Duong_Sideway ZoneThis indicator is designed to identify sideway (ranging) zones on the price chart. It uses a Moving Average (MA) and criteria such as the number of price crosses over the MA, as well as breakout checks, to determine whether the market is in a sideway state. When a sideway zone is detected, it is highlighted with a yellow background on the chart.
Key Features:
MA Line: Uses a Moving Average (MA) as the basis for trend identification.
Sideway Threshold: Based on the number of price crosses over the MA within a specific period.
Breakout Check: Excludes zones from being considered sideway if a breakout occurs beyond the ATR threshold.
Visual Highlighting: Highlights sideway zones with a yellow background for easy identification.
This indicator is ideal for traders looking to identify ranging market phases to adjust their trading strategies accordingly.
For example, if within the last 20 candles, the number of times the closing price crosses the MA5 is greater than 4, it is considered a sideway zone, except in cases where the closing price of a recent candle has broken out of the highest/ lowest price of the previous 20 candles.
Cerca negli script per "20蒙古币兑换人民币"
Long Position with 1:3 Risk Reward and 20EMA CrossoverThe provided Pine Script code implements a strategy to identify long entry signals based on a 20-EMA crossover on a 5-minute timeframe. Once a buy signal is triggered, it calculates and plots the following:
Entry Price: The price at which the buy signal is generated.
Stop Loss: The low of the previous candle, acting as a risk management tool.
Take Profit: The price level calculated based on a 1:3 risk-reward ratio.
Key Points:
Buy Signal: A buy signal is generated when the current 5-minute candle closes above the 20-EMA.
Risk Management: The stop-loss is set below the entry candle to limit potential losses.
Profit Target: The take-profit is calculated based on a 1:3 risk-reward ratio, aiming for a potential profit three times the size of the risk.
Visualization: The script plots the entry price, stop-loss, and take-profit levels on the chart for visual clarity.
Remember:
Backtesting: It's crucial to backtest this strategy on historical data to evaluate its performance and optimize parameters.
Risk Management: Always use appropriate risk management techniques, such as stop-loss orders and position sizing, to protect your capital.
Market Conditions: Market conditions can change, and strategies that worked in the past may not perform as well in the future. Continuously monitor and adapt your strategy.
By understanding the core components of this script and applying sound risk management principles, you can effectively use it to identify potential long entry opportunities in the market.
Prediction Based on Linreg & Atr
We created this algorithm with the goal of predicting future prices 📊, specifically where the value of any asset will go in the next 20 periods ⏳. It uses linear regression based on past prices, calculating a slope and an intercept to forecast future behavior 🔮. This prediction is then adjusted according to market volatility, measured by the ATR 📉, and the direction of trend signals, which are based on the MACD and moving averages 📈.
How Does the Linreg & ATR Prediction Work?
1. Trend Calculation and Signals:
o Technical Indicators: We use short- and long-term exponential moving averages (EMA), RSI, MACD, and Bollinger Bands 📊 to assess market direction and sentiment (not visually presented in the script).
o Calculation Functions: These include functions to calculate slope, average, intercept, standard deviation, and Pearson's R, which are crucial for regression analysis 📉.
2. Predicting Future Prices:
o Linear Regression: The algorithm calculates the slope, average, and intercept of past prices to create a regression channel 📈, helping to predict the range of future prices 🔮.
o Standard Deviation and Pearson's R: These metrics determine the strength of the regression 🔍.
3. Adjusting the Prediction:
o The predicted value is adjusted by considering market volatility (ATR 📉) and the direction of trend signals 🔮, ensuring that the prediction is aligned with the current market environment 🌍.
4. Visualization:
o Prediction Lines and Bands: The algorithm plots lines that display the predicted future price along with a prediction range (upper and lower bounds) 📉📈.
5. EMA Cross Signals:
o EMA Conditions and Total Score: A bullish crossover signal is generated when the total score is positive and the short EMA crosses above the long EMA 📈. A bearish crossover signal is generated when the total score is negative and the short EMA crosses below the long EMA 📉.
6. Additional Considerations:
o Multi-Timeframe Regression Channel: The script calculates regression channels for different timeframes (5m, 15m, 30m, 4h) ⏳, helping determine the overall market direction 📊 (not visually presented).
Confidence Interpretation:
• High Confidence (close to 100%): Indicates strong alignment between timeframes with a clear trend (bullish or bearish) 🔥.
• Low Confidence (close to 0%): Shows disagreement or weak signals between timeframes ⚠️.
Confidence complements the interpretation of the prediction range and expected direction 🔮, aiding in decision-making for market entry or exit 🚀.
Español
Creamos este algoritmo con el objetivo de predecir los precios futuros 📊, específicamente hacia dónde irá el valor de cualquier activo en los próximos 20 períodos ⏳. Utiliza regresión lineal basada en los precios pasados, calculando una pendiente y una intersección para prever el comportamiento futuro 🔮. Esta predicción se ajusta según la volatilidad del mercado, medida por el ATR 📉, y la dirección de las señales de tendencia, que se basan en el MACD y las medias móviles 📈.
¿Cómo Funciona la Predicción con Linreg & ATR?
Cálculo de Tendencias y Señales:
Indicadores Técnicos: Usamos medias móviles exponenciales (EMA) a corto y largo plazo, RSI, MACD y Bandas de Bollinger 📊 para evaluar la dirección y el sentimiento del mercado (no presentados visualmente en el script).
Funciones de Cálculo: Incluye funciones para calcular pendiente, media, intersección, desviación estándar y el coeficiente de correlación de Pearson, esenciales para el análisis de regresión 📉.
Predicción de Precios Futuros:
Regresión Lineal: El algoritmo calcula la pendiente, la media y la intersección de los precios pasados para crear un canal de regresión 📈, ayudando a predecir el rango de precios futuros 🔮.
Desviación Estándar y Pearson's R: Estas métricas determinan la fuerza de la regresión 🔍.
Ajuste de la Predicción:
El valor predicho se ajusta considerando la volatilidad del mercado (ATR 📉) y la dirección de las señales de tendencia 🔮, asegurando que la predicción esté alineada con el entorno actual del mercado 🌍.
Visualización:
Líneas y Bandas de Predicción: El algoritmo traza líneas que muestran el precio futuro predicho, junto con un rango de predicción (límites superior e inferior) 📉📈.
Señales de Cruce de EMAs:
Condiciones de EMAs y Puntaje Total: Se genera una señal de cruce alcista cuando el puntaje total es positivo y la EMA corta cruza por encima de la EMA larga 📈. Se genera una señal de cruce bajista cuando el puntaje total es negativo y la EMA corta cruza por debajo de la EMA larga 📉.
Consideraciones Adicionales:
Canal de Regresión Multi-Timeframe: El script calcula canales de regresión para diferentes marcos de tiempo (5m, 15m, 30m, 4h) ⏳, ayudando a determinar la dirección general del mercado 📊 (no presentado visualmente).
Interpretación de la Confianza:
Alta Confianza (cerca del 100%): Indica una fuerte alineación entre los marcos temporales con una tendencia clara (alcista o bajista) 🔥.
Baja Confianza (cerca del 0%): Muestra desacuerdo o señales débiles entre los marcos temporales ⚠️.
La confianza complementa la interpretación del rango de predicción y la dirección esperada 🔮, ayudando en las decisiones de entrada o salida en el mercado 🚀.
300-Candle Weighted Average Zones w/50 EMA SignalsThis indicator is designed to deliver a more nuanced view of price dynamics by combining a custom, weighted price average with a volatility-based zone and a trend filter (in this case, a 50-period exponential moving average). The core concept revolves around capturing the overall price level over a relatively large lookback window (300 candles) but with an intentional bias toward recent market activity (the most recent 20 candles), thereby offering a balance between long-term context and short-term responsiveness. By smoothing this weighted average and establishing a “zone” of standard deviation bands around it, the indicator provides a refined visualization of both average price and its recent volatility envelope. Traders can then look for confluence with a standard trend filter, such as the 50 EMA, to identify meaningful crossover signals that may represent trend shifts or opportunities for entry and exit.
What the Indicator Does:
Weighted Price Average:
Instead of using a simple or exponential moving average, this indicator calculates a custom weighted average price over the past 300 candles. Most historical candles receive a base weight of 1.0, but the most recent 20 candles are assigned a higher weight (for example, a weight of 2.0). This weighting scheme ensures that the calculation is not simply a static lookback average; it actively emphasizes current market conditions. The effect is to generate an average line that is more sensitive to the most recent price swings while still maintaining the historical context of the previous 280 candles.
