Muti TimeFrame 1st Minute High and a LowThis Pine Script code is designed to plot the high, close, and low prices at exactly 9:31 AM on any timeframe chart. Here's a breakdown of what the script does:
Inputs
Define the start time of the trading day (default: 9:30 AM)
Define the end time of the trading day (default: 4:00 PM)
Toggle to display daily open and close lines (default: true)
Toggle to extend lines for daily open and close (default: false)
Calculations
- Determines if the current bar is the first bar of the trading day (9:30 AM)
- Retrieves the high, close, and low prices at 9:31 AM for the current timeframe
- Plots these prices as crosses on the chart
- Draws lines for the 4 pm close and 9:30 am open, as well as lines for the high and low of the first candle
- Calculates the start and end times for a rectangle box and draws the box on the chart if the start price high and low are set
Features
- Plots the high, close, and low prices at exactly 9:31 AM on any timeframe chart
- Displays daily open and close lines
- Extends lines for daily open and close (optional)
- Draws a rectangle box around the first candle of the day (optional)
Markets
- Designed for use on various markets, including stocks, futures, forex, and crypto
This script is useful for traders who want to visualize the prices at the start of the trading day and track the market's movement throughout the day.
Cari dalam skrip untuk "Cycle"
1% Range Bars with Sequence TableOverall Logic :
The script is designed to help traders visualize and analyze price movements on the chart, where each 1% movement is highlighted with a corresponding symbol. Additionally, the table helps track and analyze the number and length of consecutive price movements in one direction, which can be useful for identifying trends and understanding market dynamics.
This script can be particularly useful for traders looking for recurring patterns in price movements and wanting to quickly identify significant changes on the chart.
Main elements of the script :
Price Percentage Change:
The script tracks the price movement by 1% from the last significant value (the value at which the last 1% change was recorded).
If the price rises by 1% or more, a green circle is displayed above the bar.
If the price drops by 1% or more, a red circle is displayed below the bar.
Sequence Counting:
The script counts the number of consecutive 1% moves upwards (green circles) and downwards (red circles).
Separate counters are maintained for upward and downward movements, increasing each time the respective movement occurs.
If an opposite movement interrupts the sequence, the counter for the opposite direction is reset.
Sequence Table:
A table displayed on the chart shows the number of sequences of 1% movements in one direction for lengths from 1 to 15 bars.
The table is updated in real-time and shows how many times sequences of a certain length occurred on the chart, where the price moved by 1% in one direction.
Ultra SessionsThe "Ultra Sessions" indicator is designed to enhance your trading strategy by clearly marking key market sessions and their associated "kill zones" directly on your chart. This powerful tool supports multiple time zones and provides customizable alerts for session opens, closes, and critical kill zones, ensuring you never miss important market movements.
Customizable Time Zones: Align the indicator with your local time by selecting from a wide range of global time zones.
Market Session Tracking: Visually track the New York, London, and Tokyo trading sessions with distinct color-coded markers.
Kill Zones: Highlight the high-volatility periods within each session to focus on key trading opportunities.
Alert System: Receive real-time alerts for session openings, closings, and kill zones, so you stay informed without constantly monitoring the chart.
Flexible Positioning: Choose the positioning of session markers to fit your chart layout, whether at the top or bottom.
Ideal for traders who want to optimize their entry and exit points by focusing on the most active and volatile times in the market, the indicator is a must-have for any serious trading setup.
M2 Global Liquidity Index (Candles)M2 Global Liquidity Index (Candles)
In this enhanced version of the original M2 Global Liquidity Index script by Mik3Christ3ns3n , I've taken the foundational concept and expanded its capabilities for more in-depth analysis and user flexibility. This updated script aggregates M2 money supply data from major global economies—China, the U.S., the Eurozone, Japan, and the U.K.—adjusted by their respective exchange rates, into a customizable global liquidity index.
Key Enhancements:
Candlestick Visualization:
• Instead of a simple line chart, I've implemented a candlestick chart, providing a more detailed representation of liquidity trends with open, high, low, and close values for each period. This allows traders to analyze the index with the same technical tools used for price charts.
Customizable Components:
• Users can now select which components (M2 data and exchange rates) to include in the index calculation, giving you the flexibility to tailor the index to specific economic factors or regions of interest.
Dynamic Color Coding:
• Candles are color-coded based on their performance (bullish or bearish), with customized wick and border colors to enhance visual clarity, making it easier to spot liquidity trends at a glance.
Overlay Option:
• This script is designed to be an overlay, allowing you to plot the Global Liquidity Index directly on your price charts, facilitating comparison between liquidity trends and asset prices.
This enhanced script is ideal for traders and analysts who want a deeper understanding of global liquidity trends and their impact on financial markets.
Prometheus TTM SqueezeThe TTM indicator is an indicator used to better understand an underlying’s direction and volatility. Positive values indicate a rising price, negative falling. There is also an element of the underlying's volatility, explained below.
When, in this particular indicator, the zero line is the aqua color, that means that the volatility has picked up. In literal terms, it means that the upper Keltner Channel is above the upper Bollinger Band and the lower Keltner Channel is below the lower Bollinger Band. The range of the Keltner Channels is greater than the range of the Bollinger bands. What this is supposed to correlate to with price action is a more volatile choppier area. See below.
This is an example of volatility picking up being shown as the speed of the underlying. When the line turns aqua the move following tends to be sharp in the respective direction. Not a smooth delivery of price.
Regarding why this script is different from the others, with this script you do not need to input a bar's back value if you do not want to. Bars back being the amount of bars used in the indicator calculation. This is because of the use of Sum of Squared Errors, or SSE. How we do it is we calculate a Simple Moving Average or SMA and the indicator using a lot of different bars back values. Then if there is an event, characterized by the oscillator crossing over or under the 0 line, we subtract the close by the SMA and square it. If there is no event we return a big value, we want the error to be as small as possible. Because we loop over every value for bars back, we get the value with the smallest error. Or the SMA closest to the price ensuring we are following it as close as we can. This also becomes the value used as the multiplier for the Keltner Channels and Bollinger Bands, we simply divide them by 10 to normalize it. This leads to ease of use. A user does not need to worry about finding the best bars back for each ticker and time frame. We have you covered! SSE is not to be regarded to be the best given values for a pocket of the market, simply an estimation.
