MTF VWAPThis indicator is an enhanced version of the traditional VWAP, providing traders with multiple timeframe views, automatic session anchoring, and customization options for optimized technical analysis.
Key Features:
1. Multiple Timeframes, One View : Visualize Daily, Weekly, Monthly, and Yearly VWAP calculations simultaneously on a single chart.
2. Automatic Anchoring : The indicator intelligently auto-anchors each VWAP calculation to the start of its respective session. This ensures accurate readings and streamlines your analysis by eliminating the need for manual adjustments.
3. Customizability : Tailor the appearance of the indicator with fully customizable colors and the ability to select your preferred price source (e.g., high, low, close, hlc3, hlcc4, or a custom one).
ממוצעים נעים
Crypto MVRV ZScore - Strategy [PresentTrading]█ Introduction and How it is Different
The "Crypto Valuation Extremes: MVRV ZScore - Strategy " represents a cutting-edge approach to cryptocurrency trading, leveraging the Market Value to Realized Value (MVRV) Z-Score. This metric is pivotal for identifying overvalued or undervalued conditions in the crypto market, particularly Bitcoin. It assesses the current market valuation against the realized capitalization, providing insights that are not apparent through conventional analysis.
BTCUSD 6h Long/Short Performance
Local
█ Strategy, How It Works: Detailed Explanation
The strategy leverages the Market Value to Realized Value (MVRV) Z-Score, specifically designed for cryptocurrencies, with a focus on Bitcoin. This metric is crucial for determining whether Bitcoin is currently undervalued or overvalued compared to its historical 'realized' price. Below is an in-depth explanation of the strategy's components and calculations.
🔶Conceptual Foundation
- Market Capitalization (MC): This represents the total dollar market value of Bitcoin's circulating supply. It is calculated as the current price of Bitcoin multiplied by the number of coins in circulation.
- Realized Capitalization (RC): Unlike MC, which values all coins at the current market price, RC is computed by valuing each coin at the price it was last moved or traded. Essentially, it is a summation of the value of all bitcoins, priced at the time they were last transacted.
- MVRV Ratio: This ratio is derived by dividing the Market Capitalization by the Realized Capitalization (The ratio of MC to RC (MVRV Ratio = MC / RC)). A ratio greater than 1 indicates that the current price is higher than the average price at which all bitcoins were purchased, suggesting potential overvaluation. Conversely, a ratio below 1 suggests undervaluation.
🔶 MVRV Z-Score Calculation
The Z-Score is a statistical measure that indicates the number of standard deviations an element is from the mean. For this strategy, the MVRV Z-Score is calculated as follows:
MVRV Z-Score = (MC - RC) / Standard Deviation of (MC - RC)
This formula quantifies Bitcoin's deviation from its 'normal' valuation range, offering insights into market sentiment and potential price reversals.
🔶 Spread Z-Score for Trading Signals
The strategy refines this approach by calculating a 'spread Z-Score', which adjusts the MVRV Z-Score over a specific period (default: 252 days). This is done to smooth out short-term market volatility and focus on longer-term valuation trends. The spread Z-Score is calculated as follows:
Spread Z-Score = (Market Z-Score - MVVR Ratio - SMA of Spread) / Standard Deviation of Spread
Where:
- SMA of Spread is the simple moving average of the spread over the specified period.
- Spread refers to the difference between the Market Z-Score and the MVRV Ratio.
🔶 Trading Signals
- Long Entry Condition: A long (buy) signal is generated when the spread Z-Score crosses above the long entry threshold, indicating that Bitcoin is potentially undervalued.
- Short Entry Condition: A short (sell) signal is triggered when the spread Z-Score falls below the short entry threshold, suggesting overvaluation.
These conditions are based on the premise that extreme deviations from the mean (as indicated by the Z-Score) are likely to revert to the mean over time, presenting opportunities for strategic entry and exit points.
█ Practical Application
Traders use these signals to make informed decisions about opening or closing positions in the Bitcoin market. By quantifying market valuation extremes, the strategy aims to capitalize on the cyclical nature of price movements, identifying high-probability entry and exit points based on historical valuation norms.
█ Trade Direction
A unique feature of this strategy is its configurable trade direction. Users can specify their preference for engaging in long positions, short positions, or both. This flexibility allows traders to tailor the strategy according to their risk tolerance, market outlook, or trading style, making it adaptable to various market conditions and trader objectives.
█ Usage
To implement this strategy, traders should first adjust the input parameters to align with their trading preferences and risk management practices. These parameters include the trade direction, Z-Score calculation period, and the thresholds for long and short entries. Once configured, the strategy automatically generates trading signals based on the calculated spread Z-Score, providing clear indications for potential entry and exit points.
It is advisable for traders to backtest the strategy under different market conditions to validate its effectiveness and adjust the settings as necessary. Continuous monitoring and adjustment are crucial, as market dynamics evolve over time.
█ Default Settings
- Trade Direction: Both (Allows for both long and short positions)
- Z-Score Calculation Period: 252 days (Approximately one trading year, capturing a comprehensive market cycle)
- Long Entry Threshold: 0.382 (Indicative of moderate undervaluation)
- Short Entry Threshold: -0.382 (Signifies moderate overvaluation)
These default settings are designed to balance sensitivity to market valuation extremes with a pragmatic approach to trade execution. They aim to filter out noise and focus on significant market movements, providing a solid foundation for both new and experienced traders looking to exploit the unique insights offered by the MVRV Z-Score in the cryptocurrency market.
Liquidation Longs/Shorts [UAlgo]🔶Description:
The "Liquidation Longs/Shorts " indicator is designed to identify potential liquidation levels for long and short positions. It calculates the distance of the selected price source (close, high, low, or open) from two moving averages (MA) and plots the resulting values on the chart. When the price is at an extreme distance from the moving averages, it suggests a potential liquidation point for either long or short positions.
🔶Key Features:
Liquidation Calculations: The indicator calculates the distance of the selected price source from two moving averages: a simple moving average (SMA) and an exponential moving average (EMA) with customizable lengths.
Color Customization: Users can customize the colors of the plotted columns representing the distance from the moving averages for long and short liquidation levels.
Liquidation Circles: The indicator marks potential liquidation levels with small circles on the chart, with customizable colors for long and short liquidations.
Orange Circles -> Identifies Potential Short Liquidations
Aqua Circles -> Identifies Potential Long Liquidations
Example:
Adaptive Source Selection: Traders can select the price source (close, high, low, or open) for liquidation calculations, allowing flexibility based on their trading strategies.
Dynamic Threshold Calculation: The indicator dynamically adjusts the liquidation threshold based on the selected moving average lengths, providing adaptability to changing market conditions.
Disclaimer:
Use with Caution: This indicator is provided for educational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
This indicator serves as a tool to assist traders in identifying potential liquidation levels, but it should be used in conjunction with other technical analysis tools and risk management practices for effective trading decision-making.
Normalised Gaussian MACD Heikin Ashi [AlgoAlpha]🌟🚀Introducing the Normalised Gaussian MACD Heikin Ashi by AlgoAlpha !
Elevate your trading game with this multipurpose indicator, crafted to pinpoint trend continuation opportunities while highlighting volatility and oversold/overbought conditions. Whether you're embarking on your trading journey or you're a seasoned market navigator, this tool is equipped with intuitive visual cues to amplify your decision-making prowess and enrich your market analysis toolkit. Let's dive into the key features, utilization strategies, and the innovative logic underpinning this indispensable trading asset.
