PΞCKΞR All-In-One (PECKER AIO)The PΞCKΞR All-In-One (PECKER AIO) indicator offers traders a comprehensive tool for technical analysis, blending various features into a single indicator. It integrates essential analytical tools such as RSI, Moving Averages, divergence detection, and multiple EMA overlays.
RSI in-chart divergences:
Identify both regular and hidden bullish/bearish divergences to anticipate potential market swings.
Visually overlay divergences directly on the chart for quick recognition.
Moving Averages:
Choose from SMA, EMA, or SMMA.
Adjustable lengths to suit different trading strategies.
Multi-Timeframe EMAs:
No matter which time-frame you are looking at, display 4-hour, daily, weekly, and more EMA levels to track critical trend changes across different timeframes.
Fully customizable with color, length, and line width options.
Price Level Markers:
Annote key price points such as daily, weekly, monthly opens, highs, lows, and mid-levels.
Monday range (High - 0.5 - Low) also included.
Adaptable to right-anchored or standard display styles to match user preferences.
This all-encompassing indicator is designed to suit both day traders and long-term strategists, providing a detailed yet straightforward approach to chart analysis.
Indicateurs et stratégies
Profit Hunter The Tower of Data指標用途 / Purpose of the Indicator
本指標旨在綜合監測加密貨幣市場的狀況。透過分析比特幣與以太坊的市值佔比、穩定幣市場比率、歷史最高點距離（ATH）及波動性指標（ATR），交易者可以獲取市場動態、評估風險以及尋找潛在的交易機會。
English: This indicator aims to provide a comprehensive monitoring of the cryptocurrency market conditions. By analyzing the market dominance of Bitcoin and Ethereum, the stablecoin market ratio, distance to all-time high (ATH), and volatility indicator (ATR), traders can gain insights into market dynamics, assess risks, and identify potential trading opportunities.
指標依據 / Basis of the Indicator
1. 市值佔比：計算比特幣和以太坊在總市場中的佔比，幫助判斷主流加密貨幣的市場情緒。
2. 穩定幣比率：評估比特幣市值與穩定幣總市值的比例，反映資金在風險資產和穩定幣之間的流動情況.
3. 歷史最高點距離（ATH）：顯示當前價格距離歷史最高價的百分比，幫助識別潛在的市場頂部或底部。
4. ATR 波動性指標：使用平均真實範圍（ATR）來測量市場的波動性，為風險管理提供參考。
1. Market Dominance: Calculates the market share of Bitcoin and Ethereum in the total market, helping to assess the market sentiment of major cryptocurrencies. 2. Stablecoin Ratio: Assesses the ratio of Bitcoin's market cap to the total market cap of stablecoins, reflecting the flow of funds between risk assets and stablecoins. 3. Distance to All-Time High (ATH): Displays the percentage distance from the current price to the historical peak, helping to identify potential market tops or bottoms. 4. ATR Volatility Indicator: Uses Average True Range (ATR) to measure market volatility, providing a reference for risk management.
數值大小含意及操作建議 / Value Interpretation and Trading Suggestions
1. 市值佔比：> 60% 顯示市場對比特幣和以太坊的信心較高，適合進行長期持有或交易；< 60% 可能表示資金流出，需謹慎觀察市場情緒。
2. 穩定幣比率：>800% 表明市場對比特幣的信心強，適宜進場交易；< 800% 反映市場對穩定幣的需求增加，建議觀望
3. ATH 距離：正值顯示當前價格低於歷史最高點，可能存在回升機會；負值則表示當前價格高於歷史最高點，需謹慎進場。
4. ATR 波動性指標：1-30 分 市場波動性低，適合穩健操作；31-70 分 市場波動性中等，需注意潛在風險；71-99 分 市場波動性高，建議減少倉位或觀望。
1. Market Dominance: > 60% indicates high confidence in Bitcoin and Ethereum, suitable for long-term holding or trading; < 60% may indicate capital outflow, caution is advised. 2. Stablecoin Ratio: > 700% suggests strong confidence in Bitcoin, suitable for entering trades; < 700% reflects increased demand for stablecoins, suggesting a watchful approach. 3. Distance to All-Time High (ATH): Positive values indicate the current price is below the historical peak, presenting a potential rebound opportunity; negative values indicate the current price is above the historical peak, caution is advised. 4. ATR Volatility Indicator: 1-30 Points indicates low market volatility, suitable for stable operations; 31-70 Points indicates moderate market volatility, watch for potential risks; 71-99 Points indicates high market volatility, recommend reducing positions or adopting a wait-and-see approach. \72\72\72
Long-Term Pivot and Golden Crossover Strategy//@version=5
strategy("Long-Term Pivot and Golden Crossover Strategy", overlay=true)
// Input for moving averages
shortTerm = input.int(100, title="Short-term SMA Period") // 100-period SMA
longTerm = input.int(200, title="Long-term SMA Period") // 200-period SMA
// Calculate moving averages
sma100 = ta.sma(close, shortTerm)
sma200 = ta.sma(close, longTerm)
// Golden crossover: when short-term SMA crosses above long-term SMA
goldenCrossover = ta.crossover(sma100, sma200)
// Calculate daily pivot points (traditional formula)
pivot = (high + low + close) / 3
support1 = pivot - (high - low)
resistance1 = pivot + (high - low)
support2 = pivot - 2 * (high - low)