Smoothing of the Weighted Average:
Once the raw weighted average is computed, an exponential smoothing function (EMA) is applied to reduce noise and produce a cleaner, more stable average line. This smoothing helps traders avoid reacting prematurely to minor price fluctuations. By stabilizing the average line, traders can more confidently identify actual shifts in market direction.
Volatility Zone via Standard Deviation Bands:
To contextualize how far price can deviate from this weighted average, the indicator uses standard deviation. Standard deviation is a statistical measure of volatility—how spread out the price values are around the mean. By adding and subtracting one standard deviation from the smoothed weighted average, the indicator plots an upper band and a lower band, creating a zone or channel. The area between these bands is filled, often with a semi-transparent color, highlighting a volatility corridor within which price and the EMA might oscillate.
This zone is invaluable in visualizing “normal” price behavior. When the 50 EMA line and the weighted average line are both within this volatility zone, it indicates that the market’s short- to mid-term trend and its average pricing are aligned well within typical volatility bounds.
Incorporation of a 50-Period EMA:
The inclusion of a commonly used trend filter, the 50 EMA, adds another layer of context to the analysis. The 50 EMA, being a widely recognized moving average length, is often considered a baseline for intermediate trend bias. It reacts faster than a long-term average (like a 200 EMA) but is still stable enough to filter out the market “chop” seen in very short-term averages.
By overlaying the 50 EMA on this custom weighted average and the surrounding volatility zone, the trader gains a dual-dimensional perspective:
Trend Direction: If the 50 EMA is generally above the weighted average, the short-term trend is gaining bullish momentum; if it’s below, the short-term trend has a bearish tilt.
Volatility Normalization: The bands, constructed from standard deviations, provide a sense of whether the price and the 50 EMA are operating within a statistically “normal” range. If the EMA crosses the weighted average within this zone, it signals a potential trend initiation or meaningful shift, as opposed to a random price spike outside normal volatility boundaries.
Why a Trader Would Want to Use This Indicator:
Contextualized Price Level:
Standard MAs may not fully incorporate the most recent price dynamics in a large lookback window. By weighting the most recent candles more heavily, this indicator ensures that the trader is always anchored to what the market is currently doing, not just what it did 100 or 200 candles ago.
Reduced Whipsaw with Smoothing:
The smoothed weighted average line reduces noise, helping traders filter out inconsequential price movements. This makes it easier to spot genuine changes in trend or sentiment.
Visual Volatility Gauge:
The standard deviation bands create a visual representation of “normal” price movement. Traders can quickly assess if a breakout or breakdown is statistically significant or just another oscillation within the expected volatility range.
Clear Trade Signals with Confirmation:
By integrating the 50 EMA and designing signals that trigger only when the 50 EMA crosses above or below the weighted average while inside the zone, the indicator provides a refined entry/exit criterion. This avoids chasing breakouts that occur in abnormal volatility conditions and focuses on those crossovers likely to have staying power.
How to Use It in an Example Strategy:
Imagine you are a swing trader looking to identify medium-term trend changes. You apply this indicator to a chart of a popular currency pair or a leading tech stock. Over the past few days, the 50 EMA has been meandering around the weighted average line, both confined within the standard deviation zone.
Bullish Example:
Suddenly, the 50 EMA crosses decisively above the weighted average line while both are still hovering within the volatility zone. This might be your cue: you interpret this crossover as the 50 EMA acknowledging the recent upward shift in price dynamics that the weighted average has highlighted. Since it occurred inside the normal volatility range, it’s less likely to be a head-fake. You place a long position, setting an initial stop just below the lower band to protect against volatility.
If the price continues to rise and the EMA stays above the average, you have confirmation to hold the trade. As the price moves higher, the weighted average may follow, reinforcing your bullish stance.
Bearish Example:
On the flip side, if the 50 EMA crosses below the weighted average line within the zone, it suggests a subtle but meaningful change in trend direction to the downside. You might short the asset, placing your protective stop just above the upper band, expecting that the statistically “normal” level of volatility will contain the price action. If the price does break above those bands later, it’s a sign your trade may not work out as planned.
Other Indicators for Confluence:
To strengthen the reliability of the signals generated by this weighted average zone approach, traders may want to combine it with other technical studies:
Volume Indicators (e.g., Volume Profile, OBV):
Confirm that the trend crossover inside the volatility zone is supported by volume. For instance, an uptrend crossover combined with increasing On-Balance Volume (OBV) or volume spikes on up candles signals stronger buying pressure behind the price action.
Momentum Oscillators (e.g., RSI, Stochastics):
Before taking a crossover signal, check if the RSI is above 50 and rising for bullish entries, or if the Stochastics have turned down from overbought levels for bearish entries. Momentum confirmation can help ensure that the trend change is not just an isolated random event.
Market Structure Tools (e.g., Pivot Points, Swing High/Low Analysis):
Identify if the crossover event coincides with a break of a previous pivot high or low. A bullish crossover inside the zone aligned with a break above a recent swing high adds further strength to your conviction. Conversely, a bearish crossover confirmed by a breakdown below a previous swing low can make a short trade setup more compelling.
Volume-Weighted Average Price (VWAP):
Comparing where the weighted average zone lies relative to VWAP can provide institutional insight. If the bullish crossover happens while the price is also holding above VWAP, it can mean that the average participant in the market is in profit and that the trend is likely supported by strong hands.
This indicator serves as a tool to balance long-term perspective, short-term adaptability, and volatility normalization. It can be a valuable addition to a trader’s toolkit, offering enhanced clarity and precision in detecting meaningful shifts in trend, especially when combined with other technical indicators and robust risk management principles.
Volume Spike DetectorVolume Spike Detector
This script is designed to identify significant spikes in trading volume and visually represent them on the chart. It calculates the 20-period simple moving average (SMA) of the trading volume and multiplies it by a user-defined threshold to determine the spike threshold. When the current volume exceeds this threshold, the script detects and highlights a volume spike.
Key Features:
Dynamic Spike Threshold:
The script calculates the spike threshold dynamically based on the average trading volume. Users can customize the threshold multiplier using an input setting.
Example: A threshold multiplier of 2.0 means the current volume must be twice the 20-period SMA to trigger a detection.
Visual Representation:
The current volume is plotted in blue bars.
The spike threshold is plotted as a red line, making it easy to visually identify when the volume crosses the threshold.
Alert Notification:
When a volume spike is detected, an alert is triggered to notify the user.
This feature is useful for real-time monitoring and spotting potential trading opportunities.
Use Case:
Traders can use this tool to identify sudden increases in trading activity, which may indicate a significant market move or event. It’s suitable for all markets, including cryptocurrencies, stocks, and forex.
Ichimoku by FarmerBTCLegal Disclaimer
This strategy, "Ichimoku by FarmerBTC," is provided for educational and informational purposes only. It does not constitute financial advice and should not be relied upon as such. Trading and investing involve substantial risk, including the potential for losing more than your initial investment. Past performance is not indicative of future results. Always consult with a qualified financial advisor before making trading or investment decisions. The author of this strategy is not responsible for any financial losses incurred through its use.
Overview
The "Ichimoku by FarmerBTC" strategy is a trend-following system built on the Ichimoku Cloud indicator, enhanced with volume analysis and a high-timeframe Simple Moving Average (HTF SMA) condition. It is designed to identify long-only trade opportunities and performs optimally on higher timeframes, such as the daily chart or above.
Core Components
1. Ichimoku Cloud
The Ichimoku Cloud is a comprehensive trend-following indicator that helps identify the overall market direction and momentum. It consists of:
Conversion Line (Tenkan-Sen): Measures short-term momentum.
Base Line (Kijun-Sen): Filters medium-term trends.
Leading Span A: The average of the Conversion and Base Lines, forming one cloud boundary.
Leading Span B: The midpoint of the highest high and lowest low over a longer period, forming the other cloud boundary.
Key Ichimoku Rules Applied:
The strategy identifies bullish trends when:
The price is above the cloud.
The cloud is bullish (Leading Span A > Leading Span B).
2. High-Timeframe Simple Moving Average (HTF SMA)
This condition ensures alignment with the broader trend:
Default SMA Length: 13 periods.
Default Timeframe: 1 day.
HTF SMA Rule:
Trades are allowed only when the price is above the HTF SMA, ensuring alignment with the larger trend.
3. Volume Analysis
The strategy uses volume to validate trade setups:
Volume MA: A 20-period moving average of volume is calculated.