Key Features:
🔧 Enhanced Customization : Tailor your experience with adjustable parameters including Fast Length, Slow Length, Source, Macd Smoothing Length, Signal Smoothing, and more.
🖌️ Visual Enhancements : Opt for Heikin Ashi Candles display and choose to show or hide MACD and Signal lines for a clutter-free chart.
🌈 Color Customization : Personalize your chart with selectable primary and secondary up and down colors to suit your visual preferences.
🔔 Advanced Alert System : Stay ahead with comprehensive alert conditions for market movements, including trend reversals, bullish and bearish swings.
How to Use:
Configure the Inputs : Start by customizing the indicator’s settings to match your trading style. Adjust the length parameters, source selection, and smoothing lengths to fine-tune the indicator’s sensitivity.
Interpret the Candles and Colors : Keep an eye on the Heikin Ashi Candles (if enabled) and the color shifts within the MACD Line Candles and Histogram. These visual cues are pivotal for identifying market trends.
Analyze with Flexibility : Make use of the option to display or hide the MACD and Signal lines based on your analysis requirements. This can help in focusing on the essential information without overcrowding your chart.
Utilize Alerts for Timely Decisions : Leverage the extensive alert system to get notified about potential market movements. These alerts can help you capture the right moment to enter or exit trades.
Basic Logic:
The Normalised Gaussian MACD Heikin Ashi by AlgoAlpha integrates Gaussian filters to elevate the traditional MACD indicator's efficiency, providing a more detailed analysis of market trends and momentum. This sophisticated approach reduces noise and enhances signal speed, which is crucial for identifying momentum trading opportunities.
Gaussian Filter Implementation : The core innovation lies in applying a Gaussian filter to the input price series. This mathematical technique smooths the price data, significantly reducing market noise and making trend signals clearer and more reliable. The Gaussian filter calculates a smoothed value for each data point by weighting nearby data points, with the weights decreasing as the distance from the current data point increases.
Refined MACD Calculation : The Gaussian MACD is derived from the difference between two Gaussian smoothed moving averages (fast and slow), which are then normalized to account for market volatility. This normalization process involves dividing the difference by a measure of market range (such as the high minus the low), and multiplying by a factor (usually 100) to scale the indicator appropriately.
🔑 This script is a versatile tool designed to aid in the identification of momentum and reversals, helping traders to make informed decisions based on technical analysis. Its customization options allow for a tailored analysis experience, fitting the unique needs and strategies of each trader.
Stoch + RSI Oscillator @shrilssThis script combines two powerful indicators, the Stochastic Oscillator and the Relative Strength Index (RSI), to offer traders a comprehensive view of market dynamics.
The Stochastic Oscillator, known for its effectiveness in identifying overbought and oversold conditions, is enhanced here with a smoothing mechanism to provide clearer signals. The script calculates the %K and %D lines of the Stochastic Oscillator, then applies a smoothing factor to %K, resulting in a smoother representation of price momentum.
Simultaneously, the RSI component offers insights into the strength of price movements. By comparing the average gains and losses over a specified period, it provides a measure of bullish and bearish sentiment within the market.
This script's innovation lies in its integration of these two indicators. The Stochastic Oscillator's smoothed %K line and the RSI are compared to dynamic thresholds, enabling traders to identify potential trend reversals and confirmations more effectively. When the RSI crosses above or below the Stochastic %D line, it can signal potential shifts in market momentum.
Time Candle Range HistoryThe 'Intraday Candle Range Average' indicator is designed to provide traders with insights into the average price range of intraday candles, specifically focusing on the period around 9:30 AM. By calculating the difference between the high and low of candles occurring at 9:30 AM, the indicator offers a dynamic view of market volatility during this critical time window. Users can customize parameters such as the number of days to consider for the average calculation, allowing for flexibility in analyzing short-term price movements. Additionally, the indicator offers a clear visualization of the current candle range compared to the historical average, aiding traders in identifying potential trading opportunities based on volatility patterns. Whether used independently or in conjunction with other technical analysis tools, the 'Intraday Candle Range Average' indicator empowers traders with valuable insights into intraday market dynamics.
MACD All In One Screener [ChartPrime]INTRODUCTION
MACD All In One Screener (ChartPrime) is a multi instrument, multi timeframe indicator designed to provide traders with a comprehensive solution to monitoring the market. This indicator is designed to be easy to use and visually appealing while also being highly flexible and feature rich. Users can pick up to 10 symbols not including the chart's symbol and set up alerts for many different signals that the MACD produces. One standout feature of this indicator is its ability to display not only each symbol individually as a MACD but you can also view its chart from within this indicator. This removes the need to flip between symbols to see the price action for your basket.
On top of that we have designed this indicator to be friendly with "indicator on indicator" by providing outputs for all of the standards of price that users may want. Included is an overview section that shows all of the symbols signals symbolically over time. Additionally we have included a table for easy monitoring. This table includes the symbol, its timeframe, the current alert, and its histogram state. To make things as user friendly as possible we have also included rich error handling that tells you exactly what is wrong with your configuration.
HOW TO USE
To use this indicator, simply add it to your chart and navigate to the settings. From there select the symbols you want to monitor and the timeframes you want to use. Next you want to navigate down to the alerts section to select the what alerts you want to receive, and what symbols you want to get alerts for. Finally, you wan to create your alert using "Any alert() function call". Now your screener is all set up!
OVERVIEW OF INPUTS
View allows you to select what the indicator currently displays. You can pick from any one of the selected symbols, an overview of all of the symbols, or simply nothing. If you want to only use the table, "None" is provided so you can move the indicator into the chart panel.
View Toggle lets you pick from displaying the MACD for the selected symbol or the Price Action as a candle chart. To see your "indicator on indicator" you will have to select a symbol from the view list. There is a bug where if you select "Overview" while you are using "indicator on indicator" your added indicator will see the last symbol you viewed. To fix this, simply change the setting of your overlaid indicator and it will correct its self.
History Length is the number of historical bars to calculate over. This feature is here to prevent the indicator from breaking due to uneven historical data between the symbols.
Show Price Line toggles a dotted line that follows the current symbols closing price when "Price" is selected under the "View Toggle" dropdown.
Show Symbol Label toggles a label that displays the current symbols name and timeframe. This only impacts the single symbol view.
Overview Label Color adjusts the color of the symbol labels for both overview and single symbol view.
MA Type lets you pick what kind of moving average you want to use for the oscillator or signal. You can pick from the standard SMA or EMA.
Fast Length is a standard input for MACD. This lets you pick the period of the fast MA.
Slow Length , just like Fast Lenght, is a standard input for MACD. This lets you pick the period of the slow MA.
Signal Length is another standard input for MACD. This lets you configure the period of the signal MA.
MACD Cross Overlay Icon is a toggle to display MACD crosses when viewing a single symbol's MACD. When the MACD has a bullish cross it will plot a bullish dot, and when it has a bearish cross it will plot a bearish dot. This is purely visual.
Regular Bullish and Bearish toggles the visual display of the divergences on the single symbol view. This does not effect the indicators ability do send alerts.
Divergence Look Right adjusts the number of bars into the future to look for confirmation of a signal. This directly impacts lag but enhances stability.
Divergence Look Left adjusts the number of bars into the past to check for a signal. A longer period will filter out smaller moves
Maximum Lookback adjusts the maximum size of a divergence.
Minimum Lookback adjusts the minimum size of a divergence.
