Double RSIDouble RSI (DRSI) Indicator
The Double RSI (DRSI) is a technical analysis tool designed to provide traders with enhanced buy and sell signals by identifying uptrend and downtrend thresholds. It refines traditional RSI-based signals by applying a "double calculation" to the Relative Strength Index (RSI), improving precision in detecting trend changes.
Key Concepts Behind the Indicator
1. Double RSI Calculation
The DRSI indicator takes the standard RSI (calculated using the closing price over a specified length) and applies a second RSI calculation to it. This creates a smoother, more refined RSI value, making it more effective at highlighting the general trend of the market.
RSI: Measures the strength of recent price movements, ranging from 0 to 100.
Double RSI (DRSI): Applies the RSI formula to the RSI values themselves, smoothing out fluctuations and generating clearer signals.
How Does the Indicator Work?
The DRSI identifies uptrends and downtrends using two user-defined thresholds:
Uptrend Threshold (Default = 59): A value above this threshold signals a potential shift into an uptrend.
Downtrend Threshold (Default = 52): A value below this threshold signals a potential shift into a downtrend.
Signal Generation
Buy Signal: A crossover occurs when the DRSI value crosses above the Downtrend Threshold, signaling the beginning of an upward movement.
Sell Signal: A crossunder occurs when the DRSI value crosses below the Uptrend Threshold, signaling the beginning of a downward movement.
Customizable Inputs
The indicator offers customizable settings for increased flexibility:
DRSI Length (Default = 13): Determines the lookback period for RSI calculations. A shorter length increases sensitivity, while a longer length smooths the signals.
Uptrend Threshold (Default = 59): Sets the level above which an uptrend is confirmed.
Downtrend Threshold (Default = 52): Sets the level below which a downtrend is confirmed.
Bar Color and Glow Effects: Traders can enable colored candles or glowing DRSI lines for better visual representation.
Why is This Indicator Useful for Traders?
1. Noise Reduction
By applying a second RSI calculation, the DRSI smooths out minor fluctuations and highlights the overall trend.
2. Clear Uptrend and Downtrend Signals
The indicator provides intuitive buy (green arrow) and sell (red arrow) markers, simplifying decision-making.
3. Customizable Thresholds
Traders can adjust the thresholds and length to better suit specific trading strategies or market conditions.
4. Bar Coloring
Bars are color-coded to indicate the trend:
Green (Above Uptrend Threshold): Indicates an uptrend.
Red (Below Downtrend Threshold): Indicates a downtrend.
How the Indicator Appears on the Chart
DRSI Line: A smooth line derived from the double RSI calculation.
Threshold Lines: Two horizontal lines (green for the Uptrend Threshold, red for the Downtrend Threshold) to visualize trend changes.
Colored Candles: Candlesticks dynamically change color based on the trend direction (green for uptrends, red for downtrends).
Buy/Sell Markers:
Buy Signal: A green upward triangle below the bar, marking the start of an uptrend.
Sell Signal: A red downward triangle above the bar, marking the start of a downtrend.
In Summary
The Double RSI (DRSI) indicator is a powerful tool for identifying uptrends and downtrends with:
Smoothed trend detection using double-calculated RSI values.
Clear, actionable buy and sell signals.
Customizable settings to match different trading styles.
By focusing on trend thresholds rather than overbought or oversold levels, the DRSI provides traders with precise, noise-free signals to optimize their trading decisions.
Indicadores e estratégias
Thygoo Countdown TimerThis custom Pine Script indicator displays a real-time countdown timer on your chart, showing the remaining time until the current candle closes based on the active timeframe. The timer is updated dynamically, providing a clear and easy-to-read countdown directly on the chart.
Features:
Real-Time Countdown: The indicator automatically calculates the time remaining for the current candle to close, updating in real-time.
Multiple Timeframes: It works with any active timeframe, including minute-based and multi-minute intervals, such as 3m, 5m, 15m, 1h, etc.
Dynamic Box Position: The countdown is displayed inside a resizable and repositionable box on the chart, placed above the current price action.
Visibility: The box and text are clearly visible, with customizable font sizes for better readability.
No Extra Clutter: The countdown text appears without any unnecessary border lines, keeping the display clean and unobtrusive.
How to Use:
Add this indicator to your chart to monitor the countdown of the current timeframe.
The timer will update automatically, showing the time left (minutes:seconds) until the next bar closes.
Adjust the chart's zoom level to ensure the timer box remains clearly visible in the right-hand section of your chart.
Ideal for:
Traders who want a quick and efficient way to track the time remaining on their current chart timeframe.
Anyone looking to add a countdown timer to their TradingView chart without the clutter of additional indicators.
RSI Divergence - Left Candles Onlyrsi
The **RSI Divergence** indicator in this script is designed to highlight **divergence** between the **Relative Strength Index (RSI)** and **price action** on a chart. Divergence can be a key signal for potential trend reversals or continuation in technical analysis.
### **Key Components of the Indicator:**
1. **RSI Calculation:**
- The **Relative Strength Index (RSI)** is calculated using a typical 14-period length, but the user can customize this input.
- RSI is a momentum oscillator that measures the speed and change of price movements, oscillating between 0 and 100. Values above 70 indicate overbought conditions, and values below 30 indicate oversold conditions.
2. **Divergence Logic:**
- **Bullish Divergence:** Occurs when the price forms a **lower low**, but the RSI forms a **higher low**. This suggests that despite price continuing to drop, momentum (RSI) is strengthening, which may indicate a potential price reversal to the upside.
- **Bearish Divergence:** Occurs when the price forms a **higher high**, but the RSI forms a **lower high**. This indicates that even though price is rising, the momentum (RSI) is weakening, which could signal a price reversal to the downside.
3. **Pivot Identification:**
- The script identifies **pivot points** (local highs and lows) on both price and RSI.
- **Bullish Divergence:** A lower price low with a higher RSI low.
- **Bearish Divergence:** A higher price high with a lower RSI high.
4. **Lookback Periods:**
- **Lookback Left (lookbackLeft):** Defines the number of bars to look back for pivot confirmation. This allows for adjusting the sensitivity of the divergence.
- The **divergence range** is constrained by two parameters:
- **Minimum range (rangeLower):** The minimum number of bars for divergence to be considered.
- **Maximum range (rangeUpper):** The maximum number of bars for divergence to be considered.
5. **Signal Generation and Plotting:**
- When a **bullish divergence** is detected, a **green label** is plotted below the bar where the divergence occurs.
- When a **bearish divergence** is detected, a **red label** is plotted above the bar.
- The script uses **`plotshape()`** to plot these labels on the chart.
6. **Alerts:**
- Alerts are configured for both **bullish** and **bearish divergences** so that you can be notified when a divergence signal occurs.
---
### **How the Indicator Works:**
- The RSI and price action are compared using **pivots**: The script checks whether the price and RSI are forming new highs or lows within the specified **lookback period**.
- If the conditions for divergence (higher/lower RSI pivot vs price pivot) are met, a signal is plotted on the chart.
- The script helps to visually identify potential reversal points and allows users to set alerts for these divergence signals.
---
### **Use Case:**
- This script is useful for traders looking to trade potential trend reversals based on **divergence** between price and RSI.
- **Bullish divergence** can indicate a **buy** opportunity, while **bearish divergence** can suggest a **sell** opportunity.
