Minervini Stage 2 AnalysisHandbook for Minervini Stage 2 Analysis Indicator
Introduction
This handbook provides detailed instructions and guidelines for using the Minervini Stage 2 Analysis Indicator based on Mark Minervini's swing trading methodology. This indicator is designed for traders focusing on US stocks, aiming to capture gains in medium to short-term uptrends (swing trading).
Understanding Stage 2
Stage 2 represents a bullish uptrend in a stock's price. Mark Minervini emphasizes entering long positions during this phase. The stage is identified using four key criteria related to moving averages (MAs).
Indicator Criteria
Stock Price Above MA 150 and 200: Indicates an overall uptrend.
MA 150 Above MA 200: Signals a stronger medium-term trend compared to the long-term trend.
MA 200 Trending Up for At Least 1 Month (22 Days): Confirms a stable uptrend.
MA 50 Above Both MA 150 and 200: Shows short-term strength and momentum.
Using the Indicator
Entering Trades: Consider long positions when all four criteria are met. This signifies that the stock is in a Stage 2 uptrend.
Monitoring Trades: Regularly check if the stock continues to meet these criteria. The indicator provides a clear visual and textual representation for ease of monitoring.
Alarm Signals and Exit Strategy
One Criterion Not Met: This serves as an alarm signal. Increased vigilance is required, and traders should prepare for a potential exit.
Two Criteria Not Met: Strong indication to close the trade. This suggests the stock may be transitioning out of Stage 2, increasing the risk of holding the position.
Risk Management
Stop-Loss Orders: Consider setting a trailing stop-loss to protect profits and minimize losses.
Position Sizing: Adjust position sizes according to your risk tolerance and portfolio strategy.
Volume and Relative Strength Analysis
Volume Analysis: Look for increased trading volume as confirmation when the stock price moves above key MAs.
Relative Strength (RS) Rating: Compare the stock's performance to the broader market to gauge its strength.
Limitations and Considerations
Market Conditions: The indicator's effectiveness may vary with market conditions. It is more reliable in a bullish market environment.
Supplementary Analysis: Combine this indicator with other analysis methods (fundamental, technical) for a holistic approach.
Continuous Learning: Stay updated with market trends and adjust your strategy accordingly.
Conclusion
The Minervini Stage 2 Analysis Indicator is a powerful tool for identifying potential long positions in uptrending stocks. Its reliance on specific criteria aligns with Mark Minervini's proven swing trading strategy. However, always exercise due diligence and risk management in your trading decisions.
Cerca negli script per "中国股票ETF"
The Flash-Strategy with Minervini Stage Analysis QualifierThe Flash-Strategy (Momentum-RSI, EMA-crossover, ATR) with Minervini Stage Analysis Qualifier
Introduction
Welcome to a comprehensive guide on a cutting-edge trading strategy I've developed, designed for the modern trader seeking an edge in today's dynamic markets. This strategy, which I've honed through my years of experience in the trading arena, stands out for its unique blend of technical analysis and market intuition, tailored specifically for use on the TradingView platform.
As a trader with a deep passion for the financial markets, my journey began several years ago, driven by a relentless pursuit of a trading methodology that is both effective and adaptable. My background in trading spans various market conditions and asset classes, providing me with a rich tapestry of experiences from which to draw. This strategy is the culmination of that journey, embodying the lessons learned and insights gained along the way.
The cornerstone of this strategy lies in its ability to generate precise long signals in a Stage 2 uptrend and equally accurate short signals in a Stage 4 downtrend. This approach is rooted in the principles of trend following and momentum trading, harnessing the power of key indicators such as the Momentum-RSI, EMA Crossover, and Average True Range (ATR). What sets this strategy apart is its meticulous design, which allows it to adapt to the ever-changing market conditions, providing traders with a robust tool for navigating both bullish and bearish scenarios.
This strategy was born out of a desire to create a trading system that is not only highly effective in identifying potential trade setups but also straightforward enough to be implemented by traders of varying skill levels. It's a reflection of my belief that successful trading hinges on clarity, precision, and disciplined execution. Whether you are a seasoned trader or just beginning your journey, this guide aims to provide you with a comprehensive understanding of how to harness the full potential of this strategy in your trading endeavors.
In the following sections, we will delve deeper into the mechanics of the strategy, its implementation, and how to make the most out of its features. Join me as we explore the nuances of a strategy that is designed to elevate your trading to the next level.
Stage-Specific Signal Generation
A distinctive feature of this trading strategy is its focus on generating long signals exclusively during Stage 2 uptrends and short signals during Stage 4 downtrends. This approach is based on the widely recognized market cycle theory, which divides the market into four stages: Stage 1 (accumulation), Stage 2 (uptrend), Stage 3 (distribution), and Stage 4 (downtrend). By aligning the signal generation with these specific stages, the strategy aims to capitalize on the most dynamic and clear-cut market movements, thereby enhancing the potential for profitable trades.
1. Long Signals in Stage 2 Uptrends
• Characteristics of Stage 2: Stage 2 is characterized by a strong uptrend, where prices are consistently rising. This stage typically follows a period of accumulation (Stage 1) and is marked by increased investor interest and bullish sentiment in the market.
• Criteria for Long Signal Generation: Long signals are generated during this stage when the technical indicators align with the characteristics of a Stage 2 uptrend.
