Bitcoin CME-Spot Z-Spread - Strategy [presentTrading]This time is a swing trading strategy! It measures the sentiment of the Bitcoin market through the spread of CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. By applying Bollinger Bands to the spread, the strategy seeks to capture mean-reversion opportunities when prices deviate significantly from their historical norms
█ Introduction and How it is Different
The Bitcoin CME-Spot Bollinger Bands Strategy is designed to capture mean-reversion opportunities by exploiting the spread between CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. The strategy uses Bollinger Bands to detect when the spread between these two correlated assets has deviated significantly from its historical norm, signaling potential overbought or oversold conditions.
What sets this strategy apart is its focus on spread trading between futures and spot markets rather than price-based indicators. By applying Bollinger Bands to the spread rather than individual prices, the strategy identifies price inefficiencies across markets, allowing traders to take advantage of the natural reversion to the mean that often occurs in these correlated assets.
BTCUSD 8hr Performance
█ Strategy, How It Works: Detailed Explanation
The strategy relies on Bollinger Bands to assess the volatility and relative deviation of the spread between CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. Bollinger Bands consist of a moving average and two standard deviation bands, which help measure how much the spread deviates from its historical mean.
🔶 Spread Calculation:
The spread is calculated by subtracting the Bitfinex spot price from the CME Bitcoin futures price:
Spread = CME Price - Bitfinex Price
This spread represents the difference between the futures and spot markets, which may widen or narrow based on supply and demand dynamics in each market. By analyzing the spread, the strategy can detect when prices are too far apart (potentially overbought or oversold), indicating a trading opportunity.
🔶 Bollinger Bands Calculation:
The Bollinger Bands for the spread are calculated using a simple moving average (SMA) and the standard deviation of the spread over a defined period.
1. Moving Average (SMA):
The simple moving average of the spread (mu_S) over a specified period P is calculated as:
mu_S = (1/P) * sum(S_i from i=1 to P)
Where S_i represents the spread at time i, and P is the lookback period (default is 200 bars). The moving average provides a baseline for the normal spread behavior.
2. Standard Deviation:
The standard deviation (sigma_S) of the spread is calculated to measure the volatility of the spread:
sigma_S = sqrt((1/P) * sum((S_i - mu_S)^2 from i=1 to P))
3. Upper and Lower Bollinger Bands:
The upper and lower Bollinger Bands are derived by adding and subtracting a multiple of the standard deviation from the moving average. The number of standard deviations is determined by a user-defined parameter k (default is 2.618).
- Upper Band:
Upper Band = mu_S + (k * sigma_S)
- Lower Band:
Lower Band = mu_S - (k * sigma_S)
These bands provide a dynamic range within which the spread typically fluctuates. When the spread moves outside of these bands, it is considered overbought or oversold, potentially offering trading opportunities.
Local view
🔶 Entry Conditions:
- Long Entry: A long position is triggered when the spread crosses below the lower Bollinger Band, indicating that the spread has become oversold and is likely to revert upward.
Spread < Lower Band
- Short Entry: A short position is triggered when the spread crosses above the upper Bollinger Band, indicating that the spread has become overbought and is likely to revert downward.
Spread > Upper Band
🔶 Risk Management and Profit-Taking:
The strategy incorporates multi-step take profits to lock in gains as the trade moves in favor. The position is gradually reduced at predefined profit levels, reducing risk while allowing part of the trade to continue running if the price keeps moving favorably.
Additionally, the strategy uses a hold period exit mechanism. If the trade does not hit any of the take-profit levels within a certain number of bars, the position is closed automatically to avoid excessive exposure to market risks.
█ Trade Direction
The trade direction is based on deviations of the spread from its historical norm:
- Long Trade: The strategy enters a long position when the spread crosses below the lower Bollinger Band, signaling an oversold condition where the spread is expected to narrow.
- Short Trade: The strategy enters a short position when the spread crosses above the upper Bollinger Band, signaling an overbought condition where the spread is expected to widen.
These entries rely on the assumption of mean reversion, where extreme deviations from the average spread are likely to revert over time.
█ Usage
The Bitcoin CME-Spot Bollinger Bands Strategy is ideal for traders looking to capitalize on price inefficiencies between Bitcoin futures and spot markets. It’s especially useful in volatile markets where large deviations between futures and spot prices occur.
