Turn of the Month Strategy on Steroids█ STRATEGY DESCRIPTION
The "Turn of the Month Strategy on Steroids" is a seasonal mean-reversion strategy designed to capitalize on price movements around the end of the month. It enters a long position when specific conditions are met and exits when the Relative Strength Index (RSI) indicates overbought conditions. This strategy is optimized for use on daily or higher timeframes.
█ WHAT IS THE TURN OF THE MONTH EFFECT?
The Turn of the Month effect refers to the observed tendency of stock prices to rise around the end of the month. This strategy leverages this phenomenon by entering long positions when the price shows signs of a reversal during this period.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The current day of the month is greater than or equal to the specified `dayOfMonth` threshold (default is 25).
The close price is lower than the previous day's close (`close < close `).
The previous day's close is also lower than the close two days ago (`close < close `).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
There is no existing open position (`strategy.position_size == 0`).
2. EXIT CONDITION
A Sell Signal is generated when the 2-period RSI exceeds 65, indicating overbought conditions. This prompts the strategy to exit the position.
█ ADDITIONAL SETTINGS
Day of Month: The day of the month threshold for triggering a Buy Signal. Default is 25.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed to exploit seasonal price patterns around the end of the month.
It performs best in markets where the Turn of the Month effect is pronounced.
Backtesting results should be analyzed to optimize the `dayOfMonth` threshold and RSI parameters for specific instruments.
دورات
Consecutive Bars Above/Below EMA Buy the Dip Strategy█ STRATEGY DESCRIPTION
The "Consecutive Bars Above/Below EMA Buy the Dip Strategy" is a mean-reversion strategy designed to identify potential buying opportunities when the price dips below a moving average for a specified number of consecutive bars. It enters a long position when the dip condition is met and exits when the price shows strength by exceeding the previous bar's high. This strategy is suitable for use on various timeframes.
█ WHAT IS THE MOVING AVERAGE?
The strategy uses either a Simple Moving Average (SMA) or an Exponential Moving Average (EMA) as a reference for identifying dips. The type and length of the moving average can be customized in the settings.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The close price is below the selected moving average for a specified number of consecutive bars (`consecutiveBarsTreshold`).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
2. EXIT CONDITION
A Sell Signal is generated when the current closing price exceeds the high of the previous bar (`close > high `). This indicates that the price has shown strength, potentially confirming the reversal and prompting the strategy to exit the position.
█ ADDITIONAL SETTINGS
Consecutive Bars Threshold: The number of consecutive bars the price must remain below the moving average to trigger a Buy Signal. Default is 3.
MA Type: The type of moving average used (SMA or EMA). Default is SMA.
MA Length: The length of the moving average. Default is 5.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for mean-reverting markets and performs best when the price frequently oscillates around the moving average.
It is sensitive to the number of consecutive bars below the moving average, which helps to identify potential dips.
Backtesting results should be analysed to optimize the Consecutive Bars Threshold, MA Type, and MA Length for specific instruments.
Turn around Tuesday on Steroids Strategy█ STRATEGY DESCRIPTION
The "Turn around Tuesday on Steroids Strategy" is a mean-reversion strategy designed to identify potential price reversals at the start of the trading week. It enters a long position when specific conditions are met and exits when the price shows strength by exceeding the previous bar's high. This strategy is optimized for ETFs, stocks, and other instruments on the daily timeframe.
█ WHAT IS THE STARTING DAY?
The Starting Day determines the first day of the trading week for the strategy. It can be set to either Sunday or Monday, depending on the instrument being traded. For ETFs and stocks, Monday is recommended. For other instruments, Sunday is recommended.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The current day is the first day of the trading week (either Sunday or Monday, depending on the Starting Day setting).
The close price is lower than the previous day's close (`close < close `).
The previous day's close is also lower than the close two days ago (`close < close `).
The signal occurs within the specified time window (between `Start Time` and `End Time`).
If the MA Filter is enabled, the close price must also be above the 200-period Simple Moving Average (SMA).
2. EXIT CONDITION
A Sell Signal is generated when the current closing price exceeds the high of the previous bar (`close > high `). This indicates that the price has shown strength, potentially confirming the reversal and prompting the strategy to exit the position.
█ ADDITIONAL SETTINGS
Starting Day: Determines the first day of the trading week. Options are Sunday or Monday. Default is Sunday.
Use MA Filter: Enables or disables the 200-period SMA filter for long entries. Default is disabled.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for markets with frequent weekly reversals.
It performs best in volatile conditions where price movements are significant at the start of the trading week.
Backtesting results should be analysed to optimize the Starting Day and MA Filter settings for specific instruments.
9:00 AM CR ModelHow to Trade the 9:00 a.m. CR Model
Define the Range:
8:00 a.m. Hourly Candle:
On the 1-hour chart, mark the high and low of the 8:00 a.m. candle.
9:00 a.m. 15-Minute Candle:
After it closes at 9:15 a.m., mark its high and low.
Identify Setup:
Turtle Soup (False Breakout):
Look for price to wick above the high (bearish) or below the low (bullish) and reverse.
Enter at a validated level (e.g., order block, fair value gap).
Breakout:
Confirm a close above the high (bullish) or below the low (bearish).
Use Fibonacci to find the midpoint (EQ) of the breakout candle and enter at that level.
Entry Rules:
Bullish Setup:
Enter below the open of the relevant candle after manipulation or breakout.
Bearish Setup:
Enter above the open of the relevant candle after manipulation or breakout.
Targets:
Opposite end of the range.
Key levels (e.g., prior highs/lows or standard deviations).
Take partials at the midpoint of the range.
Risk Management:
Always validate entries using key levels or Turtle Soup setups.
Avoid setups where the midpoint (EQ) is not hit.
TRBO COGThe TRBO COG indicator is a MACD-based tool
that enables users to identify the current trend, helping them make informed decisions on whether to call or put.
This indicator is essential for traders looking to accurately assess market conditions and make strategic trading choices.
By utilizing the TRBO COG indicator, users can gain valuable insights into market trends and optimize their trading strategies for success.
Introduction to the TRBO COG Indicator
Overview of TRBO COG and its Purpose.
trade smart by using this tool.
The Importance of Trend Identification in Trading
1. Introduction to the TRBO COG Indicator
Overview of TRBO COG and its Purpose
The TRBO COG indicator is a nifty tool designed to help traders identify the current trend in the market, giving them a better understanding of whether to go long or short on their trades. It's like having a crystal ball that whispers trend secrets to you (minus the mystical ambiance).
The Importance of Trend Identification in Trading
In the wild world of trading, identifying the trend is like knowing which way the wind is blowing. It guides you in making informed decisions, prevents you from swimming against the tide, and increases your chances of catching profitable waves. Ignoring the trend is like trying to salsa dance to a waltz – not pretty.
2. Understanding the MACD-Based Functionality
Explanation of MACD and its Role in TRBO COG
MACD, short for Moving Average Convergence Divergence, plays a crucial role in the TRBO COG indicator. It's like the secret sauce that gives your trend analysis that extra kick. MACD helps smooth out price data, making it easier to spot trend changes and potential entry points. It's like having a seasoned detective in your trading toolkit.
How MACD Enhances Trend Analysis
By using MACD in the TRBO COG indicator, traders can dive deeper into trend analysis, identifying shifts in momentum and potential trend reversals. It's like having x-ray vision in a world full of market noise – helping you cut through the clutter and focus on what really matters.
