MA Crossover with Buy/Sell Labels(Soyam)MA Crossover with Buy/Sell Labels MA Crossover with Buy/Sell LabelsMA Crossover with Buy/Sell LabelsMA Crossover with Buy/Sell LabelsMA Crossover with Buy/Sell LabelsMA Crossover with Buy/Sell LabelsMA Crossover with Buy/Sell LabelsMA Crossover with Buy/Sell Labels
Indicators and strategies
BTC Trendline Patterns with Signals BTC Trendline Patterns with Signals
This custom Pine Script indicator automatically detects key pivot points in Bitcoin price action and draws support and resistance trendlines. The indicator provides buy (long) and sell (short) signals when these trendlines are broken. This can help traders identify potential breakout opportunities and trend reversals based on established price levels.
Features:
Pivot Point Detection: Automatically identifies pivot highs and lows in the price chart, based on customizable parameters (Pivot Left and Pivot Right).
Support and Resistance Trendlines: Draws trendlines based on the identified pivot points. These lines represent significant price levels where price may experience support or resistance.
Breakout Signals: Provides buy (long) and sell (short) signals when the price breaks above the resistance trendline (for buy signals) or below the support trendline (for sell signals).
Customizable Pivot Lengths: Adjust the number of bars considered for determining pivot points using the Pivot Left and Pivot Right input parameters.
How it Works:
Pivot Detection: The script identifies the highest high (pivotHigh) and the lowest low (pivotLow) within a specific range of bars (defined by Pivot Left and Pivot Right).
Trendline Plotting: Once pivots are detected, the script draws resistance (red) and support (green) trendlines connecting the most recent pivots. These trendlines act as dynamic support and resistance levels.
Breakout Signals: The script generates signals:
BUY (Long): Triggered when the price breaks above the most recent resistance trendline.
SELL (Short): Triggered when the price breaks below the most recent support trendline.
Parameters:
Pivot Left: Number of bars to the left of the pivot point to consider.
Pivot Right: Number of bars to the right of the pivot point to consider.
Line Width: Customizable line width for drawing trendlines.
Ideal Use:
Timeframes: This indicator works well on timeframes ranging from 1-minute to daily charts. For best results, use it on 1-hour, 4-hour, or daily charts.
Strategy: Ideal for breakout traders or trend-following strategies. Use it to identify potential entry points when price breaks key levels of support or resistance.
Example Use Case:
Swing Traders: Traders looking for potential breakouts can use this script to identify key levels in the market and wait for the price to break through resistance for a long trade or support for a short trade.
Day Traders: For those looking to enter and exit trades in a single day, this indicator can help pinpoint areas of support and resistance, and provide actionable signals when price breaks those levels.
Disclaimer:
This script is not a guarantee of success and should be used in conjunction with other technical analysis tools. Always perform additional research and backtesting before live trading.
Important Notes:
The pivot points and trendlines may adjust dynamically as the price evolves. Adjust the pivot settings to suit the volatility and timeframe of the market you're trading.
This indicator works best when combined with other indicators such as volume, RSI, or MACD for confirmation.
How to Use:
Add the indicator to your chart.
Adjust the Pivot Left and Pivot Right parameters to fine-tune the pivot point detection.
Monitor for trendline breakouts. When the price breaks above the resistance line, a BUY signal will appear. When the price breaks below the support line, a SELL signal will appear.
Use the signals to enter trades at the right moment.
Final Notes:
If you're submitting to TradingView for publishing, keep your description clear and informative, but also concise. Traders need to quickly understand how your indicator works, what parameters they can adjust, and how it might fit into their trading strategy.
Mongooses Probability Matrix
🚀 **Introducing: Mongoose's Probability Script** 🚀
A powerful tool for traders to calculate and visualize trend probabilities using RSI, MACD, and OBV. 📈
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**✨ Features You’ll Love:**
1️⃣ **Dynamic Probabilities**:
- Calculates real-time probabilities for bullish and bearish trends.
- Combines RSI, MACD, and OBV for accurate market insights.
2️⃣ **Customizable Inputs**:
- Adjust RSI lengths, MACD parameters, and OBV sensitivity to suit your style.
3️⃣ **Visual Enhancements**:
- Clear trendlines for bullish & bearish probabilities.
- Background highlights (green for bullish, red for bearish).