Of course we have the option for users to enter their own bars back or multipliers. Here is a comparison of the SSE at work and a 20 period bar’s back with 2 as the multiplier on a 4 hour $QQQ.
The top one is the SSE, the bottom is 20. I turned off showing the SMA, and alerts for better visibility. We see the SSE version does not cross above 0 again until the trend totally reverses. I would much rather overestimate risk than underestimate it.
The BULL and BEAR plotted on the chart is a result of the following conditions. A BULL if the price is above our auto optimized SMA and the oscillator crosses over 0. BEAR is the opposite, price below the SMA and an oscillator cross below 0. Here is the Daily NYSE:PLTR chart to show some.
Users have the options to toggle on and off the BULL and BEAR plots, SMA, as well as input their own lookback and multipliers.
We encourage traders to not follow indicators blindly, none are 100% accurate. SSE does not guarantee that the values generated will be the best for a given moment in time. Please comment on any desired updates, all criticism is welcome!
Inverted Yield Curve (US01Y/US10Y Ratio)This indicator calculates and visualizes the ratio between the US 1-Year Treasury Yield (US01Y) and the US 10-Year Treasury Yield (US10Y). It provides a clear visual representation of the relationship between short-term and long-term interest rates, which can be a valuable tool for analyzing market conditions, potential recessions, or shifts in economic outlook.
Features:
US01Y/US10Y Ratio: The indicator plots the ratio between the 1-Year and 10-Year US Treasury Yields as a smooth curve.
Dynamic Highlighting: Portions of the curve where the ratio exceeds 1 are highlighted in red, making it easy to identify periods where short-term rates surpass long-term rates—a key signal often associated with economic shifts or inversions.
Customizable Appearance: The main curve is plotted in a light blue color for clear visibility against most chart backgrounds.
Use Cases:
Yield Curve Analysis: This indicator helps traders and analysts monitor the yield curve, specifically focusing on the relationship between short-term and long-term interest rates.
Recession Signals: An inverted yield curve, where the ratio exceeds 1, can be an early warning signal for potential economic downturns.
Market Sentiment: Use the indicator to gauge shifts in investor sentiment by tracking changes in the yield curve over time.
How to Use:
Add the script to your TradingView chart.
The light blue curve represents the ratio of US01Y/US10Y.
Red highlights indicate periods where the ratio exceeds 1, signaling potential yield curve inversion.
This indicator is ideal for traders, investors, and economists looking to incorporate yield curve analysis into their trading strategies or economic forecasts.
Forex Session Tracker [MacroGlide]Forex Session Tracker is a tool designed to track and visualize trading activity across the four key Forex market sessions: New York, London, Tokyo, and Sydney. The indicator helps traders see the time intervals of each session, their impact on price movements, and analyze volatility within these sessions.
Key Features:
• Session Visualization: The indicator highlights price ranges during the New York, London, Tokyo, and Sydney sessions using different colors, making data easier to visually interpret and analyze. Users can customize the color scheme for each session.
• Price Change Analysis: The indicator tracks the opening prices of each session and calculates the price changes by the session's close. This allows traders to assess market dynamics within each session and make informed trading decisions.
• Average Price Changes: The average price change for a specified number of sessions is calculated for each session, helping to identify trends and volatility levels.
• Time Zone Support: The indicator takes into account time zones, allowing users to adjust the display according to their location or use the market's time zone.
• Interactive Dashboard: The built-in dashboard shows the status of each session in real-time (active or inactive), recent price changes, and average changes, providing quick access to key information directly on the chart.
How to Use:
• Add the indicator to your chart and configure the displayed sessions according to your needs.
• Use color differentiation to easily identify active trading sessions and assess their impact on price movements.
• Monitor price changes in each session and analyze averages for a deeper understanding of market trends.
Methodology:
The indicator uses the time intervals of each trading session to calculate and display opening prices, price ranges, and price changes for the session. Based on this data, the Forex Session Tracker visualizes the session's high and low prices and calculates the average price change over the last several sessions. All data is displayed in real-time, considering the user's time zone settings or the market's time zone.
Originality and Usefulness:
Forex Session Tracker stands out for its ability to combine price change information from several key trading sessions into one indicator, providing traders with a simple and clear way to analyze market activity across different time zones.
Charts:
The indicator displays clean and clear charts, where each trading session is highlighted with its own color, making visual interpretation easier. The charts focus only on essential information for analysis: opening prices, session ranges, and price changes. The integrated dashboard provides quick access to key session metrics, such as activity status, recent price changes, and average values for the selected period. These features make the charts highly useful for rapid analysis and trading decision-making.
Enjoy the game!
US Market CrashesThis script allows you to manually highlight specific periods on a chart, making it easy to visualize significant market events such as recessions, market crashes, or other key timeframes. Unlike traditional indicators that are based on price movements, this script provides a flexible way to mark any custom date range directly on your Trading View charts.
Features:
Custom Date Ranges: Easily specify start and end dates for periods you want to highlight on the chart.
Custom Colors: Choose different colors for each highlighted period for clear visual distinction.
Predefined Market Crashes: By default, the script highlights 18 historical market crashes where the market declined by over 20%.
Use Cases:
Historical Analysis: Highlight and study the impact of past recessions or market crashes.
Event Marking: Mark specific economic events, earnings seasons, or other relevant periods.
Presentation: Use the highlighted periods to enhance presentations or reports on market behavior.
How to Use:
Input the start and end dates for the periods you want to highlight.
Adjust the colors and transparency as needed.
Apply the script to your chart to see the highlighted periods.
This tool is perfect for traders, analysts, and investors who want a clean and straightforward way to visualize important historical periods on their charts.
The default setup includes 18 significant market crashes with declines of over 20%.