3. Utilizing TRBO COG for Trend Identification
Step-by-Step Guide to Using TRBO COG
Using the TRBO COG indicator is as easy as making a cup of tea (well, almost). Simply input the indicator into your trading platform, follow the signals it generates, and voilà – you have a clearer picture of the prevailing trend. It's like having a trusty sidekick whispering trend insights in your ear.
Interpreting TRBO COG Signals for Trend Direction
When the TRBO COG indicator flashes its signals, it's like a lighthouse guiding you through stormy seas. Pay attention to the signals it provides – whether it indicates a bullish or bearish trend – and use this information to steer your trading decisions in the right direction. It's like having a compass in a sea of uncertainty.
4. Key Features and Components of TRBO COG
Overview of TRBO COG Components
The TRBO COG indicator consists of various components that work together to give you a holistic view of the trend. From trend lines to momentum indicators, each component plays a vital role in helping you navigate the market terrain. It's like having a full arsenal of tools at your disposal.
Understanding the Parameters for Customization
Customization is key when using the TRBO COG indicator. By tweaking the parameters to suit your trading style and preferences, you can fine-tune the indicator to provide you with tailored trend insights. It's like having a bespoke suit made – perfectly fitting and tailored to your needs.
5. Strategies for Making Informed Call Decisions
Using TRBO COG to Determine Call Timing
Timing is everything when it comes to trading, and the TRBO COG indicator can be a valuable tool in helping you pinpoint the optimal moment to make a call. By analyzing the convergence and divergence of the indicator lines, you can get a clearer picture of when the trend is in your favor, enabling you to make more informed decisions on when to enter or exit a trade.
Risk Management Techniques in Combination with TRBO COG
While the TRBO COG indicator can provide valuable insights into market trends, it's essential to pair this information with effective risk management techniques. Setting stop-loss orders, diversifying your portfolio, and avoiding emotional trading can all help mitigate potential losses and maximize your gains when using TRBO COG to inform your call decisions.
6. Case Studies and Real-World Applications
Examples of TRBO COG in Action
To truly understand the power of the TRBO COG indicator, looking at real-world examples can provide valuable insights. By examining how the indicator has been used in specific trading scenarios, you can gain a better understanding of its practical applications and potential outcomes in different market conditions.
Lessons Learned from Real Trading Scenarios
Reflecting on past trading experiences where TRBO COG was employed can offer valuable lessons for future decision-making. Understanding what worked well and what didn't in previous trades can help you refine your strategies and improve your overall trading performance when using the TRBO COG indicator.
7. Tips for Effective Implementation and Monitoring
Best Practices for Applying TRBO COG in Trading
When incorporating the TRBO COG indicator into your trading strategy, it's essential to follow best practices to maximize its effectiveness. This may include combining it with other technical indicators, testing different settings, and staying informed about market trends to make the most informed call decisions possible.
Monitoring and Adjusting TRBO COG Settings for Optimal Results
Market conditions can change rapidly, so regularly monitoring and adjusting your TRBO COG settings is crucial for achieving optimal results. By staying vigilant and adapting to evolving market trends, you can ensure that the indicator continues to provide you with accurate insights to inform your call decisions effectively.
8. Conclusion: Enhancing Decision-Making with TRBO COG
In conclusion, the TRBO COG indicator offers traders a valuable tool for identifying current trends and making informed call decisions. By understanding how to use the indicator to determine call timing, implementing effective risk management techniques, learning from real-world case studies, and following best practices for implementation and monitoring, traders can enhance their decision-making process and increase their chances of success in the market.
Conclusion: Enhancing Decision-Making with TRBO COG
Relative Risk MetricOVERVIEW
The Relative Risk Metric is designed to provide a relative measure of an asset's price, within a specified range, over a log scale.
PURPOSE
Relative Position Assessment: Visualizes where the current price stands within a user-defined range, adjusted for log scale.
Logarithmic Transformation: Utilizes the natural log to account for a log scale of prices, offering a more accurate representation of relative positions.
Calculation: The indicator calculates a normalized value via the function Relative Price = / log(UpperBound) − log(LowerBound) . The result is a value between 0 and 1, where 0 corresponds to the lower bound and 1 corresponds to the upper bound on a log scale.
VISUALIZATION
The indicator plots three series:
Risk Metric - a plot of the risk metric value that’s computed from an asset's relative price so that it lies within a logarithmic range between 0.0 & 1.0.
Smoothed Risk Metric - a plot of the risk metric that’s been smoothed.
Entry/Exit - a scatter plot for identified entry and exit. Values are expressed as percent and are coded as red being exit and green being entity. E.g., a red dot at 0.02 implies exit 2% of the held asset. A green dot at 0.01 implies use 1% of a designated capital reserve.
USAGE
Risk Metric
The risk metric transformation function has several parameters. These control aspects such as decay, sensitivity, bounds and time offset.
Decay - Acts as an exponent multiplier and controls how quickly dynamic bounds change as a function of the bar_index.
Time Offset - provides a centering effect of the exponential transformation relative to the current bar_index.
Sensitivity - controls how sensitive to time the dynamic bound adjustments should be.
Baseline control - Serves as an additive offset for dynamic bounds computation which ensures that bounds never become too small or negative.
UpperBound - provides headroom to accomodate growth an assets price from the baseline. For example, an upperbound of 3.5 accommodates a 3.5x growth from the baseline value (e.g., $100 -> $350).
LowerBound - provides log scale compression such that the overall metric provides meaningful insights for prices well below the average whilst avoiding extreme scaling. A lowerbound of 0.25 corresponds to a price that is approx one quarter of a normalised baseline in a log context.
Weighted Entry/Exit
This feature provides a weighted system for identifying DCA entry and exit. This weighting mechanism adjusts the metric's interpretation to highlight conditions based on dynamic thresholds and user-defined parameters to identify high-probability zones for entry/exit actions and provide risk-adjusted insights.
Weighting Parameters
The weighting function supports fine-tuning of the computed weighted entry/exit values
Base: determines the foundational multiplier for weighting the entry/exit value. A higher base amplifies the weighting effect, making the weighted values more pronounced. It acts as a scaling factor to control the overall magnitude of the weighting.
Exponent: adjusts the curve of the weighting function. Higher exponent values increase sensitivity, emphasizing differences between risk metric values near the entry or exit thresholds. This creates a steeper gradient for the computed entry/exit value making it more responsive to subtle shifts in risk levels.
Cut Off: specifies the maximum percentage (expressed as a fraction of 1.0) that the weighted entry/exit value can reach. This cap ensures the metric remains within a meaningful range and avoids skewing
Exit condition: Defines a threshold for exit. When the risk metric is below the exit threshold (but above the entry threshold) then entry/exit is neutral.
Entry condition: Defines a threshold for entry. When the risk metric is above the entry threshold (but below the exit threshold) then entry/exit is neutral.
Weighting Behaviour
For entry conditions - value is more heavily weighted as the metric approaches the entry threshold, emphasizing lower risk levels.
For exit conditions - value is more heavily weighted as the metric nears the exit threshold, emphasizing increased risk levels.
USE-CASES
Identifying potential overbought or oversold conditions within the specified logarithmic range.
Assisting in assessing how the current price compares to historical price levels on a logarithmic scale.
Guiding decision-making processes by providing insights into the relative positioning of prices within a log context
CONSIDERATIONS
Validation: It's recommended that backtesting over historical data be done before acting on any identified entry/exit values.
User Discretion: This indicator focus on price risk. Consider other risk factors and general market conditions as well.