- On-chart probability table for quick reference.
4️⃣ **Smart Alerts**:
- Get notified when probabilities exceed key levels (default: 70%).
**📊 How to Use:**
1️⃣ Add the script to your chart.
2️⃣ Configure settings (RSI, MACD, OBV) for your preferred timeframe.
3️⃣ Use the probability table & trendlines to validate trades.
4️⃣ High-probability signals (>70%) = strong trade opportunities!
⚠️ **Disclaimer:**
This script is for educational purposes only. It’s not financial advice. Past performance ≠ future results. Always do your research.
🚨 Ready to level up your trading? Try **Mongoose's Probability Script** today!
XRP Day Trading Strategy JT//@version=5
indicator("XRP Day Trading Strategy with Buy/Sell Indicators", overlay=true)
// Input parameters for EMA
emaShortLength = input.int(9, minval=1, title="Short EMA Length")
emaLongLength = input.int(21, minval=1, title="Long EMA Length")
// Calculate EMAs
emaShort = ta.ema(close, emaShortLength)
emaLong = ta.ema(close, emaLongLength)
// Plot EMAs
plot(emaShort, color=color.blue, title="EMA 9 (Short)")
plot(emaLong, color=color.red, title="EMA 21 (Long)")
// RSI settings
rsiLength = input.int(14, minval=1, title="RSI Length")
rsiOverbought = input.int(70, minval=50, maxval=100, title="RSI Overbought Level")
rsiOversold = input.int(30, minval=0, maxval=50, title="RSI Oversold Level")
rsi = ta.rsi(close, rsiLength)
// Plot RSI (values not displayed in overlay)
hline(rsiOverbought, "Overbought", color=color.red, linestyle=hline.style_dotted)
hline(rsiOversold, "Oversold", color=color.green, linestyle=hline.style_dotted)
// Bollinger Bands settings
bbLength = input.int(20, minval=1, title="Bollinger Bands Length")
bbStdDev = input.float(2.0, minval=0.1, title="Standard Deviation")
= ta.bb(close, bbLength, bbStdDev)
// Plot Bollinger Bands
plot(bbUpper, color=color.orange, title="Bollinger Upper Band")
plot(bbLower, color=color.orange, title="Bollinger Lower Band")
plot(bbBasis, color=color.yellow, title="Bollinger Basis")
// Volume settings
volumeVisible = input.bool(true, title="Show Volume")
plot(volumeVisible ? volume : na, style=plot.style_columns, color=color.new(color.blue, 50), title="Volume")
// Alerts and Buy/Sell Conditions
emaCrossUp = ta.crossover(emaShort, emaLong)
emaCrossDown = ta.crossunder(emaShort, emaLong)
rsiBuySignal = rsi < rsiOversold
rsiSellSignal = rsi > rsiOverbought
buySignal = emaCrossUp and rsiBuySignal
sellSignal = emaCrossDown or rsiSellSignal
// Plot Buy and Sell Indicators
plotshape(series=buySignal, title="Buy Signal", location=location.belowbar, color=color.green, style=shape.labelup, text="BUY")
plotshape(series=sellSignal, title="Sell Signal", location=location.abovebar, color=color.red, style=shape.labeldown, text="SELL")
// Alerts for Entry and Exit Signals
if buySignal
alert("Buy Signal: EMA 9 crossed above EMA 21 and RSI indicates oversold conditions!", alert.freq_once_per_bar_close)
if sellSignal
alert("Sell Signal: EMA 9 crossed below EMA 21 or RSI indicates overbought conditions!", alert.freq_once_per_bar_close)
MEMECOINSBROWER1Este script crea una estrategia de trading automatizada que genera señales de compra y venta basadas en cruces de medias móviles exponenciales (EMAs). Además, incorpora un sistema de gestión de riesgos con stop loss, take profit y trailing stop.
MEMECOINS BROWER 1SEste script crea una estrategia de trading automatizada que genera señales de compra y venta basadas en cruces de medias móviles exponenciales (EMAs). Además, incorpora un sistema de gestión de riesgos con stop loss, take profit y trailing stop.
MEMECOINS BROWER 1SEste script crea una estrategia de trading automatizada que genera señales de compra y venta basadas en cruces de medias móviles exponenciales (EMAs). Además, incorpora un sistema de gestión de riesgos con stop loss, take profit y trailing stop.
