KASPA Slope OscillatorKASPA Slope Oscillator for analyzing KASPA on the 1D (daily) chart.
The indicator is plotted in a separate pane below the price chart and uses a mathematical approach to calculate and visualize the momentum or "slope" of KASPA's price movements.
Input Parameters:
Slope Window (days):
Defines the period (66 days by default) over which the slope is calculated.
Normalization Window (days):
The window size (85 days) for normalizing the slope values between 0 and 100.
Smoothing Period:
The number of days (15 days) over which the slope values are smoothed to reduce noise.
Overbought and Oversold Levels:
Threshold levels set at 80 (overbought) and 20 (oversold), respectively.
Calculation of the Slope:
Logarithmic Price Calculation:
Converts the close price of KASPA into a logarithmic scale to account for exponential growth or decay.
Rolling Slope:
Computes the rate of change in logarithmic prices over the defined slope window.
Normalization:
The slope is normalized between 0 and 100, allowing easier identification of extreme values.
Smoothing and Visualization:
Smoothing the Slope:
A Simple Moving Average (SMA) is applied to the normalized slope for the specified smoothing period.
Plotting the Oscillator:
The smoothed slope is plotted on the oscillator chart. Horizontal lines indicate overbought (80), oversold (20), and the mid-level (50).
Background Color Indications:
Background colors (red or green) indicate when the slope crosses above the overbought or below the oversold levels, respectively, signaling potential buy or sell conditions.
Detection of Local Maxima and Minima:
The code identifies local peaks (maxima) above the overbought level and troughs (minima) below the oversold level.
Vertical background lines are highlighted in red or green at these points, signaling potential reversals.
Short Summary:
The oscillator line fluctuates between 0 and 100, representing the normalized momentum of the price.
Red background areas indicate periods when the oscillator is above the overbought level (80), suggesting a potential overbought condition or a sell signal.
Green background areas indicate periods when the oscillator is below the oversold level (20), suggesting a potential oversold condition or a buy signal.
The vertical lines on the background mark local maxima and minima where price reversals may occur.
(I also want to thank @ForgoWork for optimizing visuality and cleaning up the source code)
Cycles
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.
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.
Prometheus Volatility EMAThe Prometheus Volatility EMA is an indicator that calculates an Exponential Moving Average with the historical volatility as how we decide how sensitive to make the indicator to the most recent data.
A traditional EMA is calculated like this:
EMA = alpha * source + (1 - alpha) * EMA , where alpha = 2 / (length + 1)
Sourced from TradingView’s ta.ema built in function.
We see that the alpha value is used to determine how sensitive the EMA will be to the most recent prices, and it is derived from how many bars back are used in the calculation.
Prometheus is using the annualized historical volatility, for a specified period as the “alpha” value. The reason for this is that on more volatile assets, the EMA will follow price more closely to give you a better idea of when price may change direction.
Historical Volatility calculation:
hv = ta.stdev(math.log(close / close ), lkb) * math.sqrt(252/5)
EMA calculation:
float hv_EMA = na
hv_EMA := na(hv_EMA ) ? ta.sma(close, lkb) : hv * close + (1 - hv) * hv_EMA
Let's explain some charts to better understand this tool!
We see on a 1 year NASDAQ:SHY chart, the moving average is far from the price. This makes sense as NASDAQ:SHY has a range of 2.85% from the low to the high for this period in the photo above. It is not very volatile.
In this chart of BITSTAMP:BTCUSD we see that the EMA follows price very closely, way closer than it does on $SHY. This is because BITSTAMP:BTCUSD is much more volatile. BITSTAMP:BTCUSD has a range of 196% from the low to the high in this photo. Way more than $SHY.
We see it change on the same asset here looking at $QQQ. In the small period with the drop we see the EMA follow more closely as volatility picks up, then it quickly allows price to get far as volatility leaves.
This is the perspective we aim to provide. We encourage traders to not follow indicators blindly. No indicator is 100% accurate. This one can give you a different perspective of price strength with volatility. We encourage any comments about desired updates or criticism!
MTF Volume Flow IndicatorThe MTF Volume Flow Indicator (MTF VFI) is an advanced and versatile tool that enhances market analysis by tracking the flow of volume across multiple timeframes. By integrating volume flow with multi-timeframe analysis, this indicator provides traders with a comprehensive understanding of market trends, momentum, and potential reversals.