Divergence Drawings picks how you want to visualize the divergence. You can pick from displaying it as a line, a label, or both.
Enable Table toggles the overview table. When enabled it will show you the enabled symbols and their current state. From left to right: symbol name, timeframe, current alert, and histogram state.
Position picks where on the chart you want the table to be.
Text Color adjusts the text color of the table.
BG Color adjusts the background color of the table.
Frame Color adjust the frame color of the table.
Current Symbol Time Frame adjusts the timeframe of the chart's symbol.
Symbol 1 - 10 pick "Symbol's" symbol and timeframe. To use higher timeframes, the symbol's have to be the same type. You can't have a crypto and a stock using HTF at the same time as they don't have the same sessions and will result in an error. You can use unsafe mode (as described below) to potentially get around this.
Enable Symbol when enabled it will give you alerts for the symbol. This also enables the symbol in the overview. If this is disabled it won't send alerts, and it will not show up in overview, or the table.
Wait for Close enables waiting for the bar to close before printing an alert.
Alert Symbol Size picks what size you want the overview symbols to be.
Enable Cross Over 0 Alert: MACD crosses over the 0 line.
Enable Cross Under 0 Alert: MACD crosses under the 0 line.
Enable MACD Cross Bullish Alert: Bullish MACD cross.
Enable MACD Cross Bearish Alert: Bearish MACD cross.
Enable Histogram Bullish Turn Alert: MACD begins to turn bullish but hasn't crossed.
Enable Histogram Bearish Turn Alert: MACD begins to turn bearish but hasn't crossed.
Enable Histogram Bullish Continuation Alert: MACD is in a bullish cross state and it was declining but began rising again.
Enable Histogram Bearish Continuation Alert: MACD is in a bearish cross state and it was rising but began falling again.
Enable Bullish/Bearish Divergence Alert enables divergence alerts. Divergences are lagging, especially on a higher timeframe. These alerts will also tell you the time in the past when the divergence occurred.
Color Section is provided to allow for personalization of the indicator. Everything can be adjusted here.
Disable Error Checking: Only enable this if you want to bypass the built in error checking. This will enable 'Safe Requesting'. Safe Requesting will only request enabled symbols and you will not be able to view symbols that are not enabled in this mode. Only use this if you want to mix symbol types and you know it will work. (An example would be viewing stocks and SPY at the same time.)
CONCLUSION
The MACD All In One Screener (ChartPrime) is a versatile indicator designed to monitor multiple symbols across various timeframes. The flexibility in customization, from MACD settings to visual alerts and table presentations, allows users to tailor the screener to their needs and preferences. We hope you find this as useful and interesting as we do and wish you good luck in the market!
Enjoy
Volume Spike IndicatorHello dear traders,
Today we're discussing an indicator I've coded: the Volume Spike Indicator (VSI).
The indicator isn't a groundbreaking invention and certainly not a novelty. Nevertheless, I haven't seen this version of the indicator on TradingView before, so I'd like to introduce it.
1. The Origin of the Idea:
We're all familiar with volume charts: A volume chart visually represents the trading activity for a specific asset over a certain period, indicating the total number of shares or contracts traded.
We also know that volume spikes can significantly impact the market. A volume spike represents an extreme anomaly, a day, week, or month with an extraordinary amount of trading. However, recognizing these spikes in practice isn't always straightforward. What constitutes high volume? How do we define and identify it? The answers to these questions aren't easy.
It's commonly said that a volume spike could be identified if the volume is 25% more than the average of the two weeks prior, but how do you measure this 25%? It's not always easy to calculate, especially in real-time.
This challenge led me to develop the concept into an indicator.
How Does It Work?
Imagine being able to "feel" the market's energy like a surfer feels the ocean. The VSI does something similar by examining trading volume and comparing it to what has been typical over the past few weeks. Here's a quick look at the magic behind it:
Step 1: Establishing the Baseline: We start by establishing a baseline, i.e., the average trading volume over a given period. Let's use the last 10 days as the default setting. We choose 10 days because, in the traditional stock market, 10 days represent two weeks if you subtract weekends. This gives us a fixed line to compare against.
Step 2: Recognizing Peaks: Next, we look for days when the trading volume significantly exceeds this average. The size of the jump is where you have a say. You can set a threshold, such as 25%, to define what you consider a volume spike.
Step 3: The Calculation: This is where the math comes into play. We calculate the percentage change in today's volume compared to the average volume of the last 10 days. For example, if today's volume is 30% above the average and you've set your threshold at 25%, the VSI will recognize this as a spike.
Step 4: Visual Cue: These spikes are then plotted on a graph, with each spike represented as a bar. The height of the bar indicates the spike's percentage size, so you can see at a glance how significant a spike is.
Step 5: Intuitive Color Coding: For quick analysis, the VSI employs a color-coding system. Exceptionally high peaks, such as those exceeding a 100% increase, are highlighted in blue to emphasize their importance. Other peaks are shown in red, creating a visual hierarchy for quick volume data interpretation.
Why This Matters:
Identifying these spikes can help pinpoint the beginning or end of a trend. The idea is that when trading peaks at a certain level, there might be no more buyers or sellers willing to engage at that price level. Volume peaks, and a reversal is likely imminent. It's a simple yet effective concept. Therefore, it's crucial to use this indicator in the context of the trend, as not every spike carries the same significance.
Customizable:
The beauty of the VSI lies in its flexibility. Trading futures? You might want to adjust the averaging period to 14 days to better suit your market. You have full control over the settings to tailor them to your trading style.
Interpreting the Figures:
A positive percentage indicates a volume spike above the average – the higher the percentage, the more significant the spike.
If the percentage exceeds a certain threshold (which you can set, e.g., 25%), it signals a volume spike, indicating increased market activity that could precede significant price movement.
What makes the VSI genuinely adaptable is your ability to tweak the parameters to suit your needs.
Are you trading in a volatile market? Extend the SMA period to smooth out the noise. Trading in a 24-hour market? Adjust the length of your SMA. Seeking finer details? Shorten it. The VSI is yours to adapt to your trading strategy.
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As we wrap up this introduction to the Volume Spike Indicator, I hope you're as excited about its potential as I am. This tool, born out of curiosity and a desire for clarity in the vast ocean of market data, is designed to be your ally in navigating the waves of trading activity.
Remember, the true power of the VSI lies not just in its ability to highlight significant volume spikes, but in its adaptability to your unique trading style and needs. Whether you're charting courses through the tumultuous seas of day trading or navigating the broader currents of long-term investments, the VSI is here to offer insights and guidance.
I encourage you to experiment with it, customize it, and see how it can enhance your trading strategy. And as you do, remember that every tool, no matter how powerful, is just one piece of the puzzle. Combine the VSI with your knowledge, experience, and intuition to make informed and strategic trading decisions.
Thank you for taking the time to explore the Volume Spike Indicator with me.
Best Regards,
Karim Subhieh
Elder Force Index Oscillator @shrilssThe "Elder Force Index Oscillator" is a comprehensive tool designed to assess the strength and direction of trends in the market. This indicator combines volume and price movement to provide traders with valuable insights into market dynamics.
Key Features:
- Volume Weighted: The oscillator considers both price changes and volume, emphasizing the significance of volume in confirming price movements.
- Trend Identification: Utilizing exponential moving averages (EMAs) and Bollinger Bands (BB), the indicator identifies potential trend reversals and continuations.