Trades are allowed only when the current volume is at least 1.5x the Volume MA, indicating strong market participation.
Entry and Exit Rules
Entry Condition (Long Only):
Price above the Ichimoku Cloud: Confirms a bullish trend.
Bullish Cloud: Leading Span A > Leading Span B indicates upward momentum.
Price above the HTF SMA: Ensures alignment with the broader trend.
Volume exceeds threshold: Confirms strong market participation.
Exit Condition:
The strategy exits the position when the price moves below the Ichimoku Cloud, signaling a potential trend reversal.
Best Timeframes
This strategy is optimized for daily (1D) or higher timeframes (e.g., weekly 1W). Using it on lower timeframes may produce false signals due to increased noise in price and volume data.
Default Settings
Ichimoku Settings:
Conversion Line Period: 10
Base Line Period: 30
Lagging Span Period: 53
Displacement: 26
HTF SMA Settings:
SMA Length: 13
Timeframe: 1 Day
Volume Settings:
Volume MA Length: 20
Volume Multiplier: 1.5x
Visualization
Ichimoku Cloud:
Dynamic cloud coloring (green for bullish, red for bearish) helps identify the current trend.
HTF SMA:
A purple line overlays the chart, providing a clear representation of the high-timeframe trend.
Volume Panel:
An optional panel displays volume (blue histogram) and the Volume Moving Average (orange line) to analyze market participation.
Advantages of This Strategy
High Accuracy on Higher Timeframes:
Filtering trades using the Ichimoku Cloud, HTF SMA, and volume ensures robust trend alignment, reducing false signals.
Volume Confirmation:
Incorporates volume as a validation metric to enter trades only during strong market participation.
Easy Customization:
Parameters like Ichimoku periods, SMA length, timeframe, and volume thresholds can be adjusted to suit different assets or trading styles.
Limitations
Not Suitable for Low Timeframes:
Lower timeframes can produce excessive noise, leading to false signals.
Long-Only:
The strategy is designed only for bullish markets and does not support short trades.
Lagging Nature of Indicators:
Both the Ichimoku Cloud and SMA are lagging indicators, meaning they react to past price movements.
Conclusion
The "Ichimoku by FarmerBTC" strategy is an excellent tool for trend-following on daily or higher timeframes. Its combination of Ichimoku Cloud, high-timeframe SMA, and volume ensures a robust framework for identifying high-probability long trades in trending markets. However, users are advised to test the strategy thoroughly and manage their risk appropriately. Always consult with a financial professional before making trading decisions.
DNSE VN301!, SMA & EMA Cross StrategyDiscover the tailored Pinescript to trade VN30F1M Future Contracts intraday, the strategy focuses on SMA & EMA crosses to identify potential entry/exit points. The script closes all positions by 14:25 to avoid holding any contracts overnight.
HNX:VN301!
www.tradingview.com
Setting & Backtest result:
1-minute chart, initial capital of VND 100 million, entering 4 contracts per time, backtest result from Jan-2024 to Nov-2024 yielded a return over 40%, executed over 1,000 trades (average of 4 trades/day), winning trades rate ~ 30% with a profit factor of 1.10.
The default setting of the script:
A decent optimization is reached when SMA and EMA periods are set to 60 and 15 respectively while the Long/Short stop-loss level is set to 20 ticks (2 points) from the entry price.
Entry & Exit conditions:
Long signals are generated when ema(15) crosses over sma(60) while Short signals happen when ema(15) crosses under sma(60). Long orders are closed when ema(15) crosses under sma(60) while Short orders are closed when ema(15) crosses over sma(60).
Exit conditions happen when (whichever came first):
Another Long/Short signal is generated
The Stop-loss level is reached
The Cut-off time is reached (14:25 every day)
*Disclaimers:
Futures Contracts Trading are subjected to a high degree of risk and price movements can fluctuate significantly. This script functions as a reference source and should be used after users have clearly understood how futures trading works, accessed their risk tolerance level, and are knowledgeable of the functioning logic behind the script.
Users are solely responsible for their investment decisions, and DNSE is not responsible for any potential losses from applying such a strategy to real-life trading activities. Past performance is not indicative/guarantee of future results, kindly reach out to us should you have specific questions about this script.
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Khám phá Pinescript được thiết kế riêng để giao dịch Hợp đồng tương lai VN30F1M trong ngày, chiến lược tập trung vào các đường SMA & EMA cắt nhau để xác định các điểm vào/ra tiềm năng. Chiến lược sẽ đóng tất cả các vị thế trước 14:25 để tránh giữ bất kỳ hợp đồng nào qua đêm.
Thiết lập & Kết quả backtest:
Chart 1 phút, vốn ban đầu là 100 triệu đồng, vào 4 hợp đồng mỗi lần, kết quả backtest từ tháng 1/2024 tới tháng 11/2024 mang lại lợi nhuận trên 40%, thực hiện hơn 1.000 giao dịch (trung bình 4 giao dịch/ngày), tỷ lệ giao dịch thắng ~ 30% với hệ số lợi nhuận là 1,10.
Thiết lập mặc định của chiến lược:
Đạt được một mức tối ưu ổn khi SMA và EMA periods được đặt lần lượt là 60 và 15 trong khi mức cắt lỗ được đặt thành 20 tick (2 điểm) từ giá vào.
Điều kiện Mở và Đóng vị thế:
Tín hiệu Long được tạo ra khi ema(15) cắt trên sma(60) trong khi tín hiệu Short xảy ra khi ema(15) cắt dưới sma(60). Lệnh Long được đóng khi ema(15) cắt dưới sma(60) trong khi lệnh Short được đóng khi ema(15) cắt lên sma(60).
Điều kiện đóng vị thể xảy ra khi (tùy điều kiện nào đến trước):
Một tín hiệu Long/Short khác được tạo ra
Giá chạm mức cắt lỗ
Lệnh chưa đóng nhưng tới giờ cut-off (14:25 hàng ngày)
*Tuyên bố miễn trừ trách nhiệm:
Giao dịch hợp đồng tương lai có mức rủi ro cao và giá có thể dao động đáng kể. Chiến lược này hoạt động như một nguồn tham khảo và nên được sử dụng sau khi người dùng đã hiểu rõ cách thức giao dịch hợp đồng tương lai, đã đánh giá mức độ chấp nhận rủi ro của bản thân và hiểu rõ về logic vận hành của chiến lược này.
Người dùng hoàn toàn chịu trách nhiệm về các quyết định đầu tư của mình và DNSE không chịu trách nhiệm về bất kỳ khoản lỗ tiềm ẩn nào khi áp dụng chiến lược này vào các hoạt động giao dịch thực tế. Hiệu suất trong quá khứ không chỉ ra/cam kết kết quả trong tương lai, vui lòng liên hệ với chúng tôi nếu bạn có thắc mắc cụ thể về chiến lược giao dịch này.
Futures Correlation VisualizerOVERVIEW
This indicator plots the normalized price changes of commonly traded futures. Visualizing data in this way makes studying and understanding market participation and sentiment easier.
Note:
Only 20 symbols can be plotted. The "request" functions are limited to 40 calls , 1 timeframe counts as a call, and 2 timeframes are used per symbol. Normalized values are derived by dividing the charts timeframe by 1D data. A runtime error will occur when more than 20 symbols are enabled. This limitation is unavoidable.
INPUTS
You can configure:
Colors and color scheme
Symbols to plot (most common futures)
Norm. source (todays open / yesterdays close)
Measurement type (%, ‱, Δ)
Label, zone, and zero options
Edwin K Stochastic Candle ColorsThe Stochastic Candle Colors indicator highlights price action using candle colors based on signals from the stochastic oscillator. Here's how to use it:
1. Indicator Purpose
This indicator overlays on your price chart and changes candle colors based on stochastic oscillator signals:
Green candles: Indicate a bullish signal when the %K line crosses above the %D line in an oversold area (below 20).
Red candles: Indicate a bearish signal when the %K line crosses below the %D line in an overbought area (above 80).
2. How to Use the Inputs
K (periodK): The lookback period for calculating the %K line of the stochastic oscillator. A smaller value makes the indicator more sensitive to price changes.
D (periodD): The period for smoothing the %K line to get the %D line. A larger value creates smoother signals but may result in delays.
Smooth (smoothK): The additional smoothing applied to the %K line before calculating the %D line. This helps reduce noise.
3. How to Interpret the Candle Colors
Green Candle:
Occurs when the %K line crosses above the %D line in the oversold zone (below 20).
Signals a potential bullish reversal.