- Market Conditions: This strategy is most effective in correlated markets, like CME futures and spot Bitcoin. Traders can adjust the Bollinger Bands period and standard deviation multiplier to suit different volatility regimes.
- Backtesting: Before deployment, backtesting the strategy across different market conditions and timeframes is recommended to ensure robustness. Adjust the take-profit steps and hold periods to reflect the trader’s risk tolerance and market behavior.
█ Default Settings
The default settings provide a balanced approach to spread trading using Bollinger Bands but can be adjusted depending on market conditions or personal trading preferences.
🔶 Bollinger Bands Period (200 bars):
This defines the number of bars used to calculate the moving average and standard deviation for the Bollinger Bands. A longer period smooths out short-term fluctuations and focuses on larger, more significant trends. Adjusting the period affects the responsiveness of the strategy:
- Shorter periods (e.g., 100 bars): Makes the strategy more reactive to short-term market fluctuations, potentially generating more signals but increasing the risk of false positives.
- Longer periods (e.g., 300 bars): Focuses on longer-term trends, reducing the frequency of trades and focusing only on significant deviations.
🔶 Standard Deviation Multiplier (2.618):
The multiplier controls how wide the Bollinger Bands are around the moving average. By default, the bands are set at 2.618 standard deviations away from the average, ensuring that only significant deviations trigger trades.
- Higher multipliers (e.g., 3.0): Require a more extreme deviation to trigger trades, reducing trade frequency but potentially increasing the accuracy of signals.
- Lower multipliers (e.g., 2.0): Make the bands narrower, increasing the number of trade signals but potentially decreasing their reliability.
🔶 Take-Profit Levels:
The strategy has four take-profit levels to gradually lock in profits:
- Level 1 (3%): 25% of the position is closed at a 3% profit.
- Level 2 (8%): 20% of the position is closed at an 8% profit.
- Level 3 (14%): 15% of the position is closed at a 14% profit.
- Level 4 (21%): 10% of the position is closed at a 21% profit.
Adjusting these take-profit levels affects how quickly profits are realized:
- Lower take-profit levels: Capture gains more quickly, reducing risk but potentially cutting off larger profits.
- Higher take-profit levels: Let trades run longer, aiming for bigger gains but increasing the risk of price reversals before profits are locked in.
🔶 Hold Days (20 bars):
The strategy automatically closes the position after 20 bars if none of the take-profit levels are hit. This feature prevents trades from being held indefinitely, especially if market conditions are stagnant. Adjusting this:
- Shorter hold periods: Reduce the duration of exposure, minimizing risks from market changes but potentially closing trades too early.
- Longer hold periods: Allow trades to stay open longer, increasing the chance for mean reversion but also increasing exposure to unfavorable market conditions.
By understanding how these default settings affect the strategy’s performance, traders can optimize the Bitcoin CME-Spot Bollinger Bands Strategy to their preferences, adapting it to different market environments and risk tolerances.
Cari dalam skrip untuk "Futures"
FCNC SpreadTitle: FCNC Spread Indicator
Description:
The FCNC Spread Indicator is designed to help traders analyze the price difference (spread) between two futures contracts: the front contract and the next contract. This type of analysis is commonly used in futures trading to identify market sentiment, arbitrage opportunities, and potential roll yield strategies.
How It Works:
Front Contract: The front contract represents the futures contract closest to expiration, often referred to as the near-month contract.
Next Contract: The next contract is the futures contract that follows the front contract in the expiration cycle, typically the next available month.
Spread Calculation: frontContract - nextContract represents the difference between the price of the front contract and the next contract.
Positive Spread: A positive value means that the front contract is more expensive than the next contract, indicating backwardation.
Negative Spread: A negative value means that the front contract is cheaper than the next contract, indicating contango.
How to Use:
Input Selection: Select your desired futures contracts for the front and next contract through the input settings. The script will fetch and calculate the closing prices of these contracts.
Spread Plotting: The calculated spread is plotted on the chart, with color-coding based on the spread's value (green for positive, red for negative).
Labeling: The spread value is dynamically labeled on the chart for quick reference.