Key Features
Multi-Timeframe Volume Flow Analysis: The MTF VFI computes the Volume Flow Indicator across various timeframes, ranging from 1 minute to 1 month. This multi-timeframe analysis enables traders to observe and compare volume flow dynamics across different time horizons, offering deeper insights into market behavior.
Customizable VFI Settings: The indicator includes configurable VFI parameters such as length, coefficient, and volume cutoff, allowing users to tailor the analysis to different market conditions and trading strategies. This flexibility ensures that the indicator remains relevant across diverse market environments.
Signal Line and Delta Calculations: The script features a signal line derived from the VFI and calculates the delta values (the difference between VFI and the signal line). These delta values are essential for identifying potential buy or sell signals and are presented as histograms for easy visual interpretation.
Cumulative Delta with Dynamic Bands: The indicator introduces cumulative delta, a powerful tool that combines average and median VFI values to provide a clearer picture of market sentiment. Two standard deviation bands are plotted around the cumulative delta, offering a range within which price movements are likely to remain. These bands are smoothed using a 21-period EMA, providing a more refined view of market volatility.
Multi-Timeframe and Analysis Tables: The MTF VFI includes optional tables that display VFI, signal line, and delta values across all selected timeframes. Additionally, an analysis table presents key statistical metrics such as the highest, lowest, average, standard deviation, range, and median VFI values. These tables provide a concise summary of market conditions, aiding in strategic decision-making.
Dynamic Display Options: The indicator offers extensive customization options, allowing traders to display or hide elements such as delta histograms, delta bands, and tables. This ensures that users can focus on the most relevant information for their trading strategy.
Neutral Candle Coloring Option: Traders can enable neutral candle colors, where bearish candles are gray and bullish candles are white. This feature helps to reduce noise and maintain focus on the overall trend and volume flow analysis.
How It Works
Volume Flow Indicator Calculation: The VFI is calculated using a combination of typical price, volume, and the standard deviation of price changes. The indicator smooths the VFI based on user preferences, allowing traders to adjust the sensitivity of the analysis to better match their trading style.
Multi-Timeframe Integration: The script pulls VFI calculations from multiple timeframes, providing a holistic view of market trends. By analyzing VFI across different timeframes, traders can detect alignments or divergences in volume flow that might indicate trend strength or weakness.
Cumulative Delta and Dynamic Bands: The cumulative delta is computed by combining the average and median VFI values. Dynamic two-standard-deviation bands are plotted around this cumulative delta, providing upper and lower bounds for expected price movements. These bands are further smoothed with a 21-period EMA, enhancing their effectiveness in volatile markets.
Delta Analysis and Histogram Display: The difference between the VFI and its signal line (delta) is calculated and displayed as histograms. This visual representation helps traders quickly assess momentum and identify potential reversals or trend continuations. The cumulative delta is color-coded dynamically based on its direction, adding an extra layer of visual clarity.
Alerts
VFI Crossover Alerts: The indicator includes customizable alerts that notify traders when the VFI crosses above or below its signal line. These alerts are crucial for catching potential trend reversals or continuation signals, even when the trader is not actively monitoring the chart.
Customizable Alert Conditions: Traders can tailor alert conditions to their preferred timeframes and VFI settings, ensuring that the notifications they receive are relevant and timely for their specific trading strategies.
Application
Trend Identification and Confirmation: The MTF VFI aids in identifying and confirming trends by analyzing volume flow across multiple timeframes. This capability is particularly useful for detecting trends that may not be visible on a single timeframe.
Momentum and Divergence Analysis: By comparing VFI and delta values across timeframes, and analyzing cumulative delta with dynamic bands, traders can gain insights into market momentum and potential divergences, which are often precursors to reversals.
Strategic Decision-Making: With its comprehensive multi-timeframe analysis, cumulative delta, and statistical summaries, the MTF VFI equips traders with the information needed to make informed trading decisions, whether for short-term trades or long-term investments.
Visual Clarity and Customization: The indicator’s dynamic display options and neutral candle coloring help traders maintain a clear and focused view of the market, customizing the visualization to match their specific needs.
The MTF Volume Flow Indicator (MTF VFI) by CryptoSea is an essential tool for traders who seek to gain a deeper understanding of market trends and volume dynamics across multiple timeframes. Its advanced features and customization options make it a valuable addition to any trader’s toolkit.