Red Candle:
Occurs when the %K line crosses below the %D line in the overbought zone (above 80).
Signals a potential bearish reversal.
No Color:
No crossover occurs, or the crossover doesn't happen in overbought/oversold zones.
4. Application in Trading
Entry Points:
Buy when you see a green candle and confirm with other indicators or chart patterns.
Sell when you see a red candle and confirm with additional signals.
Trend Context:
Combine this indicator with trend-following tools like moving averages or support/resistance levels to improve accuracy.
Stop Loss/Take Profit:
Use nearby swing highs/lows for stop-loss placement.
Set profit targets based on risk-reward ratios or key levels.
5. Customization
Adjust the input parameters (K, D, and Smooth) to align the indicator's sensitivity with your trading style:
Short-term traders might prefer lower values for quicker signals.
Long-term traders might opt for higher values for smoother, more reliable signals.
6. Limitations
Signals in isolation might not be reliable. Always use this indicator in conjunction with other tools.
Avoid using during low volatility or sideways markets as stochastic oscillators can produce false signals.
Detrended Price Oscillator [NexusSignals]Detrended Price Oscillator (DPO) is a detrended price oscillator, used in technical analysis, strips out price trends in an effort to estimate the length of price cycles from peak to peak or trough to trough.
DPO is not a momentum indicator, instead highlights peaks and troughs in price, which are used to estimate buy and sell points in line with the historical cycle. (cf. to investopedia)
DPO indicator made by NexusSignals components :
a filled area that allow users to see easy the trend of an asset;
a sma moving average on chart (default length is 20)
a 20 sma on oscillator, both ma's are color coded to show uptrend / downtrend
a donchian channel applied to the dpo to show breakouts, breakdowns and resistances/support, reversals
few alerts for price crossing above ma, cross above the 0 dpo line, and for cross above and below the donchian channels top and bottom
How you can use DPO indicator ?
The detrended price oscillator (DPO) can be used for measuring the distance between peaks and troughs in the indicator that may help traders to make future decisions as they can locate the most recent trough and determine when the next one may occur in the meassured distance on oscillator between peaks and troughs.
You can use the indicator to find the potential price reversals, for example when the price of an asset is in a bearish trend and the dpo is bouncing from the donchian channel bottom, that may be a potential swing low for that asset, same thing in a bullish trend when the dpo rejecting at top of donchian channel may be a trend reversal, a pullback or swing high.
When DPO is above the 0 trend is in an uptrend and when dpo is below the zero the asset is possible to move into a downtrend.
Also crosses of DPO above and below the DPO moving average may signalising a trend change.
Indicator DashboardThis script creates an 'Indicator Dashboard' designed to assist you in analyzing financial markets and making informed decisions. The indicator provides a summary of current market conditions by presenting various technical analysis indicators in a table format. The dashboard evaluates popular indicators such as Moving Averages, RSI, MACD, and Stochastic RSI. Below, we'll explain each part of this script in detail and its purpose:
### Overview of Indicators
1. **Moving Averages (MA)**:
- This indicator calculates Simple Moving Averages (“SMA”) for 5, 14, 20, 50, 100, and 200 periods. These averages provide a visual summary of price movements. Depending on whether the price is above or below the moving average, it determines the market direction as either “Bullish” or “Bearish.”
2. **RSI (Relative Strength Index)**:
- The RSI helps identify overbought or oversold market conditions. Here, the RSI is calculated for a 14-period window, and this value is displayed in the table. Additionally, the 14-period moving average of the RSI is also included.
3. **MACD (Moving Average Convergence Divergence)**:
- The MACD indicator is used to determine trend strength and potential reversals. This script calculates the MACD line, signal line, and histogram. The MACD condition (“Bullish,” “Bearish,” or “Neutral”) is displayed alongside the MACD and signal line values.
4. **Stochastic RSI**:
- Stochastic RSI is used to identify momentum changes in the market. The %K and %D lines are calculated to determine the market condition (“Bullish” or “Bearish”), which is displayed along with the calculated values for %K and %D.
### Table Layout and Presentation
The dashboard is presented in a vertical table format in the top-right corner of the chart. The table contains two columns: “Indicator” and “Status,” summarizing the condition of each technical indicator.
- **Indicator Column**: Lists each of the indicators being tracked, such as SMA values, RSI, MACD, etc.
- **Status Column**: Displays the current status of each indicator, such as “Bullish,” “Bearish,” or specific values like the RSI or MACD.
The table also includes rounded indicator values for easier interpretation. This helps traders quickly assess market conditions and make informed decisions based on multiple indicators presented in a single location.
### Detailed Indicator Status Calculations
1. **SMA Status**: For each moving average (5, 14, 20, 50, 100, 200), the script checks if the current price is above or below the SMA. The status is determined as “Bullish” if the price is above the SMA and “Bearish” if below, with the value of the SMA also displayed.
2. **RSI and RSI Average**: The RSI value for a 14-period is displayed along with its 14-period SMA, which provides an average reading of the RSI to smooth out volatility.
3. **MACD Indicator**: The MACD line, signal line, and histogram are calculated using standard parameters (12, 26, 9). The status is shown as “Bullish” when the MACD line is above the signal line, and “Bearish” when it is below. The exact values for the MACD line, signal line, and histogram are also included.
4. **Stochastic RSI**: The %K and %D lines of the Stochastic RSI are used to determine the trend condition. If %K is greater than %D, the condition is “Bullish,” otherwise it is “Bearish.” The actual values of %K and %D are also displayed.
### Conclusion
The 'Indicator Dashboard' provides a comprehensive overview of multiple technical indicators in a single, easy-to-read table. This allows traders to quickly gauge market conditions and make more informed decisions. By consolidating key indicators like Moving Averages, RSI, MACD, and Stochastic RSI into one dashboard, it saves time and enhances the efficiency of technical analysis.
This script is particularly useful for traders who prefer a clean and organized overview of their favorite indicators without needing to plot each one individually on the chart. Instead, all the crucial information is available at a glance in a consolidated format.
Wick Detection (1 and 0) - AYNETDetailed Scientific Explanation
1. Wick Detection Logic
Definition of a Wick:
A wick, also known as a shadow, represents the price action outside the range of a candlestick's body (the region between open and close).
Upper Wick: Occurs when the high value exceeds the greater of open and close.
Lower Wick: Occurs when the low value is lower than the smaller of open and close.
Upper Wick Detection:
pinescript
Kodu kopyala
bool has_upper_wick = high > math.max(open, close)
This checks if the high price of the candle is greater than the maximum of the open and close prices. If true, an upper wick exists.
Lower Wick Detection:
pinescript
Kodu kopyala
bool has_lower_wick = low < math.min(open, close)
This checks if the low price of the candle is less than the minimum of the open and close prices. If true, a lower wick exists.
2. Binary Representation
The presence of a wick is encoded as a binary value for simplicity and computational analysis:
Upper Wick: Represented as 1 if present, otherwise 0.
pinescript
Kodu kopyala
float upper_wick_binary = has_upper_wick ? 1 : 0
Lower Wick: Represented as 1 if present, otherwise 0. This value is inverted (-1) for visualization purposes.
pinescript
Kodu kopyala
float lower_wick_binary = has_lower_wick ? 1 : 0
3. Visualization with Histograms
The plot function is used to create histograms for visualizing the binary wick data:
Upper Wicks: Plotted as positive values with green columns:
pinescript
Kodu kopyala
plot(upper_wick_binary, title="Upper Wick", color=color.new(color.green, 0), style=plot.style_columns, linewidth=2)
Lower Wicks: Plotted as negative values with red columns:
pinescript
Kodu kopyala
plot(lower_wick_binary * -1, title="Lower Wick", color=color.new(color.red, 0), style=plot.style_columns, linewidth=2)
Features and Applications
1. Wick Visualization:
Upper wicks are displayed as positive green columns.
Lower wicks are displayed as negative red columns.
This provides a clear visual representation of wick presence in historical data.
2. Technical Analysis:
Wick formations often indicate market sentiment:
Upper Wicks: Sellers pushed the price lower after buyers drove it higher, signaling rejection at the top.
Lower Wicks: Buyers pushed the price higher after sellers drove it lower, signaling rejection at the bottom.
3. Signal Generation:
Traders can use wick detection to build strategies, such as identifying key price levels or market reversals.