- Trend Strength Highlighting: With customizable options, the script highlights areas of strong and weak trend initiation, aiding traders in making informed decisions.
How It Works:
- Elder Force Index (EFI): The EFI is calculated as the EMA of price changes multiplied by volume. A positive value suggests buying pressure, while a negative value indicates selling pressure.
- EFI Moving Average (EFI MA): This smooths out the EFI, providing a clearer indication of trend direction.
- Bollinger Bands (BB): The upper and lower bands are calculated based on a specified number of standard deviations from the EFI's moving average, offering insights into potential overbought or oversold conditions.
Kshitij Malve - Minervini Trend Criteria (MTC)Purpose:
This indicator is designed to assist traders in identifying stocks that potentially meet the bullish Stage 2 trend criteria outlined by renowned stock trader Mark Minervini. It analyzes price movement in relation to moving averages and calculates certain price thresholds to provide visual signals.
Key Features:
Minervini Stage 2 Focus: Specifically targets trend characteristics highlighted in Minervini's trading methodology.
Adjustable Moving Averages: The script includes inputs for 150-day, 200-day, and 50-day moving average lengths, allowing users to customize their analysis.
Visual Trend Criteria: Each core Stage 2 trend condition is plotted below the chart as green or red dots for quick visual assessment.
Stage 2 Uptrend Signal: When all key trend conditions are met, a purple up-arrow appears beneath the price chart.
Alerts: Customizable alerts can be set up to notify the user when all conditions are met, signaling a potential Stage 2 uptrend.
Conditions Evaluated:
Price Position: Current price is above the 50-day, 150-day, and 200-day simple moving averages.
Moving Average Alignment: 50-day MA is above the 150-day MA, which is above the 200-day MA.
Uptrending 200-day MA: The 200-day MA is demonstrating an upward trend over the specified period.
30% Above 52-Week Low: Current price is at least 30% higher than the 52-week low.
Within 25% of 52-Week High: Current price is no more than 25% below the 52-week high.
Important Notes:
This indicator does not directly plot lines for conditions 4 and 5 (52-week high/low comparisons). Consider incorporating these into your chart in some way for full technical analysis in line with the Minervini method.
For additional depth, study Mark Minervini's books to fully understand the context and strategies built around these criteria.
How to Use:
Add the "Kshitij Malve - Minervini Trend Criteria" indicator to a stock chart.
Observe the placement of colored dots below the chart. A series of green dots suggests the stock is within Minervini's Stage 2 criteria.
Look for the purple up-arrow signal for confirmation that all conditions are met.
Customize alerts if you would like real-time signals of potential Stage 2 uptrends.
Trend Continuation Signals [AlgoAlpha]Introducing the Trend Continuation Signals by AlgoAlpha 🌟🚀
Elevate your trading game with this multipurpose indicator, designed to pinpoint trend continuation opportunities as well as highlight volatility and oversold/overbought conditions. Whether you're a trading novice or a seasoned market veteran, this tool offers intuitive visual cues to boost your decision-making and enhance your market analysis. Let's explore the key features, how to use it effectively, and delve into the operational mechanics that make this tool a game-changer in your trading arsenal:
Key Features:
🔥 Advanced Trend Detection : Leverages the Hull Moving Average (HMA) for superior trend tracking as compared to other MAs, offering unique insights into market momentum.
🌈 Volatility Bands : Implements adjustable bands around the trend line, which evolve with market conditions to highlight potential trading opportunities.
⚡ Trend Continuation Signals : Identifies bullish and bearish continuation signals, equipping you with actionable signals to exploit the prevailing market trend.
🎨 Intuitive Color Coding : Employs a vibrant color scheme to distinguish between uptrends, downtrends, and neutral phases, facilitating easy interpretation of the indicator's insights.
🛠 How to Use "Trend Continuation Signals ":
🔍 Setting Up : Incorporate the indicator onto your chart and customize the indicator to suite your preferences.
👀 Reading the Signals : Pay attention to the color-coded trend lines and volatility bands. Green indicates an uptrend, red signifies a downtrend, and gray denotes a neutral market condition.
📈 Identifying Entry Points : Look for bullish (▲) and bearish (▼) continuation icons below or above the price bars as signals for potential entry points for long or short positions, respectively.
🔄 Confirmation : Validate your trades with further analysis or other indicators. The Trend Continuation Signals are most effective when complemented by other technical analysis tools or fundamental insights.
📉 Risk Management : Implement stop-loss orders in line with your risk appetite and adjust them based on the volatility bands provided by the indicator to safeguard your investments.
How It Operates:
The essence of the indicator is captured through the hull moving averages for both the primary and secondary lines, set at periods of 93 and 50, respectively, to reflect market trends and pullbacks that trigger the continuation signals every time price recovers from a detected pullback.
Volatility is quantified through the standard deviation of the midline, magnified by a factor, establishing the upper and lower trend band boundaries.
Further volatility bands are plotted around the main volatility band, providing a granular view of market volatility and potential breakout or breakdown zones.
Market trend direction is determined by comparing the HMA line's current position to its previous value, enhanced by the secondary line to identify continuation patterns.
Embrace the power of the Trend Continuation Signals to enhance your trading strategy! It is important to note that all indicators are best used in confluence with other forms of analysis, happy trading! 📊💥
Inverted EMAThe concept of an inverted Exponential Moving Average (EMA) isn't commonly used in traditional technical analysis or trading strategies. Inverting the EMA essentially means taking the reciprocal of the EMA values. While it may not have widespread use or recognition, here are some potential considerations or interpretations for the inverted EMA:
1. **Inverse Trend Indicator:**
- Inverting the EMA might be considered as an alternative approach to trend analysis. When the inverted EMA is rising, it could suggest a potential bearish trend, and when it is falling, it might indicate a bullish trend. Traders might explore using this as a contrarian or unconventional trend indicator.
2. **Volatility Indicator:**
- The inverted EMA might be used as a measure of volatility. When the values are fluctuating rapidly, it could imply increased volatility in the underlying asset. This could be useful for traders who are interested in gauging market dynamics.
3. **Divergence Analysis:**
- Traders may explore divergences between price and the inverted EMA. For instance, if prices are making new highs, but the inverted EMA is not, it could signal potential weakness or divergence in the bullish trend.
4. **Inverse Moving Average Crossovers:**
- In the context of moving average crossovers, traders usually look for crossovers between shorter and longer EMAs as potential signals. Inverting this concept, crossovers between inverted short-term and long-term EMAs might be explored for unconventional trading signals.
5. **Systematic Exploration:**
- Traders and researchers sometimes experiment with unconventional indicators to discover new patterns or behaviors in the market. The inverted EMA could be part of systematic exploration to uncover unique insights that traditional indicators might not reveal.
It's important to note that the interpretation and use of the inverted EMA depend on the trader's strategy, risk tolerance, and specific market conditions. Traders should thoroughly backtest any strategy involving unconventional indicators and use them cautiously in live trading. Additionally, the effectiveness of the inverted EMA may vary across different financial instruments and timeframes.
LV Stock Valuation by Benjamin Graham's FormulaBenjamin Graham's stock valuation formula for growth companies is based on the principle that a stock is a part of a business, and that by analyzing the fundamentals of any company in the stock market, you should be able to derive its intrinsic value independent from its current stock price. Graham suggests that over the long-term, the stock price of a company and its intrinsic/fair value will converge towards each other until the stock price reflects the true value of the company. Finally, Graham recommends that after estimating the intrinsic value of a stock, investors should always purchase the stock with a "margin of safety," to protect oneself from assumptions and potential errors made in the valuation process.