TASC 2025.02 Autocorrelation Indicator█ OVERVIEW
This script implements the Autocorrelation Indicator introduced by John Ehlers in the "Drunkard's Walk: Theory And Measurement By Autocorrelation" article from the February 2025 edition of TASC's Traders' Tips . The indicator calculates the autocorrelation of a price series across several lags to construct a periodogram , which traders can use to identify market cycles, trends, and potential reversal patterns.
█ CONCEPTS
Drunkard's walk
A drunkard's walk , formally known as a random walk , is a type of stochastic process that models the evolution of a system or variable through successive random steps.
In his article, John Ehlers relates this model to market data. He discusses two first- and second-order partial differential equations, modified for discrete (non-continuous) data, that can represent solutions to the discrete random walk problem: the diffusion equation and the wave equation. According to Ehlers, market data takes on a mixture of two "modes" described by these equations. He theorizes that when "diffusion mode" is dominant, trading success is almost a matter of luck, and when "wave mode" is dominant, indicators may have improved performance.
Pink spectrum
John Ehlers explains that many recent academic studies affirm that market data has a pink spectrum , meaning the power spectral density of the data is proportional to the wavelengths it contains, like pink noise . A random walk with a pink spectrum suggests that the states of the random variable are correlated and not independent. In other words, the random variable exhibits long-range dependence with respect to previous states.
Autocorrelation function (ACF)
Autocorrelation measures the correlation of a time series with a delayed copy, or lag , of itself. The autocorrelation function (ACF) is a method that evaluates autocorrelation across a range of lags , which can help to identify patterns, trends, and cycles in stochastic market data. Analysts often use ACF to detect and characterize long-range dependence in a time series.
The Autocorrelation Indicator evaluates the ACF of market prices over a fixed range of lags, expressing the results as a color-coded heatmap representing a dynamic periodogram. Ehlers suggests the information from the periodogram can help traders identify different market behaviors, including:
Cycles : Distinguishable as repeated patterns in the periodogram.
Reversals : Indicated by sharp vertical changes in the periodogram when the indicator uses a short data length .
Trends : Indicated by increasing correlation across lags, starting with the shortest, over time.
█ USAGE
This script calculates the Autocorrelation Indicator on an input "Source" series, smoothed by Ehlers' UltimateSmoother filter, and plots several color-coded lines to represent the periodogram's information. Each line corresponds to an analyzed lag, with the shortest lag's line at the bottom of the pane. Green hues in the line indicate a positive correlation for the lag, red hues indicate a negative correlation (anticorrelation), and orange or yellow hues mean the correlation is near zero.
Because Pine has a limit on the number of plots for a single indicator, this script divides the periodogram display into three distinct ranges that cover different lags. To see the full periodogram, add three instances of this script to the chart and set the "Lag range" input for each to a different value, as demonstrated in the chart above.
With a modest autocorrelation length, such as 20 on a "1D" chart, traders can identify seasonal patterns in the price series, which can help to pinpoint cycles and moderate trends. For instance, on the daily ES1! chart above, the indicator shows repetitive, similar patterns through fall 2023 and winter 2023-2024. The green "triangular" shape rising from the zero lag baseline over different time ranges corresponds to seasonal trends in the data.
To identify turning points in the price series, Ehlers recommends using a short autocorrelation length, such as 2. With this length, users can observe sharp, sudden shifts along the vertical axis, which suggest potential turning points from upward to downward or vice versa.
MCDX_SignalThe MCDX indicator (Market Cycle Dynamic Index) is a technical indicator developed by Trung Pham. It is a tool used for analyzing the stock market, often utilized to identify big money flow (Big Money) and evaluate the strength of individual stocks or the overall market.
MCDX is known for its distinctive histogram chart with red and green bars. The red bars typically represent the inflow of big money, while the green bars indicate small money flow or outflows.
Volume Surge Webhook AlertThis TradingView indicator, named "Volume Surge Webhook Alert," is designed to find significant increases in trading volume and send out alerts with key information. It works by looking back at the volume over a certain number of past candlesticks, which you can set using the "Lookback Period" input. The indicator calculates the average volume during this period. Then, it sets a threshold for what counts as a "volume surge." This threshold is a percentage increase over the average volume, and you can adjust this percentage using the "Volume Surge Threshold (%)" input.
When the current candlestick's volume is higher than this threshold, the indicator considers it a volume surge. To help you see this visually, the indicator plots three lines on a separate chart: the average volume (in blue), the current volume (in red), and the threshold volume (in gray circles).
If a volume surge happens, the indicator creates a webhook alert. This alert sends a message in a structured format (like a digital envelope) that contains the following information: the symbol of the stock or cryptocurrency, the timeframe of the chart you're looking at, the current volume, the average volume, the threshold volume, and a simple message saying a volume surge was detected. This alert is sent only once when the candlestick closes with a volume surge.
Additionally, when a volume surge is detected, a small red exclamation mark "!" will appear above that candlestick on the main price chart.
Essentially, this indicator helps traders spot times when trading volume is unusually high, which can sometimes be a sign of important price movements. You can customize how sensitive the indicator is by changing the "Lookback Period" and the "Volume Surge Threshold (%)". The webhook alerts allow you to be notified automatically when these surges occur, so you don't have to constantly watch the charts.
MTF Fractal Bias Confluence DetectorMTF Fractal Bias Confluence Detector
This indicator, the MTF Fractal Bias Confluence Detector, is based on the idea that the market exhibits fractal behaviour. The origin of the idea traces back to 1963, when Benoit Mandelbrot analyzed the fluctuations in cotton prices over a time series starting in 1900, discovering that price changes exhibited scale-invariant patterns. This means that the curve representing daily price changes mirrored the shape of monthly price changes, highlighting the fractal nature of market behaviour. When applied to swing points across multiple timeframes (MTF), this concept suggests that swing points demonstrate similar patterns regardless of the timeframe being analyzed. These self-similar fractal structures provide traders with insights into market reversals and trends, making them a powerful tool for multi-timeframe analysis.
A Swing Point is made up of three main parts: a move away from the last Break level; forming a peak (pivot point) with a Fakeout of the peak (explained through an example later); and a subsequent move away from it. These swing points recur across all timeframes as part of cyclical momentum patterns, meaning each swing point gives rise to a new cycle of market movement. Due to the fractal nature of the market, larger cycles encompass multiple smaller ones.
The theory behind the Fractal Bias Confluence Detector utilizes the idea that the market movements are fractal in nature and illustrates how such swing points can be identified across MTFs. To do so, we examine the Peak Fakeouts within these cycles, as they form. It is not possible to know in advance how long each of these moves will last, but a Swing Point will often occur with a Peak Fakeout. Therefore, the most critical element is to identify the Peak Fakeout.
The snapshot below captures a Peak Fakeout, as discussed earlier.
Similarly, the following snapshot shows various possible breakdowns of Higher Time Frame (HTF) cycles into smaller Lower Time Frame (LTF) movements. The chart contains a white table(not part of the indicator and shown for illustration purposes only).
To further illustrate. Consider the combination of Time Frames (TF) from the 2nd row (from the above snapshot). Cycle TF (1M), Setup TF (1W), Momentum TF (1D) etc.
Price movements in the 1M TF highlight the direction in which HTF traders are pushing the market. Often, when markets have broken out of a level, they tend to form a peak and can then pull back towards the prior breakout level. Once the pullback is beyond the last breakout level, in the opposite direction, we may say the peak formation is created, and directional bias has changed. This is also called Peak Fakeout. Due to the fractal nature of the market, Swing Points on the HTF will often constitute multiple Swing Points on the LTF, though they are not always in sync. However, after such peak formation, there is a high probability that the price might move away from the peak for at least 1 candle (in the cycle TF). This theory illustrates that once a new cycle is in play, we can then look at 1W (Setup TF) to look for possible in-sync movements, at least within that 1 candle of the HTF. Repeating the same for further lower TFs, we may arrive at a confluence of Fractal Bias and see how the movements in LTF are driven by the HTF momentum.