- The indicator works best in **volatile markets** and when combined with other technical analysis tools for confirmatio
20/50 SMA Cross 200 SMAThis Pine Script code is designed to identify and visualize crossovers of two shorter-term Simple Moving Averages (SMAs), a 20-period SMA and a 50-period SMA, with a longer-term 200-period SMA on a price chart. It also includes alerts for these crossover events. Here's a breakdown:
**Purpose:**
The core idea behind this script is to detect potential trend changes. Crossovers of shorter-term moving averages over a longer-term moving average are often interpreted as bullish signals, while crossovers below are considered bearish.
**Key Components:**
1. **Moving Average Calculation:**
* `sma20 = ta.sma(close, 20)`: Calculates the 20-period SMA of the closing price.
* `sma50 = ta.sma(close, 50)`: Calculates the 50-period SMA of the closing price.
* `sma200 = ta.sma(close, 200)`: Calculates the 200-period SMA of the closing price.
2. **Crossover Detection:**
* `crossUp20 = ta.crossover(sma20, sma200)`: Returns `true` when the 20-period SMA crosses above the 200-period SMA.
* `crossDown20 = ta.crossunder(sma20, sma200)`: Returns `true` when the 20-period SMA crosses below the 200-period SMA.
* Similar logic applies for `crossUp50` and `crossDown50` with the 50-period SMA.
3. **Recent Crossover Tracking (Crucial Improvement):**
* `lookback = 7`: Defines a lookback period of 7 bars.
* `var bool hasCrossedUp20 = false`, etc.: Declares `var` (persistent) boolean variables to track if a crossover has occurred *within* the last 7 bars. This is the most important correction from previous versions.
* The logic using `ta.barssince()` is the key:
* If a crossover happens (`crossUp20` is true), the corresponding `hasCrossedUp20` is set to `true`.
* If no crossover happens on the current bar, it checks if a crossover happened within the last 7 bars using `ta.barssince(crossUp20) <= lookback`. If so, it keeps `hasCrossedUp20` as `true`. After 7 bars, it becomes `false`.
4. **Plotting Crossovers:**
* `plotshape(...)`: Plots circles on the chart to visually mark the crossovers.
* Green circles below the bars for bullish crossovers (20 and 50).
* Red circles above the bars for bearish crossovers (20 and 50).
* Different shades of green/red (green/lime, red/maroon) distinguish between 20 and 50 SMA crossovers.
5. **Plotting Moving Averages (Optional but Helpful):**
* `plot(sma20, color=color.blue, linewidth=1)`: Plots the 20-period SMA in blue.
* Similar logic for the 50-period SMA (orange) and 200-period SMA (gray).
6. **Alerts:**
* `alertcondition(...)`: Triggers alerts when crossovers occur. This is essential for real-time trading signals.
**How it Works (in Simple Terms):**
The script continuously calculates the 20, 50, and 200 SMAs. It then monitors for instances where the 20 or 50 SMA crosses the 200 SMA. When such a crossover happens, a colored circle is plotted on the chart, and an alert is triggered. The key improvement is that it remembers if a crossover occurred in the last 7 bars and continues to display the circle during that period.
**Use Case:**
Traders use this type of indicator to identify potential entry and exit points in the market. A bullish crossover (shorter SMA crossing above the longer SMA) might be a signal to buy, while a bearish crossover might be a signal to sell.
**Key Improvements over Previous Versions:**
* **Correct Lookback Implementation:** The use of `ta.barssince()` and `var` variables is the correct and efficient way to check for crossovers within a lookback period. This fixes the major flaw in earlier versions.
* **Clear Visualizations:** The use of `plotshape` with distinct colors makes it easy to distinguish between 20 and 50 SMA crossovers.
* **Alerts:** The inclusion of alerts makes the script much more practical for real-time trading.
This improved version provides a robust and useful tool for identifying and tracking SMA crossovers.
FIR Low Pass Filter Suite (FIR)The FIR Low Pass Filter Suite is an advanced signal processing indicator that applies finite impulse response (FIR) filtering techniques to price data. At its core, the indicator uses windowed-sinc filtering, which provides optimal frequency response characteristics for separating trend from noise in financial data.
The indicator offers multiple window functions including Kaiser, Kaiser-Bessel Derived (KBD), Hann, Hamming, Blackman, Triangular, and Lanczos. Each window type provides different trade-offs between main-lobe width and side-lobe attenuation, allowing users to fine-tune the frequency response characteristics of the filter. The Kaiser and KBD windows provide additional control through an alpha parameter that adjusts the shape of the window function.
A key feature is the ability to operate in either linear or logarithmic space. Logarithmic filtering can be particularly appropriate for financial data due to the multiplicative nature of price movements. The indicator includes an envelope system that can adaptively calculate bands around the filtered price using either arithmetic or geometric deviation, with separate controls for upper and lower bands to account for the asymmetric nature of market movements.
The implementation handles edge effects through proper initialization and offers both centered and forward-only filtering modes. Centered mode provides zero phase distortion but introduces lag, while forward-only mode operates causally with no lag but introduces some phase distortion. All calculations are performed using vectorized operations for efficiency, with carefully designed state management to handle the filter's warm-up period.
Visual feedback is provided through customizable color gradients that can reflect the current trend direction, with optional glow effects and background fills to enhance visibility. The indicator maintains high numerical precision throughout its calculations while providing smooth, artifact-free output suitable for both analysis and visualization.
True Amplitude Envelopes (TAE)The True Envelopes indicator is an adaptation of the True Amplitude Envelope (TAE) method, based on the research paper " Improved Estimation of the Amplitude Envelope of Time Domain Signals Using True Envelope Cepstral Smoothing " by Caetano and Rodet. This indicator aims to create an asymmetric price envelope with strong predictive power, closely following the methodology outlined in the paper.
Due to the inherent limitations of Pine Script, the indicator utilizes a Kernel Density Estimator (KDE) in place of the original Cepstral Smoothing technique described in the paper. While this approach was chosen out of necessity rather than superiority, the resulting method is designed to be as effective as possible within the constraints of the Pine environment.
This indicator is ideal for traders seeking an advanced tool to analyze price dynamics, offering insights into potential price movements while working within the practical constraints of Pine Script. Whether used in dynamic mode or with a static setting, the True Envelopes indicator helps in identifying key support and resistance levels, making it a valuable asset in any trading strategy.
Key Features:
Dynamic Mode: The indicator dynamically estimates the fundamental frequency of the price, optimizing the envelope generation process in real-time to capture critical price movements.
High-Pass Filtering: Uses a high-pass filtered signal to identify and smoothly interpolate price peaks, ensuring that the envelope accurately reflects significant price changes.
Kernel Density Estimation: Although implemented as a workaround, the KDE technique allows for flexible and adaptive smoothing of the envelope, aimed at achieving results comparable to the more sophisticated methods described in the original research.
Symmetric and Asymmetric Envelopes: Provides options to select between symmetric and asymmetric envelopes, accommodating various trading strategies and market conditions.
Smoothness Control: Features adjustable smoothness settings, enabling users to balance between responsiveness and the overall smoothness of the envelopes.
The True Envelopes indicator comes with a variety of input settings that allow traders to customize the behavior of the envelopes to match their specific trading needs and market conditions. Understanding each of these settings is crucial for optimizing the indicator's performance.
Main Settings
Source: This is the data series on which the indicator is applied, typically the closing price (close). You can select other price data like open, high, low, or a custom series to base the envelope calculations.