Moving Average: A 20-period Simple Moving Average (SMA) of the spread is also plotted to help identify trends and smooth out fluctuations.
Applications:
Trend Identification: Analyze the spread to determine market sentiment and potential trend reversals.
Divergence Detection: Look for divergences between the spread and the underlying market to identify possible shifts in trend or market sentiment. Divergences can signal upcoming reversals or provide early warning signs of a change in market dynamics.
This indicator is particularly useful for futures traders who are looking to gain insights into the market structure and to exploit differences in contract pricing. By providing a clear visualization of the spread between two key futures contracts, traders can make more informed decisions about their trading strategies.
Commitment of Trader %RThis script is a TradingView Pine Script that creates a custom indicator to analyze Commitment of Traders (COT) data. It leverages the TradingView COT library to fetch data related to futures and options markets, processes this data, and then applies the Williams %R indicator to the COT data to assist in trading decisions. Here’s a detailed explanation of its components and functionality:
Importing and Configuration:
The script imports the COT library from TradingView and sets up tooltips to explain different input options to the user.
It allows the user to choose the mode for fetching COT data, which can be based on the root of the symbol, base currency, or quote currency.
Users can also input a specific CFTC code directly, instead of relying on automatic code generation.
Inputs and Parameters:
The script provides inputs to select the type of data (futures, options, or both), the type of COT data to display (long positions, short positions, etc.), and thresholds for the Williams %R indicator.
It also allows setting the period for the Williams %R calculation.
Data Request and Processing:
The dataRequest function fetches COT data for large traders, small traders, and commercial hedgers.
The script calculates the Williams %R for each type of trader, which measures overbought and oversold conditions.
Visualization:
The script uses background colors to highlight when the Williams %R crosses the specified thresholds for commercial hedgers.
It plots the COT data and Williams %R on the chart, with different colors representing large traders, small traders, and commercial hedgers.
Horizontal lines are drawn to indicate the upper and lower thresholds.
Display Information:
A table is displayed on the chart’s lower left corner showing the current COT data and CFTC code used.
Use of COT Report in Futures Trading
The COT report is a weekly publication by the Commodity Futures Trading Commission (CFTC) that provides insights into the positions held by different types of traders in the futures markets. This information is valuable for traders as it shows:
Market Sentiment: By analyzing the positions of commercial traders (often considered to be more informed), non-commercial traders (speculative traders), and small traders, traders can gauge market sentiment and potential future movements.
Contrarian Indicators: Large shifts in positions, especially when non-commercial traders hold extreme positions, can signal potential reversals or trends.
Research on COT Data and Price Movements
Several academic studies have examined the relationship between COT data and price movements in financial markets. Here are a few key works:
"The Predictive Power of the Commitment of Traders Report" by Jacob J. (2009):
This paper explores how changes in the positions of different types of traders in the COT report can predict future price movements in futures markets.
Citation: Jacob, J. (2009). The Predictive Power of the Commitment of Traders Report. Journal of Futures Markets.
"A New Look at the Commitment of Traders Report" by Mitchell, C. (2010):
Mitchell analyzes the efficacy of using COT data as a trading signal and its impact on trading strategies.
Citation: Mitchell, C. (2010). A New Look at the Commitment of Traders Report. Financial Analysts Journal.
"Market Timing Using the Commitment of Traders Report" by Kirkpatrick, C., & Dahlquist, J. (2011):
This study investigates the use of COT data for market timing and the effectiveness of various trading strategies based on the report.
Citation: Kirkpatrick, C., & Dahlquist, J. (2011). Market Timing Using the Commitment of Traders Report. Technical Analysis of Stocks & Commodities.
These studies provide insights into how COT data can be utilized for forecasting and trading decisions, reinforcing the utility of incorporating such data into trading strategies.
VolCorrBeta [NariCapitalTrading]Indicator Overview: VolCorrBeta
The VolCorrBeta indicator is designed to analyze and interpret intermarket relationships. This indicator combines volatility, correlation, and beta calculations to provide a comprehensive view of how certain assets (BTC, DXY, CL) influence the ES futures contract (I tailored this indicator to the ES contract, but it will work for any symbol).