resistance2 = pivot + 2 * (high - low)
// Plot SMAs and pivot points on the chart
plot(sma100, color=color.blue, title="100-period SMA", linewidth=2)
plot(sma200, color=color.red, title="200-period SMA", linewidth=2)
plot(pivot, color=color.purple, title="Pivot Point", linewidth=2)
plot(support1, color=color.green, title="Support 1", linewidth=1)
plot(resistance1, color=color.green, title="Resistance 1", linewidth=1)
plot(support2, color=color.green, title="Support 2", linewidth=1)
plot(resistance2, color=color.green, title="Resistance 2", linewidth=1)
// Entry Condition: Golden crossover with price above the pivot point
longCondition = goldenCrossover and close > pivot
// Exit Condition: You can use a stop-loss and take-profit, or a bearish crossover
stopLossPercent = input.float(3, title="Stop Loss (%)") / 100 // Wider stop loss for long-term trades
takeProfitPercent = input.float(10, title="Take Profit (%)") / 100 // Higher take profit for long-term trades
// Calculate stop-loss and take-profit prices
longStopLoss = close * (1 - stopLossPercent)
longTakeProfit = close * (1 + takeProfitPercent)
// Execute strategy
if (longCondition)
strategy.entry("Long", strategy.long, stop=longStopLoss, limit=longTakeProfit)
// Optional: Exit strategy based on a bearish crossover
exitCondition = ta.crossunder(sma100, sma200)
if (exitCondition)
strategy.close("Long")
// Strategy exit with custom stop loss and take profit
strategy.exit("Take Profit/Stop Loss", from_entry="Long", stop=longStopLoss, limit=longTakeProfit)
Profit Hunter The Tower of Data指標用途 / Purpose of the Indicator
中文：本指標旨在綜合監測加密貨幣市場的狀況。透過分析比特幣與以太坊的市值佔比、穩定幣市場比率、歷史最高點距離（ATH）及波動性指標（ATR），交易者可以獲取市場動態、評估風險以及尋找潛在的交易機會。
English: This indicator aims to provide a comprehensive monitoring of the cryptocurrency market conditions. By analyzing the market dominance of Bitcoin and Ethereum, the stablecoin market ratio, distance to all-time high (ATH), and volatility indicator (ATR), traders can gain insights into market dynamics, assess risks, and identify potential trading opportunities.
指標依據 / Basis of the Indicator
中文：1. 市值佔比：計算比特幣和以太坊在總市場中的佔比，幫助判斷主流加密貨幣的市場情緒。 2. 穩定幣比率：評估比特幣市值與穩定幣總市值的比例，反映資金在風險資產和穩定幣之間的流動情況。 3. 歷史最高點距離（ATH）：顯示當前價格距離歷史最高價的百分比，幫助識別潛在的市場頂部或底部。 4. ATR 波動性指標：使用平均真實範圍（ATR）來測量市場的波動性，為風險管理提供參考。
English: 1. Market Dominance: Calculates the market share of Bitcoin and Ethereum in the total market, helping to assess the market sentiment of major cryptocurrencies. 2. Stablecoin Ratio: Assesses the ratio of Bitcoin's market cap to the total market cap of stablecoins, reflecting the flow of funds between risk assets and stablecoins. 3. Distance to All-Time High (ATH): Displays the percentage distance from the current price to the historical peak, helping to identify potential market tops or bottoms. 4. ATR Volatility Indicator: Uses Average True Range (ATR) to measure market volatility, providing a reference for risk management.
數值大小含意及操作建議 / Value Interpretation and Trading Suggestions
中文：1. 市值佔比：> 60% 顯示市場對比特幣和以太坊的信心較高，適合進行長期持有或交易；< 60% 可能表示資金流出，需謹慎觀察市場情緒。 2. 穩定幣比率：> 700% 表明市場對比特幣的信心強，適宜進場交易；< 700% 反映市場對穩定幣的需求增加，建議觀望。 3. ATH 距離：正值顯示當前價格低於歷史最高點，可能存在回升機會；負值則表示當前價格高於歷史最高點，需謹慎進場。 4. ATR 波動性指標：1-30 分 市場波動性低，適合穩健操作；31-70 分 市場波動性中等，需注意潛在風險；71-99 分 市場波動性高，建議減少倉位或觀望。
English: 1. Market Dominance: > 60% indicates high confidence in Bitcoin and Ethereum, suitable for long-term holding or trading; < 60% may indicate capital outflow, caution is advised. 2. Stablecoin Ratio: > 700% suggests strong confidence in Bitcoin, suitable for entering trades; < 700% reflects increased demand for stablecoins, suggesting a watchful approach. 3. Distance to All-Time High (ATH): Positive values indicate the current price is below the historical peak, presenting a potential rebound opportunity; negative values indicate the current price is above the historical peak, caution is advised. 4. ATR Volatility Indicator: 1-30 Points indicates low market volatility, suitable for stable operations; 31-70 Points indicates moderate market volatility, watch for potential risks; 71-99 Points indicates high market volatility, recommend reducing positions or adopting a wait-and-see approach.
Brono MacroThis indicator, developed by someone (satz) helps identify macro market trends and potential reversal points by aligning with Institutional Order Flow. It provides visual markers for key timeframes and allows traders to better time entries and exits based on larger market movements. Perfect for traders using ICT (Inner Circle Trader) concepts, it highlights critical time periods on the chart, enabling a strategic approach to trading major market trends.
