
bc1pkylhtk7srdqk6cyk7vfggzkkv8898drnmjpnvv69mp99uswh6rlstq63vr
Introduction to Indicator
Non-negative and negative values of the Williams %R indicator model.
Applicable to all time intervals.
Indicator effect display
S&P 500 Index ( SP:SPX )
S&P 500 Index ( SP:SPX )
Tesla, Inc. ( NASDAQ:TSLA )
Tesla, Inc. ( NASDAQ:TSLA )
Bitcoin / U.S. Dollar ( BITSTAMP:BTCUSD )
Bitcoin / U.S. Dollar ( BITSTAMP:BTCUSD )
Smoothed EMA LinesThe "Smoothed EMA Lines" script is a technical analysis tool designed to help traders identify trends and potential support/resistance levels in financial markets. The script plots exponential moving averages (EMAs) of the closing price for five commonly used time periods: 8, 13, 21, 55, and 200.
Key features of the script include:
Overlay: The EMAs are plotted directly on the price chart, making it easy to analyze the relationship between the moving averages and price action.
Smoothing: The script applies an additional smoothing function to each EMA, using a simple moving average (SMA) of a user-defined length. This helps to reduce noise and provide a clearer picture of the trend.
Customizable lengths: Users can easily adjust the length of each EMA and the smoothing period through the script's input parameters.
Color-coded plots: Each EMA is assigned a unique color (8: blue, 13: green, 21: orange, 55: red, 200: purple) for easy identification on the chart.
Traders can use the "Smoothed EMA Lines" script to:
Identify the overall trend direction (bullish, bearish, or neutral) based on the arrangement of the EMAs.
Spot potential support and resistance levels where the price may interact with the EMAs.
Look for crossovers between EMAs as potential entry or exit signals.
Combine the EMA analysis with other technical indicators and price action patterns for a more comprehensive trading strategy.
The "Smoothed EMA Lines" script provides a clear, customizable, and easy-to-interpret visualization of key exponential moving averages, helping traders make informed decisions based on trend analysis.
Oracle Fear and GreedCustom Fear and Greed Oscillator with Movement Table
This indicator provides a unique perspective on market sentiment by calculating a custom fear/greed oscillator based on Heikin-Ashi candles. The oscillator is centered at 50, with values above 50 suggesting bullish sentiment ("greed") and below 50 indicating bearish sentiment ("fear"). The calculation incorporates candle body size, range, and a custom "candle strength" measure, providing an innovative approach to understanding market behavior.
Key Features:
Heikin-Ashi Based Oscillator:
Utilizes Heikin-Ashi candles to compute a custom oscillator. The value is centered at 50, with deviations indicating the prevailing market sentiment.
Dynamic Gradient Coloring:
The oscillator line is dynamically colored with a smooth gradient—from blue (representing fear) at lower values to pink (representing greed) at higher values—making it visually intuitive.
Horizontal Levels:
Two additional horizontal lines are drawn at 40.62 ("Bottom") and 60.74 ("Top"), which may serve as potential oversold and overbought boundaries respectively.
Fast Movement Metrics:
Every 5 bars, the indicator calculates the percentage change in the Heikin-Ashi close. This fast movement analysis distinguishes rapid downward moves (fast fear) from rapid upward moves (fast greed), helping to capture sudden market shifts.
Information Table:
A table in the top-right corner displays the most recent fast movement values for both fear and greed, offering quick insights into short-term market dynamics.
Usage Tips:
Adjust the smoothing period to match your preferred trading timeframe.
Use the oscillator alongside other analysis tools for more robust trading decisions.
Ideal for those looking to experiment with new approaches to sentiment analysis and momentum detection.
Disclaimer:
This indicator is intended for educational and experimental purposes. It should not be used as the sole basis for any trading decisions. Always combine with comprehensive market analysis and risk management strategies.
You can add this description when publishing your indicator on TradingView to help other users understand its features and intended use.
SMA High & LowThis Pine Script indicator plots two Simple Moving Averages (SMA) based on high and low prices over a specified length. It also references the H4 (4-hour) timeframe SMA to determine the color of the lines:
- Green if the current price is above the H4 SMA High.
- Red if the current price is below the H4 SMA Low.
- Orange if the price is between the H4 SMA High and Low.
This helps traders visualize market trends based on higher timeframe SMA levels.
Multi Asset Similarity MatrixProvides a unique and visually stunning way to analyze the similarity between various stock market indices. This script uses a range of mathematical measures to calculate the correlation between different assets, such as indices, forex, crypto, etc..
Key Features:
Similarity Measures: The script offers a range of similarity measures to choose from, including SSD (Sum of Squared Differences), Euclidean Distance, Manhattan Distance, Minkowski Distance, Chebyshev Distance, Correlation Coefficient, Cosine Similarity, Camberra Index, Mean Absolute Error (MAE), Mean Squared Error (MSE), Lorentzian Function, Intersection, and Penrose Shape.
Asset Selection: Users can select the assets they want to analyze by entering a comma-separated list of tickers in the "Asset List" input field.