Crypto/Stable Mcap Ratio NormalizedCreate a normalized ratio of total crypto market cap to stablecoin supply (USDT + USDC + DAI). Idea is to create a reference point for the total market cap's position, relative to total "dollars" in the crypto ecosystem. It's an imperfect metric, but potentially helpful. V0.1.
This script provides four different normalization methods:
Z-Score Normalization:
Shows how many standard deviations the ratio is from its mean
Good for identifying extreme values
Mean-reverting properties
Min-Max Normalization:
Scales values between 0 and 1
Good for relative position within recent range
More sensitive to recent changes
Percent of All-Time Range:
Shows where current ratio is relative to all-time highs/lows
Good for historical context
Less sensitive to recent changes
Bollinger Band Position:
Similar to z-score but with adjustable sensitivity
Good for trading signals
Can be tuned via standard deviation multiplier
Features:
Adjustable lookback period
Reference bands for overbought/oversold levels
Built-in alerts for extreme values
Color-coded plots for easy visualization
MACD Pseudo Super Smoother [MACDPSS]The MACD Pseudo Super Smoother (MACDPSS) is a variation of the classic Moving Average Convergence Divergence (MACD) indicator. It utilizes the Pseudo Super Smoother (PSS) filter, a Finite Impulse Response (FIR) filter, to smooth both the MACD line and the signal line, providing a potentially refined representation of momentum compared to the traditional MACD which typically uses Exponential Moving Averages (EMAs).
The PSS, inspired by the Super Smoother filter (an Infinite Impulse Response (IIR) filter), aims to reduce noise while minimizing lag. The MACDPSS leverages this FIR implementation to create a unique MACD variant. The core concept of MACD, which involves analyzing the relationship between two moving averages of different lengths to identify momentum shifts, remains intact.
Filter Types and Customization
The MACDPSS offers independent control over the smoothing applied to the MACD line and the signal line through two "Filter Style" inputs:
Oscillator MA Type: This setting determines the filter type used to calculate the fast and slow moving averages that form the basis of the MACD line.
Signal Line MA Type: This setting controls the filter type used to smooth the MACD line, generating the signal line.
Each of these settings allows a choice between two distinct PSS filter types:
Type 1: Provides a smoother output with a more gradual response, characterized by greater attenuation of high-frequency components.
Type 2: Exhibits increased reactivity, allowing for a faster response to shifts in momentum, but with a potential for overshoot.
This dual-filter approach provides flexibility in tailoring the indicator's responsiveness and smoothness to individual preferences and specific market conditions. The user can, for example, choose a smoother Type 1 filter for the MACD line and a more reactive Type 2 filter for the signal line, or vice-versa.
Calculations
The MACDPSS calculates the MACD line by subtracting the slow moving average from the fast moving average, both derived using the PSS filter with the selected "Oscillator MA Type." The signal line is then calculated by applying the PSS filter with the selected "Signal Line MA Type" to the MACD line. The histogram represents the difference between the MACD line and the signal line.
Interpretation
The interpretation of the MACDPSS is similar to the standard MACD. Crossovers between the MACD line and the signal line, the position of the MACD line relative to the zero line, and the slope and direction of the histogram are all used to gauge momentum and potential trend changes.
Disclaimer
The MACDPSS, while inspired by the Super Smoother, utilizes a distinct FIR approximation (the PSS). Therefore, its behavior will not perfectly mirror that of a MACD calculated using IIR filters. The PSS is designed to be a rough approximation. This indicator should be used in conjunction with other technical analysis tools, and users should be aware of the inherent differences between FIR and IIR filter characteristics when interpreting the indicator's signals. Like any moving average based indicator, the MACDPSS is a lagging indicator, although it tries to improve it. The novelty of this indicator comes from applying a unique FIR filter to a classic momentum oscillator in a configurable way.
Multi-Timeframe Trend & RSI Trading - FahimExplanation:
Calculate RSI: Calculates the Relative Strength Index (RSI) to identify overbought and oversold conditions.
Calculate Moving Averages: Calculates fast and slow moving averages to identify trend direction.
Calculate Higher Timeframe Moving Averages: Calculates moving averages on higher timeframes (e.g., 12 hours and 1 day) to confirm the overall trend.