Custom AO with Open Difference**Custom AO with Open Difference Indicator**
This indicator, *Custom AO with Open Difference*, is designed to help confirm trend direction based on the relationship between the daily open price and recent 4-hour open prices. It calculates the Awesome Oscillator (AO) based on the difference between the daily open price and the average of the previous six 4-hour open prices. This approach provides insight into whether the current open price is significantly diverging from recent short-term opens, which can indicate a trend shift or continuation.
### Technical Analysis and Features
1. **Trend Confirmation**: By comparing the daily open with the mean of six previous 4-hour open prices, this indicator helps identify trends. When the current daily open is below the average of recent opens, the AO value will plot as green, signaling potential upward momentum. Conversely, if the daily open is above the recent average, the histogram will plot red, suggesting possible downward momentum.
2. **Non-Repainting**: Since it relies on completed 4-hour and daily open prices, this indicator does not repaint, ensuring that all values remain fixed after the close of each period. This non-repainting feature makes it suitable for backtesting and reliable for trend confirmation without fear of historical changes.
3. **AO Mean Calculation**: The indicator calculates the average of six previous 4-hour open prices, providing a smoothed value to reduce short-term noise. This helps in identifying meaningful deviations, making the AO values a more stable basis for trend determination than using just the latest 4-hour or daily open.
4. **Histogram for Visual Clarity**: The indicator is displayed as a histogram, making it easy to identify trend changes visually. If the AO bar turns green, it’s a signal that the 4-hour average is below the daily open, suggesting an uptrend or bullish momentum. Red bars indicate that the daily open is above the recent 4-hour averages, potentially signaling a downtrend or bearish momentum.
### Practical Application
The *Custom AO with Open Difference* is a versatile tool for confirming the open price trend without needing complex oscillators or lagging indicators. Traders can use this tool to gauge the market sentiment by observing open price variations and use it as a foundation for decision-making in both short-term and daily timeframes. Its non-repainting nature adds reliability for traders using this indicator as part of a broader trading strategy.
Voltron + DVOL/UVOL Combined IndicatorCombinations of my technical analysis and some general market exhaustion
Multi VWAPs (Daily Weekly Monthly Yearly)This indicator calculates VWAP for daily, weekly, monthly, and yearly timeframes, which can be toggled on/off in the settings.
Each VWAP (Daily, Weekly, Monthly, and Yearly) is plotted with a different color for easy distinction:
Daily VWAP: Blue
Weekly VWAP: Green
Monthly VWAP: Purple
Yearly VWAP: Red
BRD Simple Moving Averages (12, 22, 55, 100, 200)Simple and clean moving averages. Easy to change the 5 values to your own in the script editor.
52-Week Low Buy-High Sell StrategyThis strategy can be used to test how much profit you would make on a script if you invest at 52 Week Low and Sell at 52 week high previous to the 52 week low.
[TT] Delta Based Support & Resistance Before Getting to the Indicator Concept, You need to understand What delta is.
For simple yet accurate understanding lets say the difference between Buyers and sellers is called delta. In a given time frame like 15mins for example, if we have 100 buyers and 75 sellers, delta will be 25, positive number indicates the buyers are dominating that particular candle. The volume of this candle will be 175, where delta indicates who dominated by just showing 25. We are literally following the volume, or in simple words the directional volume.
Now we all know that market is moved by Buyers and sellers and not by price alone. In that case why are we depending on indicators that are moved by close price which can be manipulated in real time. There is only one element in the market that cannot be manipulated and that is volume. We are using that Delta to determine our Direction and trend.
Note : Please wait for the candle to close and Level to form and only then enter on a retest of the level.
Usage of this Indicator.
in the following pictures one can see this indicator on NSE:BANKNIFTY And NSE:NIFTY , India's most Liquidity IDX and accuracy of our indicator.
Once the Buyers dominate the market after consolidation a support is formed and when sellers dominate a resistance is formed.
NSE:NIFTY 5Mins
Nifty50 1Hr
NSE:BANKNIFTY 1Hr
BANKNIFTY 5Min
BANKNIFTY 5Min
One can Use this in any Entity with volume like Commodities and Forex but do understand that forex have different exchange and different brokers and volume so be ware while working with such. following are the Forex and BTC and Gold
BITSTAMP:BTCUSD 1Hr
FXOPEN:XAUUSD 1Hr
4Hrs
This will help You get confirmation for Many other strategies. Always remember one thing, don't search for the trade let the trade come to you. Trade only when you see a perfect confirmation.
TRADE ENTRY
Enter in a trade when the price gets back in to the level Look at the following Chart in any timeframe.
For any Explanation you can contact me in Tradingview.
Note: CVD Calculation taken from Tradingview
Sumit Infusion-ndpDarvas with pivot. This script allows user to vies darvas box with ema distance and pivot .
ATAMOKU - Ichimoku-Based Independent Scoring System
Name Origin of ATAMOKU:
The name ATAMOKU combines "Ata" (which means "I existed" in Japanese and "ancestor or father" in Turkish, which is also my name) and "Moku," meaning "cloud" in Japanese. This name reflects a unique scoring system based on Ichimoku principles, designed to help traders analyze trends and identify entry and exit points more accurately.
Scoring System Overview:
ATAMOKU leverages key Ichimoku values, including the Conversion Line, Base Line, and Leading Spans A and B. By applying mathematical functions and formulas, these values are used to generate a comprehensive score that indicates market strength and trend direction. This scoring system works independently of the price position relative to the Ichimoku cloud, allowing traders to identify potential entry and exit points in any time frame.
Signal and Smoothing Lines:
The script includes signal and smoothed lines that display signals continuously and can be customized with different smoothing techniques such as SMA, EMA, and WMA. These lines visually highlight entry and exit points, adapting to the trader's individual strategy.