Color Gradient: The script uses a color gradient to represent the similarity values between each pair of indices, with red indicating low similarity and blue indicating high similarity.
How it Works:
The script calculates the source method (Returns or Volume Modified Returns) for each index using the sec function.
It then creates a matrix to hold the current values of each index over a specified window size (default is 10).
For each pair of indices, it applies the selected similarity measure using the select function and stores the result in a separate matrix.
The script calculates the maximum and minimum values of the similarity matrix to normalize the color gradient.
Finally, it creates a table with the index names as rows and columns, displaying the similarity values for each pair of indices using the calculated colors.
Visual Insights:
The indicator provides an intuitive way to visualize the relationships between different assets. By analyzing the color-coded tables, traders can gain insights into:
Which assets are highly correlated (blue) or uncorrelated (red)
The strength and direction of these correlations
Potential trading opportunities based on similarities and differences between assets
Overall, MASM is a powerful tool for market analysis and visualization, offering a unique perspective on the relationships between various assets.
~llama3
Günlük Alış ve Satış Sinyalleri (5 Günlük ve 22 Günlük)//@version=6
indicator('Günlük Alış ve Satış Sinyalleri (5 Günlük ve 22 Günlük)', overlay = true)
// 5 günlük ve 22 günlük hareketli ortalamaların hesaplanması
sma5 = ta.sma(close, 5) // 5 günlük SMA
sma22 = ta.sma(close, 22) // 22 günlük SMA
// Alış ve satış sinyalleri
longCondition = ta.crossover(sma5, sma22) // 5 günlük SMA'nın 22 günlük SMA'yı yukarıdan kesmesi
shortCondition = ta.crossunder(sma5, sma22) // 5 günlük SMA'nın 22 günlük SMA'yı aşağıdan kesmesi
// Sinyalleri grafikte gösterme
plotshape(longCondition, style = shape.labelup, location = location.belowbar, color = color.green, size = size.small, text = 'AL', offset = -1)
plotshape(shortCondition, style = shape.labeldown, location = location.abovebar, color = color.red, size = size.small, text = 'SAT', offset = -1)
// Hareketli ortalamaların grafikte gösterimi
plot(sma5, color = color.orange, title = '5 Günlük SMA', linewidth = 2)
plot(sma22, color = color.blue, title = '22 Günlük SMA', linewidth = 2)
// Fiyattan uzaklığı görselleştirmek için SMA'lar arası mesafenin gösterilmesi
fill(plot(sma5, color = color.orange, title = '5 Günlük SMA'), plot(sma22, color = color.blue, title = '22 Günlük SMA'), color = color.new(color.gray, 90), title = 'SMA Alanı')
sma 9/20 crossThis Pine Script is designed to visualize the crossover between two Simple Moving Averages (SMAs) on a chart: a fast SMA (9-period) and a slow SMA (20-period). The script will dynamically adjust the background color based on whether the fast SMA is above or below the slow SMA.
Key Components of the Script:
Inputs for SMA Lengths:
The script allows you to adjust the lengths of the two SMAs by inputting values for smaFastLength (default = 9) and smaSlowLength (default = 20). These lengths define how many periods (candles) the SMAs consider when calculating the moving averages.
SMA Calculations:
The script calculates two SMAs using the close price:
smaFast is the 9-period SMA.
smaSlow is the 20-period SMA.
These are calculated using TradingView’s built-in ta.sma function, which computes the simple moving average for the given period.
Background Color Logic:
The background color is dynamically updated based on the crossover condition:
Green background: When the fast SMA (smaFast) is above the slow SMA (smaSlow), indicating a bullish trend.
Red background: When the fast SMA is below the slow SMA, indicating a bearish trend.
The bgcolor function is used to change the background color on the chart. The transparency of the background color is set to 35% using color.new(color.green, 35) or color.new(color.red, 35).
Plotting the SMAs:
The two SMAs are plotted on the chart for visual reference:
The fast SMA is plotted in lime green (color.blue).
The slow SMA is plotted in red (color.red).
sma 9/20 crossThis Pine Script is designed to visualize the crossover between two Simple Moving Averages (SMAs) on a chart: a fast SMA (9-period) and a slow SMA (20-period). The script will dynamically adjust the background color based on whether the fast SMA is above or below the slow SMA.
Key Components of the Script:
Inputs for SMA Lengths:
The script allows you to adjust the lengths of the two SMAs by inputting values for smaFastLength (default = 9) and smaSlowLength (default = 20). These lengths define how many periods (candles) the SMAs consider when calculating the moving averages.
SMA Calculations:
The script calculates two SMAs using the close price:
smaFast is the 9-period SMA.
smaSlow is the 20-period SMA.
These are calculated using TradingView’s built-in ta.sma function, which computes the simple moving average for the given period.
Background Color Logic:
The background color is dynamically updated based on the crossover condition:
Green background: When the fast SMA (smaFast) is above the slow SMA (smaSlow), indicating a bullish trend.
Red background: When the fast SMA is below the slow SMA, indicating a bearish trend.
The bgcolor function is used to change the background color on the chart. The transparency of the background color is set to 35% using color.new(color.green, 35) or color.new(color.red, 35).