Functionality
Input Symbols
BTCUSD : Bitcoin to USD
DXY : US Dollar Index
CL1! : Crude Oil Futures
ES1! : S&P 500 Futures
These symbols can be customized according to user preferences. The main focus of the indicator is to analyze how the price movements of these assets correlate with and lead the price movements of the ES futures contract.
Parameters for Calculation
Correlation Length : Number of periods for calculating the correlation.
Standard Deviation Length : Number of periods for calculating the standard deviation.
Lookback Period for Beta : Number of periods for calculating beta.
Volatility Filter Length : Length of the volatility filter.
Volatility Threshold : Threshold for adjusting the lookback period based on volatility.
Key Calculations
Returns Calculation : Computes the daily returns for each input symbol.
Correlation Calculation : Computes the correlation between each input symbol's returns and the ES futures contract returns over the specified correlation length.
Standard Deviation Calculation : Computes the standard deviation for each input symbol's returns and the ES futures contract returns.
Beta Calculation : Computes the beta for each input symbol relative to the ES futures contract.
Weighted Returns Calculation : Computes the weighted returns based on the calculated betas.
Lead-Lag Indicator : Calculates a lead-lag indicator by averaging the weighted returns.
Volatility Filter : Smooths the lead-lag indicator using a simple moving average.
Price Target Estimation : Estimates the ES price target based on the lead-lag indicator (the yellow line on the chart).
Dynamic Stop Loss (SL) and Take Profit (TP) Levels : Calculates dynamic SL and TP levels using volatility bands.
Signal Generation
The indicator generates buy and sell signals based on the filtered lead-lag indicator and confirms them using higher timeframe analysis. Signals are debounced to reduce frequency, ensuring that only significant signals are considered.
Visualization
Background Coloring : The background color changes based on the buy and sell signals for easy visualization (user can toggle this on/off).
Signal Labels : Labels with arrows are plotted on the chart, showing the signal type (buy/sell), the entry price, TP, and SL levels.
Estimated ES Price Target : The estimated price target for ES futures is plotted on the chart.
Correlation and Beta Dashboard : A table displayed in the top right corner shows the current correlation and beta values for relative to the ES futures contract.
Customization
Traders can customize the following parameters to tailor the indicator to their specific needs:
Input Symbols : Change the symbols for BTC, DXY, CL, and ES.
Correlation Length : Adjust the number of periods used for calculating correlation.
Standard Deviation Length : Adjust the number of periods used for calculating standard deviation.
Lookback Period for Beta : Change the lookback period for calculating beta.
Volatility Filter Length : Modify the length of the volatility filter.
Volatility Threshold : Set a threshold for adjusting the lookback period based on volatility.
Plotting Options : Customize the colors and line widths of the plotted elements.
Volume Liqidations [EagleVSniper]The Volume Liquidations Indicator is designed for traders who want to spot significant liquidation events in the cryptocurrency markets, particularly between spot and futures volumes. This powerful tool auto-detects the trading asset and compares the volume data from both spot and futures markets to highlight potential high-volume liquidation points that can significantly impact price movement. Raw source code owner - tartigradia
Features:
Auto-Detect Functionality: Automatically identifies the current trading asset, providing an option for manual selection for both spot and futures symbols.
Volume Comparison: Calculates the difference between futures and spot volumes within a user-defined timeframe, helping to identify liquidation events.
Customizable Parameters: Offers customizable options for multipliers, lookback periods, and timeframe selection to tailor the indicator to your trading strategy.
Visual Indicators: Displays liquidation volumes as color-coded columns, with green indicating potential long liquidations and red for short liquidations. It also highlights bars that exceed the high-volume threshold, providing a clear visual cue for significant liquidation events.
Spot and Futures Volume MA: Includes optional moving average plots for both spot and futures volumes, allowing for a deeper analysis of market trends.
Highlighting High-Volatility Candles: The indicator uniquely colors candles that reach a predefined volatility threshold, determined by the user-set multiplier. This functionality aims to spotlight moments of significant market volatility, providing traders with immediate visual cues.
Dynamic Ticker Selection: Seamlessly switches between auto and manual ticker selection, providing flexibility for all types of traders.