Money Flow DivergenceThe Money Flow Divergence indicator is designed to help traders identify periods when there is a significant divergence between the growth of the U.S. M2 money supply and the S&P 500 index (SPX).
This divergence can provide insights into potential market turning points, making it a valuable tool for long-term investors and traders looking to capitalize on macroeconomic trends.
How It Works:
Data Sources:
S&P 500 Index (SPX) and U.S. M2 Money Supply.
Calculating Growth Rates:
SPX Growth: The script calculates the percentage growth of the S&P 500 index by comparing the current closing price with the previous period's closing price.
M2 Growth: Similarly, it calculates the percentage growth of the U.S. M2 money supply by comparing the current value with the previous period's value.
Growth Gap/Delta:
Growth Gap: The core of the indicator is the "growth gap" or "delta," which is the difference between the M2 money supply growth and the SPX growth. This gap indicates whether liquidity in the economy (represented by M2) is outpacing or lagging behind the performance of the stock market.
Interpretation:
Positive Gap (Green Bars): When the M2 growth outpaces SPX growth, the gap is positive, indicating that there is more liquidity in the system than what is being reflected in the stock market. This scenario often signals potential upward momentum in the market, making it a good time to consider buying.
Negative Gap (Red Bars): When the SPX growth outpaces M2 growth, the gap is negative, suggesting that the market may be overextended relative to the available liquidity. This can be a warning sign of potential market corrections or downturns.
Visualization:
The indicator plots the growth gap as a histogram with bars colored based on the gap value:
Green Bars: Indicate a positive gap where M2 growth is higher than SPX growth.
Red Bars: Indicate a negative gap where SPX growth is higher than M2 growth.
The bars are thickened for better visibility, and a horizontal line at zero is plotted to help users easily distinguish between positive and negative gaps.
How To Use It:
Time Frame Selection: Users can select the desired time frame (e.g., monthly, weekly) for the data. This flexibility allows traders to analyze the indicator over different periods, depending on their investment horizon.
Monthly time frames seem to work best.
Interpreting the Indicator:
Bullish Signals: Look for sustained periods of positive growth gaps (green bars), which may indicate a favorable environment for buying or holding long positions.
Bearish Signals: Be cautious during periods of negative growth gaps (red bars), which could signal overvaluation in the market or potential pullbacks.
Enjoy and let me know if you have any questions.
Catastrophe DistanceCatastrophe Distance is a tool to visually explore the time between catastrophic price moves.
Catastrophes are defined with 2 variables:
drawdown_threshold: the amount of percent the price has to fall
lookback_period = the amount of last candles in which drawdown_threshold was reached.
Drawdown_threshold per default is 25% and lookback_period is 5, meaning per default if price moves -25% in the last 5 candles you have a catastrophe.
Feel free to play around with this values to fit all the events you consider a catastrophe.
This indicator does not provide signals. It however implies caution if the time since the last catastrophe is higher then the average time between catastrophes (of last x catastrophes).
This is marked by the label over the current price showing the actual and average time since last catastrophe turning from green to black.
Given that the distance between catastrophes is somewhat cyclical:
Maybe now is a good time to start phishing for low limit orders and reduce leverage?
Prometheus NFP LevelsThis script is a tool to mark the high and low of the most recent first Friday of the month. The significance of that day is that’s when the Bureau of Labor Statistics reports the Non Farm Payrolls (NFP) for the month prior. This number includes how many jobs were added that month, the unemployment rate, and labor force participation rate to name a few.
It is always on the first Friday of the new month, and markets tend to care about it quite a bit.
This script also allows a user to get the high and low of a specific date, the default date is the last Federal Open Market Committee day (FOMC). On this day the Federal Reserve announces the Federal Funds Interest Rate, as well as giving guidance on things like bond buying programs, to name a few.
Markets care about these days a lot, that is why we decided to make this script. Prometheus plans to update the default custom date with the most recent FOMC date as they come around.
Here we see the FOMC level high in blue, and low in yellow as well as the NFP high and low in green and red. The white boxes highlight areas where the market reacted to the levels.
On this chart we see a different asset still has interactions with the levels.