Another example within the chart:
Note: The above examples are just for illustration purposes, and other permutations and combinations of movements across multiple TFs are also possible.
This indicator aims to help users identify such fractal-bias-confluences, so that they can leverage the fractal nature of the market to get a holistic view. To do so, the indicator displays how the market has moved across multiple time frames, with respect to different historical levels.
Features:
1. The bias summary table
The following snapshot depicts the bias summary table at the bottom right of the chart.
1.1. Workings: The table will display, for various TFs, in the first four (starting from "current" to Prev ) rows, one of the following.
"F/H" , " Acronym for the failed break of the previous high",
"F/L" , " Acronym for the failed break of the previous low",
"B/H" , " Acronym for the break of the previous high",
"B/L" , " Acronym for the break of the previous low",
"IN" , " Acronym for an inside candle (never broke high or low of perv candle)",
"OT" , " Acronym for an outside candle (broke both high and low of previous candle and closing price is in between previous high and low)".
Note: these acronyms are customizable according to the user's choice of terminology in any language, as shown in the snapshot below.
1.1.1 In the above snapshot, the 1st row, called "Current", shows how the current candle is evolving with respect to the previous one. The "previous" row shows how the previous candle closed with respect to the pre-previous one. The next two rows represent the bias of the pre-previous and pre-pre-previous in a similar manner. By default, the bias is updated in real-time, even for the already closed historical candles. For example, if the previous 4H candle closed as a B/H and the current price then comes below the pre-previous 4H candle high, then the bias of the previous candle will get updated to F/H. This informs the user that the break above the pre-previous high has failed. However, the user has the option to turn this off. The information in these four rows shows the user how the market is moving currently and how it evolved before reaching the current price levels.
Note: The calculation done by the indicator is to keep track of how the price is moving with respect to the last candle levels in real-time. This means if the price first goes above the previous high and then goes below the previous low, the indicator is equipped to display what happened in the most recent time. The snapshot below shows the option to turn on/off such updates in the bias summary table.
Note: While the bias summary table is turned on, the user also has the option to turn off Prev and Prev rows, as shown in the snapshot below.
1.1.2 The 2nd to last row, called CL/CS(Consecutive Long/Short), shows whether consecutive (2+) breaks of high/low happened or not in one direction without taking out the previous candle's range in the opposite direction. When conditions are met, it will show the number of times the price has been pushed in one direction (in the above manner), followed by "L" for long and "S" for short, for each TF, for example, "4L". It gets updated in real-time for each push in the same direction. Furthermore, a good analogy of "4L" on an HTF is 4 consecutive Break of Structure (BOS) (in the same direction) on LTF, without a Change of Character (CHoCH). Another example would be Stacey Burke's 3 consecutive rises that can be mapped in the indicator, if the conditions are met for "3L" for a given TF.
1.1.3 The last row, FRC/FGC, stands for the first red/green candle. It shows whether the last candle of a TF has closed as green (i.e., close>open) after posting two red candles (i.e., close<open). This helps understand possible short-term retracements in price movements.
1.2 Customizability
1.2.1 We provide a wide range of customizable options, including multiple time frames to choose from for each type of TFs. This is shown in the snapshot below.
1.2.2 All the acronyms on the summary table are customizable and can be user-defined, including text, background color and transparency. This is shown in the snapshot below.
2. High-low lines
2.1 We also show the high and low of various TFs, including the current high and low lines (which are updated in real-time. This can be observed in one of the previous snapshots.
2.2 Previous high, low and close lines can be extended (for Cycles, Setups and Momentum TFs). Their style and thickness are also customizable. This can be observed in one of the previous snapshots.
Note: The user has the option to turn all the lines off. Sub-options include turning off the current line only. Changing the color, thickness, and transparency of the lines. This can be observed in one of the previous snapshots.
3. Last known Break / Failed Break lines.
3.1 We also depict the last known Break and Failed break lines for the user to have all the important levels at their disposal. This can be observed in one of the previous snapshots.
Note: The user has the option to turn this on/off.
4. Magnifier Box
4.1 We have provided the user to look at thirty 1m candles inside a magnifier box while they are in a higher TF chart.
The user has the option to turn this on/off.
5. Moving Averages (MA)
We have also grouped some built-in MA options for the user to utilize along with other elements of the indicator to help them get another layer of confluence.
The user has the option to turn this on/off.
Disclaimer:
The indicator leverages pre-existing theories of market movements. These can be found in decades-old published materials (like books, journals, public lectures accessible over popular video-sharing websites, etc.). As such, we do not claim to have any exclusive rights over the underlying theories. There are many analogous theories and nomenclatures that users can map onto this indicator. Users may also use the indicator in combination with other indicators.
1. Educational Use Only
The "MTF Fractal Bias Confluence Detector" is provided for educational purposes only. It does not constitute an offer, or an obligation, or a guarantee, of profitable trades or loss prevention.
2. No Financial Advice
This tool should not be viewed as financial advice for either trading or investment(s).
3. User Responsibility
Users alone bear all risks associated with any decisions they make using this tool. Past performance does not guarantee future results.
By using the "MTF Fractal Bias Confluence Detector," you acknowledge that you have read, understood and accepted this disclaimer in its entirety.
Rosiz Support 2### **Indicator Name**: Custom RSI, Stochastic, and ADX
### **Description**:
This is a multi-functional indicator that combines three popular technical analysis tools—**RSI (Relative Strength Index)**, **Stochastic Oscillator**, and **ADX (Average Directional Index)**—into a single, customizable pane. This indicator helps traders analyze momentum, overbought/oversold conditions, and trend strength simultaneously, making it a powerful tool for making informed trading decisions.
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### **Features**:
1. **RSI (Relative Strength Index)**:
- Measures the speed and change of price movements.
- Helps identify overbought (>70) and oversold (<30) conditions.
- Includes customizable length and source options.
- Background shading visually highlights overbought and oversold zones.
2. **Stochastic Oscillator**:
- Determines momentum by comparing a security's closing price to its price range over a specific period.
- Includes %K and %D lines for crossovers, which signal potential entry or exit points.
- Highlights overbought (>80) and oversold (<20) zones with background fill.
3. **ADX (Average Directional Index)**:
- Measures trend strength (higher values indicate stronger trends).
- Includes customizable smoothing and DI (Directional Indicator) length.
---
### **How to Use**:
- **RSI**: Look for overbought or oversold conditions for potential reversal points. Divergences between price and RSI may signal weakening trends.
- **Stochastic Oscillator**: Watch for %K and %D crossovers near overbought or oversold zones to confirm buy or sell signals.
- **ADX**: Use ADX values to assess trend strength:
- **ADX > 25**: Strong trend.
- **ADX < 20**: Weak or ranging market.
---
### **Customization Options**:
- **RSI Settings**: Adjust length, source, and visual parameters.
- **Stochastic Settings**: Modify %K and %D lengths and smoothing factors.
- **ADX Settings**: Fine-tune smoothing and directional index lengths.
---
### **Advantages**:
- Combines three indicators into one, reducing chart clutter.
- Customizable inputs for flexibility in various trading strategies.
- Visual enhancements (background fills and lines) for better readability.
This indicator is perfect for traders looking to combine momentum analysis, overbought/oversold signals, and trend strength in a single tool!