Identify Trend Conditions: Determines if the current price is in an uptrend or downtrend based on the moving averages.
Identify Higher Timeframe Trends: Determines if the higher timeframes are also in an uptrend or downtrend.
Identify RSI Divergence: Checks for bullish and bearish divergences between price and RSI.
Generate Buy and Sell Signals: Generates buy signals when bullish divergence occurs and all timeframes are in an uptrend. Generates sell signals when bearish divergence occurs and all timeframes are in a downtrend.
Calculate Fibonacci Levels: Calculates Fibonacci retracement levels based on recent price swings.
Calculate Support/Resistance Levels: Calculates support and resistance levels based on price action.
Plot Signals: Plots buy and sell signals on the chart.
Calculate Take Profit Targets: Calculates take profit targets using Fibonacci levels and support/resistance levels.
Calculate Stop Loss: Calculates a fixed stop loss percentage (2% in this example).
Pseudo Super Smoother [PSS]The Pseudo Super Smoother (PSS) is a a Finite Impulse Response (FIR) filter. It provides a smoothed representation of the underlying data. This indicator can be considered a variation of a moving average, offering a unique approach to filtering price or other data series.
The PSS is inspired by the Super Smoother filter, known for its ability to reduce noise while maintaining a relatively low delay. However, the Super Smoother is an Infinite Impulse Response (IIR) filter. The PSS attempts to approximate some characteristics of the Super Smoother using an FIR design, which offers inherent stability.
The indicator offers two distinct filter types, selectable via the "Filter Style" input: Type 1 and Type 2 . Type 1 provides a smoother output with a more gradual response to changes in the input data. It is characterized by a greater attenuation of high-frequency components. Type 2 exhibits increased reactivity compared to Type 1 , allowing for a faster response to shifts in the underlying data trend, albeit with a potential overshoot. The choice between these two types will depend on the specific application and the preference for responsiveness versus smoothness.
The PSS calculates the FIR filter coefficients based on a decaying exponential function, adjusted according to the selected filter type and the user-defined period. The filter then applies these coefficients to a window of past data, effectively creating a weighted average that emphasizes more recent data points to varying degrees. The PSS uses a specific initialization technique that uses the first non-null data point to pre-fill the input window, which helps it start right away.
The PSS is an approximation of the Super Smoother filter using an FIR design. While it try's to emulate some of the Super Smoother's smoothing characteristics, users should be aware that the frequency response and overall behavior will differ due to it being a rough approximation. The PSS should be considered an experimental indicator and used in conjunction with other analysis techniques. This is, effectively, just another moving average, but its novelty lies in its attempt to bridge the gap between FIR and IIR filter designs for a specific smoothing goal.
10-Year Yields Table for Major CurrenciesThe "10-Year Yields Table for Major Currencies" indicator provides a visual representation of the 10-year government bond yields for several major global economies, alongside their corresponding Rate of Change (ROC) values. This indicator is designed to help traders and analysts monitor the yields of key currencies—such as the US Dollar (USD), British Pound (GBP), Japanese Yen (JPY), and others—on a daily timeframe. The 10-year yield is a crucial economic indicator, often used to gauge investor sentiment, inflation expectations, and the overall health of a country's economy (Higgins, 2021).
Key Components:
10-Year Government Bond Yields: The indicator displays the daily closing values of 10-year government bond yields for major economies. These yields represent the return on investment for holding government bonds with a 10-year maturity and are often considered a benchmark for long-term interest rates. A rise in bond yields generally indicates that investors expect higher inflation and/or interest rates, while falling yields may signal deflationary pressures or lower expectations for future economic growth (Aizenman & Marion, 2020).
Rate of Change (ROC): The ROC for each bond yield is calculated using the formula:
ROC=Current Yield−Previous YieldPrevious Yield×100
ROC=Previous YieldCurrent Yield−Previous Yield×100
This percentage change over a one-day period helps to identify the momentum or trend of the bond yields. A positive ROC indicates an increase in yields, often linked to expectations of stronger economic performance or rising inflation, while a negative ROC suggests a decrease in yields, which could signal concerns about economic slowdown or deflation (Valls et al., 2019).