Prometheus Cauchy ProbabilityThe Cauchy probability distribution is a distribution that is better suited to be used on non normal data, such as stock returns. Markets characterized by volatility and fat-tails can be better modeled like this.
This script provides two values to a user. The blue line represents the probability for the underlying to rise. The purple line represents its probability to fall. Rise and fall by how much? By default a prediction of 0.5% is set, but users can adjust it. The script automatically calculates based on how many bars would be in an entire day. For example there are 390 minutes from 9:30am to 4:00pm est. time so the script uses 390 bars. Users have the option to set a custom bars back length.
Developer’s note. This script works best with extended market hours on. Every example shown will have it on. The more price and volatility the better!
Code breakdown:
cauchy_cdf(x, x0, gamma)=>
1 / math.pi * math.atan((x - x0) / gamma) + 0.5
This function is what calculates the Cauchy cumulative density function.
// Calculate x and gamma
x = close * (1 + pred)
x0 = hi
gamma := ta.stdev(close, Len, false)
y = cauchy_cdf(x, x0, gamma)
//down
x_lo = close * (1 - pred)
x0_lo = lo
y_lo = cauchy_cdf(x_lo, x0_lo, gamma)
x represents the target price. x0 represents the current highest price of the day. Gamma is the standard deviation of prices over the desired length. x_lo, x0_lo, are variables to determine the probability of falling. Inputting these values into the function we get back our chance of rising and falling. Our blue and purple line.
Trade Examples:
Step 1: After a move down there is some choppiness, the values are close to each other and moving sharply.
Step 2: The chance to rise (Blue Line) strongly moves above the chance to fall (Purple Line), uptrend ensues.
Step 3: Small breaks below the purple line show breaks in the overall trend.
Step 4: Strong move down in price, and up in purple line end up trend.
Step 1: Strong cross in purple and blue line, marking the start of a downtrend.
Step 2: Small breaks above the purple line show breaks in the overall trend.
Step 3: Strong move up in price, and up in the blue line end downtrend.
Day trading example:
Custom input:
Step 1: Pre market weakness ends with a move up in the blue line and price.
Step 2: Consolidation in the uptrend with a small downtrend and above the purple line.
Step 3: Strong move up in price, and up in the blue line end consolidation and resumes strong uptrend.
This example is with custom input: 100 bars back, and 1% prediction.
Step 1: Downtrend starts after a big move up.
Step 2: Big crossover in blue and purple line. Uptrend starts.
Step 3: Lines get close signaling choppiness.
Step 4: Purple crosses over blue ending uptrend.
No indicator is 100% accurate, we encourage traders to use them along with their own discretion. Please use these tools with your own decision making. Comments about desired features and updates are encouraged!
Percentage Change IndicatorPercentage Change Indicator
This indicator calculates and displays the percentage change between the current close price and the previous close price. It provides a clear visual representation of price movements, helping traders quickly identify significant changes in the market.
## Formula
The percentage change is calculated using the following formula:
```
Percentage Change = (Current Close - Previous Close) * 100 / Current Close
```
## Features
- Displays percentage change as a bar chart
- Green bars indicate positive changes
- Red bars indicate negative changes
- A horizontal line at 0% helps distinguish between positive and negative movements
## How to Use
1. Add the indicator to your chart
2. Observe the bar chart below your main price chart
3. Green bars above the 0% line indicate upward price movements
4. Red bars below the 0% line indicate downward price movements
5. The height of each bar represents the magnitude of the percentage change
This indicator can be particularly useful for:
- Identifying sudden price spikes or drops
- Analyzing the volatility of an asset
- Comparing price movements across different timeframes
- Spotting potential entry or exit points based on percentage changes
Customize the indicator's appearance in the settings to suit your charting preferences.
Note: This indicator works on all timeframes, adapting its calculations to the selected chart period.
Normalized SP100/SP400 Ratio with Shiller PE Ratio (CAPE Ratio)This indicator is designed to observe market concentration and overall valuation by combining the Shiller CAPE Ratio with the SP100/SP400 ratio.
Blue Line: Represents the Shiller CAPE Ratio, which reflects the overall market valuation.
Yellow Line: Represents the SP100/SP400 ratio, which indicates market concentration.
The combination of these two metrics provides insight into market dynamics. Historically, on the SPX monthly chart, when the yellow line (SP100/SP400 ratio) crosses below the blue line (CAPE Ratio), it has been followed by a period of stock market gains.
Justification for Combination:
The Shiller CAPE Ratio is a widely recognized indicator of market valuation, providing a long-term perspective on whether the market is overvalued or undervalued. The SP100/SP400 ratio, on the other hand, measures the concentration of the market by comparing the largest 100 companies to the next 400 mid-sized companies.
By normalizing both metrics and analyzing their relationship, this script provides a unique perspective on market movements. The crossunder of the SP100/SP400 ratio below the CAPE Ratio may signal a shift in market sentiment or concentration, often leading to potential market rallies. This combination is not just a simple merger of indicators but rather a thoughtful integration that adds value by highlighting periods where market concentration and valuation dynamics align.
World Clock [VHX]Keeping track of local times across different time zones has always been a challenge, especially when working with global markets.
But worry no more, as we now have a solution tailored for this very need. With this indicator, you can effortlessly add two different time zones to your chart, making it easier than ever to stay on top of market activity. The indicator not only shows the current date and time for the selected time zones but also integrates seamlessly with your chart, ensuring that you’re always aligned with the right market timings, no matter where you or your trades are based.
Unfortunately, the clock won't function when the market is closed.
Bitcoin Power Law Oscillator [InvestorUnknown]The Bitcoin Power Law Oscillator is a specialized tool designed for long-term mean-reversion analysis of Bitcoin's price relative to a theoretical midline derived from the Bitcoin Power Law model (made by capriole_charles). This oscillator helps investors identify whether Bitcoin is currently overbought, oversold, or near its fair value according to this mathematical model.
Key Features:
Power Law Model Integration: The oscillator is based on the midline of the Bitcoin Power Law, which is calculated using regression coefficients (A and B) applied to the logarithm of the number of days since Bitcoin’s inception. This midline represents a theoretical fair value for Bitcoin over time.