How to Use:
Setup: Configure the indicator to your preferences. You can choose between automatic or manual ticker selection, set the multiplier for the high-volume threshold, and define the lookback period for the moving average calculation.
Analysis: The indicator plots differences in volume between futures and spot markets as columns on your chart, color-coded to indicate the direction of potential liquidations.
Decision Making: Use the indicator to identify potential liquidation events. High-volume thresholds are highlighted, suggesting significant market movements. Combine this information with other analysis tools to make informed trading decisions.
BTC Volume Contango IndexBased on my previous script "BTC Contango Index" which was inspired by a Twitter post by Byzantine General:
This is a script that shows the contango between spot and futures volumes of Bitcoin to identify overbought and oversold conditions. When a market is in contango, the volume of a futures contract is higher than the spot volume. Conversely, when a market is in backwardation, the volume of the futures contract is lower than the spot volume.
The aggregate daily volumes on top exchanges are taken to obtain Total Spot Volume and Total Futures Volume. The script then plots (Total Futures Volume/Total Spot Volume) - 1 to illustrate the percent difference (contango) between spot and futures volumes of Bitcoin. This data by itself is useful, but because aggregate futures volumes are so much larger than spot volumes, no negative values are produced. To correct for this, the Z-score of contango is taken. The Z-score (z) of a data item x measures the distance (in standard deviations StdDev) and direction of the item from its mean (U):
Z-score = (x - U) / StDev
A value of zero indicates that the data item x is equal to the mean U, while positive or negative values show that the data item is above or below the mean (x Values of +2 and -2 show that the data item is two standard deviations above or below the chosen mean, respectively, and over 95.5% of all data items are contained within these two horizontal references). We substitute x with volume contango C, the mean U with simple moving average ( SMA ) of n periods (50), and StdDev with the standard deviation of closing contango for n periods (50), so the above formula becomes: Z-score = (C - SMA (50)) / StdDev(C,50).
When in contango, Bitcoin may be overbought.
When in backwardation, Bitcoin may be oversold.
The current bar calculation will always look incorrect due to TV plotting the Z-score before the bar closes.
Crude Roll Trade SimulatorEDIT : The screen cap was unintended with the script publication. The yellow arrow is pointing to a different indicator I wrote. The "Roll Sim" indicator is shown below that one. Yes I could do a different screen cap, but then I'd have to rewrite this and frankly I don't have time. END EDIT
If you have ever wanted to visualize the contango / backwardation pressure of a roll trade, this script will help you approximate it.
I am writing this description in haste so go with me on my rough explanations.
A "roll trade" is one involving futures that are continually rolled over into future months. Popular roll trade instruments are USO (oil futures) and UVXY (volatility futures).
Roll trades suffer hits from contango but get rewarded in periods of backwardation. Use this script to track the contango / backwardation pressure on what you are trading.
That involves identifying and providing both the underlying indexes and derivatives for both the front and back month of the roll trade. What does that mean? Well the defaults simulate (crudely) the UVXY roll trade: The folks at Proshares buy futures that expire 60 days away and then sell those 30 days later as short term futures (again, this is a crude description - see the prospectus) and we simulate that by providing the Roll Sim indicator the symbols VIX and VXV along with VIXY and VIXM. We also provide the days between the purchase and sale of the rolled futures contract (in sessions, which is 22 days by my reckoning).
The script performs ema smoothing and plots both the index lines (VIX and VXV as solid lines in our case) and the derivatives (VIXY and VIXM as dotted lines in our case) with the line graphs offset by the number of sessions between the buy and sell. The gap you see represents the contango / backwardation the derivative roll trades are experiencing and gives you an idea how much movement has to happen for that gap to widen, contract or even invert. The background gets painted red in periods of backwardation (when the longer term futures cost less than when sold as short term futures).
Fortunately indexes are calibrated to the same underlying factors, so their values relative to each other are meaningful (ie VXV of 18 and VIX of 15 are based on the same calculation on premiums for S&P500 symbols, with VXV being normally higher for time value). That means the indexes graph well without and adjustments needed. Unfortunately derivatives suffer contango / backwardation at different rates so the value of VIXY vs VIXM isn't really meaningful (VIXY may take a reverse split one year while VIXM doesn't) ... what is meaningful is their relative change in value day to day. So I have included a "front month multiplier" which can be used to get the front month line "moved up or down" on the screen so it can be compared to the back month.