• Rationale for Stage-Specific Signals: By focusing on Stage 2 for long trades, the strategy seeks to enter positions during the phase of strong upward momentum, thus riding the wave of rising prices and investor optimism. This stage-specific approach minimizes exposure to less predictable market phases, like the consolidation in Stage 1 or the indecision in Stage 3.
2. Short Signals in Stage 4 Downtrends
• Characteristics of Stage 4: Stage 4 is identified by a pronounced downtrend, with declining prices indicating prevailing bearish sentiment. This stage typically follows the distribution phase (Stage 3) and is characterized by increasing selling pressure.
• Criteria for Short Signal Generation: Short signals are generated in this stage when the indicators reflect a strong bearish trend.
• Rationale for Stage-Specific Signals: Targeting Stage 4 for shorting capitalizes on the market's downward momentum. This tactic aligns with the natural market cycle, allowing traders to exploit the downward price movements effectively. By doing so, the strategy avoids the potential pitfalls of shorting during the early or late stages of the market cycle, where trends are less defined and more susceptible to reversals.
In conclusion, the strategy’s emphasis on stage-specific signal generation is a testament to its sophisticated understanding of market dynamics. By tailoring the long and short signals to Stages 2 and 4, respectively, it leverages the most compelling phases of the market cycle, offering traders a clear and structured approach to aligning their trades with dominant market trends.
Strategy Overview
At the heart of this trading strategy is a philosophy centered around capturing market momentum and trend efficiency. The core objective is to identify and capitalize on clear uptrends and downtrends, thereby allowing traders to position themselves in sync with the market's prevailing direction. This approach is grounded in the belief that aligning trades with these dominant market forces can lead to more consistent and profitable outcomes.
The strategy is built on three foundational components, each playing a critical role in the decision-making process:
1. Momentum-RSI (Relative Strength Index): The Momentum-RSI is a pivotal element of this strategy. It's an enhanced version of the traditional RSI, fine-tuned to better capture the strength and velocity of market trends. By measuring the speed and change of price movements, the Momentum-RSI provides invaluable insights into whether a market is potentially overbought or oversold, suggesting possible entry and exit points. This indicator is especially effective in filtering out noise and focusing on substantial market moves.
2. EMA (Exponential Moving Average) Crossover: The EMA Crossover is a crucial component for trend identification. This strategy employs two EMAs with different timeframes to determine the market trend. When the shorter-term EMA crosses above the longer-term EMA, it signals an emerging uptrend, suggesting a potential long entry. Conversely, a crossover below indicates a possible downtrend, hinting at a short entry opportunity. This simple yet powerful tool is key in confirming trend directions and timing market entries.
3. ATR (Average True Range): The ATR is instrumental in assessing market volatility. This indicator helps in understanding the average range of price movements over a given period, thus providing a sense of how much a market might move on a typical day. In this strategy, the ATR is used to adjust stop-loss levels and to gauge the potential risk and reward of trades. It allows for more informed decisions by aligning trade management techniques with the current volatility conditions.
The synergy of these three components – the Momentum-RSI, EMA Crossover, and ATR – creates a robust framework for this trading strategy. By combining momentum analysis, trend identification, and volatility assessment, the strategy offers a comprehensive approach to navigating the markets. Whether it's capturing a strong trend in its early stages or identifying a potential reversal, this strategy aims to provide traders with the tools and insights needed to make well-informed, strategically sound trading decisions.
Detailed Component Analysis
The efficacy of this trading strategy hinges on the synergistic functioning of its three key components: the Momentum-RSI, EMA Crossover, and Average True Range (ATR). Each component brings a unique perspective to the strategy, contributing to a well-rounded approach to market analysis.
1. Momentum-RSI (Relative Strength Index)
• Definition and Function: The Momentum-RSI is a modified version of the classic Relative Strength Index. While the traditional RSI measures the velocity and magnitude of directional price movements, the Momentum-RSI amplifies aspects that reflect trend strength and momentum.
• Significance in Identifying Trend Strength: This indicator excels in identifying the strength behind a market's move. A high Momentum-RSI value typically indicates strong bullish momentum, suggesting the potential continuation of an uptrend. Conversely, a low Momentum-RSI value signals strong bearish momentum, possibly indicative of an ongoing downtrend.
• Application in Strategy: In this strategy, the Momentum-RSI is used to gauge the underlying strength of market trends. It helps in filtering out minor fluctuations and focusing on significant movements, providing a clearer picture of the market's true momentum.
2. EMA (Exponential Moving Average) Crossover
• Definition and Function: The EMA Crossover component utilizes two exponential moving averages of different timeframes. Unlike simple moving averages, EMAs give more weight to recent prices, making them more responsive to new information.
• Contribution to Market Direction: The interaction between the short-term and long-term EMAs is key to determining market direction. A crossover of the shorter EMA above the longer EMA is an indicator of an emerging uptrend, while a crossover below signals a developing downtrend.
• Application in Strategy: The EMA Crossover serves as a trend confirmation tool. It provides a clear, visual representation of the market's direction, aiding in the decision-making process for entering long or short positions. This component ensures that trades are aligned with the prevailing market trend, a crucial factor for the success of the strategy.
3. ATR (Average True Range)
• Definition and Function: The ATR is an indicator that measures market volatility by calculating the average range between the high and low prices over a specified period.
• Role in Assessing Market Volatility: The ATR provides insights into the typical market movement within a given timeframe, offering a measure of the market's volatility. Higher ATR values indicate increased volatility, while lower values suggest a calmer market environment.