Settings and Customization:
ATAMOKU offers several customization options to suit various trading preferences:
Scoring Method:
The scoring system uses hierarchical comparisons of Ichimoku values, with configurable weights for each comparison.
Smoothing Techniques:
Users can choose from several smoothing methods (SMA, EMA, WMA) to adjust signal sensitivity, allowing traders to fine-tune the display according to their preferred trading style.
Period Adjustments:
Options for adjusting the period of the scoring and smoothing calculations are provided to accommodate different time frames and trading strategies.
Display and Visualization:
ATAMOKU presents the data using a histogram and line chart format, enabling traders to observe trends and potential entry and exit points quickly and clearly.
Key Features:
Flexibility Across Time Frames, usable on any time frame without restriction.
Independent Cloud Position Scoring, Generates signals and identifies entry and exit points independently of the price position relative to the cloud.
Multi-Dimensional Analysis, Analyzes various Ichimoku data points and uses mathematical functions to offer traders a comprehensive market view.
Support and Contact:
For further information, customization questions, or support, please feel free to reach out via Private Message on TradingView. If you have a Premium account, additional contact details can also be included in the Signature field below.
Cloud [BRTLab]🔍 Overview
BRTLab Cloud is a powerful indicator designed to provide traders with a precise view of market trends and potential reversal points by combining an adapted Cloud similar to Ichimoku with custom mathematical logic. This indicator not only highlights trend direction and support/resistance zones but also integrates a Trend Reversal Signal (based on BRTLab Wave Hunter logic) to identify possible turning points, as well as a custom RSI to help spot entry opportunities within the cloud. It’s an effective tool for assessing both current trends and potential reversal points, while factoring in market uncertainty.
🔑 Key Features & Parameters
The BRTLab Cloud indicator operates similarly to the Ichimoku Cloud, but with an adapted trend-detection logic to provide more accurate signals. The primary methodology of the script is to determine the market trend using the Cloud, and then identify potential entry points based on signals derived from reversal points, overbought and oversold conditions using a custom RSI oscillator.
To enhance the versatility of the indicator, several filtering components are integrated, allowing users to tailor the signals to their specific trading styles:
Uncertainty Zones: The script features a unique uncertainty filter, which is visually represented by bars colored in orange on the chart. These zones highlight periods when the trend direction indicated by the Cloud might be changing, alerting the user to potential risks and advising caution before entering trades.
Cloud Width Filtering: A cloud width filter helps eliminate signals during weak trends, ensuring that only well-formed trends are considered for trading, which reduces the likelihood of acting on unreliable signals.
Trend Reversal Signal: The Trend Reversal Signal serves as a predictor for potential trend changes. It provides a signal marked with the symbol "↺" on the chart, indicating that a trend change is likely, and that the Cloud may soon shift direction. After this signal appears, continuing to trade with the current trend may be risky due to the potential reversal.
Key adjustable parameters include:
Cloud Timeframe: This setting allows the user to choose the timeframe for displaying the Cloud, either on the current timeframe or higher timeframes. Higher timeframes provide more stable and reliable trend directions, making this setting essential for adapting the indicator to different strategies.
Minimum Cloud Width (%): This parameter sets the minimum cloud width in percentage to filter out weak signals. By excluding signals on narrow clouds, the trader ensures that only significant trends are considered.
Signal Sensitivity: This adjusts the strength of the buy and sell signals generated by the custom RSI oscillator. A higher sensitivity value leads to stronger signals, which are ideal for traders seeking more decisive entry points.
Uncertainty Sensitivity: This setting helps define the "zone of uncertainty" on the chart, signaling potential reversals or areas where the trend may shift. A lower value makes the indicator more sensitive to uncertainty, potentially reducing the number of entries in risky conditions and filtering out unreliable signals.
Potential Take-Profit: This optional feature allows the user to display potential exit points based on the indicator's trend analysis. It provides an additional layer of guidance for setting targets and managing exits.
Among these settings, Cloud Timeframe, Signal Sensitivity, and Uncertainty Sensitivity offer the most flexibility, allowing users to adjust the script to match their preferred trading style:
The parameters Cloud Timeframe, Signal Sensitivity, and Uncertainty Sensitivity offer flexibility, with Cloud Timeframe providing stable trend direction from higher timeframes and Signal Sensitivity adjusting entry signal strength. The Uncertainty Sensitivity parameter filters high-risk areas, reducing potential entries by identifying trend ambiguity on the chart.
⚙️ Signals & Logic
The BRTLab Cloud indicator generates buy and sell signals based on a combination of cloud settings, custom RSI values, and uncertainty filters. The signal logic is designed to identify clear and reliable entry points, ensuring the trader can act with confidence. Here's how the signals work:
Long Signals (Buy): When the cloud is colored blue (indicating an uptrend), the custom RSI indicates a potential reversal within the cloud, and the uncertainty filter does not signal a risk zone, the indicator generates a buy signal. Additionally, the cloud width must meet the minimum percentage set in the "Minimum Cloud Width (%)" setting, which helps to exclude weak signals from narrow clouds, ensuring only strong trends are considered.
Short Signals (Sell): When the cloud is colored red (indicating a downtrend), the custom RSI signals a potential reversal inside the cloud, and the uncertainty filter does not indicate a risk zone, the indicator generates a sell signal. Similarly, the cloud width must match the minimum setting in "Minimum Cloud Width (%)", which filters out weak signals from narrow clouds.