Midline Distance Calculation: The distance between Bitcoin’s current price and the Power Law midline is computed as a percentage, indicating how far above or below the price is from this theoretical value.
float a = input.float (-16.98212206, 'Regression Coef. A', group = "Power Law Settings")
float b = input.float (5.83430649, 'Regression Coef. B', group = "Power Law Settings")
normalization_start_date = timestamp(2011,1,1)
calculation_start_date = time == timestamp(2010, 7, 19, 0, 0) // First BLX Bitcoin Date
int days_since = request.security('BNC:BLX', 'D', ta.barssince(calculation_start_date))
bar() =>
= request.security('BNC:BLX', 'D', bar())
int offset = 564 // days between 2009/1/1 and "calculation_start_date"
int days = days_since + offset
float e = a + b * math.log10(days)
float y = math.pow(10, e)
float midline_distance = math.round((y / btc_close - 1.0) * 100)
Oscillator Normalization: The raw distance is converted into a normalized oscillator, which fluctuates between -1 and 1. This normalization adjusts the oscillator to account for historical extremes, making it easier to compare current conditions with past market behavior.
float oscillator = -midline_distance
var float min = na
var float max = na
if (oscillator > max or na(max)) and time >= normalization_start_date
max := oscillator
if (min > oscillator or na(min)) and time >= normalization_start_date
min := oscillator
rescale(float value, float min, float max) =>
(2 * (value - min) / (max - min)) - 1
normalized_oscillator = rescale(oscillator, min, max)
Overbought/Oversold Identification: The oscillator provides a clear visual representation, where values near 1 suggest Bitcoin is overbought, and values near -1 indicate it is oversold. This can help identify potential reversal points or areas of significant market imbalance.
Optional Moving Average: Users can overlay a moving average (either SMA or EMA) on the oscillator to smooth out short-term fluctuations and focus on longer-term trends. This is particularly useful for confirming trend reversals or persistent overbought/oversold conditions.
This indicator is particularly useful for long-term Bitcoin investors who wish to gauge the market's mean-reversion tendencies based on a well-established theoretical model. By focusing on the Power Law’s midline, users can gain insights into whether Bitcoin’s current price deviates significantly from what historical trends would suggest as a fair value.
Anomaly Detection with Standard Deviation [CHE]Anomaly Detection with Standard Deviation in Trading
Application for Traders
Traders can use this indicator to identify potential turning points in the market. Anomalies above the upper threshold may indicate overbought conditions, suggesting a possible reversal or sell opportunity. Conversely, anomalies below the lower threshold might signal oversold conditions, presenting a potential buying opportunity. By combining these signals with other technical analysis tools, traders can make more informed decisions and refine their trading strategies.
Introduction
Welcome to this presentation on Anomaly Detection using Standard Deviation in the context of trading. This method helps traders identify unusual price movements that may indicate potential trading opportunities. We will walk through the concept, explain how to set up the indicator, and discuss how traders can utilize it effectively.
Concept Overview
Anomaly Detection using Standard Deviation is a statistical method that identifies price points in a financial market that deviate significantly from the norm. The method relies on calculating the moving average and the standard deviation of a chosen price indicator over a specified period. By defining thresholds (e.g., 3 standard deviations above and below the mean), the method flags these deviations as anomalies, which can signal potential trading opportunities.
1. Selecting the Data Source
Description: The first step in setting up the indicator is choosing the price data that will be analyzed. Common options include the closing price, opening price, highest price, lowest price, or a combination of these (such as the average of the open, high, low, and close prices, known as OHLC4).
Importance: The choice of data source affects the sensitivity and relevance of the detected anomalies.
2. Setting the Calculation Period
Description: The calculation period refers to the number of time units (such as days, hours, or minutes) used to compute the moving average and standard deviation. A typical default period might be 20 units.
Importance: A shorter period makes the indicator more responsive to recent changes, while a longer period smooths out short-term fluctuations and highlights more significant trends.
3. Determining the Number of Displayed Lines and Labels
Description: Traders can configure how many anomaly lines and labels are displayed on the chart at any given time. This is crucial for maintaining a clear and readable chart, especially in volatile markets.
Importance: Limiting the number of displayed anomalies helps avoid clutter and focuses attention on the most recent or relevant data points.
4. Calculating the Mean and Standard Deviation
Description: The mean (or moving average) represents the central tendency of the price data, while the standard deviation measures the dispersion or volatility around this mean.
Importance: These statistical measures are fundamental to determining the thresholds for what constitutes an "anomaly."
5. Defining Anomaly Thresholds
Description: Anomaly thresholds are typically set at 3 standard deviations above and below the mean. Prices that exceed these thresholds are considered anomalies, signaling potential overbought (above the upper threshold) or oversold (below the lower threshold) conditions.
Importance: These thresholds help traders identify extreme market conditions that might present trading opportunities.
6. Identifying Anomalies
Description: The indicator checks whether the high or low prices exceed the defined thresholds. If they do, these price points are flagged as anomalies.
Importance: Identifying these points can alert traders to unusual market behavior, prompting them to consider buying, selling, or holding their positions.
7. Visualizing the Anomalies
Description: The indicator plots the thresholds on the chart as lines, with anomalies highlighted through additional visual cues, such as labels or lines.
Importance: This visualization makes it easy for traders to spot significant deviations from the norm, which might warrant further analysis or immediate action.
8. Managing Displayed Anomalies
Description: To keep the chart organized, the indicator automatically removes the oldest lines and labels when the number exceeds the user-defined limit.
Importance: This feature ensures that the chart remains clear and focused on the most relevant data points, preventing information overload.
Conclusion
The Anomaly Detection with Standard Deviation indicator is a powerful tool for identifying significant deviations in market behavior. By customizing parameters such as the calculation period and the number of displayed anomalies, traders can tailor the indicator to suit their specific needs, leading to more effective trading decisions.