We chose to have the user input the date the way we did, not as a timestamp, for this code:
ts_start = timestamp(event_year, event_month, event_day, 9, 30)
ts_end = timestamp(event_year, event_month, event_day+1, 0, 0)
Adding one to the inputted date gives us a simple way to define the time range.
Prometheus encourages users to use indicators as tools along with their own discretion. No indicator is 100% accurate. We encourage comments about requested features and criticism.
Smoothed SuperTrend with VWAP Confirmation [CHE] Smoothed SuperTrend with Automated Optimization and VWAP Confirmation
Overview
The "Smoothed SuperTrend with VWAP Confirmation" is an advanced technical analysis indicator designed for precise trend identification and trading signal generation. This script integrates a smoothed version of the popular SuperTrend indicator with an additional layer of confirmation using the Volume-Weighted Average Price (VWAP). The combination of these two elements offers traders a powerful tool for identifying optimal entry and exit points in the market.
Key Features
1. Smoothed SuperTrend
- Super Smoother Algorithm: The SuperTrend in this script is not just a regular one; it is enhanced by the Super Smoother filter, which reduces market noise and provides more reliable trend signals.
- Customizable Parameters: Traders can adjust three different sets of SuperTrend parameters (factor and ATR length), allowing them to tailor the indicator to their specific trading strategies.
- Automatic Optimization: The script automatically evaluates the performance of each SuperTrend parameter set and selects the one with the best cumulative performance. This selection process can be set to pick either the best or the worst performing parameter set, depending on the trader's preference.
2. VWAP Confirmation
- Precise Trend Confirmation: Once the best-performing SuperTrend is identified, the script further refines the signals by using VWAP as a confirmation tool. VWAP is a highly respected indicator in the trading community, often used to assess the true average price of an asset.
- Long and Short Signal Generation: The script generates Long and Short signals only when the price action is confirmed by both the SuperTrend and VWAP. For a Long signal, the price must be above the VWAP, and for a Short signal, it must be below the VWAP. This dual confirmation ensures higher accuracy and reduces the likelihood of false signals.
3. Visual and Informative Labels
- Signal Labels: Upon confirmation of a trend reversal by both the SuperTrend and VWAP, the script plots clear labels on the chart, indicating confirmed Long or Short signals. These labels are customizable in terms of color, text, and size, ensuring they fit seamlessly into any chart setup.
- Best Parameters Display: At the close of the most recent bar, the script displays a label that provides detailed information about the best-performing SuperTrend parameters and their cumulative performance. This feature keeps traders informed about which settings are currently most effective.
Input Customization Options
1. Super Smoother Length
- Traders can define the length of the Super Smoother filter, which is used to smooth both price data and ATR (Average True Range) values. This input allows traders to control the sensitivity of the indicator, with shorter lengths providing faster responses and longer lengths offering smoother trends.
2. SuperTrend Parameters
- Factor: For each of the three SuperTrends, traders can set a unique factor that determines the distance of the SuperTrend bands from the average price. A higher factor results in wider bands and fewer signals, while a lower factor results in narrower bands and more signals.
- ATR Length: Traders can also specify the length of the ATR used in each SuperTrend calculation. A longer ATR period captures broader market volatility, while a shorter period focuses on more immediate price movements.
3. Label Settings
- Label Colors: The script allows full customization of label colors for Long and Short signals, ensuring that they match the trader’s chart aesthetics.
- Label Text Colors and Sizes: Traders can adjust the text color and size of the labels for Long, Short, and information labels, allowing them to prioritize visibility and readability on their charts.
4. Performance Selection Mode
- Best or Worst Performer: This input allows traders to select whether the script should optimize for the best or worst performing SuperTrend parameter set. This flexibility is useful in different market conditions, where a trader might want to analyze either the strongest trend or focus on a contrarian strategy.
5. VWAP Calculation
- The script automatically recalculates the VWAP based on trend changes, ensuring that the confirmation signals are as accurate and relevant as possible to the current market context.
Important Note
This script is designed to provide more accurate trend signals and confirmations, but like all technical indicators, it should not be used in isolation. It is recommended to use this tool as part of a broader trading strategy, including proper risk management and consideration of fundamental market conditions.