[GrandAlgo] Impulse & Balance
The Impulse & Balance indicator identifies and labels three key levels—Impulse, Balance, and Apex—offering traders a structured and dynamic view of market behavior. Starting with the detection of Impulse levels, the indicator calculates corresponding Balance zones and Apex levels to provide actionable insights into price movement, potential reversals, and trend stability.
This indicator adapts seamlessly to all timeframes and market types, giving traders a powerful tool for understanding market dynamics and refining their strategies.
How It Works:
Impulse: Identifies critical price levels where significant market conditions occur. These Impulse levels serve as the foundation for calculating Balance and Apex levels.
Balance: Derived from Impulse levels, Balance zones mark areas of equilibrium where price tends to stabilize. These zones often act as key support or resistance areas.
Apex: The Apex is calculated as a pivotal level where price momentum within the Impulse reaches a peak, highlighting potential reversal or reaction points.
The indicator dynamically updates these levels in real-time as price evolves, ensuring that traders always have the most relevant data on their charts.
Key Features:
Automatically detects Impulse, Balance, and Apex levels for structured market analysis.
Continuously recalculates levels in real-time as price action evolves.
Offers customizable parameters for sensitivity and detection range.
Works seamlessly across all timeframes and market types.
Provides clear visual labels for effortless interpretation.
Use Cases:
Spot potential reversal zones or price reaction points using Apex levels.
Identify key price stabilizations with Balance zones for support and resistance analysis.
Monitor Impulse levels for insights into significant market conditions and momentum.
Suitable for various instruments, including Forex, crypto, stocks, and indices.
Month Separator
Month Separator Indicator
This Pine Script indicator separates each month on the chart by visually marking the change between months.
Features:
The indicator detects when the month changes.
It highlights the background with a semi-transparent blue color to differentiate the months.
A small red triangle is plotted at the top of the chart at the beginning of each new month, providing a clear visual cue.
Customization:
You can easily adjust the colors or styles in the script by modifying the bgcolor and plotshape functions.
The indicator works on all timeframes, but it is especially useful on higher timeframes (like daily or weekly charts) to track monthly transitions.
This script is ideal for traders who want a clear visual representation of month boundaries to analyze trends and key levels more effectively.
BTC ETF Inflows and Outflows with Combined BTC CorrelationThis script tracks Bitcoin Spot ETF inflows and outflows, calculating their correlation with Bitcoin's price to identify market trends and sentiment. It provides visual insights into ETF flows and the relationship with BTC price movements.
NOTE: The script relies on volume and opens / closes for calculating inflows and outflows. An ETF might issue more shares, which would skew the numbers.
Alternate RTH Background OnlyThis “Alternate RTH Background Only” script highlights the chart background in alternating colors for each new day during the regular trading session (9:30–16:00 EST). It detects the start of a new calendar day (midnight) to increment its day counter, then applies a different semi-transparent color to the 9:30–16:00 bars for easy daily separation. No lines or indicators are plotted—only the background shading changes each day.
BTC-SPX Momentum Gauge + EMA SignalHere's an explanation of the market dynamics and signal benefits of this script:
Momentum and Sentiment Indicator:
The script uses the momentum of the S&P 500 to change the chart's background color, providing a quick visual cue of market sentiment. Green indicates potential bullish momentum in the broader market, while red suggests bearish momentum. This can help traders gauge overall market direction at a glance.
Bitcoin Trend Analysis:
By plotting the scaled TEMA of Bitcoin (BTC), traders can see how Bitcoin's trend correlates or diverges from the current asset being analyzed. Since Bitcoin is often viewed as a hedge against traditional financial systems or inflation, its trend can signal broader economic shifts or investor sentiment towards alternative investments.
Dual Trend Confirmation:
The script offers two trend lines: one for Bitcoin and one for the current ticker. When these lines move in tandem, it might indicate a strong market trend across both traditional and crypto markets. Divergence between these lines can highlight potential market anomalies or opportunities for arbitrage or hedging.
Smoothness vs. Reactivity:
The use of TEMA for Bitcoin provides a smoother signal than a simple moving average, reducing lag while still reacting to price changes. This can be particularly useful for identifying longer-term trends in Bitcoin's volatile market. The 20-period EMA for the current ticker, on the other hand, gives a quicker response to price changes in the asset you're directly trading.
Cross-Asset Correlation:
By overlaying Bitcoin's trend on another asset's chart, traders can analyze how these markets might influence each other. For instance, if Bitcoin is in an uptrend while a traditional asset is declining, it might suggest capital rotation into cryptocurrencies.
Trading Signals:
Crossovers or divergences between the TEMA of Bitcoin and the EMA of the current ticker could be used as signals for entry or exit points. For example, if the BTC TEMA crosses above the current ticker's EMA, it might suggest a shift towards crypto assets.
Risk Management:
The visual cues from the background color and moving averages can aid in risk management. For example, trading in the direction of the momentum indicated by the background color might be seen as going with the market flow, potentially reducing risk.
Macro-Economic Insights:
The relationship between Bitcoin and traditional markets can offer insights into macroeconomic conditions, particularly related to inflation, monetary policy, and investor sentiment towards fiat currencies.
Headwind and tailwind:
Currently BTC correlated trade instruments experience headwind or tailwind from the broader market. This indicator lets the user see it to help their trade decision process.
Additional Statement:
As the market realizes the dangers of the fiat that its construct is built upon and evolves and migrates into stable money, incorruptible by inflation, this indicator will reveal the external influence of that corruptible and the internal influence of the incorruptible; having diminishing returns as the rise of stable money overtakes the treasuries of the fiat construct.
G. Santostasi's Bimodal Regimes Power Law G. Santostasi's Bimodal Regimes Power Law Model
Invite-Only TradingView Indicator
The Bimodal Power Law Model is a powerful TradingView indicator that provides a detailed visualization of Bitcoin's price behavior relative to its long-term power law trend. By leveraging volatility-normalized deviations, this model uncovers critical upper and lower bounds that govern Bitcoin’s price dynamics.
Key Features:
Power Law Support Line:
The model highlights the power law support line, a natural lower bound that has consistently defined Bitcoin's price floor over time. This line provides a crucial reference point for identifying accumulation zones.
Volatility-Normalized Upper Bound:
The indicator introduces a volatility-normalized upper channel, dynamically defined by the deviations from the power law. This bound represents the natural ceiling for Bitcoin’s price action and adjusts in real time to reflect changes in market volatility.
Color-Shaded Volatility Bounds:
The upper and lower bounds are visualized as color-shaded regions that represent the range of current volatility relative to the power law trend. These shaded regions dynamically expand or contract based on the level of market volatility, providing an intuitive view of Bitcoin’s expected price behavior under normalized conditions.
Two Regime Analysis:
Using a Gaussian Hidden Markov Model (HMM), the indicator separates Bitcoin's price action into two distinct regimes:
Above the power law:
Bullish phases characterized by overextensions.
Below the power law:
Bearish or accumulation phases where price consolidates below the trend.
Dynamic Bounds with Standard Deviations:
The model plots 2 standard deviation bands for both regimes, offering precise insights into the natural limits of Bitcoin’s price fluctuations. Peaks exceeding these bounds are contextualized as anomalies caused by historically higher volatility, emphasizing the consistency of normalized deviations.
Enhanced Visualization and Analysis:
The indicator integrates running averages calculated using deviations from the power law trend and smoothed volatility data to ensure a visually intuitive representation of Bitcoin’s price behavior. These insights help traders and researchers identify when price action is approaching statistically significant levels.