Best regards
Chervolino
Market Indicator by Atilla YurtsevenThis TradingView script is designed to analyze and visualize market trends by showing the percentage drops from the all-time high (ATH) of a stock or any other financial instrument. It also calculates and displays key statistical levels such as the mean, median, and various percentage thresholds. This indicator helps traders identify significant retracement levels and possible support/resistance zones based on historical price movements.
Indicator Settings:
- The indicator is named "Market // Atilla Yurtseven" and can be overlaid on the price chart.
- Users can choose to use the closing price (Use Close Price) or the high/low prices.
- Options are provided to show the ATH, ATL (All-Time Low), mean, median, and various minor and macro percentage levels.
Color Customization:
- The script allows customization of text and line colors for different levels, making it adaptable to different charting styles.
Initial Variable Setup:
- The script initializes several variables, including ATH, ATL, and arrays to store price data.
The round and roundy functions are used to format the values for display purposes.
ATH/ATL Calculation:
- The script checks if the current price exceeds the previous ATH and updates the ATH accordingly.
- Similarly, the script calculates the ATL based on the lowest point after reaching the ATH.
Mean and Median Calculation:
- The mean is calculated as the average drop from the ATH, while the median is the middle value in the sorted array of drops.
- These statistics provide insight into the overall trend and are used to identify significant price levels.
Plotting the Levels:
The script plots the ATH, ATL, mean, median, and various percentage retracement levels (12.5%, 25%, 37.5%, etc.).
The levels are color-coded based on user preferences, making it easier to interpret the chart visually.
Labels and Text Display:
- The script dynamically creates and updates labels on the chart to show the values of the ATH, ATL, mean, median, and other key levels.
- This feature allows traders to see at a glance how far the current price is from these critical levels.
Hit Detection:
- The script includes logic to detect if the price is within the range of the mean and median. If the price is within this range, the color of the fill between these levels changes, highlighting this area on the chart.
This script is a powerful tool for traders who want to analyze the retracement levels from historical highs. By displaying the mean, median, and various percentage levels, it provides a comprehensive view of potential support and resistance areas, helping traders make more informed decisions. The customizable nature of the script allows it to fit seamlessly into different trading strategies and charting styles.
Disclaimer:
This script is provided for informational and educational purposes only and does not constitute financial or investment advice. The author, Atilla Yurtseven, is not responsible for any financial losses or damages that may occur as a result of using this script. Trading and investing in financial markets involve risk, and past performance is not indicative of future results. Users should conduct their own research and consult with a qualified financial advisor before making any investment decisions. Use this script at your own risk.
Trade smart, stay safe.
Atilla Yurtseven
Envelop-Ama-VivekThe Adaptive Moving Average (AMA) is a type of moving average developed by Perry Kaufman, designed to adapt to the market's volatility. Unlike traditional moving averages that use fixed periods for smoothing, the AMA adjusts its sensitivity based on the market's noise and trends.
### Key Features of AMA:
1. **Adaptive Sensitivity:**
- The AMA responds more quickly to significant market movements while filtering out minor fluctuations. This is achieved by adjusting the smoothing constant dynamically.
- In trending markets, the AMA becomes more sensitive, allowing it to capture trends faster.
- In choppy or sideways markets, the AMA reduces its sensitivity, thus minimizing the impact of noise and avoiding false signals.
2. **Efficiency Ratio (ER):**
- The ER is a core component of the AMA. It measures the efficiency of price movement by comparing the net price change to the total price change over a given period.
- A higher ER indicates a strong trend, while a lower ER suggests more noise in the market.
3. **Smoothing Constant (SC):**
- The SC determines how much weight is given to the most recent price relative to the previous AMA value.
- The SC is dynamically adjusted based on the ER, with higher values used during strong trends and lower values during volatile or choppy periods.
### Applications of AMA:
- **Trend Detection:** The AMA is useful for identifying the start of a new trend or confirming an existing one, as it adjusts quickly to significant price movements.
- **Noise Reduction:** By adapting to market conditions, the AMA helps in filtering out market noise, making it easier to distinguish between genuine trends and short-term fluctuations.
- **Entry and Exit Signals:** Traders can use the AMA to generate buy and sell signals. For instance, when the price crosses above the AMA, it might indicate a buying opportunity, and when it crosses below, it might signal a selling opportunity.
### Benefits:
- **Adaptive Nature:** Its ability to adjust to market conditions makes the AMA more reliable in different market environments.
- **Reduced Lag:** Compared to traditional moving averages, the AMA reduces lag during trending markets, allowing for quicker responses to price movements.
### Drawbacks:
- **Complexity:** The calculation of the AMA is more complex compared to simple moving averages, which might make it less accessible to some traders.
- **Parameter Sensitivity:** The effectiveness of the AMA can vary depending on the chosen parameters (e.g., length, fast length, slow length), requiring careful tuning.
In summary, the AMA is a powerful tool for traders looking to capture trends while minimizing the impact of market noise. Its adaptive nature makes it suitable for various market conditions, providing a balance between responsiveness and noise reduction.
Fear/Greed Zone Reversals [UAlgo]The "Fear/Greed Zone Reversals " indicator is a custom technical analysis tool designed for TradingView, aimed at identifying potential reversal points in the market based on sentiment zones characterized by fear and greed. This indicator utilizes a combination of moving averages, standard deviations, and price action to detect when the market transitions from extreme fear to greed or vice versa. By identifying these critical turning points, traders can gain insights into potential buy or sell opportunities.
🔶 Key Features
Customizable Moving Averages: The indicator allows users to select from various types of moving averages (SMA, EMA, WMA, VWMA, HMA) for both fear and greed zone calculations, enabling flexible adaptation to different trading strategies.
Fear Zone Settings:
Fear Source: Select the price data point (e.g., close, high, low) used for Fear Zone calculations.
Fear Period: This defines the lookback window for calculating the Fear Zone deviation.
Fear Stdev Period: This sets the period used to calculate the standard deviation of the Fear Zone deviation.
Greed Zone Settings:
Greed Source: Select the price data point (e.g., close, high, low) used for Greed Zone calculations.