Uncertainty Filter: The uncertainty filter plays a key role in ensuring that signals are reliable. If the uncertainty filter detects a risk zone (highlighted by orange-colored bars on the chart), the signal is considered less reliable, and traders are advised to be cautious. This feature significantly reduces the chances of acting on false signals.
Visualization: When a buy or sell signal is triggered, the indicator provides clear visual cues such as arrows or symbols on the chart to help the trader easily identify the signal. These visual cues are accompanied by the respective cloud color (blue for uptrend, red for downtrend), making it easy for traders to interpret the market direction at a glance.
🌟 Why it's Unique
The BRTLab Cloud indicator is based on a cloud system similar to the Ichimoku Cloud, but with several unique enhancements that significantly improve trend analysis and reversal detection:
Combination of Ichimoku Cloud and Trend Reversal Detection: The indicator incorporates a modified mathematical logic for more accurate detection of trend reversal points. This enhanced logic makes it more effective at spotting reversals compared to traditional methods. Additionally, the indicator provides a clear display of trends from higher timeframes without repainting, allowing traders to rely on more stable and reliable trend data, which is particularly useful for multi-timeframe analysis.
Unique Cloud Width Filtering: The "Minimum Cloud Width (%)" setting ensures that only strong trends trigger buy or sell signals, filtering out weak signals from narrow clouds. A wider cloud indicates a more established and reliable trend, providing further confidence in the trade direction.
Custom RSI Signal Sensitivity: The custom RSI has been optimized for more accurate entry and exit points across different trend phases. The "Signal Sensitivity" setting allows traders to adjust the indicator based on current market conditions, making it adaptable to both volatile and stable market environments. This helps to identify trend reversals with greater precision.
Enhanced Visualization: The indicator offers flexible visualization options, including gradient cloud styles and extremum zones, which aid in confirming key levels. These features enhance the trader’s ability to interpret market conditions and make informed decisions about entry and exit points.
🔶 Application of the Indicator
Example Usage:
Trading with BRTLab Cloud involves taking trend signals within the cloud. Long and short signals occur when the price reaches significant levels in the cloud, filtered by "Signal Sensitivity," "Uncertainty Sensitivity," and "Minimum Cloud Width (%)" settings. These features allow traders to determine optimal entry and exit points by signaling potential reversals while factoring in market uncertainty.
✅ Conclusion
BRTLab Cloud is a versatile and advanced tool for trend and reversal analysis, blending Ichimoku-style cloud methodology, Trend Reversal Signals (based on BRTLab Wave Hunter logic), and a custom RSI to deliver accurate entry and exit points. This indicator suits both short- and long-term trading strategies, providing precise signals that help minimize risk, particularly in uncertain market conditions.
⚠️ Risk Disclaimer
Trading involves significant risk, and most day traders experience losses. All content, tools, scripts, articles, and educational materials provided by BRTLab are solely for informational and educational purposes. Past performance does not guarantee future results.
Systematic Investment Tracker with Enhanced Features DCATürkçe Açıklama:
Bu TradingView Pine Script kodu, belirlenen tarih aralığında iki farklı yatırım stratejisi uygulayarak yatırım performansını analiz etmeyi sağlar. Kullanıcı, "Sürekli Alım" ve "Düştükçe Alım" stratejileri arasında bir karşılaştırma yapabilir. Her stratejide, toplam harcama, elde edilen miktar, ortalama maliyet ve kâr yüzdesi hesaplanır. Kod ayrıca dinamik alım miktarını ayarlama ve grafiksel işaretleyiciler ekleme özelliklerine sahiptir. Performans karşılaştırması için grafik üzerinde bilgi etiketi ve bir tablo sunulur. İki dil arasında geçiş yapma (Türkçe/İngilizce) seçeneği de mevcuttur.
English Description:
This TradingView Pine Script code enables users to analyze investment performance by applying two different investment strategies within a specified date range. Users can compare between "Systematic Purchase" and "Purchase on Decline" strategies. For each strategy, total expenditure, quantity acquired, average cost, and profit percentage are calculated. The script includes options for dynamic purchase adjustment and graphical markers. A performance comparison is presented through an info label and a table on the chart. Additionally, there is an option to switch between English and Turkish languages.
Pivot Points (Standard, Woodie, Camarilla, Fibonacci)Pivot Points is a technical indicator that is used to determine the levels at which price may face support or resistance. The Pivot Points indicator consists of a pivot point (PP) level and several support (S) and resistance (R) levels.
Calculation
PP, resistance and support values are calculated in different ways, depending on the type of the indicator, specified by the Type field in indicator inputs. To calculate PP and support/resistance levels, the values OPENcurr, OPENprev, HIGHprev, LOWprev, CLOSEprev are used, which are the values of the current open and previous open, high, low and close, respectively, on the indicator resolution. The indicator resolution is set by the input of the Pivots Timeframe. If the Pivots Timeframe is set to AUTO (the default value), then the increased resolution is determined by the following algorithm:
for intraday resolutions up to and including 15 min, DAY (1D) is used
for intraday resolutions more than 15 min, WEEK (1W) is used
for daily resolutions MONTH is used (1M)
for weekly and monthly resolutions, 12-MONTH (12M) is used
Simplest Strategy Crossover with Labels Buy/Sell to $1000This Pine Script code, titled Custom Moving Average Crossover with Labels, is a trading indicator developed for the TradingView platform. It enables traders to visualize potential buy and sell signals based on the crossover of two moving averages, offering customizable settings for enhanced flexibility. Here’s a breakdown of its key features:
Key Features
User-Defined Moving Averages:
The script includes two moving averages: a fast and a slow one. Users can adjust the periods of each average (default values are 10 for the fast MA and 100 for the slow MA), allowing them to adapt the indicator to various market conditions and trading styles.