History: This setting determines how much historical data the indicator should consider when calculating the envelopes. A value of 0 will make the indicator process all available data, while a higher value restricts it to the most recent n bars. This can be useful for reducing the computational load or focusing the analysis on recent market behavior.
Iterations: This parameter controls the number of iterations used in the envelope generation algorithm. More iterations will typically result in a smoother envelope, but can also increase computation time. The optimal number of iterations depends on the desired balance between smoothness and responsiveness.
Kernel Style: The smoothing kernel used in the Kernel Density Estimator (KDE). Available options include Sinc, Gaussian, Epanechnikov, Logistic, and Triangular. Each kernel has different properties, affecting how the smoothing is applied. For example, Gaussian provides a smooth, bell-shaped curve, while Epanechnikov is more efficient computationally with a parabolic shape.
Envelope Style: This setting determines whether the envelope should be Static or Dynamic. The Static mode applies a fixed period for the envelope, while the Dynamic mode automatically adjusts the period based on the fundamental frequency of the price data. Dynamic mode is typically more responsive to changing market conditions.
High Q: This option controls the quality factor (Q) of the high-pass filter. Enabling this will increase the Q factor, leading to a sharper cutoff and more precise isolation of high-frequency components, which can help in better identifying significant price peaks.
Symmetric: This setting allows you to choose between symmetric and asymmetric envelopes. Symmetric envelopes maintain an equal distance from the central price line on both sides, while asymmetric envelopes can adjust differently above and below the price line, which might better capture market conditions where upside and downside volatility are not equal.
Smooth Envelopes: When enabled, this setting applies additional smoothing to the envelopes. While this can reduce noise and make the envelopes more visually appealing, it may also decrease their responsiveness to sudden market changes.
Dynamic Settings
Extra Detrend: This setting toggles an additional high-pass filter that can be applied when using a long filter period. The purpose is to further detrend the data, ensuring that the envelope focuses solely on the most recent price oscillations.
Filter Period Multiplier: This multiplier adjusts the period of the high-pass filter dynamically based on the detected fundamental frequency. Increasing this multiplier will lengthen the period, making the filter less sensitive to short-term price fluctuations.
Filter Period (Min) and Filter Period (Max): These settings define the minimum and maximum bounds for the high-pass filter period. They ensure that the filter period stays within a reasonable range, preventing it from becoming too short (and overly sensitive) or too long (and too sluggish).
Envelope Period Multiplier: Similar to the filter period multiplier, this adjusts the period for the envelope generation. It scales the period dynamically to match the detected price cycles, allowing for more precise envelope adjustments.
Envelope Period (Min) and Envelope Period (Max): These settings establish the minimum and maximum bounds for the envelope period, ensuring the envelopes remain adaptive without becoming too reactive or too slow.
Static Settings
Filter Period: In static mode, this setting determines the fixed period for the high-pass filter. A shorter period will make the filter more responsive to price changes, while a longer period will smooth out more of the price data.
Envelope Period: This setting specifies the fixed period used for generating the envelopes in static mode. It directly influences how tightly or loosely the envelopes follow the price action.
TAE Smoothing: This controls the degree of smoothing applied during the TAE process in static mode. Higher smoothing values result in more gradual envelope curves, which can be useful in reducing noise but may also delay the envelope’s response to rapid price movements.
Visual Settings
Top Band Color: This setting allows you to choose the color for the upper band of the envelope. This band represents the resistance level in the price action.
Bottom Band Color: Similar to the top band color, this setting controls the color of the lower band, which represents the support level.
Center Line Color: This is the color of the central price line, often referred to as the carrier. It represents the detrended price around which the envelopes are constructed.
Line Width: This determines the thickness of the plotted lines for the top band, bottom band, and center line. Thicker lines can make the envelopes more visible, especially when overlaid on price data.
Fill Alpha: This controls the transparency level of the shaded area between the top and bottom bands. A lower alpha value will make the fill more transparent, while a higher value will make it more opaque, helping to highlight the envelope more clearly.
The envelopes generated by the True Envelopes indicator are designed to provide a more precise and responsive representation of price action compared to traditional methods like Bollinger Bands or Keltner Channels. The core idea behind this indicator is to create a price envelope that smoothly interpolates the significant peaks in price action, offering a more accurate depiction of support and resistance levels.
One of the critical aspects of this approach is the use of a high-pass filtered signal to identify these peaks. The high-pass filter serves as an effective method of detrending the price data, isolating the rapid fluctuations in price that are often lost in standard trend-following indicators. By filtering out the lower frequency components (i.e., the trend), the high-pass filter reveals the underlying oscillations in the price, which correspond to significant peaks and troughs. These oscillations are crucial for accurately constructing the envelope, as they represent the most responsive elements of the price movement.
The algorithm works by first applying the high-pass filter to the source price data, effectively detrending the series and isolating the high-frequency price changes. This filtered signal is then used to estimate the fundamental frequency of the price movement, which is essential for dynamically adjusting the envelope to current market conditions. By focusing on the peaks identified in the high-pass filtered signal, the algorithm generates an envelope that is both smooth and adaptive, closely following the most significant price changes without overfitting to transient noise.
Compared to traditional envelopes and bands, such as Bollinger Bands and Keltner Channels, the True Envelopes indicator offers several advantages. Bollinger Bands, which are based on standard deviations, and Keltner Channels, which use the average true range (ATR), both tend to react to price volatility but do not necessarily follow the peaks and troughs of the price with precision. As a result, these traditional methods can sometimes lag behind or fail to capture sudden shifts in price momentum, leading to either false signals or missed opportunities.
In contrast, the True Envelopes indicator, by using a high-pass filtered signal and a dynamic period estimation, adapts more quickly to changes in price behavior. The envelopes generated by this method are less prone to the lag that often affects standard deviation or ATR-based bands, and they provide a more accurate representation of the price's immediate oscillations. This can result in better predictive power and more reliable identification of support and resistance levels, making the True Envelopes indicator a valuable tool for traders looking for a more responsive and precise approach to market analysis.
In conclusion, the True Envelopes indicator is a powerful tool that blends advanced theoretical concepts with practical implementation, offering traders a precise and responsive way to analyze price dynamics. By adapting the True Amplitude Envelope (TAE) method through the use of a Kernel Density Estimator (KDE) and high-pass filtering, this indicator effectively captures the most significant price movements, providing a more accurate depiction of support and resistance levels compared to traditional methods like Bollinger Bands and Keltner Channels. The flexible settings allow for extensive customization, ensuring the indicator can be tailored to suit various trading strategies and market conditions.
3_SMA_Strategy_V-Singhal by ParthibIndicator Name: 3_SMA_Strategy_V-Singhal by Parthib
Description:
The 3_SMA_Strategy_V-Singhal by Parthib is a dynamic trend-following strategy that combines three key simple moving averages (SMA) — SMA 20, SMA 50, and SMA 200 — to generate buy and sell signals. This strategy uses these SMAs to capture and follow market trends, helping traders identify optimal entry (buy) and exit (sell) points. Additionally, the strategy highlights the closing price (CP), which plays a critical role in confirming buy and sell signals.
The strategy also features a Second Buy Signal triggered if the price falls more than 10% after an initial buy signal, providing a re-entry opportunity with a different visual highlight for the second buy signal.