Graham's stock valuation formula to calculate intrinsic value was originally shown in the 1962 edition of Security Analysis as follows:
V = EPS * (8.5 + 2g)
where:
V = intrinsic value per share (over the next 7-10 years)
EPS = earnings per share (over the trailing twelve months (TTM))
8.5 = price-to-earnings (P/E) base for a no-growth company
g = reasonably expected annual growth rate (over the next 7-10 years)
In 1974, Graham revised this formula, as published in The Intelligent Investor, to include a discount rate (aka required rate of return). This was after he concluded that the greatest contributing to stock values and prices over the past decade had been due to interest rates.
Graham's current stock valuation formula is shown below:
V = (EPS * (8.5 + 2g) * Z) / Y
where:
V = intrinsic value per share (over the next 7-10 years)
EPS = diluted earnings per share (over the trailing twelve months (TTM))
8.5 = price-to-earnings (P/E) base for a no-growth company (you can change it manually)
g = reasonably expected annual growth rate (calculated by 5-Yr EPS CAGR%) (you can change year period)
Z = average yield of XXX Bonds (4.4 is default on Graham's formula)
Y = current yield of XXX Bonds
Current bond yield values (Z and Y) are selected as an example from Turkey. You need to change it according to the country of stocks.
Buy price (BP) = Intrinsic value per share * (1 - Margin of safety %)
Margin of safety = selected 20% (you need to change it to 0, if you don’t want to use margin of safety and to see intrinsic value)
Buy price > Current market price: Consider buying the stock, as the current market price appears to be undervalued.
Buy price < Current market price: Consider selling or not buying the stock, as the current market price appears to be overvalued.
Keep in mind that this buy/sell recommendation is purely based on Graham's stock valuation formula and the current market price, and ignores all other fundamental, news, and market factors investors should examine as well before making an investment decision.
Buy price is calculated for 5 different P/E values in the script.
1. with fixed P/E
2. with current P/E
3. with forward P/E
4. with sector P/E (optional)
5. with index P/E (optional)
You can also do calculations by using different growth rate by selecting that option.
Different type of moving averages is also included in the script as an option.
VWMACD Oscillator @shrilssThe VWMACD Oscillator is a unique and innovative trading indicator designed to provide insights into market momentum using the Volume Weighted Moving Average Convergence Divergence (VWMACD) concept. This script amalgamates various elements to offer a comprehensive view of market trends and potential reversal points.
Key Features:
- Fast Period: Adjust the fast moving average period to fine-tune the sensitivity of the indicator to short-term price movements.
- Slow Period: Set the slow moving average period to control the responsiveness of the indicator to longer-term trends.
- Signal Period: Determine the signal line period to smooth out fluctuations and identify potential trade signals.
- Longer Period: Define the longer period to capture extended trends and market cycles.
How it Works:
The VWMACD Oscillator is derived from the convergence and divergence of two volume-weighted moving averages. It combines the volume factor with the source input to create a robust momentum oscillator. The fast and slow moving averages are calculated by weighting the source with the corresponding volume, providing a unique perspective on market strength.
Dynamic Price Targets @shrilssDynamic Price Targets is a designed to provide traders with a comprehensive view of dynamic price levels based on Volume Weighted Moving Average (VWMA) and standard deviation. This script allows users to identify potential support and resistance zones, aiding in strategic decision-making during market analysis.
The script calculates the VWMA of a chosen price source over a specified length, establishing a dynamic baseline for market trends. The standard deviation is then used to derive multiple upper and lower targets, each representing a certain deviation from the VWMA. These levels are color-coded for clarity, with upper targets displayed in shades of red and lower targets in shades of green.
EMA Crossover Strategy with RSI Filter BIGTIME 5mThis script essentially creates a trading strategy that goes long when there is an EMA crossover, but only if the RSI is below a certain overbought level. It goes short when there is an EMA crossunder, but only if the RSI is above a certain oversold level. The moving averages are plotted on the chart for visual reference.
SCALPING 5m
Pairs: BIGTIME/USDT--- API3/USDT---BAKE/USDT--- ZIL/USDT
[blackcat] L1 Fibonacci MA BandThe true charm of the Fibonacci moving average band lies not only in its predictive ability. Its essence is that it combines the beauty of mathematics with the practicality of market analysis, providing traders with a powerful tool to optimize trading strategies. It's not a simple number game, but a wisdom that sees into the deeper structure of the market.
Next, we will delve into the core technical indicators of the Fibonacci moving average band - WHALES, RESOLINE, STICKLINE functions, and TRENDLINE, as well as their clever applications. The WHALES indicator, with its 12-period exponential moving average, captures short-term market trends; the RESOLINE indicator, through the 120-period EMA, reveals mid-term market movements; the STICKLINE function, distinguishes the relationship between WHALES and RESOLINE with colors, providing clear visual aids; while TRENDLINE, combining price slope with EMA, depicts more detailed market changes for traders.
The integrated application of these indicators has built a multi-dimensional market analysis framework for traders. They help traders examine the market from different angles, judge the market status more accurately, and make wiser decisions in the ever-changing market environment. The Fibonacci moving average band indicator is like a lighthouse, emitting guiding light in the ocean of trader's navigation.
1. `xsl(src, len)` function: This function calculates a value called the linear regression slope. Len defines the length of the linear regression. Then, this function normalizes the difference between the current value of the linear regression and the previous value. The formula is `(lrc - lrprev) / timeframe.multiplier`.
2. `whales`, `resoline`, and `trendline` are Exponential Moving Averages (EMA) calculated in different ways. "whales" is the 13-period closing price EMA, "resoline" is the 144-period closing price EMA, and "trendline" is a more complicated EMA. It is the 50-period EMA calculated by the 21-period closing price slope multiplied by 23 plus the closing price.
3. The `plotcandle` function draws two sets of candlestick charts. One set shows in blue when "whales" is greater than "resoline", and the other set shows in green when "whales" is less than "resoline".
4. The `plot` function draws three lines: "whales", "resoline", and "trendline". "whales" is displayed in orange with a line thickness of 2. "resoline" is displayed in yellow with a line thickness of 1. "trendline" is displayed in red with a line thickness of 3.
5. The last line draws a conditional line. When the closing price is less than the "trendline", the green "trendline" is drawn, otherwise, it is not drawn. This is a logical judgment, the drawing operation is only executed when the condition is met.
Institutional Demand and Supply Indicator- Professional Zones V1*** Technical Analysis intro to Demand & Supply Zones:
Analyzing supply and demand has become a prevalent approach for day and swing traders engaged in equity, forex, and futures markets. The objective of studying supply and demand zones is to anticipate potential price pivots before they occur, providing traders with a strategic advantage. While various charting and trading strategies fall within the supply and demand framework, our emphasis will primarily be on Institutional Zones of Demand and Supply Imbalances, as highlighted by our TradingView indicator.
See the demstration for what Demand & Supply Zones inbalances may look like:
To start, let's deconstruct the mentioned expression. The term 'institutional' holds significant importance in our trading approach. As a retail trader, it's crucial to grasp that individuals like you and me have minimal influence over and impact on price movements in major markets. The daily price fluctuations are primarily driven by substantial transactions conducted by large institutions and hedge funds, involving substantial quantities of buying and selling in the equity market.