As a practical matter, I have come to hide the lines for the derivatives (like VIXY and VIXM) and just focus on the gap changes between the indexes which gives me an idea of what is going on in the market and what contango/backwardation pressure is likely to exist next week.
Hope it is useful to you.
Binance OI Stochastic MFIibb.co Binance Open Interest Stochastic Money Flow Index (OI Stochastic MFI)
Inspiration:
This indicator is an innovative tool combining the traditional Money Flow Index (MFI) and Stochastic Oscillator concepts, enhanced by directly incorporating Open Interest data from Binance Futures BTCUSDT perpetual contracts.
What is it and what does it measure?
The traditional Money Flow Index (MFI) measures the flow of money considering both price and volume.
Open Interest represents the total number of outstanding futures contracts at any given moment, offering deeper insight into speculative involvement and investors' positioning.
This indicator replaces the traditional volume input with Open Interest, providing a more accurate perspective of speculative inflows and outflows in Bitcoin's perpetual futures market.
Advantages and Applications:
Higher accuracy for futures markets, particularly cryptocurrencies, due to direct usage of Binance Futures data reflecting real and speculative activities.
Clear identification of extreme overbought and oversold levels.
Provides objective visual signals for buying (green upward arrows) and selling (red downward arrows).
How to interpret:
The indicator oscillates between values of 0 and 100.
Values above the configured overbought level (e.g., 80) indicate potential downward reversals.
Values below the configured oversold level (e.g., 20) indicate potential upward reversals.
Crossovers of the K-line (blue) with the D-line (orange) generate immediate buy or sell signals.
Practical use:
Long (buy): Look for a green upward arrow after the indicator exits an oversold region.
Short (sell): Look for a red downward arrow after the indicator exits an overbought region.
This indicator is especially useful for traders operating perpetual futures contracts, providing increased precision and clarity for decision-making based on speculative money flows.
ConeCastConeCast is a forward-looking projection indicator that visualizes a future price range (or "cone") based on recent trend momentum and adaptive volatility. Unlike lagging bands or reactive channels, this tool plots a predictive zone 3–50 bars ahead, allowing traders to anticipate potential price behavior rather than merely react to it.
How It Works
The core of ConeCast is a dynamic trend-slope engine derived from a Linear Regression line fitted over a user-defined lookback window. The slope of this trend is projected forward, and the cone’s width adapts based on real-time market volatility. In calm markets, the cone is narrow and focused. In volatile regimes, it expands proportionally, using an ATR-based % of price to scale.
Key Features
📈 Predictive Cone Zone: Visualizes a forward range using trend slope × volatility width.
🔄 Auto-Adaptive Volatility Scaling: Expands or contracts based on market quiet/chaotic states.
📊 Regime Detection: Identifies Bull, Bear, or Neutral states using a tunable slope threshold.
🧭 Multi-Timeframe Compatible: Slope and volatility can be calculated from higher timeframes.
🔔 Smart Alerts: Detects price entering the cone, and signals trend regime changes in real time.
🖼️ Clean Visual Output: Optionally includes outer cones, trend-trail marker, and dashboard label.
How to Use It
Use on 15m–4H charts for best forward visibility.
Look for price entering the cone as a potential trend continuation setup.
Monitor regime changes and volatility expansion to filter choppy market zones.
Tune the slope sensitivity and ATR multiplier to match your symbol's behavior.
Use outer cones to anticipate aggressive swings and wick traps.
What Makes It Unique
ConeCast doesn’t follow price — it predicts a possible future price envelope using trend + volatility math, without relying on lagging indicators or repainting logic. It's a hybrid of regression-based forecasting and dynamic risk zoning, designed for swing traders, scalpers, and algo developers alike.
Limitations
ConeCast projects based on current trend and volatility — it does not "know" future price. Like all projection tools, accuracy depends on trend persistence and market conditions. Use this in combination with confirmation signals and risk management.
Quarterly Cycle Theory with DST time AdjustedThe Quarterly Theory removes ambiguity, as it gives specific time-based reference points to look for when entering trades. Before being able to apply this theory to trading, one must first understand that time is fractal:
Yearly Quarters = 4 quarters of three months each.