• Application in Strategy: Within this strategy, the ATR is instrumental in tailoring risk management techniques, particularly in setting stop-loss levels. By accounting for the market's volatility, the ATR ensures that stop-loss orders are placed at levels that are neither too tight (risking premature exits) nor too loose (exposing to excessive risk).
In summary, the combination of Momentum-RSI, EMA Crossover, and ATR in this trading strategy provides a comprehensive toolkit for market analysis. The Momentum-RSI identifies the strength of market trends, the EMA Crossover confirms the market direction, and the ATR guides in risk management by assessing volatility. Together, these components form the backbone of a strategy designed to navigate the complexities of the financial markets effectively.
1. Signal Generation Process
• Combining Indicators: The strategy operates by synthesizing signals from the Momentum-RSI, EMA Crossover, and ATR indicators. Each indicator serves a specific purpose: the Momentum-RSI gauges trend momentum, the EMA Crossover identifies the trend direction, and the ATR assesses the market’s volatility.
• Criteria for Signal Validation: For a signal to be considered valid, it must meet specific criteria set by each of the three indicators. This multi-layered approach ensures that signals are not only based on one aspect of market behavior but are a result of a comprehensive analysis.
2. Conditions for Long Positions
• Uptrend Confirmation: A long position signal is generated when the shorter-term EMA crosses above the longer-term EMA, indicating an uptrend.
• Momentum-RSI Alignment: Alongside the EMA crossover, the Momentum-RSI should indicate strong bullish momentum. This is typically represented by the Momentum-RSI being at a high level, confirming the strength of the uptrend.
• ATR Consideration: The ATR is used to fine-tune the entry point and set an appropriate stop-loss level. In a low volatility scenario, as indicated by the ATR, the stop-loss can be set tighter, closer to the entry point.
3. Conditions for Short Positions
• Downtrend Confirmation: Conversely, a short position signal is indicated when the shorter-term EMA crosses below the longer-term EMA, signaling a downtrend.
• Momentum-RSI Confirmation: The Momentum-RSI should reflect strong bearish momentum, usually seen when the Momentum-RSI is at a low level. This confirms the bearish strength of the market.
• ATR Application: The ATR again plays a role in determining the stop-loss level for the short position. Higher volatility, as indicated by a higher ATR, would warrant a wider stop-loss to accommodate larger market swings.
By adhering to these mechanics, the strategy aims to ensure that each trade is entered with a high probability of success, aligning with the market’s current momentum and trend. The integration of these indicators allows for a holistic market analysis, providing traders with clear and actionable signals for both entering and exiting trades.
Customizable Parameters in the Strategy
Flexibility and adaptability are key features of this trading strategy, achieved through a range of customizable parameters. These parameters allow traders to tailor the strategy to their individual trading style, risk tolerance, and specific market conditions. By adjusting these parameters, users can fine-tune the strategy to optimize its performance and align it with their unique trading objectives. Below are the primary parameters that can be customized within the strategy:
1. Momentum-RSI Settings
• Period: The lookback period for the Momentum-RSI can be adjusted. A shorter period makes the indicator more sensitive to recent price changes, while a longer period smoothens the RSI line, offering a broader view of the momentum.
• Overbought/Oversold Thresholds: Users can set their own overbought and oversold levels, which can help in identifying extreme market conditions more precisely according to their trading approach.
2. EMA Crossover Settings
• Timeframes for EMAs: The strategy uses two EMAs with different timeframes. Traders can modify these timeframes, choosing shorter periods for a more responsive approach or longer periods for a more conservative one.
• Source Data: The choice of price data (close, open, high, low) used in calculating the EMAs can be varied depending on the trader’s preference.
3. ATR Settings
• Lookback Period: Adjusting the lookback period for the ATR impacts how the indicator measures volatility. A longer period may provide a more stable but less responsive measure, while a shorter period offers quicker but potentially more erratic readings.
• Multiplier for Stop-Loss Calculation: This parameter allows traders to set how aggressively or conservatively they want their stop-loss to be in relation to the ATR value.
Here are the standard settings:
Aleem Trend Supertrend EMA Title: "Supertrend and 200 EMA Crossover Strategy"
Description:
This script is designed to provide traders with a robust and original trading strategy by combining the Supertrend indicator with a 200-period Exponential Moving Average (EMA). The core concept is to utilize the strengths of both indicators to determine optimal entry and exit points.
The Supertrend indicator is well-regarded for its precision in signaling trend reversals by considering the volatility of the market, as measured by the Average True Range (ATR). It is particularly useful for identifying ongoing trends and potential reversals.
The 200 EMA is a widely-used indicator that many traders look to as a determinant of the long-term trend. When the price is above the 200 EMA, the overall market sentiment is considered bullish, and when below, bearish.
By combining these two, the script generates a Buy signal under the following conditions:
When the Supertrend turns bullish (color changes from red to green) with the closing price above the 200 EMA, or
When the price crosses above the 200 EMA while the Supertrend is already green.
A Sell signal is generated when:
The Supertrend turns bearish (color changes from green to red) with the closing price below the 200 EMA, or
The price crosses below the 200 EMA while the Supertrend is already red.
To avoid repetitive signals and to maintain clarity, the script has been enhanced with a feature to prevent multiple consecutive Buy or Sell signals. Once a Buy or Sell signal is generated, the script will not produce another identical signal until an opposing signal or an exit condition is met.
Exit signals for both Buy and Sell positions are provided to indicate when the trend is weakening or reversing, based on the Supertrend's color change in relation to the 200 EMA.