The presented chart illustrates the price dynamics of ES, representing the S&P500 E-mini futures.
See the Example below for Demand & Supply Zones:
Recognizing the pivotal role of institutions in influencing market prices is essential for comprehending the creation of supply and demand imbalances. This understanding is derived from an analysis of historical price movements.
Price action manifests in two primary forms: balanced and imbalanced. Balanced price action represents a flat, consolidative market movement characterized by a sideways overall direction. In contrast, imbalanced price action denotes a pronounced upward or downward shift in price. The critical insight lies in the fact that institutional demand and supply imbalances emerge when the market transitions from balanced to imbalanced price action. The following illustration provides an example of balanced price action.
Below is example that measure the strength/ weakness of Demand & Supply zones!!!!
The duration of consolidation directly influences the size of the demand/supply zone, with its strength gauged by the originating time frame. Each zone may emerge on various time frames, ranging from the largest on the 1-Month time frame to the smallest on the 30-Minute time frame. Automatic labeling of supply and demand zones occurs based on their respective time frames.
Weaker zones are associated with the 30-Minute time frame, indicating a formation period of merely two 30-minute candles. This limited time span restricts the opportunity for institutions to execute substantial orders, resulting in smaller bounces and rejections, typically lasting no more than a few days.
In contrast, larger zones like 1 Day, 1 Week, and 1 Month have the potential to instigate significant market swings lasting for weeks, months, or even years. It is imperative to consider not only the current placement of demand and supply zones but also the strength associated with each zone. Examining the instance of the market bottoming and reversing, it becomes evident that the demand zone was notably robust, being a powerful weekly zone.
These zones operate on an order-based principle, distinguishing them from standard trend-based support and resistance levels. Unlike conventional levels, a supply zone doesn't transform into demand when price action surpasses it, and vice versa. If the price action drops below demand or above supply, even by a mere $0.01, indicating that all buy orders have been fulfilled, the demand or supply zone is then removed from the chart.
While it is feasible to approach these zone breaks as continuation opportunities based on the ongoing significant price action, predicting the extent of price movement after breaking supply or demand during that phase remains uncertain. Nevertheless, drawing upon my years of experience in demand and supply, I've observed a tendency for the market to eventually gravitate toward the next viable demand zone if the current one breaks. This is because without a pivot induced by an institutional-created demand or supply imbalance, there often lacks sufficient participation to sustain a prolonged trend reversal.
Limitations for the Indicator:
TradingView has a few constraints that impact the functionality of the Professional Zones - Institutional Supply and Demand Imbalances indicator. The primary limitation arises from the data provided by TradingView to its users. A basic TradingView account grants access to only 5,000 candles of data. Therefore, users operating on a 1-minute time frame can view a maximum of 5,000 candles leading up to the current point. This is crucial because our advanced indicator analyzes historical price action to identify demand and supply zones, displaying them on your chart. Consequently, users on a 1-minute time frame can only observe zones formed within the last 5,000 candles. Older demand and supply zones cannot be showcased. However, with a Premium TradingView subscription, users can access up to 20,000 candles, significantly expanding the potential zones visible on smaller time frames.
To address this limitation, we strongly recommend examining larger time frames before commencing your trading day, as there might be an older zone hidden from view. Once identified on, for instance, a 30-minute time frame, you can easily take note of the demand zone and its location.
Please Note for the what is offered in the indicator:
4 options to chose EMA/SMA/VMA/HMA
1 option to choose VWAP
Options to choose the on/off for Demand & Supply zones alone with to choose how it will read the candle pattern based on a "Use 2X Candle Logic & Factor %%
Options to choose zone labels on/off and Price levels on/off
Options to change the wording on "Demand Text": D to any wording
Options to change the wording on "Supply Text": S to any wording
Option to turn on /off broken zones
Option to choose how many zone extentions to show above or below price on chart
Option to choose on/off how many "TF" = Time Frames/ Zones from 1 week down to the 15 minutes
PS will try and update with charts and the setting box
Dual Dynamic Fibonacci Grouped Averages with Color ChangeRed Bearish Green Bullish
Using grouped fib averages, works similar to SMA
FluxFilter Trend Strategy [BITsPIP]Hello fellow traders, I'm excited to share with you the FluxFilter Trend Strategy, a trading approach I've developed for those interested in exploring trend-following strategies. My goal was to create something straightforward and accessible, so traders looking to refine their portfolios can easily integrate its features. By the end of this guide, I hope you'll have a solid grasp of how the FluxFilter Trend Strategy functions, appreciate its benefits, understand its potential drawbacks, and see how it might fit into various trading contexts.
I) Overview
The FluxFilter Trend Strategy is tailored to align with the market's long-term trend. It examines the price data from the previous year to gauge the market's overall trajectory by employing moving averages. Subsequently, within shorter timeframes, the strategy utilizes a combination of modified Supertrend, Hull Suite, and various trend-following and filtering techniques to generate buy or sell signals. Although its advanced take profit and stop loss mechanisms might initially present a learning curve, they are integral to the strategy's effectiveness. They are designed to secure gains by capturing prevailing trends and mitigating the impact of false reversal signals.
II) Deep Backtesting
Deep backtesting stands as a cornerstone in the development of trading strategies, offering a robust method for traders to assess the performance of their strategy against historical data. This process yields a retrospective view, illustrating how the strategy might have navigated through past market fluctuations, thereby shedding light on its potential robustness and areas for refinement. However, it's crucial to acknowledge that a strategy's performance can be influenced by a myriad of factors including market dynamics, the chosen timeframe, and the inherent attributes of the traded asset. Consequently, it's advisable to conduct thorough backtesting under various conditions to ascertain the strategy's reliability before applying it to actual trading scenarios.
III) Benefits
A primary advantage of the FluxFilter Trend Strategy is its proficiency in discerning genuine market trends from mere price fluctuations, thereby avoiding premature or uncertain trades. Unlike approaches that take high risks on speculative trades, this strategy prioritizes a high degree of confidence in the direction of the trade. It meticulously waits for a clear confirmation of the market trend. Once this certainty is established, the strategy promptly generates trade signals, ensuring that traders are positioned to capitalize on optimal market entry points without delay. This approach not only enhances the potential for profit but also aligns with a disciplined and methodical trading ethos.
IV) Applications
FluxFilter Trend Strategy can be applied across various timeframes, with a particular efficacy in those under 15 minutes. Its adaptable framework means it can be customized to cater to a variety of asset classes, encompassing stocks, commodities, forex, and cryptocurrencies. Initially, the strategy was specifically calibrated for low-volatile cryptocurrencies, as reflected in the default settings for stop loss and take profit values. It's important to recognize that the unique volatility and trend patterns of your selected market necessitate careful adjustments to these parameters. This fine-tuning of profit targets and stop loss thresholds is crucial for aligning the strategy with the specific dynamics of your chosen market, which I will discuss shortly.
V) Strategy's Logic
1. Trend Identification: My conviction lies in the power of trend trading to yield long-term gains. Central to the FluxFilter Trend Strategy is the Hull Suite indicator, a tool developed by InSilico, serving as one of the confirmation indicators. This indicator acts as a compass for trend direction; a price residing above the Hull Suite line signals an uptrend, potentially marking an entry point for a buy position or confirming it. In contrast, a price positioned below this line suggests a downtrend, potentially indicating a strategic moment to sell or confirming the sell.