Use Cases:
Support and Resistance Identification:
Use the power law support line and upper volatility bounds to identify critical levels for buying or taking profit.
Cycle Analysis:
Distinguish between sustainable trends and speculative bubbles based on deviations from the power law.
Risk Management:
The shaded volatility regions provide a dynamic measure of risk, helping traders gauge when Bitcoin is overbought or oversold relative to its historical norms.
Market Timing: Understand Bitcoin’s cyclical behavior to time entries and exits based on its position within the shaded bounds.
Note:
This indicator is designed for long-term Bitcoin investors, researchers, and advanced traders who seek to leverage statistical regularities in Bitcoin’s price behavior. Available by invitation only.
Timed Ranges [mktrader]The Timed Ranges indicator helps visualize price ranges that develop during specific time periods. It's particularly useful for analyzing market behavior in instruments like NASDAQ, S&P 500, and Dow Jones, which often show reactions to sweeps of previous ranges and form reversals.
### Key Features
- Visualizes time-based ranges with customizable lengths (30 minutes, 90 minutes, etc.)
- Tracks high/low range development within specified time periods
- Shows multiple cycles per day for pattern recognition
- Supports historical analysis across multiple days
### Parameters
#### Settings
- **First Cycle (HHMM-HHMM)**: Define the time range of your first cycle. The duration of this range determines the length of all subsequent cycles (e.g., "0930-1000" creates 30-minute cycles)
- **Number of Cycles per Day**: How many consecutive cycles to display after the first cycle (1-20)
- **Maximum Days to Display**: Number of historical days to show the ranges for (1-50)
- **Timezone**: Select the appropriate timezone for your analysis
#### Style
- **Box Transparency**: Adjust the transparency of the range boxes (0-100)
### Usage Example
To track 30-minute ranges starting at market open:
1. Set First Cycle to "0930-1000" (creates 30-minute cycles)
2. Set Number of Cycles to 5 (will show ranges until 11:30)
3. The indicator will display:
- Range development during each 30-minute period
- Visual progression of highs and lows
- Color-coded cycles for easy distinction
### Use Cases
- Identify potential reversal points after range sweeps
- Track regular time-based support and resistance levels
- Analyze market structure within specific time windows
- Monitor range expansions and contractions during key market hours
### Tips
- Use in conjunction with volume analysis for better confirmation
- Pay attention to breaks and sweeps of previous ranges
- Consider market opens and key session times when setting cycles
- Compare range sizes across different time periods for volatility analysis
SCE Price Action SuiteThis is an indicator designed to use past market data to mark key price action levels as well as provide a different kind of insight. There are 8 different features in the script that users can turn on and off. This description will go in depth on all 8 with chart examples.
#1 Absorption Zones
I defined Absorption Zones as follows.
//----------------------------------------------
//---------------Absorption---------------------
//----------------------------------------------
box absorptionBox = na
absorptionBar = ta.highest(bodySize, absorptionLkb)
bsab = ta.barssince(bool(ta.change(absorptionBar)))
if bsab == 0 and upBar and showAbsorption
absorptionBox := box.new(left = bar_index - 1, top = close, right = bar_index + az_strcuture, bottom = open, border_color = color.rgb(0, 80, 75), border_width = boxLineSize, bgcolor = color.rgb(0, 80, 75))
absorptionBox
else if bsab == 0 and downBar and showAbsorption
absorptionBox := box.new(left = bar_index - 1, top = close, right = bar_index + az_strcuture, bottom = open, border_color = color.rgb(105, 15, 15), border_width = boxLineSize, bgcolor = color.rgb(105, 15, 15))
absorptionBox
What this means is that absorption bars are defined as the bars with the largest bodies over a selected lookback period. Those large bodies represent areas where price may react. I was inspired by the concept of a Fair Value Gap for this concept. In that body price may enter to be a point of support or resistance, market participants get “absorbed” in the area so price can continue in whichever direction.
#2 Candle Wick Theory/Strategy
I defined Candle Wick Theory/Strategy as follows.
//----------------------------------------------
//---------------Candle Wick--------------------
//----------------------------------------------
highWick = upBar ? high - close : downBar ? high - open : na
lowWick = upBar ? open - low : downBar ? close - low : na
upWick = upBar ? close + highWick : downBar ? open + highWick : na
downWick = upBar ? open - lowWick : downBar ? close - lowWick : na
downDelivery = upBar and downBar and high > upWick and highWick > lowWick and totalSize > totalSize and barstate.isconfirmed and session.ismarket
upDelivery = downBar and upBar and low < downWick and highWick < lowWick and totalSize > totalSize and barstate.isconfirmed and session.ismarket
line lG = na
line lE = na
line lR = na
bodyMidpoint = math.abs(body) / 2
upWickMidpoint = math.abs(upWickSize) / 2
downWickkMidpoint = math.abs(downWickSize) / 2
if upDelivery and showCdTheory
cpE = chart.point.new(time, bar_index - 1, downWickkMidpoint)
cpE2 = chart.point.new(time, bar_index + bl, downWickkMidpoint)
cpG = chart.point.new(time, bar_index + bl, downWickkMidpoint * (1 + tp))
cpR = chart.point.new(time, bar_index + bl, downWickkMidpoint * (1 - sl))
cpG1 = chart.point.new(time, bar_index - 1, downWickkMidpoint * (1 + tp))
cpR1 = chart.point.new(time, bar_index - 1, downWickkMidpoint * (1 - sl))
lG := line.new(cpG1, cpG, xloc.bar_index, extend.none, color.green, line.style_solid, 1)
lE := line.new(cpE, cpE2, xloc.bar_index, extend.none, color.white, line.style_solid, 1)
lR := line.new(cpR1, cpR, xloc.bar_index, extend.none, color.red, line.style_solid, 1)
lR
else if downDelivery and showCdTheory
cpE = chart.point.new(time, bar_index - 1, upWickMidpoint)
cpE2 = chart.point.new(time, bar_index + bl, upWickMidpoint)
cpG = chart.point.new(time, bar_index + bl, upWickMidpoint * (1 - tp))
cpR = chart.point.new(time, bar_index + bl, upWickMidpoint * (1 + sl))
cpG1 = chart.point.new(time, bar_index - 1, upWickMidpoint * (1 - tp))
cpR1 = chart.point.new(time, bar_index - 1, upWickMidpoint * (1 + sl))
lG := line.new(cpG1, cpG, xloc.bar_index, extend.none, color.green, line.style_solid, 1)
lE := line.new(cpE, cpE2, xloc.bar_index, extend.none, color.white, line.style_solid, 1)
lR := line.new(cpR1, cpR, xloc.bar_index, extend.none, color.red, line.style_solid, 1)
lR
First I get the size of the wicks for the top and bottoms of the candles. This depends on if the bar is red or green. If the bar is green the wick is the high minus the close, if red the high minus the open, and so on. Next, the script defines the upper and lower bounds of the wicks for further comparison. If the candle is green, it's the open price minus the bottom wick. If the candle is red, it's the close price minus the bottom wick, and so on. Next we have the condition for when this strategy is present.
Down delivery:
Occurs when the previous candle is green, the current candle is red, and:
The high of the current candle is above the upper wick of the previous candle.
The size of the current candle's top wick is greater than its bottom wick.
The total size of the previous candle is greater than the total size of the current candle.
The current bar is confirmed (barstate.isconfirmed).
The session is during market hours (session.ismarket).
Up delivery:
Occurs when the previous candle is red, the current candle is green, and:
The low of the current candle is below the lower wick of the previous candle.