Greed Period: This defines the lookback window for calculating the Greed Zone deviation.
Greed Stdev Period: This sets the period used to calculate the standard deviation of the Greed Zone deviation.
Alert Conditions: Integrated alert conditions notify traders in real-time when a reversal in the fear or greed zone is detected, allowing for timely decision-making.
🔶 Interpreting Indicator
Greed Zone: A Greed Zone is highlighted when the price deviates significantly above the chosen moving average. This suggests market sentiment might be leaning towards greed, potentially indicating a selling opportunity.
Fear Zone Reversal: A Fear Zone is highlighted when the price deviates significantly below the chosen moving average of the selected price source. This suggests market sentiment might be leaning towards fear, potentially indicating a buying opportunity. When the indicator identifies a reversal from a fear zone, it suggests that the market is transitioning from a period of intense selling pressure to a more neutral or potentially bullish state. This is typically indicated by an upward arrow (▲) on the chart, signaling a potential buy opportunity. The fear zone is characterized by high price volatility and overselling, making it a crucial point for traders to consider entering the market.
Greed Zone Reversal: Conversely, a Greed Zone is highlighted when the price deviates significantly above the chosen moving average. This suggests market sentiment might be leaning towards greed, potentially indicating a selling opportunity. When the indicator detects a reversal from a greed zone, it indicates that the market may be moving from an overbought condition back to a more neutral or bearish state. This is marked by a downward arrow (▼) on the chart, suggesting a potential sell opportunity. The greed zone is often associated with overconfidence and high buying activity, which can precede a market correction.
🔶 Why offer multiple moving average types?
By providing various moving average types (SMA, EMA, WMA, VWMA, HMA) , the indicator offers greater flexibility for traders to tailor the indicator to their specific trading strategies and market preferences. Different moving averages react differently to price data and can produce varying signals.
SMA (Simple Moving Average): Provides an equal weighting to all data points within the specified period.
EMA (Exponential Moving Average): Gives more weight to recent data points, making it more responsive to price changes.
WMA (Weighted Moving Average): Allows for custom weighting of data points, providing more flexibility in the calculation.
VWMA (Volume Weighted Moving Average): Considers both price and volume data, giving more weight to periods with higher trading volume.
HMA (Hull Moving Average): A combination of weighted moving averages designed to reduce lag and provide a smoother curve.
Offering multiple options allows traders to:
Experiment: Traders can try different moving averages to see which one produces the most accurate signals for their specific market.
Adapt to different market conditions: Different market conditions may require different moving average types. For example, a fast-moving market might benefit from a faster moving average like an EMA, while a slower-moving market might be better suited to a slower moving average like an SMA.
Personalize: Traders can choose the moving average that best aligns with their personal trading style and risk tolerance.
In essence, providing a variety of moving average types empowers traders to create a more personalized and effective trading experience.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Hurst Exponent SmoothedDescription:
The Hurst Exponent Smoothed indicator provides a dynamic analysis of market behavior by calculating the Hurst Exponent over a specified lookback period. This tool is especially useful for identifying whether a market is trending or mean-reverting.
Key Features:
Lookback Period: Set to 90 by default, this parameter controls how many periods the indicator considers for its calculations. Adjusting this value allows you to fine-tune the sensitivity of the indicator to recent price action.
Market Analysis: The Hurst Exponent gives insights into the nature of price movement:
A value near 0.5 suggests a random walk, indicating that the market is unpredictable.
Values above 0.5 indicate a trending market where price movements exhibit persistence, suggesting that the current trend may continue.
Values below 0.5 point to a mean-reverting market, where price movements tend to reverse, making it a potential signal for contrarian trading strategies.
Usage:
Trend Following: When the Hurst Exponent is consistently above 0.5, it may indicate a strong trend. Traders can use this information to align with the current market direction.
Mean Reversion: If the Hurst Exponent falls below 0.5, it could signal that the market is more likely to revert to the mean, offering opportunities for mean-reversion strategies.
Visuals:
The indicator displays a smooth line oscillating between values, giving traders a clear visual cue for the current market condition.
The script is optimized for various timeframes, as demonstrated on the BTCUSD pair on a 270-minute chart. Traders can adapt the lookback period based on their trading style and the specific asset being analyzed.
Open Source: This script is open-source and free to use. Feel free to customize and adapt it to your needs!
75: Notable Financial CrisesThe TradingView script named "75: Notable Financial Crises" visualizes and marks significant financial crises on a financial chart.
This script plots vertical lines on the a chart corresponding to specific dates associated with notable financial crises in history. These crises could include events like the Great Depression (1929), Black Monday (1987), the Dot-com Bubble (2000), the Global Financial Crisis (2008), and others. By marking these dates on a chart, traders and analysts can easily observe the impact of these events on market behavior.
High-Low of X BarOverview
The High-Low of X Bar indicator allows traders to visualize historical high and low values from a specific number of bars ago directly on the chart.
Provides insight into past price action by displaying high, low, and their difference at the most recent bar.
Customizable inputs and color settings for labels enhance usability and visual integration with your chart.
Key Features
Historical Data Analysis: Displays the high, low, and the difference between these values from a specified number of bars ago.
Customizable Inputs: Set the number of bars ago to review historical price points, with a range from 1 to 2000 bars. Premium users can exceed this range.
Dynamic Labeling: Option to show high, low, and difference values as labels on the chart, with customizable text and background colors.
Color Customization: Customize label colors for high, low, and difference values, as well as for cases with insufficient bars.
Inputs
Number of Bars Ago: Enter the number of bars back from the current bar to analyze historical high and low values.
Show High Value: Toggle to display the historical high value.
Show Low Value: Toggle to display the historical low value.
Show Difference Value: Toggle to display the difference between high and low values.
Color Settings
High Label Background Color: Set the background color of the high value label.
High Label Text Color: Choose the text color for the high value label.
Low Label Background Color: Set the background color of the low value label.
Low Label Text Color: Choose the text color for the low value label.