Features:
Three Simple Moving Averages (SMA):
SMA 20: Short-term moving average reflecting immediate market trends.
SMA 50: Medium-term moving average showing the prevailing trend.
SMA 200: Long-term moving average that indicates the overall market trend.
Buy Signal (B1):
Triggered when:
SMA 200 > SMA 50 > SMA 20, indicating a bullish market structure.
The closing price is positioned below all three SMAs, confirming a potential upward reversal.
A green label appears at the low of the bar with the text B1-Price, indicating the price at which the buy signal is generated.
Second Buy Signal (B2):
Triggered if the price falls more than 10% after the first buy signal, providing an opportunity to re-enter the market at a potentially better price.
A blue label appears at the low of the bar with the text B2-Price, showing the price at which the second buy opportunity arises.
Sell Signal (S):
Triggered when:
SMA 20 > SMA 50 > SMA 200, indicating a bearish trend.
The closing price (CP) is positioned above all three SMAs, confirming a potential downward movement.
A red label appears at the high of the bar with the text S-Price, showing the price at which the sell signal is triggered.
How It Works:
Buy Conditions:
SMA 200 > SMA 50 > SMA 20: Indicates a bullish market where the long-term trend (SMA 200) is above the medium-term (SMA 50), and the medium-term trend is above the short-term (SMA 20).
Closing price below all three SMAs: Confirms that the price is in a favorable position for a potential upward reversal.
Sell Conditions:
SMA 20 > SMA 50 > SMA 200: This setup indicates a bearish trend.
Closing price above all three SMAs: Confirms that the price is in a favorable position for a potential downward movement.
Second Buy Signal (B2): If the price falls more than 10% after the first buy signal, the strategy triggers a second buy opportunity (B2) at a potentially better price. This helps traders take advantage of pullbacks or corrections after an initial favorable entry.
Labeling System:
B1-Price: The first buy signal label, appearing when the market is bullish and the closing price is below all three SMAs.
B2-Price: The second buy signal label, triggered if the price falls more than 10% after the initial buy signal.
S-Price: The sell signal label, appearing when the market turns bearish and the closing price is above all three SMAs.
How to Use:
Add the Indicator: Add "3_SMA_Strategy_V-Singhal by Parthib" to your chart on TradingView.
Interpret Buy Signals (B1): Look for green labels with the text "B1-Price" when the closing price (CP) is below all three SMAs and the trend is bullish.
Interpret Second Buy Signals (B2): If the price falls more than 10% after the first buy, look for blue labels with "B2-Price" and a re-entry opportunity.
Interpret Sell Signals (S): Look for red labels with the text "S-Price" when the market turns bearish, and the closing price (CP) is above all three SMAs.
Conclusion:
The 3_SMA_Strategy_V-Singhal by Parthib is an efficient and simple trend-following tool for traders looking to make informed buy and sell decisions. By combining the power of three SMAs and the closing price (CP) confirmation, this strategy helps traders to buy when the market shows a strong bullish setup and sell when the trend turns bearish. Additionally, the second buy signal feature ensures that traders don’t miss out on re-entry opportunities after price corrections, giving them a chance to re-enter the market at a favorable price.
Lanczos CandlesThis indicator reconstructs price action using Lanczos resampling, incorporating lower timeframe data to create a more detailed representation of market movements. Traditional candle aggregation on higher timeframes tends to lose some price action detail - this indicator attempts to preserve more of that information through mathematical resampling.
The indicator samples price data from a lower timeframe and uses the Lanczos algorithm, a mathematical method commonly used in signal processing and image resampling, to reconstruct the price series at the chart's timeframe. The process helps maintain price movements that might otherwise be smoothed out in regular candle aggregation.
The main settings allow you to select the source timeframe for sampling, adjust the Lanczos filter width to balance smoothness versus detail preservation, and optionally enable Heikin Ashi calculation. The filter width parameter (default: 3) affects how aggressive the smoothing is - higher values produce smoother results while lower values retain more of the original variation.
This approach can be useful for technical analysis when you want to work with higher timeframes while maintaining awareness of significant price movements that occurred within those candles. The optional Heikin Ashi mode can help visualize trends in the resampled data.
The indicator works best when there's a clear ratio between your chart timeframe and the source timeframe (for example, using 1-minute data to build 5-minute candles).
IPO Lifecycle Sell Strategy [JARUTIR]IPO Lifecycle Sell Strategy with Dynamic Buy Date and Multiple Sell Rules
This custom TradingView script is designed for traders looking to capitalize on dynamic strategies for IPOs and growth stocks, by implementing several sell rules based on price action and technical indicators. It provides a set of sell rules that are applied dynamically depending on the stock's lifecycle and price action, allowing users to lock in profits and minimize drawdowns based on key technical thresholds.
The four sell strategies incorporated into this script are inspired by the book "The Lifecycle Trade", a resource that focuses on capturing profits while managing risk in different phases of a stock's lifecycle, from IPO to high-growth stages.
Key Features:
Buy Price and Buy Date: You can either manually input your buy price and date or let the script automatically detect the buy date based on the specified buy price.
Multiple Sell Strategies: Choose from 4 predefined sell strategies:
Ascender Rule : Captures strong momentum from IPO stocks by selling portions at specific price levels or technical conditions.
Midterm Rule : Focuses on holding for longer periods, with defensive sell signals triggered when the stock deviates significantly from peak price or key moving averages.
40 Week Rule : Designed for long-term holds, this rule triggers a sell when the stock closes below the 40-week moving average.
Everest Rule : Aggressive strategy for selling into strength based on parabolic moves or gap downs, ideal for high momentum stocks.
Interactive Features:
Horizontal Green Line showing the buy price level from the buy date.
Visual Sell Signals appear only after the buy date to ensure that your analysis is relevant to the stock lifecycle.
Customizable settings, allowing you to choose your preferred sell rule strategy and automate buy date detection.
This script is perfect for traders using a strategic, systematic approach to IPOs and high-growth stocks, whether you're looking for quick exits during momentum phases or holding for longer-term growth.
Usage:
Input your Buy Price and Buy Date, or allow the script to automate the buy date detection.
Select a Sell Rule strategy based on your risk profile and trading style.
View visual signals for selling when specific conditions are met.
Frequently Asked Questions (FAQs):
Q1: How do I input my Buy Price and Buy Date?
The script allows you to either manually input the Buy Price and Buy Date or use the automated detection. If you choose automated detection, the script will automatically assign the buy date when the price crosses above your set Buy Price.
Q2: What is the purpose of the "Sell Rules"?
The script offers four sell strategies to help manage different types of stocks in varying phases of their lifecycle:
Ascender Rule: Targets IPO stocks showing positive momentum.
Midterm Rule: A defensive strategy for stocks in a steady uptrend.
40 Week Rule: Long-term hold strategy designed to ride stocks through extended growth.
Everest Rule: Aggressive strategy to capture profits during parabolic price moves.
Q3: What is the significance of the Green Line at Buy Price?
The Green Line represents your entry point (Buy Price) on the chart. It will appear from the buy date onwards, helping you track the performance of your stock relative to your entry.
Q4: Can I customize the Sell Strategy?
Yes! You can choose from the available Sell Rules (Ascender Rule, Midterm Rule, 40 Week Rule, Everest Rule) via an input option in the script. Each strategy has its own unique triggers based on price action, moving averages, and time-based conditions.