This strategy is flexible and can be utilized across various time frames and asset classes. It aims to aid traders in making more informed decisions by highlighting potential reversals and continuations in the market trend.
Usage:
To use this script, traders should observe the Buy and Sell signals as potential entry points. Exit signals should be taken as prompts to close positions or to protect profits with stop-loss adjustments. As with all strategies, it's recommended to use this in conjunction with other analysis methods and to backtest thoroughly before live implementation.
ZenTrend Price CyclesZenTrend attempts to plot the cycles that occur as the price cycles between the top and bottom of long- and short-term price linear regression channels.
The indicator observes a fast (35-period) and a slow (100-period) linear regression channel and plots their slopes on an oscillator. When the slope of the fast channel crosses above or below the slope of the slow channel, a signal is plotted.
The red line is the slope of the fast channel; blue is the slope of the slow channel
A green dot and background indicates the slope of recent price action has crossed above the slope of long-term price action.
A red dot and background indicates the slope of recent price action has crossed below the slope of long-term price action.
A gray dot indicates the slope of recent price action is slowing. The difference between the long- and short-term slopes is narrowing.
Here are things I look for when observing price cycles
Where does the cross occur? Crosses high above or below the 'zero line' indicate a more extreme change in price channel slopes.
Flat line: crosses that occur while the lines are flat often indicate chop.
"Curve" of the line - a cross that occurs as the slope lines are starting to curve up/down indicates a sharper and more extreme change in price channel slope.
Donchian Channels %I enjoy Donchian Channels for identifying trends. However, I hate having them on my chart. They are next to impossible to interpret at a glance. This script converts DCs to a % making a useful oscillator. The horizontal lines on the chart correspond to the Fib retracements below 50%. There are many ways to trade using this script and it works on any time frame. Moving average crosses are worth your attention, particularly, the 34 period MA (purple line). Enjoy and happy trading.
Optimized Alligator RateA less conventional way of utilizing the "Williams Alligator," the Optimized Rate uses the rate of change of the averages within the Alligator in order to potentially forecast with greater accuracy. The true optimization comes from the calculation of the "McGinley Dynamic" to create zero lag smoothed moving averages. It's important to note the standard Alligator has always used the SMMA. Lastly, divergence between the rates has been calculated in plotting for clarification.
Catching Trend Reversals by shorting tops and buying bottomsHOLP (High of the low period) and LOHP (Low of the high period)
Catching Trend Reversals by shorting tops and buying bottoms
using this Swing High/Low Indicator
Trading Strategy comes from Mastering the Trade, by John Carter pg 300.
Trading Rules for Sells, Buys are reversed
1. Identifying a trending market, where today's price is making a 20-day high (17-18 day highs are also fine)
Note this is configurable by setting the trending period variable (defaults to 20)
For example if price is making a 20 period high or 20 period low, it will show a triangle up/down above the candle.
2. Identify the high bar in the uptrend
3. Go short once the price action closes below the low of this high bar
4. The initial stop is the high of the high bar.
5. If you are in the trade on the third day or period, use a 2 bar trailing stop.
You can check 2-bar trailing stop to draw the line, defaults to off.
Stop is indicated by the white dot.
Code Converted from TradeStation EasyLanguage
I can't find the original source anymore for the swing high/low plots, but if someone knows,
let me know and I'll credit here.
Distribution Histogram [SS]This is the frequency histogram indicator. It does just that—creates a frequency histogram distribution based on your desired lookback period. It then uses Pine's new Polyline function to plot a normal curve of the expected results for a normal distribution. This allows you to see quite a few things:
🎯 Firstly, it allows you to see where the accumulation rests in terms of a bell curve. The histogram represents a bell curve, and you can visually observe what the curve would look like.
🎯 Secondly, it will assess the normal distribution and the degree of skewness based on the curve itself. The indicator imports the SPTS statistics library to assess the distribution using Kurtosis and Skewness. However, it also adds functionality in this regard by making a qualitative assessment of the data. For example, if there are heavy left tails or heavier right tails present in the histogram, the indicator will alert you that a heavier left or right tail has been observed.
🎯 Thirdly, it provides you with the kurtosis and skewness of the dataset.
🎯 Fourthly, it provides the mean, median, and mode of the dataset, as well as the maximum and minimum values within the dataset.
🎯 Lastly, it provides you with the ability to toggle on tips/explanations of the curve itself. Simply toggle on "Show Distribution Explanation" in the settings menu:
How is the indicator helpful for trading?
If you are a mean reversion trader, this helps you identify the areas and price ranges of high and low accumulation. It also allows you to ascertain the probability by looking at the standard deviation of the bell curve. Remember, the majority of values should fall between -1 and 1 standard deviation of the mean (68%).
If it is revealed that the distribution has a heavier right or left tail, you will know that the stock is more likely to experience sudden drops and shifts in the curve in one direction or the other. Heavier left tails will tend to shift to the values on the far left, and vice versa for right tails.
Customization
You can turn off and on the following:
👉 The normal curve,
👉 The standard deviation levels, and
👉 The distribution explanations and tips.
Conclusion: And that is the indicator! Hope you enjoy it!
Candle Counter from 9:30 AM to 4:00 PMThis Pine Script, designed for TradingView, serves as a candle counter exclusively for a 5-minute chart. It operates within the specific market hours of 9:30 AM to 4:00 PM. Key features of the script include:
Market Hours Specification: The script is configured to track candles only during the trading hours from 9:30 AM to 4:00 PM.