Conclusion
The "Smoothed SuperTrend with VWAP Confirmation" script is an innovative trading tool that combines the strengths of the SuperTrend and VWAP indicators. By integrating smoothing techniques and automatic parameter optimization, this indicator provides traders with more accurate and reliable trend signals. The added confirmation by VWAP further enhances the precision of the entry and exit points, making it an excellent choice for traders looking to improve their technical analysis and trading outcomes. This tool is especially valuable for those who prefer customizable inputs and a systematic approach to trading, ensuring that the indicator adapts to various market conditions and individual trading styles.
Best regards
Chervolino
Entropy Indicator [CHE]Entropy in Technical Analysis Using TradingView
Slide 1: Title
Entropy in Technical Analysis Using TradingView
Introduction to the concept of entropy
Application in technical analysis
Understanding the use of entropy as a market indicator
Slide 2: What is Entropy?
Definition and Origins:
Entropy originates from thermodynamics and information theory.
In thermodynamics, entropy describes the degree of disorder or randomness in a system.
In information theory, entropy quantifies the uncertainty or unpredictability of information content.
Mathematical Definition:
Entropy measures the unpredictability of a system.
The basic idea: Higher entropy means more randomness; lower entropy indicates more predictability.
Formula: Entropy is calculated using the probabilities of different outcomes, based on how frequently certain price levels are reached.
Slide 3: Entropy in Financial Markets
Why Entropy Matters:
Market Uncertainty: Entropy can measure the level of uncertainty or randomness in financial markets.
Volatility Indicator: High entropy may indicate a volatile, unpredictable market, while low entropy suggests a stable, predictable market.
Applications in Trading:
Trend Analysis: Identifying periods of high entropy can help detect potential trend reversals or periods of market consolidation.
Risk Management: Using entropy to adjust trading strategies based on the perceived level of market uncertainty.
Slide 4: How Entropy is Calculated in Trading
Step-by-Step Process:
Data Collection:
The first step is to gather the relevant price data over a specific period, such as 200 closing prices. This data forms the basis of the entropy calculation, representing the market's recent behavior.
Defining Bins:
The price range within the collected data is divided into a fixed number of bins or intervals. These bins represent different price levels. For instance, if you choose 5 bins, the price range will be split into 5 equal segments.
Assigning Data to Bins:
The next step is to assign each price within the data to one of these bins. This step helps in understanding how frequently the price falls within specific ranges, indicating the distribution of prices over the period.
Calculating Probabilities:
After assigning the data to bins, calculate the probability for each bin by dividing the number of data points in each bin by the total number of data points. These probabilities reflect how often prices fall into each range.
Computing Entropy:
Entropy is then calculated based on the distribution of these probabilities. The formula involves summing the products of each probability and the logarithm of that probability. This calculation tells us how evenly the prices are distributed across the bins.
Interpretation for Traders:
High entropy indicates that the prices are spread evenly across the bins, suggesting a highly random and uncertain market. Low entropy, on the other hand, shows that prices are concentrated in fewer bins, indicating more predictable and stable market conditions.
Slide 5: Implementing and Using Entropy in TradingView
How It Works in TradingView:
Data Period: Typically, entropy is calculated over a specific number of bars (e.g., 200), representing recent market activity. The longer the period, the broader the market behavior considered.
Bin Division: The price range during this period is divided into a set number of bins. These bins help to categorize price levels and assess how spread out the market’s activity is.
Entropy Calculation: The indicator evaluates the spread of prices across these bins to determine the level of market disorder. This is visualized on the chart as an entropy line, helping traders to see fluctuations in market uncertainty.
Practical Application:
As a trader, you can use the entropy indicator to gauge when the market is in a state of high uncertainty (high entropy) or low uncertainty (low entropy). This insight can inform decisions on when to take riskier trades or when to stay conservative.
Slide 6: Interpreting the Entropy Indicator
High Entropy:
Characteristics:
Indicates a high level of market disorder, where price movements are more random and less predictable.
Suggests volatile or unpredictable market conditions.
Implications for Traders:
During periods of high entropy, traders might need to exercise greater caution, reduce position sizes, or employ more defensive trading strategies.
High entropy could signal potential trend reversals or significant market movements, making it a critical period to watch closely.
Low Entropy:
Characteristics:
Suggests that the market is more predictable, with prices showing less variation and more consistent trends.
Typically associated with trending markets where price movement is more orderly.
Implications for Traders:
In a low entropy environment, traders might favor trend-following strategies, as the market shows clearer directional movement.