Time-Restricted Signal Validity:
The indicator includes settings for active trading hours, defined in UTC time. Users specify a start and end hour, making it possible to limit buy and sell signals to certain times of the day. This is especially useful for traders who wish to avoid signals outside their preferred trading hours or during periods of high volatility.
Crossover-Based Buy and Sell Signals:
Buy Signal: A "Buy" label is triggered and displayed when the fast moving average crosses above the slow moving average within the user-defined trading hours, signifying a potential upward trend.
Sell Signal: A "Sell" label is generated when the fast moving average crosses below the slow moving average, indicating a possible downtrend. Labels are displayed on the chart, color-coded for easy identification: green for buys and red for sells.
Profit Target Labels (+100 Points):
After each buy or sell entry, the indicator tracks price movements. When the price increases by 100 points from a buy entry or decreases by 100 points from a sell entry, a +100 label appears to signify a 100-point movement.
These labels serve as checkpoints to help traders assess performance and decide on further actions, such as taking profits or adjusting stop losses.
Visual Customization:
The moving averages are color-coded (blue for fast MA, red for slow MA) for easy distinction, and label text appears in white to enhance visibility against various chart backgrounds.
Benefits for Traders
Efficient Trade Identification: The moving average crossover combined with time-based restrictions allows traders to capture key market trends within chosen hours.
Clear Profit Checkpoints: The +100 point label alerts traders to significant price movement, useful for those looking for set profit targets.
Flexibility: Customizable inputs give users control over the indicator’s behavior, making it suitable for both day trading and swing trading.
This indicator is designed for traders looking to enhance their technical analysis with reliable, user-defined buy/sell signals, helping to increase confidence and improve trade timing based on objective data.
Use AI to create trend trading.This strategy is a trend trading strategy. This strategy used data from AI 2020-2023 as training data.
Based on Binance, it gives you about 6500% return from 2017 to now. But I put this strategy in a margin strategy of 5x. If you calculate the return by 5x, it brings about 783,000,000%.
If you assume there is no fee, you can earn about 8,443,000,000%.
Updated Volume SuperTrend AI (Expo)// This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) creativecommons.org
// © Zeiierman
//@version=5
indicator("Volume SuperTrend AI (Expo)", overlay=true)
// ~~ ToolTips {
t1="Number of nearest neighbors in KNN algorithm (k): Increase to consider more neighbors, providing a more balanced view but possibly smoothing out local patterns. Decrease for fewer neighbors to make the algorithm more responsive to recent changes. Number of data points to consider (n): Increase for more historical data, providing a broader context but possibly diluting recent trends. Decrease for less historical data to focus more on recent behavior."
t2="Length of weighted moving average for price (KNN_PriceLen): Higher values create a smoother price line, influencing the KNN algorithm to be more stable but less sensitive to short-term price movements. Lower values enhance responsiveness in KNN predictions to recent price changes but may lead to more noise. Length of weighted moving average for SuperTrend (KNN_STLen): Higher values lead to a smoother SuperTrend line, affecting the KNN algorithm to emphasize long-term trends. Lower values make KNN predictions more sensitive to recent SuperTrend changes but may result in more volatility."
t3="Length of the SuperTrend (len): Increase for a smoother trend line, ideal for identifying long-term trends but possibly ignoring short-term fluctuations. Decrease for more responsiveness to recent changes but risk of more false signals. Multiplier for ATR in SuperTrend calculation (factor): Increase for wider bands, capturing larger price movements but possibly missing subtle changes. Decrease for narrower bands, more sensitive to small shifts but risk of more noise."
t4="Type of moving average for SuperTrend calculation (maSrc): Choose based on desired characteristics. SMA is simple and clear, EMA emphasizes recent prices, WMA gives more weight to recent data, RMA is less sensitive to recent changes, and VWMA considers volume."
t5="Color for bullish trend (upCol): Select to visually identify upward trends. Color for bearish trend (dnCol): Select to visually identify downward trends. Color for neutral trend (neCol): Select to visually identify neutral trends."