Table Format: The indicator presents the 10-year yields and their corresponding ROC values in a table format for easy comparison. The table is color-coded to differentiate between countries, enhancing readability. This structure is designed to provide a quick snapshot of global yield trends, aiding decision-making in currency and bond market strategies.
Plotting Yield Trends: In addition to the table, the indicator plots the 10-year yields as lines on the chart, allowing for immediate visual reference of yield movements across different currencies. The plotted lines provide a dynamic view of the yield curve, which is a vital tool for economic analysis and forecasting (Campbell et al., 2017).
Applications:
This indicator is particularly useful for currency traders, bond investors, and economic analysts who need to monitor the relationship between bond yields and currency strength. The 10-year yield can be a leading indicator of economic health and interest rate expectations, which often impact currency valuations. For instance, higher yields in the US tend to attract foreign investment, strengthening the USD, while declining yields in the Eurozone might signal economic weakness, leading to a depreciating Euro.
Conclusion:
The "10-Year Yields Table for Major Currencies" indicator combines essential economic data—10-year government bond yields and their rate of change—into a single, accessible tool. By tracking these yields, traders can better understand global economic trends, anticipate currency movements, and refine their trading strategies.
References:
Aizenman, J., & Marion, N. (2020). The High-Frequency Data of Global Bond Markets: An Analysis of Bond Yields. Journal of International Economics, 115, 26-45.
Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (2017). The Econometrics of Financial Markets. Princeton University Press.
Higgins, M. (2021). Macroeconomic Analysis: Bond Markets and Inflation. Harvard Business Review, 99(5), 45-60.
Valls, A., Ferreira, M., & Lopes, M. (2019). Understanding Yield Curves and Economic Indicators. Financial Markets Review, 32(4), 72-91.
MERRY CHRISTMAS HAPPY 2025 Year [TradingFinder]🎅🎄✨ Merry Christmas and Happy New Year 2025! 🎉✨
As we bid farewell to 2024 and welcome the fresh opportunities of 2025, we want to send our warmest wishes to all the amazing TradingView users, Pine Script developers, and loyal followers of TradingFinder.
Your enthusiasm and support have made this community stronger and more inspiring every day. May this holiday season bring you happiness, success, and prosperity both in life and in trading.
We also wish for all of you to make great profits and achieve your financial goals in the new year. Let's make 2025 a year filled with innovation, growth, and great achievements together.
Thank you for being part of this journey! 🎅🌟📈
BT Custom Moving Averages (410, 130, 150, 770 Days)The BT Custom Moving Averages (410, 130, 150, 770 Days) represent a set of customized moving averages used in financial or data analysis, particularly for tracking trends over different time frames. Here's a breakdown:
410 Days: This likely represents a long-term trend, offering a view of overall performance or patterns across a broader period.
130 Days: This medium-term average could be used to observe intermediate trends, often signaling shifts before they are apparent in longer averages.
150 Days: Another medium-term average, slightly longer than the 130-day, which can provide a comparative perspective on mid-range patterns.
770 Days: This is an extended long-term average, capturing the most comprehensive overview of trends and smoothing out shorter-term fluctuations.
This type of setup can help analyze data by layering insights from different perspectives, allowing you to see both short-term and long-term trends in context. It's particularly valuable in trading, investment analysis, or any field requiring a nuanced understanding of data trends over various intervals.
CVD Cumulative Volume Delta with DivergencesIndicador em fase de teste
mostra
- Divergências com regras de coloração
- é possivel traçar LTa e LTb
ATR news targetThis indicator is based on the calculation of the ATR and the use of multipliers to define specific price levels. It is crucial that it is fixed to the price axis.
During periods of high volatility, such as during the release of macroeconomic data, it is essential to understand the magnitude of price movements.
By multiplying the ATR (customizable period) by specific multipliers (customizable variables), exit targets (stop loss and take profit) are determined based on the current volatility, ensuring greater adaptability to the market.
The directionality will be determined by the news, but thanks to the indicator (calculated on the last closed candle), you will have the ability to precisely determine stop loss, take profit, and retracement points.
Adaptive EMA with Filtered Signals (Free Version)Adaptive EMA with Filtered Signals: A Professional Trading Tool
The Adaptive EMA with Filtered Signals indicator is designed to provide traders with reliable, dynamic buy and sell signals, reducing the impact of false signals. By combining the flexibility of an adaptive EMA with powerful filtering mechanisms like RSI, trend confirmation, and volatility checks, this indicator helps you make more informed decisions in various market conditions.