Daily Reset: Each trading day, the candle counter resets, starting anew from the market opening at 9:30 AM.
Candle Counting: It increments a counter with each 5-minute candle during the specified market hours.
Label Display: The counter number for each candle is displayed as a label at the candle's low point. This label is in bright white color with large font size, ensuring clear visibility against various chart backgrounds.
5-Minute Chart Specificity: The script is tailored to function only when the chart is set to a 5-minute timeframe, making it ideal for traders focusing on intraday movements.
New Day Detection: Utilizes a function to identify the start of a new trading day, ensuring accurate daily counting.
This script is particularly useful for traders who focus on intraday trading within the standard stock market hours, providing a clear and easy-to-read candle count that resets daily.
ATR Range Accumulation by Standard Deviation and Volume [SS]So, this is an indicator/premise I have been experimenting with, which mixes ATR with Z-Score and Volume metrics.
What does the indicator do?
The indicator, on the lower timeframes, uses an ATR approach to determine short-term ranges. It takes the average ATR range over a designated lookback period and plots out the levels like so:
It then calculates the Z-Score for these ATR targets (shown in the chart above) and calculates, over the designated lookback period, how often price accumulates at that standard deviation level.
The indicator is essentially a hybrid of my Z-Score Support and Resistance indicator and my frequency distribution indicator. It combines both concepts into one.
You also have the option of sorting by volume accumulation. This will display the accumulation of the ranges by volume accumulation, like so:
Larger Timeframes:
If you want to see the accumulation by volume or standard deviation on the larger timeframes, you can. Simply toggle on your preferred setting:
Show Total Accumulation Breakdown:
This will break down the levels, over the lookback period, by standard deviation. This is similar to the Z-Score support and resistance indicator. It will then show you how often price accumulates at these various standard deviation levels. Here is an example on the daily timeframe using the 1D chart settings:
Inversely, you can repeat this, with the Z-Score levels, but show accumulation by volume. This will print 5 boxes, which are between +3 Standard Deviations and -3 Standard Deviations, like so:
Here we can see that 61% of volume accumulation is between -1 and 1 standard deviation.
Using it to Trade:
For swing trading, I suggest using the larger timeframe information. However, for both swing and day traders, it is also helpful to use the ATR display. You can modify the ATR display to show the levels on any timeframe by selecting which timeframe you would like to see ATR ranges for. If you are trading on the 1 or 5-minute chart, I suggest leaving the levels at no shorter than a 60-minute timeframe.
You can also use these levels on the daily for the weekly levels, etc.
The accumulation being shown will be based on the current chart timeframe. This is a function of Pinescript, but in this case, it's actually advantageous because if you are trading on the shorter timeframe, and a level has 0% recent accumulation, it's unlikely we will see that level soon or overly quickly. Intraday retracements will generally happen to areas of high accumulation.
How this indicator is different:
The difference in this indicator comes from its focus on accumulation in relation to Standard Deviation. There is one thing that is consistent among retail traders, algorithms, market makers, and funds, and that is looking at the market in terms of standard deviation. Each person, market maker, and algorithm may be slightly nuanced in how it conceptualizes standard deviation (whether it be since the inception of the ticker (or IPO), or the previous 500 days, or the previous 100 days, etc.), but the premise remains consistent. Standard Deviation is a really important, if not the most important, metric to pay attention to. Another important metric is volume. Thus, the premise is that combining volume accumulation with standard deviation should, theoretically, be telling. We can see the extent of buying at various standard deviations and whether a stock is really a buy or not.
And that's the indicator! Hope you enjoy it. Leave your comments and questions below.
Safe trades!
Hi-Lo-GaugesIntroducing the 'Hi-Lo-Gauges' indicator, a powerful tool designed to provide a comprehensive visual representation of key price metrics. This indicator leverages up to 8 preset gauges, each catering to a specific aspect of market data:
All-time high and low
Current 52 Weeks high and low
Current Annual High and Low
Current Semi-Annual High and Low
Current Quarterly High and Low
Current Monthly High and Low
Current Weekly High and Low
Current Daily High and Low
Users have the flexibility to choose all 8 or selectively display specific gauges. For each metric, the gauge dynamically adapts, with the low value set as the minimum and the high value as the maximum. Measurement options include utilizing the highest and lowest closes or the literal highest and lowest prices.
The active price of the underlying asset serves as the reference point, allowing users to gauge the percentage move on the scale between the chosen minimum and maximum. Complete customization is at the users' fingertips, enabling them to tailor the indicator's appearance to suit their preferences.
With 'Hi-Lo-Gauges,' traders and analysts can intuitively monitor and interpret diverse price metrics, fostering a deeper understanding of market dynamics and supporting more informed decision-making.
Note: 'Hi-Lo-Gauges' is visible and applicable exclusively on the daily timeframe due to the nature of the metrics used.
TASC 2024.01 Gap Momentum System█ OVERVIEW
TASC's January 2024 edition of Traders' Tips features an article titled “Gap Momentum” by Perry J. Kaufman. The article discusses how a trader might create a momentum strategy based on opening gap data. This script implements the Gap Momentum system presented therein.
█ CONCEPTS
In the article, Perry J. Kaufman introduces Gap Momentum as a cumulative series constructed in the same way as On-Balance Volume (OBV) , but using gap openings (today’s open minus yesterday’s close).
To smoothen the resulting time series (i.e., obtain the " signal line "), the author applies a simple moving average . Subsequently, he proposes the following two trading rules for a long-only trading system:
• Enter a long position when the signal line is moving higher.