Q5: Does this script work for stocks and crypto?
Yes, this script is designed for both stocks and cryptocurrencies. It works on any asset where price data and timeframes are available.
Q6: How do the Weekly Moving Averages (WSMA) work in this strategy?
The script uses weekly moving averages (WSMA) to track longer-term trends. These are essential for some of the sell rules, such as the Midterm Rule and 40 Week Rule, which rely on the stock's movement relative to the 40-week moving average.
Q7: Will the script plot a Sell Signal immediately after the Buy Date?
No, sell signals will only be plotted after the Buy Date. This ensures that the sell strategy is relevant to your actual holding period and avoids premature triggers.
Q8: How do I interpret the Sell Signal?
The script will plot a Red Sell Signal above the bar when the sell conditions are met, based on the selected strategy. This indicates that it may be a good time to exit the position according to your chosen rule.
Q9: Can I use this strategy on different timeframes?
Yes, you can apply the script to any timeframe. However, some sell strategies, like the Midterm Rule and 40 Week Rule, are designed to work best with weekly data, so it's recommended to use these strategies with longer timeframes.
Q10: Does this script have any alerts?
Yes! The script supports alert conditions that will notify you when the sell conditions are met according to your selected rule. You can set up alerts to stay informed without needing to watch the chart constantly.
Q11: What if I want to disable some of the sell rules?
You can select your preferred sell rule using the "Select Sell Rule" dropdown. If you don’t want to use a particular rule, simply choose a different strategy or leave it inactive.
------------------------------
Disclaimer:
This strategy is intended for educational purposes only. It should not be considered financial advice. Always perform your own research and consult with a professional before making any trading decisions. Trading involves significant risk, and you should never trade with money you cannot afford to lose.
Polyphase MACD (PMACD)The Polyphase MACD (PMACD) uses polyphase decimation to create a continuous estimate of higher timeframe MACD behavior. The number of phases represents the timeframe multiplier - for example, 3 phases approximates a 3x higher timeframe.
Traditional higher timeframe MACD indicators update only when each higher timeframe bar completes, creating stepped signals that can miss intermediate price action. The PMACD addresses this by maintaining multiple phase-shifted MACD calculations and combining them with appropriate anti-aliasing filters. This approach eliminates the discrete jumps typically seen in higher timeframe indicators, though the resulting signal may sometimes deviate from the true higher timeframe values due to its estimative nature.
The indicator processes price data through parallel phase calculations, each analyzing a different time-offset subset of the data. These phases are filtered and combined to prevent aliasing artifacts that occur in simple timeframe conversions. The result is a smooth, continuous signal that begins providing meaningful values immediately, without requiring a warm-up period of higher timeframe bars.
The PMACD maintains the standard MACD components - the MACD line (fast MA - slow MA), signal line, and histogram - while providing a more continuous view of higher timeframe momentum. Users can select between EMA and SMA calculations for both the oscillator and signal components, with all calculations benefiting from the same polyphase processing technique.
Weekend BoxesWeekend Box Indicator
This indicator highlights weekend trading periods by drawing color-coded boxes from Saturday to Sunday. Each box includes a percentage label showing the price change during the weekend period. Green boxes indicate positive moves, while red boxes show negative moves. Use this to easily spot and analyze weekend volatility patterns.
set for UTC +5
Polyphase Stochastic RSI (PSRSI)The Polyphase Stochastic RSI (PSRSI) provides a continuous estimate of higher timeframe Stochastic RSI behavior by using polyphase decimation. The number of phases represents the timeframe multiplier - for example, 3 phases approximates a 3x higher timeframe.
While traditional higher timeframe indicators only update at the completion of each higher timeframe bar, the PSRSI creates a continuous signal by maintaining multiple phase-shifted calculations and combining them with appropriate anti-aliasing filters. This approach eliminates the gaps and discontinuities typically seen in higher timeframe indicators, though the resulting signal may sometimes deviate from the true higher timeframe values due to its estimative nature.
The indicator processes data through parallel phase calculations, each handling a different subset of price data offset in time. These phases are then filtered and combined to prevent aliasing artifacts that occur in simple timeframe conversions. The result is a smooth, continuous signal that starts providing meaningful values immediately, without requiring a warm-up period of higher timeframe bars.
Users can choose between RSI and Stochastic RSI modes, with both benefiting from the same polyphase processing technique. The indicator maintains the standard interpretation of overbought and oversold conditions while providing a more continuous view of higher timeframe momentum.
MCP Stop Strategy [JARUTIR]The MCP Stop Strategy is a trading tool designed to help traders lock in profits and manage risks. It is based on the concept of setting a MCP (Mental Capacity Preservation) Stop explained in the book "The Lifecycle Trade". I call it Maximum Controllable Profit Stop which helps protect profits once a stock or asset reaches a new peak. The MCP Stop is dynamically calculated based on the Buy Price and the All Time High Price (Peak Price), and is adjusted using a customizable percentage (MCP%) to retain a portion of the gains from the peak price during a drawdown.
Key Features :
MCP Stop Calculation: The script calculates the MCP Stop as:
MCP Stop = Buy Price + (Peak Price - Buy Price) x MCP%
This helps you protect a portion of your gains (defined by MCP%) as the price moves in your favor.
Flexible Buy Date Option:
You can either manually input a Buy Date or let the script automatically detect the Buy Date when the price first meets or exceeds the user-defined Buy Price.
After the Buy Date, the MCP Stop, Buy Price, and Peak Price are plotted on the chart for easy visualization.
Customizable Parameters:
Buy Price: The price at which the asset was bought.
MCP Percentage: The percentage of profit from the peak that you want to retain in case of a drawdown.
Lookback Length: The number of bars to consider when calculating the Peak Price (All Time High).
How to Use the Script :
Set the Buy Price: Enter the price at which you bought the asset.
Set the MCP%: Enter the percentage of profits you want to protect from the peak. For example, if you want to retain 10% of the gain from the peak, set this to 10.
Choose the Buy Date Method:
Automated Buy Date: The script will automatically detect the first bar where the price meets or exceeds the Buy Price.
Manual Buy Date: If you prefer to specify a particular Buy Date, input the desired date and time.
View the MCP Stop and Peak Price: After the Buy Date (either manually or automatically detected), the MCP Stop, Buy Price, and Peak Price will be plotted on the chart.
Monitor the MCP Stop Trigger: The script will alert you when the price falls below the MCP Stop, indicating a potential exit point to protect profits.
Frequently Asked Questions (FAQs):
1. What is the MCP Stop?
The MCP Stop is a dynamic stop-loss level that adjusts based on your Buy Price and the All Time High Price (Peak Price). It protects a portion of your gains from the peak, which is defined by the MCP%. For example, if you set the MCP% to 10%, the script will retain 10% of the gains from the peak and use this as a stop-loss.
2. How does the Buy Date work?
The Buy Date is the date when you entered the position:
If you choose Automated Buy Date, the script will automatically set the Buy Date to the first bar when the price meets or exceeds the Buy Price.
If you choose Manual Buy Date, you can specify a particular date and time when you want the strategy to start calculating and plotting the MCP Stop and Peak Price.
3. What happens if the price falls below the MCP Stop?
If the price drops below the MCP Stop, the script will mark this as a potential exit point, helping you protect profits. A visual alert (MCP STOP) will be shown on the chart when the price reaches or falls below the MCP Stop.