Low entropy can also suggest more reliable trading opportunities, where the risk of sudden, unpredictable price swings is reduced.
Slide 7: Use Cases and Strategy Integration
Practical Use Cases:
Trend Reversals: Use entropy to identify potential points where a market may shift from trending to consolidating, or vice versa. A sudden increase in entropy might indicate the end of a stable trend and the start of a more volatile period.
Volatility Detection: Detect periods of increased market volatility by observing spikes in entropy. These periods can be critical for adjusting your trading strategy, either by scaling back or by taking advantage of the increased movement.
Strategy Integration:
Risk Management: Incorporate entropy into your risk management strategy by adjusting position sizes, leverage, or stop-loss levels based on the current entropy reading. In high entropy conditions, it might be wise to take smaller, more conservative positions.
Combining Indicators: Entropy can be effectively combined with other indicators, such as moving averages or RSI, to provide a more comprehensive view of market conditions. For example, using entropy alongside a trend indicator can help confirm whether a trend is strong and likely to continue, or if it's weakening and at risk of reversal.
Slide 8: Advantages and Limitations of Entropy
Advantages:
Unique Perspective: Entropy offers a unique way to measure market uncertainty that complements traditional volatility measures. It provides traders with insights into the randomness and predictability of price movements, which can be crucial for strategic decision-making.
Dynamic Analysis: Entropy adapts to changes in market conditions, offering real-time insights into the level of market disorder. This makes it a valuable tool for traders who need to stay responsive to the market's evolving dynamics.
Limitations:
Complex Interpretation: Unlike more straightforward indicators, entropy requires a deeper understanding to interpret correctly. Traders need to be familiar with how entropy levels relate to market behavior and what actions to take in response.
Sensitivity to Parameters: The results can vary significantly depending on the number of bins and the data period chosen, requiring careful parameter selection. Traders may need to experiment with different settings to find the most informative configuration for their specific market or trading style.
Slide 9: Conclusion
Key Takeaways:
Entropy as a Tool: Provides a unique perspective on market dynamics by measuring unpredictability. This can help traders better understand the nature of market conditions and tailor their strategies accordingly.
Practical Application: Can enhance trading strategies, particularly in volatile markets, by helping to identify periods of high uncertainty and adjusting risk management practices.
Further Exploration: Experimenting with different bin sizes and periods can help fine-tune the entropy indicator for specific markets and trading strategies. Traders are encouraged to combine entropy with other indicators to build a more robust trading framework.
Final Thoughts:
Entropy is a powerful concept that, when applied correctly, can offer valuable insights into market behavior. It should be used in conjunction with other tools and indicators to make informed trading decisions, particularly in markets where unpredictability plays a significant role.
This presentation provides a comprehensive overview of entropy, its significance in financial markets, and how it can be practically applied as an indicator in TradingView. The focus is on how traders can use entropy to enhance their trading strategies and improve their understanding of market conditions.
Best regards
Chervolino
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.
Big Volumes HighlighterBig Volumes Highlighter
Overview:
The "Big Volume Highlighter" is a powerful tool designed to help traders quickly identify candles with the highest trading volume over a specified period. This indicator not only highlights the most significant volume candles but also color-codes them based on the candle's direction—green for bullish (close > open) and red for bearish (close < open). Whether you're analyzing volume spikes or looking for key moments in price action, this indicator provides clear visual cues to enhance your trading decisions.
Features:
Customizable Lookback Period: Define the number of candles to consider when determining the highest volume.
Automatic Color Coding: Candles with the highest volume are highlighted in green if bullish and red if bearish.
Visual Clarity: The indicator marks the significant volume candles with a triangle above the bar and changes the background color to match, making it easy to spot important volume events at a glance.
Use Cases:
Volume Spike Detection:
Quickly identify when a large volume enters the market, which may indicate significant buying or selling pressure.
Trend Confirmation: Use volume spikes to confirm trends or potential reversals by observing the direction of the high-volume candles.
Market Sentiment Analysis: Understand market sentiment by analyzing the direction of the candles with the biggest volumes.
How to Use:
Add the "Big Volume Highlighter" to your chart.
Adjust the lookback period to suit your analysis.
Observe the highlighted candles for insights into market dynamics.
This script is ideal for traders who want to incorporate volume analysis into their technical strategy, providing a simple yet effective way to monitor significant volume changes in the market.
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