• Exit when the signal line is moving lower.
█ CALCULATIONS
The calculation of Gap Momentum involves the following steps:
1. Calculate the ratio of the sum of positive gaps over the past N days to the sum of negative gaps (absolute values) over the same time period.
2. Add the resulting gap ratio to the cumulative time series. This time series is the Gap Momentum.
3. Keep moving forward, as in an N-day moving average.
Price PressureDescription:
The Price Pressure Indicator, developed by OmegaTools, is a robust and versatile tool designed to assist traders in analyzing market dynamics and identifying potential trend shifts. This open-source script, offers a unique approach to understanding price pressure over specified periods, enhancing the user's ability to make informed trading decisions.
Key Features:
1. Dynamic Length Configuration: The indicator allows users to customize the length parameter, ranging from 9 to 100, providing flexibility in adapting to different market conditions.
2. Extensions Control: Traders can fine-tune the extension levels (ob) between 50 and 90, allowing for precise adjustments based on their risk tolerance and trading preferences.
3. Normalization and Oscillation: The script employs a normalization function to standardize price data, offering a clearer representation of market pressure. The resulting oscillator visualizes the normalized pressure, highlighting potential market trends.
4. Pressure Calculation: The indicator calculates price pressure by considering the difference between the previous high and the current close, as well as the difference between the current close and the previous low. This innovative approach enhances the accuracy of pressure analysis.
5. Smoothing Option: While the script currently uses a simple moving average for smoothing, traders have the option to explore other smoothing methods by uncommenting the "smt" input line.
6. Visual Clarity: The indicator provides a visually intuitive representation of pressure and signal lines, aiding traders in quickly interpreting market conditions. The color-coded display enhances user experience, with the ability to discern bullish and bearish pressures.
7. Premium and Discount Zones: The script identifies premium and discount areas, assisting traders in spotting potential buying or selling opportunities. The premium and discount lines can be adjusted based on individual risk tolerance and strategy.
How to Use:
1. Adjust the length and extension parameters based on your trading preferences.
2. Interpret the oscillator and signal lines for insights into market pressure.
3. Utilize premium and discount zones to identify potential entry or exit points.
4. Experiment with different smoothing options for a customized analysis.
Concepts and Methodology:
The Price Pressure Indicator utilizes a normalization function and oscillation to quantify market pressure. By calculating the difference between highs and lows, the script provides a nuanced understanding of current market conditions. The smoothing option further refines the analysis, offering traders a comprehensive tool for trend identification.
Explore, experiment, and leverage the power of the Price Pressure Indicator to enhance your trading strategy on TradingView.
Perfect RSIOverview:
The "Enhanced RSI" is a comprehensive TradingView indicator designed to provide traders with a nuanced and detailed analysis of market conditions using the Relative Strength Index (RSI). It amalgamates various RSI calculation methods to offer a more robust and adaptable approach to technical analysis.
Originality:
This script is unique in its synthesis of multiple RSI calculation techniques, including Regular RSI, Dynamic RSI, DMI RSI, Wilder's RSI, TSI RSI, Momentum RSI, and PPO RSI. By combining these methods, the script creates a distinctive and versatile tool for traders seeking a holistic view of RSI dynamics.
How It Works:
Diverse RSI Calculations:
Regular RSI: Calculates standard RSI with user-defined length and source.
Dynamic RSI: Adjusts RSI dynamically based on price movement direction.
DMI RSI: Uses Directional Movement Index for RSI calculation.
Wilder's RSI: Implements Wilder's smoothing technique for RSI.
TSI RSI: Utilizes True Strength Index for RSI calculation.
Momentum RSI: Calculates RSI based on momentum.
PPO RSI: Applies Percentage Price Oscillator for RSI calculation.
Composite RSI:
Combines the individual RSIs into three composite indices (RSI1, RSI2, RSI) using a weighted average approach.
Dynamic Level Adjustment:
Uses the correlation coefficient to dynamically adjust overbought and oversold levels, enhancing adaptability to market changes.
Visualization and Background Coloring:
Visualizes overbought and oversold zones on the chart.
Adjusts background color based on these conditions for clearer interpretation.
How to Use:
Installation:
Copy and paste the script into the Pine Editor on TradingView.
Adjust parameters as needed.
Analysis:
Utilize the "Enhanced RSI" as a comprehensive analysis tool for RSI dynamics.
Consider it as a confirmation tool alongside other technical indicators.
Customization:
Experiment with different RSI lengths and methods to align with your trading strategy.
Backtest the script to validate its effectiveness.
Considerations:
Complexity:
The script is sophisticated; users are advised to understand each calculation method before reliance.
Parameter Sensitivity:
Effectiveness may vary based on chosen parameters; thorough backtesting and parameter optimization are recommended.
Chaos CypherOverview
Technically a smooth linear rate transformation, the "Chaos Cypher" drew some inspiration from the principles of Markov and chaos. Aside from price action, this combination provides a different lens through which to observe and interpret market movements. Markov models are based on the principle that future states depend only on the current state, not on the sequence of events that preceded it. Chaos theory deals with systems that are highly sensitive to initial conditions, a concept popularly referred to as the butterfly effect.
Efficient with Minimal Data: Designed to perform efficiently, the CC indicator is particularly useful in situations regardless of extensive historical data, except for obvious back testing, while still providing strength at identifying potential overbought/oversold zones and critical divergences.