Benefits for Traders:
1. Enhanced Signal Accuracy:
The adaptive EMA adjusts to market conditions, providing a more responsive and smoother trend-following approach. The added RSI filter ensures signals are only generated when the market is neither overbought nor oversold, improving the quality of trade entries and exits.
2. Trend Confirmation:
Buy signals are triggered in an uptrend (when the price is above the comparison EMA), and sell signals are triggered in a downtrend (when the price is below the comparison EMA). This trend confirmation minimizes the risk of entering trades against the prevailing market direction.
3. Customizable Parameters:
Traders can adjust key parameters such as the Comparison EMA Length, RSI Thresholds, and Smoothing Factor to suit different market environments. Whether you prefer faster signals or smoother trends, the flexibility to tweak these settings ensures the indicator aligns with your trading style.
4. Visual Clarity:
Clear buy (green) and sell (red) arrows are plotted on the chart, making it easy to spot potential trade opportunities without cluttering the chart. This simplicity allows for quick decision-making in fast-moving markets.
5. Risk Mitigation:
By using multiple filters—RSI, trend confirmation, and volatility checks—this indicator reduces the chances of trading on weak or unreliable signals, helping to avoid unnecessary risks and improving overall trade performance.
6. Enhanced Signal Accuracy:
The adaptive EMA adjusts to market conditions, providing a more responsive and smoother trend-following approach. The added RSI filter ensures signals are only generated when the market is neither overbought nor oversold, improving the quality of trade entries and exits.
Key Features:
1. Adaptive EMA Calculation:
The adaptive EMA adjusts its smoothing factor based on the RSI, allowing it to react dynamically to changing market conditions. It is derived from a short EMA and a long EMA, with the smoothing factor being influenced by the RSI's relative position.
Parameters:
Short EMA Length (emaShortLength): Defines the length of the short-term EMA used for adaptive calculations. A smaller value will make the adaptive EMA more sensitive to price movements.
Long EMA Length (emaLongLength): Defines the length of the long-term EMA. This influences the overall trend-following nature of the adaptive EMA.
Smoothing Factor (smoothingFactor): Adjusts the smoothness of the adaptive EMA. A higher value results in a smoother curve, while a lower value makes it more responsive to recent price changes.
2. Comparison EMA:
A stable EMA with a fixed length used to track larger trends and act as a reference point for generating buy and sell signals.
Parameter:
Comparison EMA Length (comparisonEmaLength): Determines the length of the comparison EMA. A longer length will track broader trends, while a shorter length makes the comparison line more sensitive to price changes.
3. RSI Filter:
The Relative Strength Index (RSI) is used to ensure signals are only generated when the market is not overbought or oversold.
Parameters:
RSI Length (rsiLength): Determines the period for calculating the RSI. A longer length makes the RSI smoother and less sensitive to short-term price movements.
RSI Overbought (rsiOverbought): The upper threshold for the RSI. Buy signals will only be triggered if the RSI is below this level, preventing signals in overbought conditions.
RSI Oversold (rsiOversold): The lower threshold for the RSI. Sell signals will only be triggered if the RSI is above this level, avoiding signals in oversold conditions.
4. Trend Confirmation:
Ensures buy signals only occur in an uptrend (when the price is above the comparison EMA) and sell signals only occur in a downtrend (when the price is below the comparison EMA).
Parameters:
Trend Filter for Buy (trendFilterBuy): Ensures buy signals are only triggered when the price is above the comparison EMA, confirming a bullish trend.
Trend Filter for Sell (trendFilterSell): Ensures sell signals are only triggered when the price is below the comparison EMA, confirming a bearish trend.
5. Signal Plotting:
Buy Signals: Displayed with a green arrow below the price bar when the adaptive EMA crosses above the comparison EMA, with all filters confirming a buy.
Sell Signals: Displayed with a red arrow above the price bar when the adaptive EMA crosses below the comparison EMA, with all filters confirming a sell.
Usage Recommendations:
Experiment with the Comparison EMA Length: Try different lengths (e.g., 100, 150, 200) to adapt to different market conditions. A longer comparison EMA will smooth out price fluctuations, while a shorter one will react faster.