2. Noise Reduction: The financial markets are known for their 'noise'—short-lived price movements that can obscure the true market direction. The FluxFilter Trend Strategy is designed to sift through this noise, thereby facilitating more lucid and informed trading decisions. It employs a set of straightforward yet innovative techniques to single out significant misleading fluctuations. This is achieved by analyzing recent bars to spot bars with unusually large bodies, which often represent misleading market noise.
3. Risk Management: A key facet of the strategy is its emphasis on pragmatic risk management. Traders are empowered to establish practical stop-loss and take-profit levels, tailoring these crucial parameters to the specific market they are engaging in. This customization is instrumental in optimizing long-term profitability, ensuring that the strategy adapts fluidly to the unique characteristics and volatility patterns of different trading environments.
VI) Strategy's Input Settings and Default Values
1. Modified Supertrend
i. Factor: Serving as a multiplier in the Average True Range (ATR) calculation, this parameter adjusts the distance of the Supertrend line relative to the price chart. Elevating the factor value widens the gap between the Supertrend line and price, offering a more conservative stance. On the flip side, diminishing the factor value pulls the Supertrend line closer to the price action, heightening its sensitivity. While the preset value is 1, you have the flexibility to modify this to suit your trading approach.
ii. ATR Length: This defines the count of bars that are incorporated into the ATR computation, directly influencing the Supertrend's adaptability to market changes. With a default setting of 30 bars, it strikes a balance, smoothing over short-term fluctuations while maintaining a meaningful sensitivity to market trends. Adjusting this parameter allows you to tailor the indicator's responsiveness to suit your trading strategy, considering the volatility and behavioral patterns of the asset you are trading.
2. Hull Suite
i. Hull Suite Length: Designed for capturing long-term trends, the Hull Suite Length is configured at 1000. Functioning comparably to moving averages, the Hull Suite features upper and lower bands, though these are not employed in our current strategy.
ii. Length Multiplier: It's advisable to maintain a minimal value for the Length Multiplier, prioritizing the optimization of the Hull Suite Length. Presently, it is set to 1.
3. Filtering Indicators
i. Fluctuation Filtering Percentage: It's advisable to set this parameter to ten times the size of the average bar in your specific market, as this helps effectively mitigate the impact of market fluctuations. While the initial default is 0.4(%), based on the BTCUSDT market, it's crucial to adjust this figure to align with the characteristics of different assets or markets you're trading in.
ii. Fluctuation Filtering Bars: This parameter designates the count of preceding bars to consider when assessing market fluctuations. It's fully customizable, allowing you to tailor it based on your market insights. The preset default is 3, a balance chosen to minimize susceptibility to potentially misleading signals.
iii. Trend Confirmation Percentage: This metric is pivotal for verifying the viability of a trend post-entry. If the trade doesn't achieve this percentage in profit, it indicates a deviation from the expected trend. Under such circumstances, it may be prudent to exit the trade prematurely rather than awaiting the stop-loss trigger. It's recommended to set this parameter at half the size of the average candle body for the market you're analyzing. The initial default is set at 0.2(%).
4. StopLoss and TakeProfit
i. StopLoss and TakeProfit Settings: Two distinct approaches are available. Semi-Automatic StopLoss/TakeProfit Setting and Manual StopLoss/TakeProfit Setting. The Semi-Automatic mode streamlines the process by allowing you to input values for a 5-minute timeframe, subsequently auto-adjusting these values across various timeframes, both lower and higher. Conversely, the Manual mode offers full control, enabling you to meticulously define TakeProfit values for each individual timeframe.
ii. TakeProfit Threshold # and TakeProfit Value #: Imagine this mechanism as an ascending staircase. Each step represents a range, with the lower boundary (TakeProfit Value) designed to close the trade upon being reached, and the upper boundary (TakeProfit Threshold) upon being hit, propelling the trade to the next level, and forming a new range. This stair-stepping approach enhances risk management and has the potential to increase profitability. The pre-set configurations are tailored for volatile markets, such as BTCUSDT. It's advisable to devote time to tailoring these settings to your specific market, aiming to achieve optimal results based on backtesting.
iii. StopLoss Value: In line with its name, this value marks the limit of loss you're prepared to accept should the market trend go against your expectations. It's crucial to note that once your asset reaches the first TakeProfit range, the initial StopLoss value becomes obsolete, supplanted by the first TakeProfit Value. The default StopLoss value is pegged at 1.8(%), a figure worth considering in your trading strategy.
VII) Entry Conditions
The principal element that triggers the signal is the Modified Supertrend. Additional indicators serve as confirmatory tools. Nonetheless, to refine your strategy effectively, it's crucial to fine-tune the parameters. This involves adjusting input variables such as take profit levels, threshold parameters, and the filtering values discussed previously.
VIII) Exit Conditions
The strategy stipulates exit conditions primarily governed by stop loss and take profit parameters. On infrequent occasions, if the trend lacks confirmation post-entry, the strategy mandates an exit upon the issuance of a reverse signal (whether confirmed or unconfirmed) by the strategy itself.
Good Luck!!
Clustered Asset Moving Average @shrilssThe Clustered Asset Moving Average script is designed to provide traders with a unique perspective on a cluster of multiple assets. By combining the closing prices and volumes of 12 specified assets, this indicator calculates a Clustered Moving Average to reveal potential trends and market sentiment within this asset cluster.
Key Features:
- Asset Cluster Analysis:
The script considers 12 assets, including well-known names such as Google (GOOG), Microsoft (MSFT), Apple (AAPL), Tesla (TSLA), and others.
It calculates the price and volume of each asset to form a comprehensive view of the asset cluster.
- Clustered Moving Average Calculation:
The Asset Price and Volume are combined to calculate the Clustered Moving Average
This moving average reflects the relationship between the aggregated price and volume of the specified assets.
- Multiple Exponential Moving Averages (EMA):
The script includes three EMAs (10, 25, and 100) applied to the Clustered Moving Average, providing different time perspectives.
Users can customize the visibility of each EMA based on their trading preferences.
- Visual Representation:
The indicator offers a visual representation of the Clustered Moving Average, allowing traders to quickly identify trends and potential reversal points.
Different EMAs are color-coded, enhancing visual clarity.
MTF MA ChaserThis is my own Moving Averages analysis tool, if anyone else will find it useful.
How It Works:
Upon adding the indicator to the chart, it calculates the selected Moving Averages for the defined timeframes. The main chart will display these MAs according to the user's chosen timeframe and type (default is the chart timeframe). Simultaneously, a table is generated on the chart, showcasing the percentage difference of the current price from these MAs across various timeframes. This table is color-coded to indicate different market states, such as proximity to MA/price crossovers.
Key Features:
Multi-Timeframe Analysis: Users can view Moving Average data from different timeframes (5m, 15m, 1H, 4H, 1D, 1W) on their current chart. This allows for quick and efficient analysis without the need to switch between different timeframe charts.
Variety of Moving Averages: The indicator supports different types of MAs, including EMA (Exponential Moving Average), SMA (Simple Moving Average), and others, providing flexibility in analysis.
Realtime Data Option: Users can choose to display real-time data for MAs, enabling them to make timely trading decisions based on the most current market information.
Customizable Display: The indicator features a customizable table that displays the MA values and their differences from the current price in percentages. Users can show or hide this table and adjust its position and text size according to their preference.