Simplified Momentum Analysis: With further inspiration from the triple smoothed exponential rate, the CC actually uses linear regression for its calculations. This approach allows for a clear and more straightforward identification of deviations in momentum. The smoothing helps allow it to provide details while still operating at a fast pace due to the regression speed.
Adaptable to Various Timeframes: The transformation calculation then employed effectively narrows its scope in relation to the pace, enhancing its applicability across multiple timeframes and periods. This flexibility makes it a versatile tool suitable for various strategies and market conditions.
Fisher Transform Style Presentation: The indicator is presented in a style reminiscent of the Fisher Transform. However, this method of the script recalculates based on every individual dataset. To maintain efficiency, the adjustable length only applies to the regression rate.
The Chaos Cypher when compared to the Fisher Transform
Inversion Option for Leads: Lastly, an intriguing find when testing this script is the potential of the inversion option. This aspect proved particularly useful when searching for pullbacks on a trending market.
Conclusion
This indicator is designed to be forward-thinking and attempts to combine theoretical concepts with practicality. It has the ability to work with minimal data, adapt to various timeframes, and provide clear views of market movements. It back tested very well even when unrealistically used as a sole instrument.
"Two states differing by imperceptible amounts may eventually evolve into two considerably different states ... If, then, there is any error whatever in observing the present state—and in any real system such errors seem inevitable—an acceptable prediction of an instantaneous state in the distant future may well be impossible....In view of the inevitable inaccuracy and incompleteness of weather observations, precise very-long-range forecasting would seem to be nonexistent." -Edward Norton Lorenz
Pipe tops & bottoms v1.0This indicator detects Pipe Tops and Pipe Bottoms chart patterns, using the concept described by Thomas Bulkowski: Tops , Bottoms .
Pipe tops and bottoms patterns are marked on the chart. You can change the indicator sensitivity by using the main settings which define detected price variation boundaries. This will lead to more dense or sparse pattern detection.
Once the bar following each detected top or bottom pattern satisfies signal condition (the current close price must be higher than the high of the pipe bottom, or lower than the low of the pipe top), these bars are also marked on the chart and can be used to define potential long or short entry points.
You can optionally choose to show only signal marks on the chart (this is preferable to avoid visual cluttering), or both pattern and signal marks.
Script calculations are based on the 'Pipe Bottoms Indicator Based on Thomas Bulkowski's Theories' indicator developed by BoilderRoomColdCaller in 2020.
Comparative Relative Strength AutoselectComparative Relative Strength (CRS) is a relative momentum indicator, used to compare a security against an index, or against another security. The comparison is used to show the relative performance to each other.
This script is a Quality of Life improvement, which attempts to match the base symbol to its relevant index on the local stock exchange. Thus automagically selecting the best and most relevant comparative symbol.
Features:
*optional comparative symbol override, in case your favourite index is not included in this script, or you want to force it to function as as a traditional cRS script without the autoselect feature.
* optional moving average crossover line
* optional absolute momentum calculation, calculating the excess return of the basesymbol and comparativesymbol against its own simple moving average.
ayogetit Trades™ Dynamic 5DMAThe Dynamic 5-Day Moving Average (MA) indicator is designed to provide traders with a consistent, time-adjusted moving average line across various timeframes. This indicator is especially useful for traders who switch between multiple timeframes and want a moving average that represents a fixed 5-day period, ensuring that the MA reflects a consistent lookback period relative to the amount of trading time each candle represents.
Features:
Timeframe Adaptability: Automatically adjusts the MA period to correspond to a 5-day lookback, regardless of the selected timeframe.
Intraday Precision: For intraday charts (5m, 15m, 30m, 1h, 2h, 4h), the indicator calculates the number of periods within the 5-day span based on the chart's timeframe.
Daily and Weekly Timeframe Compatibility: Sets the period to 5 for daily charts to maintain the 5-day MA, and to 1 for weekly charts, where each candlestick represents a week's worth of trading days.
Calculation Logic:
The indicator begins by defining the total number of trading minutes in 5 days, based on a standard 6.5-hour trading day.
A dynamic period calculation function then determines the number of those intervals that fit into the 5-day minute total for the selected timeframe.
For daily charts, the period is a straightforward 5, while for weekly charts, the period is set to 1, reflecting the average of the past 5 trading days.
GuageLibrary "Gauge"
The gauge library utilizes a gaugeParams object, encapsulating crucial parameters for gauge creation. Essential attributes include num (the measured value) , min (the minimum value equating to 100% on the gauge's minimum scale) , and max (the maximum value equating to 100% on the gauge's maximum scale) . The size attribute (defaulting to 10) splits the scale into increments, each representing 100% divided by the specified size.
The num value dynamically shifts within the gauge based on its percentage move from the mathematical average between min and max . When num is below the average, the minimum portion of the scale activates, displaying the appropriate percentage based on the distance from the average to the minimum. The same principle applies when num exceeds the average. The 100% scale is reached at either end when num equals min or max .
The library offers full customization, allowing users to configure color schemes, labels, and titles. The gauge can be displayed either vertically (default) or horizontally. The colors employ a gradient, adapting based on the number's movement. Overall, the gauge library provides a flexible and comprehensive tool for visualizing and interpreting numerical values within a specified range.
OneThingToRuleThemAll [v1.4]This script was created because I wanted to be able to display a contextual chart of commonly used indicators for scalping and swing traders, with the ability to control the visual representation on the charts as their cross-overs, cross-unders, or changes of state happen in real time. Additionally, I wanted the ability to control how or when they are displayed. While looking through other community projects, I found they lacked the ability to full customize the output controls and values used for these indicators.