The size of the current candle's bottom wick is greater than its top wick.
The total size of the previous candle is greater than the total size of the current candle.
The current bar is confirmed.
The session is during market hours
Then risk is plotted from the percentage that users can input from an ideal entry spot.
#3 Candle Size Theory
I defined Candle Size Theory as follows.
//----------------------------------------------
//---------------Candle displacement------------
//----------------------------------------------
line lECD = na
notableDown = bodySize > bodySize * candle_size_sensitivity and downBar and session.ismarket and barstate.isconfirmed
notableUp = bodySize > bodySize * candle_size_sensitivity and upBar and session.ismarket and barstate.isconfirmed
if notableUp and showCdSizeTheory
cpE = chart.point.new(time, bar_index - 1, close)
cpE2 = chart.point.new(time, bar_index + bl_strcuture, close)
lECD := line.new(cpE, cpE2, xloc.bar_index, extend.none, color.rgb(0, 80, 75), line.style_solid, 3)
lECD
else if notableDown and showCdSizeTheory
cpE = chart.point.new(time, bar_index - 1, close)
cpE2 = chart.point.new(time, bar_index + bl_strcuture, close)
lECD := line.new(cpE, cpE2, xloc.bar_index, extend.none, color.rgb(105, 15, 15), line.style_solid, 3)
lECD
This plots candles that are “notable” or out of the ordinary. Candles that are larger than the last by a value users get to specify. These candles' highs or lows, if they are green or red, act as levels for support or resistance.
#4 Candle Structure Theory
I defined Candle Structure Theory as follows.
//----------------------------------------------
//---------------Structure----------------------
//----------------------------------------------
breakDownStructure = low < low and low < low and high > high and upBar and downBar and upBar and downBar and session.ismarket and barstate.isconfirmed
breakUpStructure = low > low and low > low and high < high and downBar and upBar and downBar and upBar and session.ismarket and barstate.isconfirmed
if breakUpStructure and showStructureTheory
cpE = chart.point.new(time, bar_index - 1, close)
cpE2 = chart.point.new(time, bar_index + bl_strcuture, close)
lE := line.new(cpE, cpE2, xloc.bar_index, extend.none, color.teal, line.style_solid, 3)
lE
else if breakDownStructure and showStructureTheory
cpE = chart.point.new(time, bar_index - 1, open)
cpE2 = chart.point.new(time, bar_index + bl_strcuture, open)
lE := line.new(cpE, cpE2, xloc.bar_index, extend.none, color.red, line.style_solid, 3)
lE
It is a series of candles to create a notable event. 2 lower lows in a row, a lower high, then green bar, red bar, green bar is a structure for a breakdown. 2 higher lows in a row, a higher high, red bar, green bar, red bar for a break up.
#5 Candle Swing Structure Theory
I defined Candle Swing Structure Theory as follows.
//----------------------------------------------
//---------------Swing Structure----------------
//----------------------------------------------
line htb = na
line ltb = na
if totalSize * swing_struct_sense < totalSize and upBar and downBar and high > high and showSwingSturcture and session.ismarket and barstate.isconfirmed
cpS = chart.point.new(time, bar_index - 1, high)
cpE = chart.point.new(time, bar_index + bl_strcuture, high)
htb := line.new(cpS, cpE, xloc.bar_index, color = color.red, style = line.style_dashed)
htb
else if totalSize * swing_struct_sense < totalSize and downBar and upBar and low > low and showSwingSturcture and session.ismarket and barstate.isconfirmed
cpS = chart.point.new(time, bar_index - 1, low)
cpE = chart.point.new(time, bar_index + bl_strcuture, low)
ltb := line.new(cpS, cpE, xloc.bar_index, color = color.teal, style = line.style_dashed)
ltb
A bearish swing structure is defined as the last candle’s total size, times a scalar that the user can input, is less than the current candles. Like a size imbalance. The last bar must be green and this one red. The last high should also be less than this high. For a bullish swing structure the same size imbalance must be present, but we need a red bar then a green bar, and the last low higher than the current low.
#6 Fractal Boxes
I define the Fractal Boxes as follows
//----------------------------------------------
//---------------Fractal Boxes------------------
//----------------------------------------------
box b = na
int indexx = na
if bar_index % (n * 2) == 0 and session.ismarket and showBoxes
b := box.new(left = bar_index, top = topBox, right = bar_index + n, bottom = bottomBox, border_color = color.rgb(105, 15, 15), border_width = boxLineSize, bgcolor = na)
indexx := bar_index + 1
indexx
The idea of this strategy is that the market is fractal. It is considered impossible to be able to tell apart two different time frames from just the chart. So inside the chart there are many many breakouts and breakdowns happening as price bounces around. The boxes are there to give you the view from your timeframe if the market is in a range from a time frame that would be higher than it. Like if we are inside what a larger time frame candle’s range. If we break out or down from this, we might be able to trade it. Users can specify a lookback period and the box is that period’s, as an interval, high and low. I say as an interval because it is plotted every n * 2 bars. So we get a box, price moves, then a new box.
#7 Potential Move Width
I define the Potential Move Width as follows
//----------------------------------------------
//---------------Move width---------------------
//----------------------------------------------
velocity = V(n)
line lC = na
line l = na
line l2 = na
line l3 = na
line l4 = na
line l5 = na
line l6 = na
line l7 = na
line l8 = na
line lGFractal = na
line lRFractal = na
cp2 = chart.point.new(time, bar_index + n, close + velocity)
cp3 = chart.point.new(time, bar_index + n, close - velocity)
cp4 = chart.point.new(time, bar_index + n, close + velocity * 5)
cp5 = chart.point.new(time, bar_index + n, close - velocity * 5)
cp6 = chart.point.new(time, bar_index + n, close + velocity * 10)
cp7 = chart.point.new(time, bar_index + n, close - velocity * 10)
cp8 = chart.point.new(time, bar_index + n, close + velocity * 15)
cp9 = chart.point.new(time, bar_index + n, close - velocity * 15)
cpG = chart.point.new(time, bar_index + n, close + R)
cpR = chart.point.new(time, bar_index + n, close - R)
if ((bar_index + n) * 2 - bar_index) % n == 0 and session.ismarket and barstate.isconfirmed and showPredictionWidtn
cp = chart.point.new(time, bar_index, close)
cpG1 = chart.point.new(time, bar_index, close + R)
cpR1 = chart.point.new(time, bar_index, close - R)
l := line.new(cp, cp2, xloc.bar_index, extend.none, color.aqua, line.style_solid, 1)
l2 := line.new(cp, cp3, xloc.bar_index, extend.none, color.aqua, line.style_solid, 1)
l3 := line.new(cp, cp4, xloc.bar_index, extend.none, color.red, line.style_solid, 1)
l4 := line.new(cp, cp5, xloc.bar_index, extend.none, color.red, line.style_solid, 1)
l5 := line.new(cp, cp6, xloc.bar_index, extend.none, color.teal, line.style_solid, 1)
l6 := line.new(cp, cp7, xloc.bar_index, extend.none, color.teal, line.style_solid, 1)
l7 := line.new(cp, cp8, xloc.bar_index, extend.none, color.blue, line.style_solid, 1)
l8 := line.new(cp, cp9, xloc.bar_index, extend.none, color.blue, line.style_solid, 1)
l8
By using the past n bar’s velocity, or directional speed, every n * 2 bars. I can use it to scale the close value and get an estimate for how wide the next moves might be.