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Input settings for K and N values
k = input.int(3, title = "Neighbors", minval=1, maxval=100,inline="AI", group="AI Settings")
n_ = input.int(10, title ="Data", minval=1, maxval=100,inline="AI", group="AI Settings", tooltip=t1)
n = math.max(k,n_)
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Input settings for prediction values
KNN_PriceLen = input.int(20, title="Price Trend", minval=2, maxval=500, step=10,inline="AITrend", group="AI Trend")
KNN_STLen = input.int(100, title="Prediction Trend", minval=2, maxval=500, step=10, inline="AITrend", group="AI Trend", tooltip=t2)
aisignals = input.bool(true,title="AI Trend Signals",inline="signal", group="AI Trend")
Bullish_col = input.color(color.lime,"",inline="signal", group="AI Trend")
Bearish_col = input.color(color.red,"",inline="signal", group="AI Trend")
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Define SuperTrend parameters
len = input.int(10, "Length", minval=1,inline="SuperTrend", group="Super Trend Settings")
factor = input.float(3.0,step=.1,inline="SuperTrend", group="Super Trend Settings", tooltip=t3)
maSrc = input.string("WMA","Moving Average Source", ,inline="", group="Super Trend Settings", tooltip=t4)
upCol = input.color(color.lime,"Bullish Color",inline="col", group="Super Trend Coloring")
dnCol = input.color(color.red,"Bearish Color",inline="col", group="Super Trend Coloring")
neCol = input.color(color.blue,"Neutral Color",inline="col", group="Super Trend Coloring", tooltip=t5)
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Calculate the SuperTrend based on the user's choice
vwma = switch maSrc
"SMA" => ta.sma(close*volume, len) / ta.sma(volume, len)
"EMA" => ta.ema(close*volume, len) / ta.ema(volume, len)
"WMA" => ta.wma(close*volume, len) / ta.wma(volume, len)
"RMA" => ta.rma(close*volume, len) / ta.rma(volume, len)
"VWMA" => ta.vwma(close*volume, len) / ta.vwma(volume, len)
atr = ta.atr(len)
upperBand = vwma + factor * atr
lowerBand = vwma - factor * atr
prevLowerBand = nz(lowerBand )
prevUpperBand = nz(upperBand )
lowerBand := lowerBand > prevLowerBand or close < prevLowerBand ? lowerBand : prevLowerBand
upperBand := upperBand < prevUpperBand or close > prevUpperBand ? upperBand : prevUpperBand
int direction = na
float superTrend = na
prevSuperTrend = superTrend
if na(atr )
direction := 1
else if prevSuperTrend == prevUpperBand
direction := close > upperBand ? -1 : 1
else
direction := close < lowerBand ? 1 : -1
superTrend := direction == -1 ? lowerBand : upperBand
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Collect data points and their corresponding labels
price = ta.wma(close,KNN_PriceLen)
sT = ta.wma(superTrend,KNN_STLen)
data = array.new_float(n)
labels = array.new_int(n)
for i = 0 to n - 1
data.set(i, superTrend )
label_i = price > sT ? 1 : 0
labels.set(i, label_i)
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Define a function to compute distance between two data points
distance(x1, x2) =>
math.abs(x1 - x2)
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Define the weighted k-nearest neighbors (KNN) function
knn_weighted(data, labels, k, x) =>
n1 = data.size()
distances = array.new_float(n1)
indices = array.new_int(n1)
// Compute distances from the current point to all other points
for i = 0 to n1 - 1
x_i = data.get(i)
dist = distance(x, x_i)
distances.set(i, dist)
indices.set(i, i)
// Sort distances and corresponding indices in ascending order
// Bubble sort method
for i = 0 to n1 - 2
for j = 0 to n1 - i - 2
if distances.get(j) > distances.get(j + 1)
tempDist = distances.get(j)
distances.set(j, distances.get(j + 1))
distances.set(j + 1, tempDist)
tempIndex = indices.get(j)
indices.set(j, indices.get(j + 1))
indices.set(j + 1, tempIndex)
// Compute weighted sum of labels of the k nearest neighbors
weighted_sum = 0.
total_weight = 0.
for i = 0 to k - 1
index = indices.get(i)
label_i = labels.get(index)
weight_i = 1 / (distances.get(i) + 1e-6)
weighted_sum += weight_i * label_i
total_weight += weight_i
weighted_sum / total_weight
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Classify the current data point
current_superTrend = superTrend
label_ = knn_weighted(data, labels, k, current_superTrend)
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Plot
col = label_ == 1?upCol:label_ == 0?dnCol:neCol
plot(current_superTrend, color=col, title="Volume Super Trend AI")
upTrend = plot(superTrend==lowerBand?current_superTrend:na, title="Up Volume Super Trend AI", color=col, style=plot.style_linebr)
Middle = plot((open + close) / 2, display=display.none, editable=false)
downTrend = plot(superTrend==upperBand?current_superTrend:na, title="Down Volume Super Trend AI", color=col, style=plot.style_linebr)
fill_col = color.new(col,90)
fill(Middle, upTrend, fill_col, fillgaps=false,title="Up Volume Super Trend AI")
fill(Middle, downTrend, fill_col, fillgaps=false, title="Down Volume Super Trend AI")
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~}
// ~~ Ai Super Trend Signals
Start_TrendUp = col==upCol and (col !=upCol or col ==neCol) and aisignals
Start_TrendDn = col==dnCol and (col !=dnCol or col ==neCol) and aisignals
// ~~ Add buy and sell signals
plotshape(Start_TrendUp, title="Buy Signal", location=location.belowbar, color=Bullish_col, style=shape.labelup, text="BUY")
plotshape(Start_TrendDn, title="Sell Signal", location=location.abovebar, color=Bearish_col, style=shape.labeldown, text="SELL")
Adaptive ema Cloud v1 Trend & Trade Signals"adaptive ema cloud v1 trend & trade signals" is a comprehensive technical indicator aimed at assisting traders in identifying market trends, trade entry points, and potential take profit (tp) and stop-loss (sl) levels. this indicator combines adaptive exponential moving average (ema) clouds with standard deviation bands to create a visual trend and signal system, enabling users to better analyze price action.
key features:
adaptive ema cloud: calculates a dynamic ema-based cloud using a simple moving average (sma) line, with upper and lower deviation bands based on standard deviations. users can adjust the standard deviation multiplier to modify the cloud's width.
trend direction detection: the indicator determines trend direction by comparing the close price to the ema cloud and signals bullish or bearish trends when the price crosses key levels.
take profit (tp) and stop-loss (sl) points: adaptive tp and sl levels are calculated based on the deviation bands, providing users with suggested exit points when a trade is triggered.