4. Can I adjust the Lookback Length for Peak Price?
Yes, you can customize the Lookback Length (the number of bars the script considers when calculating the Peak Price) by entering a value in the input field. By default, it is set to 1000 bars, which represents a few months of historical data, but you can increase or decrease this based on your trading strategy.
5. Why would I want to use the automated Buy Date?
The Automated Buy Date is useful for traders who want the script to automatically track the Buy Date when the price first reaches or exceeds the Buy Price. This is helpful when you're unsure of the exact entry date but know the price at which you bought the asset. It simplifies the process by eliminating the need for manual input.
6. Can I use this strategy for long and short positions?
The current version of this script is designed for long positions, where you buy an asset and want to protect your profits as the price increases. If you're interested in applying it to short positions, you would need to adjust the logic accordingly (e.g., tracking the lowest price instead of the peak price).
7. Can I modify the script to fit my trading strategy?
Yes, this script is highly customizable. You can adjust parameters such as Buy Price, MCP%, and Lookback Length to suit your specific trading style. You can also tweak the visual appearance of the plotted lines and alerts.
Disclaimer:
This strategy is intended for educational purposes only. It should not be considered financial advice. Always perform your own research and consult with a professional before making any trading decisions. Trading involves significant risk, and you should never trade with money you cannot afford to lose.
TradingCharts SCTR [Bginvestor]This indicator is replicating Tradingcharts, SCTR plot. If you know, you know.
Brief description: The StockCharts Technical Rank (SCTR), conceived by technical analyst John Murphy, emerges as a pivotal tool in evaluating a stock’s technical prowess. This numerical system, colloquially known as “scooter,” gauges a stock’s strength within various groups, employing six key technical indicators across different time frames.
How to use it:
Long-term indicators (30% weight each)
-Percent above/below the 200-day exponential moving average (EMA)
-125-day rate-of-change (ROC)
Medium-term indicators (15% weight each)
-percent above/below 50-day EMA
-20-day rate-of-change
Short-term indicators (5% weight each)
-Three-day slope of percentage price oscillator histogram divided by three
-Relative strength index
How to use SCTR:
Investors select a specific group for analysis, and the SCTR assigns rankings within that group. A score of 99.99 denotes robust technical performance, while zero signals pronounced underperformance. Traders leverage this data for strategic decision-making, identifying stocks with increasing SCTR for potential buying or spotting weak stocks for potential shorting.
Credit: I've made some modifications, but credit goes to GodziBear for back engineering the averaging / scaling of the equations.
Note: Not a perfect match to TradingCharts, but very, very close.
Buying and Selling Volume Pressure S/RThis custom indicator aims to visualize underlying market pressure by cumulatively analyzing where trade volume occurs relative to each candle's price range. By separating total volume into "buying" (when price closes near the high of the bar) and "selling" (when price closes near the low of the bar), the indicator identifies shifts in dominance between buyers and sellers over a defined lookback period.
When cumulative buying volume surpasses cumulative selling volume (a "bullish cross"), it suggests that buyers are gaining control. Conversely, when cumulative selling volume exceeds cumulative buying volume (a "bearish cross"), it indicates that sellers are taking the upper hand.
Based on these crossovers, the indicator derives dynamic Support and Resistance lines. After a bullish cross, it continuously tracks and updates the lowest low that occurs while the trend is bullish, forming a support zone. Similarly, after a bearish cross, it updates the highest high that appears during the bearish trend, forming a resistance zone.
A Mid Line is then calculated as the average of the current dynamic support and resistance levels, providing a central reference point. Around this Mid Line, the script constructs an upper and lower channel based on standard deviation, offering a sense of volatility or "divergence" from the mean level.
Finally, the indicator provides simple buy and sell signals: a buy signal is triggered when the price closes back above the Mid Line, suggesting a potential shift toward bullish conditions, while a sell signal appears when the price closes below the Mid Line, hinting at a possible bearish move.
In summary, this indicator blends volume-based market pressure analysis with adaptive support and resistance detection and overlays them onto the chart. It helps traders quickly gauge who controls the market (buyers or sellers), identify dynamic levels of support and resistance, and receive alerts on potential trend changes—simplifying decision-making in rapidly evolving market conditions.
Important Notice:
Trading financial markets involves significant risk and may not be suitable for all investors. The use of technical indicators like this one does not guarantee profitable results. This indicator should not be used as a standalone analysis tool. It is essential to combine it with other forms of analysis, such as fundamental analysis, risk management strategies, and awareness of current market conditions. Always conduct thorough research or consult with a qualified financial advisor before making trading decisions. Past performance is not indicative of future results.
Disclaimer:
Trading financial instruments involves substantial risk and may not be suitable for all investors. Past performance is not indicative of future results. This indicator is provided for informational and educational purposes only and should not be considered investment advice. Always conduct your own research and consult with a licensed financial professional before making any trading decisions.
Note: The effectiveness of any technical indicator can vary based on market conditions and individual trading styles. It's crucial to test indicators thoroughly using historical data and possibly paper trading before applying them in live trading scenarios.
RSI and Bollinger Bands Screener [deepakks444]Indicator Overview
The indicator is designed to help traders identify potential long signals by combining the Relative Strength Index (RSI) and Bollinger Bands across multiple timeframes. This combination allows traders to leverage the strengths of both indicators to make more informed trading decisions.
Understanding RSI
What is RSI?
The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. Developed by J. Welles Wilder Jr. for stocks and forex trading, the RSI is primarily used to identify overbought or oversold conditions in an asset.
How RSI Works:
Calculation: The RSI is calculated using the average gains and losses over a specified period, typically 14 periods.
Range: The RSI oscillates between 0 and 100.
Interpretation:
Key Features of RSI:
Momentum Indicator: RSI helps identify the momentum of price movements.
Divergences: RSI can show divergences, where the price makes a higher high, but the RSI makes a lower high, indicating potential reversals.
Trend Identification: RSI can also help identify trends. In an uptrend, the RSI tends to stay above 50, and in a downtrend, it tends to stay below 50.
Understanding Bollinger Bands
What is Bollinger Bands?
Bollinger Bands are a type of trading band or envelope plotted two standard deviations (positively and negatively) away from a simple moving average (SMA) of a price. Developed by financial analyst John Bollinger, Bollinger Bands consist of three lines:
Upper Band: SMA + (Standard Deviation × Multiplier)
Middle Band (Basis): SMA
Lower Band: SMA - (Standard Deviation × Multiplier)
How Bollinger Bands Work:
Volatility Measure: Bollinger Bands measure the volatility of the market. When the bands are wide, it indicates high volatility, and when the bands are narrow, it indicates low volatility.
Price Movement: The price tends to revert to the mean (middle band) after touching the upper or lower bands.
Support and Resistance: The upper and lower bands can act as dynamic support and resistance levels.
Key Features of Bollinger Bands:
Volatility Indicator: Bollinger Bands help traders understand the volatility of the market.
Mean Reversion: Prices tend to revert to the mean (middle band) after touching the bands.
Squeeze: A Bollinger Band Squeeze occurs when the bands narrow significantly, indicating low volatility and a potential breakout.
Combining RSI and Bollinger Bands
Strategy Overview:
The strategy aims to identify potential long signals by combining RSI and Bollinger Bands across multiple timeframes. The key conditions are:
RSI Crossing Above 60: The RSI should cross above 60 on the 15-minute timeframe.