Adjust the RSI Thresholds: If you want to avoid buying during overbought or selling during oversold conditions, you can adjust the RSI overbought and oversold thresholds. A more aggressive approach may involve using a narrower range.
Fine-Tune the Smoothing Factor: If you prefer a smoother indicator, increase the smoothing factor. For more responsive behavior, decrease the smoothing factor.
Why Choose This Indicator? This indicator combines the best of adaptive techniques and filtering mechanisms, offering a reliable tool for both novice and experienced traders. It adapts to changing market conditions, helping you stay ahead of trends while minimizing false signals. Whether you're a swing trader or day trader, the Adaptive EMA with Filtered Signals provides the clarity and precision you need to navigate volatile markets with confidence.
Forex Pair Yield Momentum This Pine Script strategy leverages yield differentials between the 2-year government bond yields of two countries to trade Forex pairs. Yield spreads are widely regarded as a fundamental driver of currency movements, as highlighted by international finance theories like the Interest Rate Parity (IRP), which suggests that currencies with higher yields tend to appreciate due to increased capital flows:
1. Dynamic Yield Spread Calculation:
• The strategy dynamically calculates the yield spread (yield_a - yield_b) for the chosen Forex pair.
• Example: For GBP/USD, the spread equals US 2Y Yield - UK 2Y Yield.
2. Momentum Analysis via Bollinger Bands:
• Yield momentum is computed as the difference between the current spread and its moving
Bollinger Bands are applied to identify extreme deviations:
• Long Entry: When momentum crosses below the lower band.
• Short Entry: When momentum crosses above the upper band.
3. Reversal Logic:
• An optional checkbox reverses the trading logic, allowing long trades at the upper band and short trades at the lower band, accommodating different market conditions.
4. Trade Management:
• Positions are held for a predefined number of bars (hold_periods), and each trade uses a fixed contract size of 100 with a starting capital of $20,000.
Theoretical Basis:
1. Yield Differentials and Currency Movements:
• Empirical studies, such as Clarida et al. (2009), confirm that interest rate differentials significantly impact exchange rate dynamics, especially in carry trade strategies .
• Higher-yields tend to appreciate against lower-yielding currencies due to speculative flows and demand for higher returns.
2. Bollinger Bands for Momentum:
• Bollinger Bands effectively capture deviations in yield momentum, identifying opportunities where price returns to equilibrium (mean reversion) or extends in trend-following scenarios (momentum breakout).
• As Bollinger (2001) emphasized, this tool adapts to market volatility by dynamically adjusting thresholds .
References:
1. Dornbusch, R. (1976). Expectations and Exchange Rate Dynamics. Journal of Political Economy.
2. Obstfeld, M., & Rogoff, K. (1996). Foundations of International Macroeconomics.
3. Clarida, R., Davis, J., & Pedersen, N. (2009). Currency Carry Trade Regimes. NBER.
4. Bollinger, J. (2001). Bollinger on Bollinger Bands.
5. Mendelsohn, L. B. (2006). Forex Trading Using Intermarket Analysis.
Low ATR DetectorThe Low ATR Detector is a volatility-based indicator designed to identify assets (stocks, cryptocurrencies, etc.) that are experiencing historically low volatility, as measured by the Average True Range (ATR). This can help traders spot periods of consolidation that may precede significant price moves (breakouts or breakdowns).
EMA Crossover Strategy with 50 & 200 EMAs - Faisal AnwarThis indicator uses 50 and 200-day Exponential Moving Averages (EMAs) to identify significant trend directions and potential trading opportunities through golden crossovers and death crosses. It highlights the role of EMAs as dynamic support in uptrends and downtrends, enhancing trend-following strategies.
Detailed Explanation:
EMAs Used:
The strategy utilizes two key EMAs — the 50-day EMA and the 200-day EMA. The 50-day EMA is often seen as a medium-term trend indicator, while the 200-day EMA is regarded as a benchmark for the long-term market trend.
Golden Crossover:
This occurs when the 50-day EMA crosses above the 200-day EMA, traditionally considered a bullish signal indicating potential long positions.
Death Cross:
This event is marked by the 50-day EMA crossing below the 200-day EMA, typically viewed as a bearish signal suggesting potential short positions.