Limited Timeframe Support: The indicator is designed to work on equal or higher timeframes relative to the current chart's timeframe. It specifically supports 5-minute (5m), 15-minute (15m), 1-hour (1H), 4-hour (4H), 1-day (1D), and 1-week (1W) timeframes. This means if your current chart is set to a 1-hour timeframe, the indicator will only show MA data for 1-hour and longer timeframes (4H, 1D, 1W), but not for shorter ones like 5m or 15m.
Yet, you can go down to a 1 - 4 minute chart for scalping purposes if necessary.
Smart DCA StrategyINSPIRATION
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 BITSTAMP: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.
STRATEGY IN ACTION
Here you see the indicator running on the BITSTAMP:BTCUSD pair. You can read the indicator as follows:
Vertical green bands on historical candles represents where buy signals triggered in the past
Table on the top right represents the results of the A/B backtest against a standard DCA strategy
Green Smart Buy column shows that Smart DCA was more profitable than standard DCA on this backtest. That is shown by the percentage GOA (Gain on Account) and the Avg Cost
Smart Buy Zone label marks the threshold which the entire candle must be below to trigger a buy signal (line can be changed to a box under plotting settings)
Green color of Smart Buy Zone label represents that the open candle is still valid for a buy signal. A signal will only be generated if the candle closes while this label is still green
Below is the same BITSTAMP:BTCUSD chart a couple of days later. Notice how the threshold has been broken and the Smart Buy Zone label has turned from green to red. No buy signal can be triggered for this day - even if the candle retraced and closed below the threshold before daily candle close.
Notice how the green vertical bands tend to be present after significant pullbacks in price. This is the reason the strategy works! Below is the same BITSTAMP:BTCUSD chart, but this time zoomed out to present a clearer picture of the times it would invest vs times it would sit out of the market. You will notice it invests heavily in bear markets and significant pullbacks, and does not buy anything during bull markets.
Finally, to visually demonstrate the indicator on an asset other than BTC, here is an example on CRYPTO:ETHUSD . In this case the current daily high has not touched the threshold so it is still possible for this to be a valid buy trigger on daily candle close. The vertical green band will not print until the buy trigger is confirmed.
BACKTEST RESULTS
Now for some backtest results to demonstrate the improved performance over a standard DCA strategy using all non-stablecoin assets in the top 30 cryptos by marketcap.
I've used the TradingView ticker (exchange name denoted as CRYPTO in the symbol search) for every symbol tested with the exception of BTCUSD because there was some dodgy data at the beginning of the TradingView BTCUSD chart which overinflated the effectiveness of the Smart DCA strategy on that ticker. For BTCUSD I've used the BITSTAMP exchange data. The symbol links below will take you to the correct chart and exchange used for the test.
I'm using the GOA (Gain on Account) values to present how each strategy performed.
The value on the left side is the standard DCA result and the right is the Smart DCA result.
✅ means Smart DCA strategy outperformed the standard DCA strategy
❌ means standard DCA strategy outperformed the Smart DCA strategy
To avoid overfitting, and to prove that this strategy does not suffer from overfitting, I've used the exact same input parameters for every symbol tested below. The settings used in these backtests are:
Buying strictness scale: 9
Validation days: 0
You can absolutely tweak the values per symbol to further improve the results of each, however I think using identical settings on every pair tested demonstrates a higher likelihood that the results will be similar in the live markets.
I'm presenting results for two time periods:
First price data available for trading pair -> closing candle on Friday 26th Jan 2024 (ALL TIME)
Opening candle on Sunday 1st Jan 2023 -> closing candle on Friday 26th Jan 2024 (JAN 2023 -> JAN 2024)
ALL TIME:
BITSTAMP:BTCUSD 80,884% / 133,582% ✅
CRYPTO:ETHUSD 17,231% / 36,146% ✅
CRYPTO:BNBUSD 5,314% / 2,702% ❌
CRYPTO:SOLUSD 1,745% / 1,171% ❌
CRYPTO:XRPUSD 2,585% / 4,544% ✅
CRYPTO:ADAUSD 338% / 353% ✅
CRYPTO:AVAXUSD 130% / 160% ✅
CRYPTO:DOGEUSD 13,690% / 16,432% ✅
CRYPTO:TRXUSD 414% / 466% ✅
CRYPTO:DOTUSD -16% / -7% ✅
CRYPTO:LINKUSD 1,161% / 2,164% ✅
CRYPTO:TONUSD 25% / 47% ✅
CRYPTO:MATICUSD 1,769% / 1,587% ❌
CRYPTO:ICPUSD 70% / 50% ❌
CRYPTO:SHIBUSD -20% / -19% ✅
CRYPTO:LTCUSD 486% / 718% ✅
CRYPTO:BCHUSD -4% / 3% ✅
CRYPTO:LEOUSD 102% / 151% ✅
CRYPTO:ATOMUSD 46% / 91% ✅
CRYPTO:UNIUSD -16% / 1% ✅
CRYPTO:ETCUSD 283% / 414% ✅
CRYPTO:OKBUSD 1,286% / 1,935% ✅
CRYPTO:XLMUSD 1,471% / 1,592% ✅
CRYPTO:INJUSD 830% / 1,035% ✅
CRYPTO:OPUSD 138% / 195% ✅
CRYPTO:NEARUSD 23% / 44% ✅
Backtest result analysis:
Assuming we have an initial investment amount of $10,000 spread evenly across each asset since the creation of each asset, it would have provided the following results.
Standard DCA Strategy results:
Average percent return: 4,998.65%
Profit: $499,865
Closing balance: $509,865
Smart DCA Strategy results:
Average percent return: 7,906.03%
Profit: $790,603
Closing balance: $800,603
JAN 2023 -> JAN 2024:
BITSTAMP:BTCUSD 47% / 66% ✅
CRYPTO:ETHUSD 26% / 33% ✅
CRYPTO:BNBUSD 15% / 17% ✅
CRYPTO:SOLUSD 272% / 394% ✅
CRYPTO:XRPUSD 7% / 12% ✅
CRYPTO:ADAUSD 43% / 59% ✅
CRYPTO:AVAXUSD 116% / 151% ✅
CRYPTO:DOGEUSD 8% / 14% ✅
CRYPTO:TRXUSD 48% / 65% ✅
CRYPTO:DOTUSD 24% / 35% ✅
CRYPTO:LINKUSD 83% / 124% ✅
CRYPTO:TONUSD 7% / 21% ✅
CRYPTO:MATICUSD -3% / 7% ✅
CRYPTO:ICPUSD 161% / 196% ✅
CRYPTO:SHIBUSD 1% / 8% ✅
CRYPTO:LTCUSD -15% / -7% ✅
CRYPTO:BCHUSD 47% / 68% ✅
CRYPTO:LEOUSD 9% / 11% ✅
CRYPTO:ATOMUSD 1% / 15% ✅
CRYPTO:UNIUSD 9% / 23% ✅
CRYPTO:ETCUSD 27% / 40% ✅
CRYPTO:OKBUSD 21% / 30% ✅
CRYPTO:XLMUSD 11% / 19% ✅
CRYPTO:INJUSD 477% / 446% ❌
CRYPTO:OPUSD 77% / 91% ✅
CRYPTO:NEARUSD 78% / 95% ✅
Backtest result analysis:
Assuming we have an initial investment amount of $10,000 spread evenly across each asset for the duration of 2023, it would have provided the following results.
Standard DCA Strategy results:
Average percent return: 61.42%
Profit: $6,142
Closing balance: $16,142
Smart DCA Strategy results:
Average percent return: 78.19%
Profit: $7,819
Closing balance: $17,819