Difference Label Background Color: Set the background color of the difference label.
Difference Label Text Color: Choose the text color for the difference label.
Not Enough Bars Label Background Color: Set the background color for the label shown when there are insufficient bars.
Not Enough Bars Label Text Color: Choose the text color for the insufficient bars label.
Usage Instructions
Add to Chart: Apply the High-Low of X Bar indicator to your TradingView chart.
Configure Settings: Adjust the number of bars ago and display options according to your analysis needs.
Customize Appearance: Set the colors for the labels to match your chart's style.
Analyze: Review the high, low, and their difference directly on your chart for immediate insights into past price movements.
Notes
Ensure your chart has sufficient historical data for the indicator to function properly.
Customize label visibility and colors based on your preference and trading strategy.
BTC Hash Rate to Price RatioDescription:
The BTC Hash Rate to Price Ratio indicator is a sophisticated tool designed to assist traders in identifying potential market turning points for Bitcoin by combining network health, market sentiment, and valuation metrics. This indicator integrates three key components—Hash Rate, RSI (Relative Strength Index), and MVRV (Market Value to Realized Value)—to provide a comprehensive analysis of Bitcoin's market dynamics.
Key Features:
Hash Rate Analysis: Assesses the computational power of the Bitcoin network, reflecting network health and miner confidence. Changes in the hash rate can signal shifts in market sentiment.
RSI (Relative Strength Index): A momentum oscillator that measures the speed and change of price movements, identifying overbought or oversold conditions. Smoothed RSI provides clearer insights into market momentum.
MVRV (Market Value to Realized Value): A valuation metric comparing Bitcoin's market value to its realized value, offering insights into whether Bitcoin is overvalued or undervalued. Smoothed MVRV enhances signal accuracy.
How It Works:
Red Zones (Sell Signals): Highlighted when both the MVRV and RSI are above the hash rate, indicating potential market tops.
Green Zones (Buy Signals): Highlighted when both the MVRV and RSI are below the hash rate and MVRV is under 15, suggesting potential market bottoms.
Customizable Parameters: Allows traders to adjust smoothing periods and signal thresholds, tailoring the indicator to different trading strategies and market conditions.
Visual Aids: Includes dotted lines at key RSI levels (15 and 75) for quick reference to potential overbought and oversold conditions.
Benefits:
Comprehensive Analysis: Combines technical, fundamental, and network metrics to offer a well-rounded perspective on market conditions.
Early Warning Signals: Aims to provide early indications of potential market reversals, helping traders make informed decisions.
Flexibility: Suitable for both short-term and long-term trading strategies, allowing for adaptation to various market environments.
Usage Tips:
Use this indicator in conjunction with other technical analysis tools and fundamental insights for best results.
Consider the broader market context and macroeconomic factors when interpreting signals.
Practice sound risk management techniques to optimize trading performance.
Unlock the potential of your Bitcoin trading strategy with the BTC Hash Rate to Price Ratio indicator, and gain deeper insights into market dynamics to make more informed trading decisions.
[2024] Inverted Yield CurveInverted Yield Curve Indicator
Overview:
The Inverted Yield Curve Indicator is a powerful tool designed to monitor and analyze the yield spread between the 10-year and 2-year US Treasury rates. This indicator helps traders and investors identify periods of yield curve inversion, which historically have been reliable predictors of economic recessions.
Key Features:
Yield Spread Calculation: Accurately calculates the spread between the 10-year and 2-year Treasury yields.
Visual Representation: Plots the yield spread on the chart, with clear visualization of positive and negative spreads.
Inversion Highlighting: Background shading highlights periods where the yield curve is inverted (negative spread), making it easy to spot critical economic signals.
Alerts: Customizable alerts notify users when the yield curve inverts, allowing timely decision-making.
Customizable Yield Plots: Users can choose to display the individual 2-year and 10-year yields for detailed analysis.
How It Works:
Data Sources: Utilizes the Federal Reserve Economic Data (FRED) for fetching the 2-year and 10-year Treasury yield rates.
Spread Calculation: The script calculates the difference between the 10-year and 2-year yields.
Visualization: The spread is plotted as a blue line, with a grey zero line for reference. When the spread turns negative, the background turns red to indicate an inversion.
Customizable Plots: Users can enable or disable the display of individual 2-year and 10-year yields through simple input options.
Usage:
Economic Analysis: Use this indicator to anticipate potential economic downturns by monitoring yield curve inversions.
Market Timing: Identify periods of economic uncertainty and adjust your investment strategies accordingly.
Alert System: Set alerts to receive notifications whenever the yield curve inverts, ensuring you never miss crucial economic signals.
Important Notes:
Data Accuracy: Ensure that the FRED data symbols (FRED
and FRED
) are correctly referenced and available in your TradingView environment.
Customizations: The script is designed to be flexible, allowing users to customize plot colors and alert settings to fit their preferences.
Disclaimer:
This indicator is intended for educational and informational purposes only. It should not be considered as financial advice. Always conduct your own research and consult with a financial advisor before making investment decisions.
Moving Average Ratio [InvestorUnknown]Overview
The "Moving Average Ratio" (MAR) indicator is a versatile tool designed for valuation, mean-reversion, and long-term trend analysis. This indicator provides multiple display modes to cater to different analytical needs, allowing traders and investors to gain deeper insights into the market dynamics.
Features
1. Moving Average Ratio (MAR):
Calculates the ratio of the chosen source (close, open, ohlc4, hl2 …) to a longer-term moving average of choice (SMA, EMA, HMA, WMA, DEMA)
Useful for identifying overbought or oversold conditions, aiding in mean-reversion strategies and valuation of assets.
For some high beta asset classes, like cryptocurrencies, you might want to use logarithmic scale for the raw MAR, below you can see the visual difference of using Linear and Logarithmic scale on BTC
2. MAR Z-Score:
Computes the Z-Score of the MAR to standardize the ratio over chosen time period, making it easier to identify extreme values relative to the historical mean.