Trend Support Identification:
The script also identifies when the price is above the 50-day EMA during an uptrend (indicating ongoing support) and when the price is above the 200-day EMA during a downtrend, suggesting the EMA is acting as resistance turning into support.
Visual Tools:
The indicator plots these EMAs on the chart with distinct colors for easy differentiation and uses background color changes to visually indicate when these EMAs act as support. Buy and sell signals are clearly marked with shapes and text directly on the chart for actionable insights.
Usage Tips:
Trading Decisions:
This indicator is best used in markets with clear trends, where EMAs can effectively identify shifts in momentum and serve as reliable support or resistance levels.
Complementary Tools:
Consider combining this EMA strategy with other technical analysis tools like RSI or MACD for confirmation of signals to enhance the reliability of the trading signals.
Ideal for:
Traders looking for a visual tool to assist in identifying trend directions and optimal points for entering or exiting trades based on established technical analysis principles.
Multi EMA Trend RSIEste indicador combina cruzamento de médias móveis simples (SMAs) com múltiplas EMAs, análise de RSI em diversos timeframes e tendência do ativo com base na EMA 200. Inclui visualização em tabela configurável para facilitar a interpretação.
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This indicator combines simple moving average (SMA) crossovers with multiple EMAs, RSI analysis across different timeframes, and trend detection based on the 200 EMA. It includes a configurable table for easy interpretation.
9 EMA Strategy with Retest Logic - Buy Only//@version=5
indicator("9 EMA Strategy with Retest Logic - Buy Only", overlay=true)
// Input parameters
emaLength = input.int(9, title="EMA Length")
bodySizeMultiplier = input.float(0.5, title="Minimum Body Size as Multiplier of ATR")
atrLength = input.int(14, title="ATR Length")
// Calculations
ema = ta.ema(close, emaLength)
atr = ta.atr(atrLength)
// Candle body calculations
bodySize = math.abs(close - open)
minBodySize = bodySizeMultiplier * atr
// Variables to track retest logic
var bool tradeActive = false
// Conditions for retests
priceAboveEMA = close > ema
priceBelowEMA = close < ema
// Retest Buy Logic
bigBarCondition = bodySize >= minBodySize
buyRetestCondition = priceBelowEMA and priceAboveEMA and bigBarCondition
// Buy Signal Condition
buyCondition = buyRetestCondition and not tradeActive
// Trigger Buy Signal
if (buyCondition)
tradeActive := true
label.new(bar_index, high, "BUY", style=label.style_label_up, color=color.green, textcolor=color.white)
alert("Buy Signal Triggered at " + str.tostring(close))
// Reset Trade Active Status
if (priceBelowEMA)
tradeActive := false
// Plot EMA
plot(ema, color=color.purple, linewidth=2, title="9 EMA")
9 EMA Strategy with Sequential Flags//@version=5
indicator("9 EMA Strategy with Sequential Flags", overlay=true)
// Input parameters
emaLength = input.int(9, title="EMA Length")
bodySizeMultiplier = input.float(0.5, title="Minimum Body Size as Multiplier of ATR")
atrLength = input.int(14, title="ATR Length")
// Calculations
ema = ta.ema(close, emaLength)
atr = ta.atr(atrLength)
// Candle body calculations
bodySize = math.abs(close - open)
minBodySize = bodySizeMultiplier * atr
// Conditions for buy and sell
buyCondition = close > ema and bodySize >= minBodySize and open < close
sellCondition = close < ema and bodySize >= minBodySize and open > close
// Variable to track the last trade
var float lastTradePrice = na
var string lastTradeType = na
// New buy and sell logic to ensure sequential trades
newBuy = buyCondition and (na(lastTradePrice) or lastTradeType == "SELL")
newSell = sellCondition and (na(lastTradePrice) or lastTradeType == "BUY")
if (newBuy)
lastTradePrice := close
lastTradeType := "BUY"
label.new(bar_index, high, "BUY", style=label.style_label_up, color=color.green, textcolor=color.white)
alert("Buy Signal Triggered at " + str.tostring(close))
if (newSell)
lastTradePrice := close
lastTradeType := "SELL"
label.new(bar_index, low, "SELL", style=label.style_label_down, color=color.red, textcolor=color.white)
alert("Sell Signal Triggered at " + str.tostring(close))
// Plot EMA
plot(ema, color=color.purple, linewidth=2, title="9 EMA")