The script leverages standard RSI/MACD/VWAP/MVWAP/EMA calculations to help a trader visually make more informed decisions on entering or exiting a trade, depending on their understanding on what the indicators represent. Paired with a table directly on the chart, it allows a trader to quickly reference values to make more informed decisions without having to look away from the price action or look through multiple indicator outputs.
The main functionality of the indicator is controlled within the settings directly on the chart. There a user can enable the visual representations, or disable, and configure how they are displayed on the charts by altering their values or style types.
Users have the ability to enable/disable visual representations of:
The indicator chart
RSI Cross-over and RSI Reversals
MACD Uptrends and Downtrends
VWAP Cross-overs and Cross-unders
VWAP Line
MVWAP Cross-overs and Cross-unders
MVWAP Line
EMA Cross-overs and Cross-unders
EMA Line
Some traders like to use these visual indications as thresholds to enter or exit trades. Its best to find out which ones work the best with the security you are trying to trade. Personally, I use the table as a reference in conjunction with the RSI chart indicators to help me decide a logical trailing stop if I am scalping. Some users might like the track EMA200 crossovers, and have visual representations on the chart for when that happens. However, users may use the other indicators in other methods, and this script provides the ability to be able to configure those both visually and by value.
The pine script code is open source and itself is fairly straightforward, it is mostly written to provide the ultimate level of control the the user of the various indicators. Please reach out to me directly if you would like a further understanding of the code and an explanation on anything that may be unclear.
Enjoy :)
-dead1.
SMA Cross with a Price FilterA moving average strategy generates an entry (buy) signal when the price goes above the moving average, and an exit (sell) signal when the price goes below the moving average. But it gives lots of whipsaws and noise depends on the moving average we use. A fast moving average gives more whipsaws and a slow moving average gives less whipsaws. To reduce the noise/whipsaws, we can add a filter on a fast/slow moving average. It will improve entry/exit performance significantly specially for those who don't want to watch the market actively.
I created this indicator with a price filter. This means the price of an underlying asset must be at least a specific percentage above its moving average to generate a buy signal and a specific percentage below its moving average to generate a sell signal. This price filter can also be a confirmation after the price crosses above/below its SMA. I couldn't find any indicator yet based on this idea. So I wrote this indicator and publishing it so it helps those who are interested.
I use 200 SMA and 3% price filter as default and using SPY as an example. So,
ENTRY signal when the closing price of SPY is 3% above its 200 SMA.
EXIT signal when the closing price of SPY is 3% below its 200 SMA.
Enjoy and let me know if it works.
** This chart only generates entry (buy) and exit (sell) signals. Please, do your own diligence to make any investment or trading decisions.
Capital Accumulation Plan (CAP) Simulator 2.0Description:
This indicator serves as a simulation tool for the Capital Accumulation Plan (CAP). The CAP is an investment strategy involving regular contributions of a fixed amount at consistent intervals, regardless of market fluctuations. This simulator allows you to visualize how your invested capital might grow over time, considering a fixed monthly investment in a given financial instrument.
How to Use:
Customize the monthly investment amount, the day of the month for the investment, and the simulation period. Also, input the percentage of taxation on potential dividends and the Total Expense Ratio (TER) of the financial instrument. The indicator calculates the portfolio value over time, the invested capital, and the average cost. If applicable, it also calculates the dividend amounts over time and the corresponding taxes to be paid.
The indicator displays how these metrics would change over time following the PAC strategy.
Important Notes:
Apply exclusively to the daily chart; a fix for the chosen day absence will be implemented shortly.
Advanced Divergence OscillatorIntroduction to ADO
The Advanced Divergence Oscillator (ADO) is a modern tool crafted for traders in various markets like stocks, forex, or cryptocurrencies. Imagine it as a smart gadget that helps you understand the ebb and flow of market prices. Unlike standard tools, ADO provides a more nuanced view, enabling you to grasp subtle changes in market trends.
Functionality of ADO
ADO operates by observing and comparing market price movements over different timeframes. Picture a racetrack where cars are moving at various speeds. Some are racing ahead, while others are gradually picking up pace. ADO keeps track of these varying 'speeds' in market prices.
By analyzing these movements, ADO generates a smooth, flowing line – the oscillator. This line moves in a wave-like pattern, offering hints about the market's momentum and possible future trends. When the line moves up, it suggests increasing prices, and when it moves down, it hints at falling prices.
How to Use ADO
Setup: You can easily integrate ADO into your trading platform, adjusting settings like length and color to suit your preference.
Reading the Oscillator: Watch for the oscillator's movement. Rising and falling patterns can indicate potential buying or selling opportunities.
Identifying Divergences: ADO excels in spotting divergences – situations where market prices and the oscillator don't align. For instance, if prices are climbing but the oscillator is falling, it might signal a potential price drop ahead.
Brief History of the Ultimate Oscillator
The concept of oscillators in trading isn’t new. The Ultimate Oscillator, developed by Larry Williams in the 1970s, is a foundational tool in this field. Williams' innovation was to combine short, intermediate, and long-term market trends into a single oscillator. This approach offered a more comprehensive market view, helping traders make informed decisions.
The ADO is a step further in this evolution. It takes the core principles of the Ultimate Oscillator and enhances them with proper smoothing and divergence detection methods. This evolution represents the continuous effort in the trading community to refine tools for better market analysis and decision-making.