Enhancements and Future Improvements
1. Wick Length Measurement
Instead of binary detection, measure the actual length of the wick:
pinescript
Kodu kopyala
float upper_wick_length = high - math.max(open, close)
float lower_wick_length = math.min(open, close) - low
This approach allows for thresholds to identify significant wicks:
pinescript
Kodu kopyala
bool significant_upper_wick = upper_wick_length > 10 // For wicks longer than 10 units.
bool significant_lower_wick = lower_wick_length > 10
2. Alerts for Long Wicks
Trigger alerts when significant wicks are detected:
pinescript
Kodu kopyala
alertcondition(significant_upper_wick, title="Long Upper Wick", message="A significant upper wick has been detected.")
alertcondition(significant_lower_wick, title="Long Lower Wick", message="A significant lower wick has been detected.")
3. Combined Wick Analysis
Analyze both upper and lower wicks to assess volatility:
pinescript
Kodu kopyala
float total_wick_length = upper_wick_length + lower_wick_length
bool high_volatility = total_wick_length > 20 // Combined wick length exceeds 20 units.
Conclusion
This script provides a compact and computationally efficient way to detect candlestick wicks and represent them as binary data. By visualizing the data with histograms, traders can easily identify wick formations and use them for technical analysis, signal generation, and volatility assessment. The approach can be extended further to measure wick length, detect significant wicks, and integrate these insights into automated trading systems.
Trend & Volume Dynamics Indicator (Color identifying the Trend)Benefits
1. Trend Identification:
o The script calculates a 20-period Weighted Moving Average (WMA) of the closing prices. This helps in smoothing out price data to identify the underlying trend.
o The color of the WMA line changes based on the price position relative to the WMA:
Green: When the current price is above the WMA, indicating a potential uptrend.
Red: When the current price is below the WMA, indicating a potential downtrend.
Blue: When the price is exactly at the WMA, indicating no clear trend.
2. Volume Dynamics:
o The script also plots the volume with a color-coding mechanism:
Green: When the current volume is higher than the previous period's volume, indicating increasing trading activity.
Red: When the current volume is lower than the previous period's volume, indicating decreasing trading activity.
o The volume bars are plotted with 90% transparency, making them less visually dominant but still informative.
Usage
• Overlay: The indicator is set to overlay=true, meaning it will be plotted directly on the price chart, allowing users to see the WMA and volume dynamics in the context of the price movements.
• WMA Length: The length of the WMA is set to 20 periods, which is a common setting for short to medium-term trend analysis.
• Visual Cues: The color changes in both the WMA and volume bars provide immediate visual cues about the trend and volume dynamics, helping traders make quicker decisions.
Detailed Explanation of the Script
1. Indicator Declaration:
o Declares the indicator with a descriptive name and specifies that it should be overlaid on the price chart.
2. WMA Calculation:
o Defines the length of the WMA and calculates it using the closing prices.
3. Plotting the WMA:
o Plots the WMA with full brightness (0 transparency).
4. Color-Coding the WMA:
o Changes the color of the WMA line based on the price's position relative to the WMA.
5. Volume Indicator:
o Plots the volume bars with color-coding based on the volume change from the previous period and with 90% transparency.
Conclusion
One of the most best combinations of Volume and Moving average and works on any given timeframe and charts
Meme Coin Buy Signal Indicator by asharThis custom TradingView indicator is specifically designed for meme coins, using technical analysis indicators to identify optimal buy signals. It combines short-term moving averages, volume spikes, and Bitcoin trend alignment to pinpoint potential entry points during high-momentum periods.
Indicator Components:
Moving Averages (MA): A 5-period fast MA and a 13-period slow MA highlight short-term price momentum. Buy signals are generated when the fast MA crosses above the slow MA, indicating potential upward momentum.
Volume Spike Detection: The indicator detects high-volume periods using a multiplier. If the current volume exceeds the 10-period average volume by the set multiplier (default: 2.0), it indicates increased buying interest, which is crucial for meme coins.
Bitcoin Trend Alignment: The trend of Bitcoin, a market-wide sentiment indicator, is gauged with a 20-day moving average. Buy signals are validated only when Bitcoin is also in an uptrend, providing additional bullish confirmation for meme coins.
Buy Signal Criteria: A buy signal is triggered when:
The fast MA crosses above the slow MA.
Volume is above the average by the set multiplier.
The price is above the slow MA.
Bitcoin is trending up based on the 20-day moving average.
This indicator is ideal for meme coin traders looking to time entries with momentum-driven trends, aligning volume and trend indicators for a more comprehensive approach to high-risk assets.
Honest Volatility Grid [Honestcowboy]The Honest Volatility Grid is an attempt at creating a robust grid trading strategy but without standard levels.
Normal grid systems use price levels like 1.01;1.02;1.03;1.04... and place an order at each of these levels. In this program instead we create a grid using keltner channels using a long term moving average.
🟦 IS THIS EVEN USEFUL?
The idea is to have a more fluid style of trading where levels expand and follow price and do not stick to precreated levels. This however also makes each closed trade different instead of using fixed take profit levels. In this strategy a take profit level can even be a loss. It is useful as a strategy because it works in a different way than most strategies, making it a good tool to diversify a portfolio of trading strategies.
🟦 STRATEGY
There are 10 levels below the moving average and 10 above the moving average. For each side of the moving average the strategy uses 1 to 3 orders maximum (3 shorts at top, 3 longs at bottom). For instance you buy at level 2 below moving average and you increase position size when level 6 is reached (a cheaper price) in order to spread risks.
By default the strategy exits all trades when the moving average is reached, this makes it a mean reversion strategy. It is specifically designed for the forex market as these in my experience exhibit a lot of ranging behaviour on all the timeframes below daily.
There is also a stop loss at the outer band by default, in case price moves too far from the mean.
What are the risks?
In case price decides to stay below the moving average and never reaches the outer band one trade can create a very substantial loss, as the bands will keep following price and are not at a fixed level.
Explanation of default parameters
By default the strategy uses a starting capital of 25000$, this is realistic for retail traders.
Lot sizes at each level are set to minimum lot size 0.01, there is no reason for the default to be risky, if you want to risk more or increase equity curve increase the number at your own risk.
Slippage set to 20 points: that's a normal 2 pip slippage you will find on brokers.
Fill limit assumtion 20 points: so it takes 2 pips to confirm a fill, normal forex spread.
Commission is set to 0.00005 per contract: this means that for each contract traded there is a 5$ or whatever base currency pair has as commission. The number is set to 0.00005 because pinescript does not know that 1 contract is 100000 units. So we divide the number by 100000 to get a realistic commission.
The script will also multiply lot size by 100000 because pinescript does not know that lots are 100000 units in forex.
Extra safety limit
Normally the script uses strategy.exit() to exit trades at TP or SL. But because these are created 1 bar after a limit or stop order is filled in pinescript. There are strategy.orders set at the outer boundaries of the script to hedge against that risk. These get deleted bar after the first order is filled. Purely to counteract news bars or huge spikes in price messing up backtest.
🟦 VISUAL GOODIES
I've added a market profile feature to the edge of the grid. This so you can see in which grid zone market has been the most over X bars in the past. Some traders may wish to only turn on the strategy whenever the market profile displays specific characteristics (ranging market for instance).
These simply count how many times a high, low, or close price has been in each zone for X bars in the past. it's these purple boxes at the right side of the chart.
🟦 Script can be fully automated to MT5
There are risk settings in lot sizes or % for alerts and symbol settings provided at the bottom of the indicator. The script will send alert to MT5 broker trying to mimic the execution that happens on tradingview. There are always delays when using a bridge to MT5 broker and there could be errors so be mindful of that. This script sends alerts in format so they can be read by tradingview.to which is a bridge between the platforms.
Use the all alert function calls feature when setting up alerts and make sure you provide the right webhook if you want to use this approach.
Almost every setting in this indicator has a tooltip added to it. So if any setting is not clear hover over the (?) icon on the right of the setting.
Weekly COTAdjusted COT Index
Improves upon: "COT Index Commercials vs large and small Speculators" by SystematicFutures
How: CoT Indexes are adjusted by Open Interest to normalise data over time, and threshold background colours are in-line with Larry Williams recommendations from his book.
Note: This indicator is **only** accurate on the Daily time-frame due to the mid-week release date for CoT data.
This script calculates and plots the Adjusted Commitment of Traders (COT) Index for Commercial, Large Speculator, and Retail (Small Speculator) categories.
The CoT Index is adjusted by Open Interest to normalise data through time, following the methodology of Larry Williams, providing insights into how these groups are positioned in the market with an arguably more historically accurate context.
COT Categories
-------------------
- Commercials (Producers/Hedgers): Large entities hedging against price changes in the underlying asset.