RSI Above 60 on Higher Timeframes: The RSI should already be above 60 on the hourly and daily timeframes.
Price Above 20MA or Walking on Upper Bollinger Band: The price should be above the 20-period moving average of the Bollinger Bands or walking on the upper Bollinger Band.
Strategy Details:
RSI Calculation:
Calculate the RSI for the 15-minute, 1-hour, and 1-day timeframes.
Check if the RSI crosses above 60 on the 15-minute timeframe.
Ensure the RSI is above 60 on the 1-hour and 1-day timeframes.
Bollinger Bands Calculation:
Calculate the Bollinger Bands using a 20-period moving average and 2 standard deviations.
Check if the price is above the 20-period moving average or walking on the upper Bollinger Band.
Entry and Exit Signals:
Long Signal: When all the above conditions are met, consider a long entry.
Exit: Exit the trade when the price crosses below the 20-period moving average or the stop-loss is hit.
Example Usage
Setup:
Add the indicator to your TradingView chart.
Configure the inputs as per your requirements.
Monitoring:
Look for the long signal on the chart.
Ensure that the RSI is above 60 on the 15-minute, 1-hour, and 1-day timeframes.
Check that the price is above the 20-period moving average or walking on the upper Bollinger Band.
Trading:
Enter a long position when the criteria are met.
Set a stop-loss below the low of the recent 15-minute candle or based on your risk management rules.
Monitor the trade and exit when the RSI returns below 60 on any of the timeframes or when the price crosses below the 20-period moving average.
House Rules Compliance
No Financial Advice: This strategy is for educational purposes only and should not be construed as financial advice.
Risk Management: Always use proper risk management techniques, including stop-loss orders and position sizing.
Past Performance: Past performance is not indicative of future results. Always conduct your own research and analysis.
TradingView Guidelines: Ensure that any shared scripts or strategies comply with TradingView's terms of service and community guidelines.
Conclusion
This strategy combines RSI and Bollinger Bands across multiple timeframes to identify potential long signals. By ensuring that the RSI is above 60 on higher timeframes and that the price is above the 20-period moving average or walking on the upper Bollinger Band, traders can make more informed decisions. Always remember to conduct thorough research and use proper risk management techniques.
Sunil's Three 3 Inside Up Down IndicatorThree candlestick Pattern Bullish Reversal- Three Inside Up => Formed by a Bullish Harami pattern followed by a confirmation candle closing above the previous candle.
Three candlestick Pattern Bearish Reversal- Three Inside Down => Formed by a Bearish Harami pattern followed by a confirmation candle closing below the previous candle.
Auto Swing TPAutomatic TP generator from recent swing highs and swing lows
Multiple long & short TPs from current price are displayed.
Results will differ by timeframe.
The main parameter is the "cell size" which is the least significant price move for the current asset. The default value of 0.4% is optimized for crypto. You may want to use less for less volatile asset classes.
How it works
We divide price into cells of a certain percent sizes, mainly because this makes the computation a lot easier.
We note in which bar every price cell was last visited. We take the distance to the current bar and then the logarithm of that to a certain base (the "time dimension"). Using a logarithm gives a nice balance of near-term and long-term targets. We call that logarithmic value the "level" of that price cell.
If a price cell has a significantly higher or lower level (at least by +2 or -2) than the cell above or below, this is considered a possible TP area.
Finally we check if the trade makes sense (meaning is of a certain size, at least 10 cells by default). If yes, we reduce the TP by a bit (by default 2 cells) and add it to the chart.
Sector Relative Strength [Afnan]This indicator calculates and displays the relative strength (RS) of multiple sectors against a chosen benchmark. It allows you to quickly compare the performance of various sectors within any global stock market. While the default settings are configured for the Indian stock market , this tool is not limited to it; you can use it for any market by selecting the appropriate benchmark and sector indices.
📊 Key Features ⚙️
Customizable Benchmark: Select any symbol as your benchmark for relative strength calculation. The default benchmark is set to `NSE:CNX100`. This allows for global market analysis by selecting the appropriate benchmark index of any country.
Multiple Sectors: Analyze up to 23 different sector indices. The default settings include major NSE sector indices. This can be customized to any market by using the relevant sector indices of that country.
Individual Sector Control: Toggle the visibility of each sector's RS on the chart.
Color-Coded Plots: Each sector's RS is plotted with a distinct color for easy identification.
Adjustable Lookback Period: Customize the lookback period for RS calculation.
Interactive Table: A sortable table displays the current RS values for all visible sectors, allowing for quick ranking.
Table Customization: Adjust the table's position, text size, and visibility.
Zero Line: A horizontal line at zero provides a reference point for RS values.
🧭 How to Use 🗺️
Add the indicator to your TradingView chart.
Select your desired benchmark symbol. The default is `NSE:CNX100`. For example, use SPY for the US market, or DAX for the German market.
Adjust the lookback period as needed.
Enable/disable the sector indices you want to analyze. The default includes major NSE sector indices like `NSE:CNXIT`, `NSE:CNXAUTO`, etc.
Customize the table's appearance as needed.
Observe the RS plots and the table to identify sectors with relative strength or weakness.
📝 Note 💡
This indicator is designed for sectorial analysis. You can use it with any market by selecting the appropriate benchmark and sector indices.
The default settings are configured for the Indian stock market with `NSE:CNX100` as the benchmark and major NSE sector indices pre-selected.
The relative strength calculation is based on the price change of the sector index compared to the benchmark over the lookback period.
Positive RS values indicate relative outperformance, while negative values indicate relative underperformance.
👨💻 Developer 🛠️
Afnan Tajuddin
Weekly Open LineThis indicator displays the weekly open price on the chart. It automatically updates every Monday to reflect the opening price of the current week. A dashed line is drawn to indicate the weekly open, and a label stating "Monday" is shown on each Monday for easy identification.
Features:
Automatically calculates the weekly open on Mondays.
Displays a dashed line at the weekly open price.
Labels the weekly open with the text "Monday" for visibility.
Indikator ini menampilkan harga open mingguan di grafik. Indikator ini secara otomatis diperbarui setiap hari Senin untuk mencerminkan harga pembukaan minggu berjalan. Garis putus-putus digambar untuk menunjukkan open mingguan, dan sebuah label yang menyatakan "Moday" ditampilkan setiap hari Senin untuk memudahkan identifikasi.
Market Open Levels v3This indicator "Market Open Levels v3" allows a chart user to automatically display up to 20 previous price levels at the open price of up to 8 different markets simultaneously on one indicator.
The user can specify custom labels for each market's price level, as well as adjust the GMT Offset to allow for market open times in a different timezone than the chart's displayed time.
Displays price level at specified market open times. For instance, if a user specifies a market opens at 08:00, then a price level (horizontal line) will be drawn at the most recent 08:00 candle's open price (if GMT Offset is set to 0).
See tooltips for more information on specific inputs.
Smart DCA Strategy (Public)INSPIRATION
While Dollar Cost Averaging (DCA) is a popular and stress-free investment approach, I noticed an opportunity for enhancement. Standard DCA involves buying consistently, regardless of market conditions, which can sometimes mean missing out on optimal investment opportunities. This led me to develop the Smart DCA Strategy – a 'set and forget' method like traditional DCA, but with an intelligent twist to boost its effectiveness.