Plotting the SMAs:
The two SMAs are plotted on the chart for visual reference:
The fast SMA is plotted in lime green (color.lime).
The slow SMA is plotted in red (color.red).
Open Interest ImbalanceThis Pine Script indicator displays options open interest (OI) imbalances and max pain levels (highlighted with yellow dots). It shows continuous strike intervals as colored boxes—blue for call dominance and red for put dominance—with box heights scaled by total OI. You can easily adjust the color intensity to suit your preferences.
Currently it contains the OI imbalance data for GME and CHWY
Questions? Contact me at kurtkot@gmail.com.
If you find this indicator useful, donations of any ERC20 coin to 0x3e90543611Cf128d136f72C943Aa36a2bd286315 are appreciated.
TEMA OBOS Strategy PakunTEMA OBOS Strategy
Overview
This strategy combines a trend-following approach using the Triple Exponential Moving Average (TEMA) with Overbought/Oversold (OBOS) indicator filtering.
By utilizing TEMA crossovers to determine trend direction and OBOS as a filter, it aims to improve entry precision.
This strategy can be applied to markets such as Forex, Stocks, and Crypto, and is particularly designed for mid-term timeframes (5-minute to 1-hour charts).
Strategy Objectives
Identify trend direction using TEMA
Use OBOS to filter out overbought/oversold conditions
Implement ATR-based dynamic risk management
Key Features
1. Trend Analysis Using TEMA
Uses crossover of short-term EMA (ema3) and long-term EMA (ema4) to determine entries.
ema4 acts as the primary trend filter.
2. Overbought/Oversold (OBOS) Filtering
Long Entry Condition: up > down (bullish trend confirmed)
Short Entry Condition: up < down (bearish trend confirmed)
Reduces unnecessary trades by filtering extreme market conditions.
3. ATR-Based Take Profit (TP) & Stop Loss (SL)
Adjustable ATR multiplier for TP/SL
Default settings:
TP = ATR × 5
SL = ATR × 2
Fully customizable risk parameters.
4. Customizable Parameters
TEMA Length (for trend calculation)
OBOS Length (for overbought/oversold detection)
Take Profit Multiplier
Stop Loss Multiplier
EMA Display (Enable/Disable TEMA lines)
Bar Color Change (Enable/Disable candle coloring)
Trading Rules
Long Entry (Buy Entry)
ema3 crosses above ema4 (Golden Cross)
OBOS indicator confirms up > down (bullish trend)
Execute a buy position
Short Entry (Sell Entry)
ema3 crosses below ema4 (Death Cross)
OBOS indicator confirms up < down (bearish trend)
Execute a sell position
Take Profit (TP)
Entry Price + (ATR × TP Multiplier) (Default: 5)
Stop Loss (SL)
Entry Price - (ATR × SL Multiplier) (Default: 2)
TP/SL settings are fully customizable to fine-tune risk management.
Risk Management Parameters
This strategy emphasizes proper position sizing and risk control to balance risk and return.
Trading Parameters & Considerations
Initial Account Balance: $7,000 (adjustable)
Base Currency: USD
Order Size: 10,000 USD
Pyramiding: 1
Trading Fees: $0.94 per trade
Long Position Margin: 50%
Short Position Margin: 50%
Total Trades (M5 Timeframe): 128
Deep Test Results (2024/11/01 - 2025/02/24)BTCUSD-5M
Total P&L：+1638.20USD
Max equity drawdown：694.78USD
Total trades：128
Profitable trades:44.53
Profit factor:1.45
These settings aim to protect capital while maintaining a balanced risk-reward approach.
Visual Support
TEMA Lines (Three EMAs)
Trend direction is indicated by color changes (Blue/Orange)
ema3 (short-term) and ema4 (long-term) crossover signals potential entries
OBOS Histogram
Green → Strong buying pressure
Red → Strong selling pressure
Blue → Possible trend reversal
Entry & Exit Markers
Blue Arrow → Long Entry Signal
Red Arrow → Short Entry Signal
Take Profit / Stop Loss levels displayed
Strategy Improvements & Uniqueness
This strategy is based on indicators developed by "l_lonthoff" and "jdmonto0", but has been significantly optimized for better entry accuracy, visual clarity, and risk management.
Enhanced Trend Identification with TEMA
Detects early trend reversals using ema3 & ema4 crossover
Reduces market noise for a smoother trend-following approach
Improved OBOS Filtering
Prevents excessive trading
Reduces unnecessary risk exposure
Dynamic Risk Management with ATR-Based TP/SL
Not a fixed value → TP/SL adjusts to market volatility
Fully customizable ATR multiplier settings
(Default: TP = ATR × 5, SL = ATR × 2)
Summary
The TEMA + OBOS Strategy is a simple yet powerful trading method that integrates trend analysis and oscillators.
TEMA for trend identification
OBOS for noise reduction & overbought/oversold filtering
ATR-based TP/SL settings for dynamic risk management
Before using this strategy, ensure thorough backtesting and demo trading to fine-tune parameters according to your trading style.