Helps in detecting significant deviations from the mean, which can indicate potential reversal points and buying/selling opportunities
3. MAR Trend Analysis:
Uses a combination of short-term (default 1, raw MAR) and long-term moving averages of the MAR to identify trend changes.
Provides a visual representation of bullish and bearish trends based on moving average crossings.
Using Logarithmic scale can improve the visuals for some asset classes.
4. MAR Momentum:
Measures the momentum of the MAR by calculating the difference over a specified period.
Useful for detecting changes in the market momentum and potential trend reversals.
5. MAR Rate of Change (ROC):
Calculates the rate of change of the MAR to assess the speed and direction of price movements.
Helps in identifying accelerating or decelerating trends.
MAR Momentum and Rate of Change are very similar, the only difference is that the Momentum is expressed in units of the MAR change and ROC is expressed as % change of MAR over chosen time period.
Customizable Settings
General Settings:
Display Mode: Select the display mode from MAR, MAR Z-Score, MAR Trend, MAR Momentum, or MAR ROC.
Color Bars: Option to color the bars based on the current display mode.
Wait for Bar Close: Toggle to wait for the bar to close before updating the MAR value.
MAR Settings:
Length: Period for the moving average calculation.
Source: Data source for the moving average calculation.
Moving Average Type: Select the type of moving average (SMA, EMA, WMA, HMA, DEMA).
Z-Score Settings:
Z-Score Length: Period for the Z-Score calculation.
Trend Analysis Settings:
Moving Average Type: Select the type of moving average for trend analysis (SMA, EMA).
Longer Moving Average: Period for the longer moving average.
Shorter Moving Average: Period for the shorter moving average.
Momentum Settings:
Momentum Length: Period for the momentum calculation.
Rate of Change Settings:
ROC Length: Period for the rate of change calculation.
Calculation and Plotting
Moving Average Ratio (MAR):
Calculates the ratio of the price to the selected moving average type and length.
Plots the MAR with a gradient color based on its Z-Score, aiding in visual identification of extreme values.
// Moving Average Ratio (MAR)
ma_main = switch ma_main_type
"SMA" => ta.sma(src, len)
"EMA" => ta.ema(src, len)
"WMA" => ta.wma(src, len)
"HMA" => ta.hma(src, len)
"DEMA" => ta.dema(src, len)
mar = (waitforclose ? src : src) / ma_main
z_col = color.from_gradient(z, -2.5, 2.5, color.green, color.red)
plot(disp_mode.mar ? mar : na, color = z_col, histbase = 1, style = plot.style_columns)
barcolor(color_bars ? (disp_mode.mar ? (z_col) : na) : na)
MAR Z-Score:
Computes the Z-Score of the MAR and plots it with a color gradient indicating the magnitude of deviation from the mean.
// MAR Z-Score
mean = ta.sma(math.log(mar), z_len)
stdev = ta.stdev(math.log(mar),z_len)
z = (math.log(mar) - mean) / stdev
plot(disp_mode.mar_z ? z : na, color = z_col, histbase = 0, style = plot.style_columns)
plot(disp_mode.mar_z ? 1 : na, color = color.new(color.red,70))
plot(disp_mode.mar_z ? 2 : na, color = color.new(color.red,50))
plot(disp_mode.mar_z ? 3 : na, color = color.new(color.red,30))
plot(disp_mode.mar_z ? -1 : na, color = color.new(color.green,70))
plot(disp_mode.mar_z ? -2 : na, color = color.new(color.green,50))
plot(disp_mode.mar_z ? -3 : na, color = color.new(color.green,30))
barcolor(color_bars ? (disp_mode.mar_z ? (z_col) : na) : na)
MAR Trend:
Plots the MAR along with its short-term and long-term moving averages.
Uses color changes to indicate bullish or bearish trends based on moving average crossings.
// MAR Trend - Moving Average Crossing
mar_ma_long = switch ma_trend_type
"SMA" => ta.sma(mar, len_trend_long)
"EMA" => ta.ema(mar, len_trend_long)
mar_ma_short = switch ma_trend_type
"SMA" => ta.sma(mar, len_trend_short)
"EMA" => ta.ema(mar, len_trend_short)
plot(disp_mode.mar_t ? mar : na, color = mar_ma_long < mar_ma_short ? color.new(color.green,50) : color.new(color.red,50), histbase = 1, style = plot.style_columns)
plot(disp_mode.mar_t ? mar_ma_long : na, color = mar_ma_long < mar_ma_short ? color.green : color.red, linewidth = 4)
plot(disp_mode.mar_t ? mar_ma_short : na, color = mar_ma_long < mar_ma_short ? color.green : color.red, linewidth = 2)
barcolor(color_bars ? (disp_mode.mar_t ? (mar_ma_long < mar_ma_short ? color.green : color.red) : na) : na)
MAR Momentum:
Plots the momentum of the MAR, coloring the bars to indicate increasing or decreasing momentum.
// MAR Momentum
mar_mom = mar - mar
// MAR Momentum
mom_col = mar_mom > 0 ? (mar_mom > mar_mom ? color.new(color.green,0): color.new(color.green,30)) : (mar_mom < mar_mom ? color.new(color.red,0): color.new(color.red,30))
plot(disp_mode.mar_m ? mar_mom : na, color = mom_col, histbase = 0, style = plot.style_columns)
MAR Rate of Change (ROC):
Plots the ROC of the MAR, using color changes to show the direction and strength of the rate of change.
// MAR Rate of Change
mar_roc = ta.roc(mar,len_roc)
// MAR ROC
roc_col = mar_roc > 0 ? (mar_roc > mar_roc ? color.new(color.green,0): color.new(color.green,30)) : (mar_roc < mar_roc ? color.new(color.red,0): color.new(color.red,30))
plot(disp_mode.mar_r ? mar_roc : na, color = roc_col, histbase = 0, style = plot.style_columns)
Summary:
This multi-purpose indicator provides a comprehensive toolset for various trading strategies, including valuation, mean-reversion, and trend analysis. By offering multiple display modes and customizable settings, it allows users to tailor the indicator to their specific analytical needs and market conditions.