- Large Speculators (Non-commercials): Professional traders and funds speculating on price movements.
- Retail Traders (Nonreportable/Small Speculators): Small individual traders, typically less informed.
Features
----------
- Open Interest Adjustment
- The net positions for each category are normalized by Open Interest to account
for varying contract sizes.
- Customisable Look-back Period
- You can adjust the number of weeks for the index calculation to control the
historical range used for comparison.
- Thresholds for Extremes
- Upper and lower thresholds (configurable) are provided to mark overbought and
oversold conditions.
- Defaults
- Overbought: <=20
- Oversold: >= 80
- Hide Current Week Option
- Optionally hide the current week's data until market close for more accurate comparison.
- Visual Aids
- Plot the Commercials, Large Speculators, and Retail indexes, and optionally highlight extreme positioning.
Inputs
--------
- weeks
- Number of weeks for historical range comparison.
- upperExtreme and lowerExtreme
- Thresholds to identify overbought/oversold conditions (default 80/20).
- hideCurrentWeek
- Option to hide current week's data until market close.
- markExtremes
- Highlight extremes where any index crosses the upper or lower thresholds.
- Options to display or hide indexes for Commercials, Large Speculators, and Small Speculators.
Outputs
----------
- The script plots the COT Index for each of the three categories and highlights periods of extreme positioning with customisable thresholds.
Usage
-------
- This tool is useful for traders who want to track the positioning of different market participants over time.
- By identifying the extreme positions of Commercials, Large Speculators, and Retail traders, it can give insights into market sentiment and potential reversals.
- Reversals of trend can be confirmed with RSI Divergence (daily), for example
- Continuation can be confirmed with RSI overbought/oversold conditions (daily), and/or hidden RSI Hidden Divergence, for example
Volume Flow ConfluenceVolume Flow Confluence (CMF-KVO Integration)
Core Function:
The Volume Flow Confluence Indicator combines two volume-analysis methods: Chaikin Money Flow (CMF) and the Klinger Volume Oscillator (KVO). It displays a histogram only when both indicators align in their respective signals.
Signal States:
• Green Bars: CMF is positive (> 0) and KVO is above its signal line
• Red Bars: CMF is negative (< 0) and KVO is below its signal line
• No Bars: When indicators disagree
Technical Components:
Chaikin Money Flow (CMF):
Measures the relationship between volume and price location within the trading range:
• Calculates money flow volume using close position relative to high/low range
• Aggregates and normalizes over specified period
• Default period: 20
Klinger Volume Oscillator (KVO):
Evaluates volume in relation to price movement:
• Tracks trend changes using HLC3
• Applies volume force calculation
• Uses two EMAs (34/55) with a signal line (13)
Practical Applications:
1. Signal Identification
- New colored bars after blank periods show new agreement between indicators
- Color intensity differentiates new signals from continuations
- Blank spaces indicate lack of agreement
2. Trend Analysis
- Consecutive colored bars show continued indicator agreement
- Transitions between colors or to blank spaces show changing conditions
- Can be used alongside other technical analysis tools
3. Risk Considerations
- Signals are not predictive of future price movement
- Should be used as one of multiple analysis tools
- Effectiveness may vary across different markets and timeframes
Technical Specifications:
Core Algorithm
CMF = Σ(((C - L) - (H - C))/(H - L) × V)n / Σ(V)n
KVO = EMA(VF, 34) - EMA(VF, 55)
Where VF = V × |2(dm/cm) - 1| × sign(Δhlc3)
Signal Line = EMA(KVO, 13)
Signal Logic
Long: CMF > 0 AND KVO > Signal
Short: CMF < 0 AND KVO < Signal
Neutral: All other conditions
Parameters
CMF Length = 20
KVO Fast = 34
KVO Slow = 55
KVO Signal = 13
Volume = Regular/Actual Volume
Data Requirements
Price Data: OHLC
Volume Data: Required
Minimum History: 55 bars
Recommended Timeframe: ≥ 1H
Credits:
• Marc Chaikin - Original CMF development
• Stephen Klinger - Original KVO development
• Alex Orekhov (everget) - CMF script implementation
• nj_guy72 - KVO script implementation
No Trade Zone Indicator [CHE]No Trade Zone Indicator
The "No Trade Zone Indicator " is a powerful tool designed to help traders identify periods when the market may not present favorable trading opportunities. By analyzing the percentage change in the 20-period Simple Moving Average (SMA20) relative to a dynamically adjusted threshold based on market volatility, this indicator highlights times when it's prudent to stay out of the market.
Why Knowing When Not to Trade Is Important
Understanding when not to trade is just as crucial as knowing when to enter or exit a position. Trading during periods of low volatility or uncertain market direction can lead to unnecessary risks and potential losses. By recognizing these "No Trade Zones," you can:
- Avoid Low-Probability Trades: Reduce the chances of entering trades with unfavorable risk-to-reward ratios.
- Preserve Capital: Protect your investment from unpredictable market movements.
- Enhance Focus: Concentrate on high-quality trading opportunities that align with your strategy.
How the Indicator Works
- SMA20 Calculation: Computes the 20-period Simple Moving Average of closing prices to identify the market's short-term trend.
- ATR Measurement: Calculates the Average True Range (ATR) over a user-defined period (default is 14) to assess market volatility.
- Dynamic Threshold: Determines an adjusted threshold by multiplying the ATR percentage by a Threshold Adjustment Factor (default is 0.05).
- Trend Analysis: Compares the percentage change of the SMA20 against the adjusted threshold to evaluate market momentum.
- Status Identification:
- Long: Indicates a rising SMA20 above the threshold—suggesting a potential upward trend.
- Short: Indicates a falling SMA20 above the threshold—suggesting a potential downward trend.
- No Trade: Signals when the SMA20 change is below the threshold, marking a period of low volatility or indecision.
Features
- Customizable Settings: Adjust the ATR period and Threshold Adjustment Factor to suit different trading styles and market conditions.
- Visual Indicators: Colored columns represent market status—green for "Long," red for "Short," and gray for "No Trade."
- On-Chart Table: An optional table displays the current market status directly on your chart for quick reference.
- Alerts: Set up alerts to receive notifications when the market enters a "No Trade Zone," helping you stay informed without constant monitoring.
How to Use the Indicator
1. Add to Chart: Apply the "No Trade Zone Indicator " to your preferred trading chart on TradingView.
2. Configure Settings: Customize the ATR period and Threshold Adjustment Factor based on your analysis and risk tolerance.
3. Interpret Signals:
- Green Columns: Consider looking for buying opportunities as the market shows upward momentum.
- Red Columns: Consider looking for selling opportunities as the market shows downward momentum.
- Gray Columns: Refrain from trading as the market lacks clear direction.
4. Monitor Alerts: Use the alert feature to get notified when the market status changes, allowing you to make timely decisions.
Conclusion
Incorporating the "No Trade Zone Indicator " into your trading toolkit can enhance your decision-making process by clearly indicating when the market may not be conducive to trading. By focusing on periods with favorable conditions and avoiding low-volatility times, you can improve your trading performance and achieve better results over the long term.
*Trade wisely, and remember—the best trade can sometimes be no trade at all.*
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
best regards
Chervolino
Average Up and Down Candles Streak with Predicted Next CandleThis indicator is designed to analyze price trends by examining the patterns of up and down streaks (consecutive bullish or bearish candles) over a defined period. It uses this data to provide insights on whether the next candle is likely to be bullish or bearish, and it visually displays relevant information on the chart.
Here’s a breakdown of what the indicator does:
1. Inputs and Parameters
Period (Candles): Defines the number of candles used to calculate the average length of bullish and bearish streaks. For example, if the period is set to 20, the indicator will analyze the past 20 candles to determine average up and down streak lengths.
Bullish/Bearish Bias Signal Toggle: These options allow users to show or hide visual signals (green or red circles) when there’s a bullish or bearish bias in the trend based on the indicator’s calculations.
2. Streak Calculation
The indicator looks at each candle within the period to identify if it closed up (bullish) or down (bearish).
Up Streak: The indicator counts consecutive bullish candles. When there’s a bearish candle, it resets the up streak count.
Down Streak: Similarly, it counts consecutive bearish candles and resets when a bullish candle appears.
Averages: Over the defined period, the indicator calculates the average length of up streaks and average length of down streaks. This provides a baseline to assess whether the current streak is typical or extended.