#8 Linear regression
//----------------------------------------------
//---------------Linear Regression--------------
//----------------------------------------------
lr = showLR ? ta.linreg(close, n, 0) : na
plot(lr, 'Linear Regression', color.blue)
I used TradingView’s built in linear regression to not reinvent the wheel. This is present to see past market strength of weakness from a different perspective.
User input
Users can control a lot about this script. For the strategy based plots you can enter what you want the risk to be in percentages. So the default 0.01 is 1%. You can also control how far forward the line goes.
Look back at where it is needed as well as line width for the Fractal Boxes are controllable. Also users can check on and off what they would like to see on the charts.
No indicator is 100% reliable, do not follow this one blindly. I encourage traders to make their own decisions and not trade solely based on technical indicators. I encourage constructive criticism in the comments below. Thank you.
4EMAs+OpenHrs+FOMC+CPIThis script displays 4 custom EMAs of your choice based on the Pine script standard ema function.
Additionally the following events are shown
1. Opening hours for New York Stock exchange
2. Opening Time for London Stock exchange
3. US CPI Release Dates
4. FOMC press conference dates
5. FOMC meeting minutes release dates
I have currently added FOMC and CPI Dates for 2025 but will keep updating in January of every year (at least as long as I stay in the game :D)
Quarter Shift IdentifierQuarter Shift Identifier
This indicator helps traders and analysts identify significant price movements between quarters. It calculates the percentage change from the close of the previous quarter to the current price and signals when this change exceeds a 4% threshold.
Key Features:
• Automatically detects quarter transitions
• Calculates quarter-to-quarter price changes
• Signals significant shifts when the change exceeds 4%
• Displays blue up arrows for bullish shifts and red down arrows for bearish shifts
How it works:
1. The script tracks the closing price of each quarter
2. When a new quarter begins, it calculates the percentage change from the previous quarter's close
3. If the change exceeds 4%, an arrow is plotted on the chart
This tool can be useful for:
• Identifying potential trend changes at quarter boundaries
• Analyzing seasonal patterns in price movements
• Supplementing other technical analysis tools for a comprehensive market view
Recommended Timeframes are Weekly and Daily.
Disclaimer:
This indicator is for informational and educational purposes only. It is not financial advice and should not be the sole basis for any investment decisions. Always conduct your own research and consider your personal financial situation before trading or investing. Past performance does not guarantee future results.
It Screams When Crypto BottomsGet ready to ride the crypto rollercoaster with your new favourite tool for catching Bitcoin at its juiciest, most oversold moments.
This isn’t just another boring indicator — it screams when it’s time to load your bags and get ready for the ride back up!
Expect it to scream just once or twice per cycle at the very bottom, so you know exactly when the party starts!
Why You'll Love It:
Crypto-Exclusive Magic: It does not really matter what chart you are on; this indicator only bothers about the original and realised market cap of BTC. We all know the rest will follow.
Big Picture Focus: Designed for daily. No noisy intraday drama — just pure, clear signals.
Screaming Alerts: When the signal hits, it’s like a neon sign screaming, “Crypto Bottomed!"
Think of this indicator as your backstage pass to the crypto world’s most dramatic moments. It’s not subtle — it’s bold, loud, and ready to help you time the market like a pro.
P.S.: Use it only on a daily chart. Don’t even try it on shorter timeframes — it won’t scream, and you’ll miss the show! 🙀
Integrated Market Analysis IndicatorThe Integrated Market Analysis Indicator is designed to provide traders with a macro perspective on market conditions, focusing on the S&P 500 (SPX) and market volatility (VIX), to assist in swing trading decisions. This script integrates various technical indicators and market health metrics to generate scores that help in assessing the overall market trend, potential breakout opportunities, and mean reversion scenarios. It is tailored for traders who wish to align their individual stock or index trades with broader market movements.
Functionality:
Trend Analysis: The script analyzes the trend of the S&P 500 using moving averages (5-day SMA, 10-day EMA, 20-day EMA) to determine whether the market is in an uptrend, downtrend, or neutral state. This provides a foundation for understanding the general market direction.
Volatility Assessment: It uses the VIX to gauge market volatility, which is crucial for risk management. The script calculates thresholds based on the 20-day SMA of the VIX to categorize the market volatility into low, medium, or high.
Market Breadth: The advance/decline ratio (A/D ratio) from the USI:ADVQ and USI:DECLQ indices gives an indication of market participation, helping to understand if the market movement is broad-based or led by a few stocks.
Scoring System: Three scores are calculated:
Trend Score: Evaluates the market trend in conjunction with volume, market breadth, and VIX to assign a grade from 'A' to 'D'.
Breakout Score: Assesses potential breakout conditions by looking at price action relative to dynamic support/resistance levels, short-term momentum, and volume.
Mean Reversion Score: Identifies conditions where mean reversion might occur, based on price movement, volume, and high VIX levels, indicating potential overbought or oversold conditions.
Risk Management: Position sizing recommendations are provided based on VIX levels and the calculated scores, aiming to adjust exposure according to market conditions.
How to Use the Script:
Application: Apply this indicator on any stock or index chart in TradingView. Since it uses data from SPX and VIX, the scores will reflect the macro environment regardless of the underlying chart.
Interpreting Scores:
Trend Score: Use this to gauge the overall market direction. An 'A' score might suggest a strong uptrend, making it a good time for bullish trades, while a 'D' could indicate a bearish environment.
Breakout Score: Look for 'A' scores when considering trades that aim to capitalize on breakouts. A 'B' might suggest a less certain breakout, requiring more caution.
Mean Reversion Score: A 'B' or 'A' here might be a signal to look for trades where you expect the price to revert to the mean after an extreme move.
Risk Management: Use the suggested position sizes ('Normal Size', '1/3 Size', '1/4 Size', '1/10 Size') to manage your risk exposure. Higher VIX levels or lower scores suggest reducing position sizes to mitigate risk.
Visual Cues: The script plots various SMAs, EMAs, and dynamic support/resistance levels, providing visual indicators of where the market might find support or resistance, aiding in entry and exit decisions.
How NOT to Use the Script:
Not for Intraday Trading: This indicator is designed for swing trading, focusing on daily or longer timeframes. Using it for intraday trading might not provide the intended insights due to its macro focus.
Avoid Over-reliance: While the script provides valuable insights, do not rely solely on it for trading decisions. Always consider additional analysis, news, and fundamental data.
Do Not Ignore Individual Stock Analysis: Although the script gives a macro view, individual stock analysis is crucial. The macro conditions might suggest a trend, but stock-specific factors could contradict this.
Not for High-Frequency Trading: The script's logic and the data it uses are not optimized for high-frequency trading strategies where microsecond decisions are made.
Misinterpretation of Scores: Do not misinterpret the scores as absolute signals. They are guidelines that should be part of a broader trading strategy.
Logic Explanation:
Moving Averages: The script uses different types of moving averages to smooth out price data, providing a clearer view of the trend over short to medium-term periods.
ATR for Volatility: The Average True Range (ATR) is used to calculate dynamic support and resistance levels, giving a sense of how much price movement can be expected, which helps in setting realistic expectations for price action.
VIX for Risk: By comparing current VIX levels to its 20-day SMA, the script assesses market fear or complacency, adjusting risk exposure accordingly.
Market Breadth: The A/D ratio helps to understand if the market movement is supported by a broad base of stocks or if it's narrow, which can influence the reliability of the trend.
This indicator should be used as part of a comprehensive trading strategy, providing a macro overlay to your trading decisions, ensuring you're not fighting against the broader market trends or volatility conditions. Remember, while it can guide your trading, always integrate it with other forms of analysis for a well-rounded approach.