peak and valley detection: detects peaks and valleys in price, aiding traders in spotting potential support and resistance areas.
gradient-based cloud fill: dynamically fills the cloud with a gradient color based on trend strength, helping users visually gauge trend intensity.
trade tracking: tracks recent trades and records them in an internal memory, allowing users to view the last 20 trade outcomes, including whether tp or sl was hit.
how to use:
trend signals: look for green arrows (bullish trend) or red arrows (bearish trend) to identify potential entries based on trend crossovers.
tp/sl management: tp and sl levels are automatically calculated and displayed, with alerts available to notify users when these levels are reached.
adjustable settings: customize period length, standard deviation multiplier, and color preferences to match trading preferences and chart style.
inputs-
period: defines the look-back period for ema calculations.
standard deviation multiplier: adjusts cloud thickness by setting the multiplier for tp and sl bands.
gauge size: scales the gradient intensity for trend cloud visualization.
up/down colors: allows users to set custom colors for bullish and bearish bars.
alert conditions: this script has built-in alerts for trend changes, tp, and sl levels, providing users with automated notifications of important trading signals.
Universal Trend and Valuation System [QuantAlgo]Universal Trend and Valuation System 📊🧬
The Universal Trend and Valuation System by QuantAlgo is an advanced indicator designed to assess asset valuation and trends across various timeframes and asset classes. This system integrates multiple advanced statistical indicators and techniques with Z-score calculations to help traders and investors identify overbought/sell and oversold/buy signals. By evaluating valuation and trend strength together, this tool empowers users to make data-driven decisions, whether they aim to follow trends, accumulate long-term positions, or identify turning points in mean-reverting markets.
💫 Conceptual Foundation and Innovation
The Universal Trend and Valuation System by QuantAlgo provides a unique framework for assessing market valuation and trend dynamics through a blend of Z-score analysis and trend-following algorithm. Unlike traditional indicators that only reflect price direction, this system incorporates multi-layered data to reveal the relative value of an asset, helping users determine whether it’s overvalued, undervalued, or approaching a trend reversal. By combining high quality trend-following tools, such as Dynamic Score Supertrend, DEMA RSI, and EWMA, it evaluates trend stability and momentum quality, while Z-scores of performance ratios like Sharpe, Sortino, and Omega standardize deviations from historical trends, enabling traders and investors to spot extreme conditions. This dual approach allows users to better identify accumulation (undervaluation) and distribution (overvaluation) phases, enhancing strategies like Dollar Cost Averaging (DCA) and overall timing for entries and exits.
📊 Technical Composition and Calculation
The Universal Trend-Following Valuation System is composed of several trend-following and valuation indicators that create a dynamic dual scoring model:
Risk-Adjusted Ratios (Sharpe, Sortino, Omega): These ratios assess trend quality by analyzing an asset’s risk-adjusted performance. Sharpe and Sortino provide insight into trend consistency and risk/reward, while Omega evaluates profitability potential, helping traders and investors assess how favorable a trend or an asset is relative to its associated risk.
Dynamic Z-Scores: Z-scores are applied to various metrics like Price, RSI, and RoC, helping to identify statistical deviations from the mean, which indicate potential extremes in valuation. By combining these Z-scores, the system produces a cumulative score that highlights when an asset may be overbought or oversold.
Aggregated Trend-Following Indicators: The model consolidates multiple high quality indicators to highlight probable trend shifts. This helps confirm the direction and strength of market moves, allowing users to spot reversals or entry points with greater clarity.
📈 Key Indicators and Features
The Universal Trend and Valuation System combines various technical and statistical tools to deliver a well-rounded analysis of market trends and valuation:
The indicator utilizes trend-following indicators like RSI with DEMA smoothing and Dynamic Score Supertrend to minimize market noise, providing clearer and more stable trend signals. Sharpe, Sortino, and Omega ratios are calculated to assess risk-adjusted performance and volatility, adding a layer of analysis for evaluating trend quality. Z-scores are applied to these ratios, as well as Price and Rate of Change (RoC), to detect deviations from historical trends, highlighting extreme valuation levels.
The system also incorporates multi-layered visualization with gradient color coding to signal valuation states across different market conditions. These adaptive visual cues, combined with threshold-based alerts for overbought and oversold zones, help traders and investors track probable trend reversals or continuations and identify accumulation or distribution zones, adding reliability to both trend-following and mean-reversion strategies.
⚡️ Practical Applications and Examples
✅ Add the Indicator: Add the Universal Trend-Following Valuation System to your favourites and to your chart.
👀 Monitor Trend Shifts and Valuation Levels: Watch the average Z score, trend probability state and gradient colors to identify overbought and oversold conditions. During undervaluation, consider using a DCA strategy to gradually accumulate positions (buy), while overvaluation may signal distribution or profit-taking phases (sell).
🔔 Set Alerts: Configure alerts for significant trend or valuation changes, ensuring you can act on market movements promptly, even when you’re not actively monitoring the charts.
🌟 Summary and Usage Tips
The Universal Trend and Valuation System by QuantAlgo is a highly adaptable tool, designed to support both trend-following and valuation analysis across different market environments. By combining valuation metrics with high quality trend-following indicators, it helps traders and investors identify the relative value of an asset based on historical norms, providing more reliable overbought/sell and oversold/buy signals. The tool’s flexibility across asset types and timeframes makes it ideal for both short-term trading and long-term investment strategies like DCA, allowing users to capture meaningful trends while minimizing noise.