3. Current and Average Streak Display
The indicator displays the current up and down streak lengths alongside the average streak lengths for comparison. This data appears in a table on the chart, allowing you to see at a glance:
The current streak length (for both up and down trends)
The average streak length for up and down trends over the chosen period
4. Trend Prediction for the Next Candle
Next Candle Prediction: Based on the current streak and its comparison to the average, the indicator predicts the likely direction of the next candle:
Bullish: If the current up streak is shorter than the average up streak, suggesting that the bullish trend could continue.
Bearish: If the current down streak is shorter than the average down streak, indicating that the bearish trend may continue.
Neutral: If the current streak length is near the average, which could signal an upcoming reversal.
This prediction appears in a table on the chart, labeled as “Next Candle.”
5. Previous Candle Analysis
The Previous Candle entry in the table reflects the last completed candle (directly before the current candle) to show whether it was bullish, bearish, or neutral.
This data gives a reference point for recent price action and helps validate the next candle prediction.
6. Visual Signals and Reversal Zones
Bullish/Bearish Bias Signals: The indicator can plot green circles on bullish bias and red circles on bearish bias to highlight points where the trend is likely to continue.
Reversal Zones: If the current streak length reaches or exceeds the average, it suggests the trend may be overextended, indicating a potential reversal zone. The indicator highlights these zones with shaded backgrounds (green for possible bullish reversal, red for bearish) on the chart.
Summary of What You See on the Chart
Bullish and Bearish Bias Signals: Green or red circles mark areas of expected continuation in the trend.
Reversal Zones: Shaded areas in red or green suggest that the trend might be about to reverse.
Tables:
The Next Candle prediction table displays the trend direction of the previous candle and the likely trend of the next candle.
The Streak Information table shows the current up and down streak lengths, along with their averages for easy comparison.
Practical Use
This indicator is helpful for traders aiming to understand trend momentum and potential reversals based on historical patterns. It’s particularly useful for swing trading, where knowing the typical length of bullish or bearish trends can help in timing entries and exits.
PTS - Bollinger Bands with Trailing StopPTS - Bollinger Bands with Trailing Stop Strategy
Overview
The "PTS - Bollinger Bands with Trailing Stop" strategy is designed to capitalize on strong bullish market movements by combining the Bollinger Bands indicator with a dynamic trailing stop based on the Average True Range (ATR). This strategy aims to enter long positions during upward breakouts and protect profits through an adaptive exit mechanism.
Key Features
1. Bollinger Bands Indicator
Basis Moving Average Type: Choose from SMA, EMA, SMMA, WMA, or VWMA for the Bollinger Bands' basis line. Length: Adjustable period for calculating the moving average and standard deviation (default is 20). Standard Deviation Multiplier (StdDev): Determines the width of the bands (default is 2.0). Source: Select the price data used for calculations (default is the closing price).
2. Entry Conditions
The strategy enters a long position when the closing price crosses above the upper Bollinger Band , indicating strong upward momentum.
3. Exit Conditions
Trailing Stop Loss: Implemented using ATR to adjust dynamically with market volatility. ATR Length: Period for calculating ATR (default is 14). ATR Multiplier for Trailing Stop: Determines how closely the trailing stop follows the price (default is 2.0). Close Below Lower Bollinger Band: The strategy exits the long position if the closing price crosses below the lower Bollinger Band .
4. Risk Management
Commission and Slippage: Commission is set at 0.1%; slippage is set to 3. Position Sizing: Uses 100% of equity per trade (adjustable).
5. Date Range Filter
Specify the time period during which the strategy is active. Start Date: January 1, 2018. End Date: December 31, 2069.
Customizable Inputs
BB Length: Adjust the period for Bollinger Bands calculation. BB StdDev: Modify the standard deviation multiplier. Basis MA Type: Select the moving average type. Source: Choose the price data source. Offset: Shift the Bollinger Bands on the chart. ATR Length: Set the period for ATR calculation. ATR Multiplier for Trailing Stop: Adjust the trailing stop sensitivity.
Thought for 1m 7s
Description for the "PTS - Bollinger Bands with Trailing Stop" Strategy
PTS - Bollinger Bands with Trailing Stop Strategy
Overview
The "PTS - Bollinger Bands with Trailing Stop" strategy is designed to capitalize on strong bullish market movements by combining the Bollinger Bands indicator with a dynamic trailing stop based on the Average True Range (ATR). This strategy aims to enter long positions during upward breakouts and protect profits through an adaptive exit mechanism.
Key Features
1. Bollinger Bands Indicator
Basis Moving Average Type: Choose from SMA, EMA, SMMA, WMA, or VWMA for the Bollinger Bands' basis line. Length: Adjustable period for calculating the moving average and standard deviation (default is 20). Standard Deviation Multiplier (StdDev): Determines the width of the bands (default is 2.0). Source: Select the price data used for calculations (default is the closing price).
2. Entry Conditions
The strategy enters a long position when the closing price crosses above the upper Bollinger Band , indicating strong upward momentum.
3. Exit Conditions
Trailing Stop Loss: Implemented using ATR to adjust dynamically with market volatility. ATR Length: Period for calculating ATR (default is 14). ATR Multiplier for Trailing Stop: Determines how closely the trailing stop follows the price (default is 2.0). Close Below Lower Bollinger Band: The strategy exits the long position if the closing price crosses below the lower Bollinger Band .
4. Risk Management
Commission and Slippage: Commission is set at 0.1%; slippage is set to 3. Position Sizing: Uses 100% of equity per trade (adjustable).
5. Date Range Filter
Specify the time period during which the strategy is active. Start Date: January 1, 2018. End Date: December 31, 2069.
Customizable Inputs
BB Length: Adjust the period for Bollinger Bands calculation. BB StdDev: Modify the standard deviation multiplier. Basis MA Type: Select the moving average type. Source: Choose the price data source. Offset: Shift the Bollinger Bands on the chart. ATR Length: Set the period for ATR calculation. ATR Multiplier for Trailing Stop: Adjust the trailing stop sensitivity.
How the Strategy Works
1. Initialization
Calculates Bollinger Bands and ATR based on selected parameters.
2. Entry Logic
Opens a long position when the closing price exceeds the upper Bollinger Band.
3. Exit Logic
Uses a trailing stop loss based on ATR. Exits if the closing price drops below the lower Bollinger Band.
4. Date Filtering
Executes trades only within the specified date range.
Advantages
Adaptive Risk Management: Trailing stop adjusts to market volatility. Simplicity: Clear entry and exit signals. Customizable Parameters: Tailor the strategy to different assets or conditions.
Considerations
Aggressive Position Sizing: Using 100% equity per trade is high-risk. Market Conditions: Best in trending markets; may produce false signals in sideways markets. Backtesting: Always test on historical data before live trading.
Disclaimer
This strategy is intended for educational and informational purposes only. Trading involves significant risk, and past performance is not indicative of future results. Assess your financial situation and consult a financial advisor if necessary.
Usage Instructions
1. Apply the Strategy: Add it to your TradingView chart. 2. Configure Inputs: Adjust parameters to suit your style and asset. 3. Analyze Backtest Results: Use the Strategy Tester. 4. Optimize Parameters: Experiment with input values. 5. Risk Management: Evaluate position sizing and incorporate risk controls.
Final Notes
The "PTS - Bollinger Bands with Trailing Stop" strategy provides a framework to leverage momentum breakouts while managing risk through adaptive trailing stops. Customize and test thoroughly to align with your trading objectives.
Forex Relative Strength MatrixTraders often feel uncertain about which Forex pair to open a position with. This indicator is designed to help in that regard.
This indicator was created as described in the book Swing Trading with Heiken Ashi and Stochastics. In the original, the author suggests using it for swing trading. The author recommends applying it to a monthly chart with an 8-period moving average to analyze the context.
The logic of the indicator is to measure the relative strength of each currency by checking if the price of each Forex pair is above or below a chosen moving average. If the price is above the moving average, the base currency is awarded 1 point, indicating strength. If below, it scores 0, indicating weakness. By accumulating points across multiple pairs, the indicator ranks currencies from strongest to weakest, helping traders identify potential pairs for trading.
Trend Identification:
After identifying relative strength, the trader should observe the general trend using a 100-period SMA on 4-hour charts. If the price is above the SMA, the trend is bullish; if below, it is bearish.
Buy Logic:
A buy is triggered when the base currency is strong (price is above the moving average) and the quote currency is weak (price is below the moving average). After identifying the trend direction, the entry is confirmed by a color change in Heiken Ashi candles (from red to green in an uptrend) and a stochastic crossover in the trend’s direction.