The goal was to build something more profitable than a standard DCA strategy so it was equally important that this indicator could backtest its own results in an A/B test manner against the regular DCA strategy.
WHY IS IT SMART?
The key to this strategy is its dynamic approach: buying aggressively when the market shows signs of being oversold, and sitting on the sidelines when it's not. This approach aims to optimize entry points, enhancing the potential for better returns while maintaining the simplicity and low stress of DCA.
WHAT THIS STRATEGY IS, AND IS NOT
This is an investment style strategy. It is designed to improve upon the common standard DCA investment strategy. It is therefore NOT a day trading strategy. Feel free to experiment with various timeframes, but it was designed to be used on a daily timeframe and that's how I recommend it to be used.
You may also go months without any buy signals during bull markets, but remember that is exactly the point of the strategy - to keep your buying power on the sidelines until the markets have significantly pulled back. You need to be patient and trust in the historical backtesting you have performed.
HOW IT WORKS
The Smart DCA Strategy leverages a creative approach to using Moving Averages to identify the most opportune moments to buy. A trigger occurs when a daily candle, in its entirety including the high wick, closes below the threshold line or box plotted on the chart. The indicator is designed to facilitate both backtesting and live trading.
HOW TO USE
Settings:
The input parameters for tuning have been intentionally simplified in an effort to prevent users falling into the overfitting trap.
The main control is the Buying strictness scale setting. Setting this to a lower value will provide more buying days (less strict) while higher values mean less buying days (more strict). In my testing I've found level 9 to provide good all round results.
Validation days is a setting to prevent triggering entries until the asset has spent a given number of days (candles) in the overbought state. Increasing this makes entries stricter. I've found 0 to give the best results across most assets.
In the backtest settings you can also configure how much to buy for each day an entry triggers. Blind buy size is the amount you would buy every day in a standard DCA strategy. Smart buy size is the amount you would buy each day a Smart DCA entry is triggered.
You can also experiment with backtesting your strategy over different historical datasets by using the Start date and End date settings. The results table will not calculate for any trades outside what you've set in the date range settings.
Backtesting:
When backtesting you should use the results table on the top right to tune and optimise the results of your strategy. As with all backtests, be careful to avoid overfitting the parameters. It's better to have a setup which works well across many currencies and historical periods than a setup which is excellent on one dataset but bad on most others. This gives a much higher probability that it will be effective when you move to live trading.
The results table provides a clear visual representation as to which strategy, standard or smart, is more profitable for the given dataset. You will notice the columns are dynamically coloured red and green. Their colour changes based on which strategy is more profitable in the A/B style backtest - green wins, red loses. The key metrics to focus on are GOA (Gain on Account) and Avg Cost.
Live Trading:
After you've finished backtesting you can proceed with configuring your alerts for live trading.
But first, you need to estimate the amount you should buy on each Smart DCA entry. We can use the Total invested row in the results table to calculate this. Assuming we're looking to trade on
BTCUSD
Decide how much USD you would spend each day to buy BTC if you were using a standard DCA strategy. Lets say that is $5 per day
Enter that USD amount in the Blind buy size settings box
Check the Blind Buy column in the results table. If we set the backtest date range to the last 10 years, we would expect the amount spent on blind buys over 10 years to be $18,250 given $5 each day
Next we need to tweak the value of the Smart buy size parameter in setting to get it as close as we can to the Total Invested amount for Blind Buy
By following this approach it means we will invest roughly the same amount into our Smart DCA strategy as we would have into a standard DCA strategy over any given time period.
After you have calculated the Smart buy size, you can go ahead and set up alerts on Smart DCA buy triggers.
BOT AUTOMATION
In an effort to maintain the 'set and forget' stress-free benefits of a standard DCA strategy, I have set my personal Smart DCA Strategy up to be automated. The bot runs on AWS and I have a fully functional project for the bot on my GitHub account. Just reach out if you would like me to point you towards it. You can also hook this into any other 3rd party trade automation system of your choice using the pre-configured alerts within the indicator.
PLANNED FUTURE DEVELOPMENTS
Currently this is purely an accumulation strategy. It does not have any sell signals right now but I have ideas on how I will build upon it to incorporate an algorithm for selling. The strategy should gradually offload profits in bull markets which generates more USD which gives more buying power to rinse and repeat the same process in the next cycle only with a bigger starting capital. Watch this space!
MARKETS
Crypto:
This strategy has been specifically built to work on the crypto markets. It has been developed, backtested and tuned against crypto markets and I personally only run it on crypto markets to accumulate more of the coins I believe in for the long term. In the section below I will provide some backtest results from some of the top crypto assets.
Stocks:
I've found it is generally more profitable than a standard DCA strategy on the majority of stocks, however the results proved to be a lot more impressive on crypto. This is mainly due to the volatility and cycles found in crypto markets. The strategy makes its profits from capitalising on pullbacks in price. Good stocks on the other hand tend to move up and to the right with less significant pullbacks, therefore giving this strategy less opportunity to flourish.
Forex:
As this is an accumulation style investment strategy, I do not recommend that you use it to trade Forex.
For more info about this strategy including backtest results, please see the full description on the invite only version of this strategy named "Smart DCA Strategy"
MACD Aggressive Scalp SimpleComment on the Script
Purpose and Structure:
The script is a scalping strategy based on the MACD indicator combined with EMA (50) as a trend filter.
It uses the MACD histogram's crossover/crossunder of zero to trigger entries and exits, allowing the trader to capitalize on short-term momentum shifts.
The use of strategy.close ensures that positions are closed when specified conditions are met, although adjustments were made to align with Pine Script version 6.
Strengths:
Simplicity and Clarity: The logic is straightforward and focuses on essential scalping principles (momentum-based entries and exits).
Visual Indicators: The plotted MACD line, signal line, and histogram columns provide clear visual feedback for the strategy's operation.
Trend Confirmation: Incorporating the EMA(50) as a trend filter helps avoid trades that go against the prevailing trend, reducing the likelihood of false signals.
Dynamic Exit Conditions: The conditional logic for closing positions based on weakening momentum (via MACD histogram change) is a good way to protect profits or minimize losses.
Potential Improvements:
Parameter Inputs:
Make the MACD (12, 26, 9) and EMA(50) values adjustable by the user through input statements for better customization during backtesting.
Example:
pine
Copy code
macdFast = input(12, title="MACD Fast Length")
macdSlow = input(26, title="MACD Slow Length")
macdSignal = input(9, title="MACD Signal Line Length")
emaLength = input(50, title="EMA Length")
Stop Loss and Take Profit:
The strategy currently lacks explicit stop-loss or take-profit levels, which are critical in a scalping strategy to manage risk and lock in profits.
ATR-based or fixed-percentage exits could be added for better control.
Position Size and Risk Management:
While the script uses 50% of equity per trade, additional options (e.g., fixed position sizes or risk-adjusted sizes) would be beneficial for flexibility.
Avoid Overlapping Signals:
Add logic to prevent overlapping signals (e.g., opening a new position immediately after closing one on the same bar).
Backtesting Optimization:
Consider adding labels or markers (label.new or plotshape) to visualize entry and exit points on the chart for better debugging and analysis.
The inclusion of performance metrics like max drawdown, Sharpe ratio, or profit factor would help assess the strategy's robustness during backtesting.
Compatibility with Live Trading:
The strategy could be further enhanced with alert conditions using alertcondition to notify the trader of buy/sell signals in real-time.