Sell Logic:
A sell is triggered when the base currency is weak (price is below the moving average) and the quote currency is strong (price is above the moving average). The sell entry is confirmed by a color change in Heiken Ashi candles (from green to red in a downtrend) and a stochastic crossover aligned with the trend.
Entry Chart:
The entry chart used is the 4-hour chart. The trader should look for entry signals following a pullback in the trend direction, using Heiken Ashi candles. Entry is made when the Heiken Ashi candles change color (from red to green in an uptrend) and there is a smooth crossover of the stochastic indicator in the trend’s direction.
It would also be possible to adapt the indicator for day trading strategies with targets of 1 to 2 days. Here is a recommended setup:
Relative Strength Identification (1-Hour Chart):
Instead of monthly charts, use a 1-hour chart to identify currency strength with a 20-period moving average.
The 20-period moving average on the 1-hour chart captures a balanced view of short- to medium-term direction, covering nearly a day’s worth of trading but with enough sensitivity for day trading.
General Trend (5-Minute Chart with 100 SMA):
On the 5-minute chart, observe the 100-period SMA to identify the general trend direction throughout the day.
Price above the 100 SMA indicates an uptrend, and below indicates a downtrend, confirming the movement in shorter timeframes.
Entry Chart and Signals (5-Minute Chart):
Use the 15-minute chart to look for entry opportunities, focusing on pullbacks in the main trend direction.
Entry Signals: Enter the position when Heiken Ashi candles change color in the trend direction (from red to green in an uptrend) and the stochastic indicator makes a smooth crossover in the trend’s direction.
Options Series - Technical Analysis Chart➤ Simple Technical Chart Only:
➤ With MA-20 Overlay and Volatility background bars:
➤ With RSI Candles:
⭐ Overview and How It Works:
This script provides a multi-asset analysis tool to assess various market conditions across four symbols simultaneously. It combines several indicators such as daily price change, Moving Averages (MA), Bollinger Bands (BB), Parabolic SAR, RSI, and VWAP to generate buy/sell signals and trend indicators. Its strength lies in the layered use of indicators to enhance signal reliability, making it valuable for traders needing cross-validation in decision-making.
⭐ Key Features and Functionality:
The script evaluates each symbol's price against various indicators and conditions:
Daily Price Conditions: It checks if each symbol’s close price is above or below the previous day’s open, close, and intra-day ranges, forming a foundational bullish/bearish condition.
Range Breakout 1st 5min Candle (ORB): Opening Range Breakout levels are calculated and compared with current close prices, detecting breakout/breakdown conditions.
ORB Body: This basically calculates the previous day Daily candle body size, if todays Daily candle body size is greater than previous day, then we can say that we are having good momentum else its likely to be in-sidebar trading.
Moving Averages (MA): It leverages EMA-20, 2-day, and 3-day exponential moving averages to gauge short to medium-term trends.
RSI and VWAP: Relative Strength Index (RSI) determines overbought or oversold conditions, while VWAP compares prices to volume-weighted levels.
Bollinger Bands and Trend Analysis: Detects volatility and potential breakout conditions.
Concept of ORB Body:
Current_PrevDay_Body = (math.max(var_Current_PrevD_Open, var_Current_PrevD_Close) - math.min(var_Current_PrevD_Open, var_Current_PrevD_Close))
Current_Upper_ORB = var_Current_D_Open + Current_PrevDay_Body
Current_Lower_ORB = var_Current_D_Open - Current_PrevDay_Body
Current_TodayDay_Body = math.max(var_Current_D_Open, var_Current_Close) - math.min(var_Current_D_Open, var_Current_Close)
Current_ORBBody = Current_TodayDay_Body > Current_PrevDay_Body
Current_Upper_ORB_bull = (var_Current_Close > Current_Upper_ORB)
Current_Lower_ORB_bear = (var_Current_Close < Current_Lower_ORB)
🎨 Visualizations and User Experience:
The script can dynamically display colored backgrounds indicating trends when conditions are met. For example, the bgcolor function changes the background when certain trend-based criteria are satisfied, offering visual cues to users. Additionally, the checkbox input toggles trend bar visualizations, enhancing user experience by providing a quick visual reference without needing to interpret individual data points manually.
RSI-Based Candle Coloring:
➤ The script customizes candle colors based on RSI thresholds, specifically defining upper (60) and lower (40) RSI levels. When the RSI value exceeds the upper threshold, candles are colored as bullish (green), and if it falls below the lower threshold, candles are colored as bearish (red). Neutral RSI values result in a default color (gray).
➤ This setup offers a visually intuitive way to identify potential trend directions based on RSI levels, making it ideal for traders looking to gauge momentum visually.
⭐ Settings and Customization:
With multiple user-configurable inputs, the script allows for tailored analysis. Customizable parameters, such as enabling/disabling trend bars and setting various look-back periods for indicators like Bollinger Bands and Moving Averages, make it adaptable to various trading styles and preferences. It also allows users to modify visual elements like colors and styles, improving flexibility.
⭐ Uniqueness of the Concept:
The unique aspect of this script is its multi-symbol approach combined with complex conditions. By comparing not only one but four symbols simultaneously, it provides a broader market view and allows traders to correlate signals across different assets, offering a potential edge for diversified or comparative strategies. Additionally, the incorporation of ORB and multi-timeframe MAs gives it a robustness often lacking in simpler single-symbol scripts.
🚀 Conclusion:
This script is a powerful multi-indicator tool suited for traders looking for a comparative, multi-symbol analysis. With features like ORB, Bollinger Band-based trend detection, and MA cross-verification, it can assist traders in identifying and validating trend signals across assets. The user-friendly visualizations and customizable settings further enhance its usability, making it versatile for various trading strategies and preferences.
MFI Strategy with Oversold Zone Exit and AveragingThis strategy is based on the Money Flow Index (MFI) and aims to enter a long position when the MFI exits an oversold zone, with specific rules for limit orders, stop-loss, and take-profit settings. Here's a detailed breakdown:
Key Components
1. **Money Flow Index (MFI)**: The strategy uses the MFI, a volume-weighted indicator, to gauge whether the market is in an oversold condition (default threshold of MFI < 20). Once the MFI rises above the oversold threshold, it signals a potential buying opportunity.
2. **Limit Order for Long Entry**: Instead of entering immediately after the oversold condition is cleared, the strategy places a limit order at a price slightly below the current price (by a user-defined percentage). This helps achieve a better entry price.
3. **Stop-Loss and Take-Profit**:
- **Stop-Loss**: A stop-loss is set to protect against significant losses, calculated as a percentage below the entry price.
- **Take-Profit**: A take-profit target is set as a percentage above the entry price to lock in gains.
4. **Order Cancellation**: If the limit order isn’t filled within a specific number of bars (default is 5 bars), it’s automatically canceled to avoid being filled at a potentially suboptimal price as market conditions change.
Strategy Workflow
1. **Identify Oversold Zone**: The strategy checks if the MFI falls below a defined oversold level (default is 20). Once this condition is met, the flag `inOversoldZone` is set to `true`.
2. **Wait for Exit from Oversold Zone**: When the MFI rises back above the oversold level, it’s considered a signal that the market is potentially recovering, and the strategy prepares to enter a position.
3. **Place Limit Order**: Upon exiting the oversold zone, the strategy places a limit order for a long position at a price below the current price, defined by the `Long Entry Percentage` parameter.
4. **Monitor Limit Order**: A counter (`barsSinceEntryOrder`) starts counting the bars since the limit order was placed. If the order isn’t filled within the specified number of bars, it’s canceled automatically.
5. **Set Stop-Loss and Take-Profit**: Once the order is filled, a stop-loss and take-profit are set based on user-defined percentages relative to the entry price.
6. **Exit Strategy**: The trade will close automatically when either the stop-loss or take-profit level is hit.
Advantages
- **Risk Management**: With configurable stop-loss and take-profit, the strategy ensures losses are limited while capturing profits at pre-defined levels.
- **Controlled Entry**: The use of a limit order below the current price helps secure a better entry point, enhancing risk-reward.
- **Oversold Exit Trigger**: Using the exit from an oversold zone as an entry condition can help catch reversals.
Disadvantages
- **Missed Entries**: If the limit order isn’t filled due to insufficient downward movement after the oversold signal, potential opportunities may be missed.
- **Dependency on MFI Sensitivity**: As the MFI is sensitive to both price and volume, its fluctuations might not always accurately represent oversold conditions.
Overall Purpose
The strategy is suited for traders who want to capture potential reversals after oversold conditions in the market, with a focus on precise entries, risk management, and an automated exit plan.