Monthly Quarters = 4 quarters of one week each.
Weekly Quarters = 4 quarters of one day each (Monday - Thursday). Friday has its own specific function.
Daily Quarters = 4 quarters of 6 hours each = 4 trading sessions of a trading day.
Sessions Quarters = 4 quarters of 90 minutes each.
90 Minute Quarters = 4 quarters of 22.5 minutes each.
Yearly Cycle: Analogously to financial quarters, the year is divided in four sections of three months each:
Q1 - January, February, March.
Q2 - April, May, June (True Open, April Open).
Q3 - July, August, September.
Q4 - October, November, December.
S&P 500 E-mini Futures (daily candles) — Monthly Cycle.
Monthly Cycle: Considering that we have four weeks in a month, we start the cycle on the first month’s Monday (regardless of the calendar Day):
Q1 - Week 1: first Monday of the month.
Q2 - Week 2: second Monday of the month (True Open, Daily Candle Open Price).
Q3 - Week 3: third Monday of the month.
Q4 - Week 4: fourth Monday of the month.
S&P 500 E-mini Futures (4 hour candles) — Weekly Cycle.
Weekly Cycle: Daye determined that although the trading week is composed by 5 trading days, we should ignore Friday, and the small portion of Sunday’s price action:
Q1 - Monday.
Q2 - Tuesday (True Open, Daily Candle Open Price).
Q3 - Wednesday.
Q4 - Thursday.
S&P 500 E-mini Futures (1 hour candles) — Daily Cycle.
Daily Cycle: The Day can be broken down into 6 hour quarters. These times roughly define the sessions of the trading day, reinforcing the theory’s validity:
Q1 - 18:00 - 00:00 Asia.
Q2 - 00:00 - 06:00 London (True Open).
Q3 - 06:00 - 12:00 NY AM.
Q4 - 12:00 - 18:00 NY PM.
S&P 500 E-mini Futures (15 minute candles) — 6 Hour Cycle.
6 Hour Quarters or 90 Minute Cycle / Sessions divided into four sections of 90 minutes each (EST/EDT):
Asian Session
Q1 - 18:00 - 19:30
Q2 - 19:30 - 21:00 (True Open)
Q3 - 21:00 - 22:30
Q4 - 22:30 - 00:00
London Session
Q1 - 00:00 - 01:30
Q2 - 01:30 - 03:00 (True Open)
Q3 - 03:00 - 04:30
Q4 - 04:30 - 06:00
NY AM Session
Q1 - 06:00 - 07:30
Q2 - 07:30 - 09:00 (True Open)
Q3 - 09:00 - 10:30
Q4 - 10:30 - 12:00
NY PM Session
Q1 - 12:00 - 13:30
Q2 - 13:30 - 15:00 (True Open)
Q3 - 15:00 - 16:30
Q4 - 16:30 - 18:00
S&P 500 E-mini Futures (5 minute candles) — 90 Minute Cycle.
Micro Cycles: Dividing the 90 Minute Cycle yields 22.5 Minute Quarters, also known as Micro Sessions or Micro Quarters:
Asian Session
Q1/1 18:00:00 - 18:22:30
Q2 18:22:30 - 18:45:00
Q3 18:45:00 - 19:07:30
Q4 19:07:30 - 19:30:00
Q2/1 19:30:00 - 19:52:30 (True Session Open)
Q2/2 19:52:30 - 20:15:00
Q2/3 20:15:00 - 20:37:30
Q2/4 20:37:30 - 21:00:00
Q3/1 21:00:00 - 21:23:30
etc. 21:23:30 - 21:45:00
London Session
00:00:00 - 00:22:30 (True Daily Open)
00:22:30 - 00:45:00
00:45:00 - 01:07:30
01:07:30 - 01:30:00
01:30:00 - 01:52:30 (True Session Open)
01:52:30 - 02:15:00
02:15:00 - 02:37:30
02:37:30 - 03:00:00
03:00:00 - 03:22:30
03:22:30 - 03:45:00
03:45:00 - 04:07:30
04:07:30 - 04:30:00
04:30:00 - 04:52:30
04:52:30 - 05:15:00
05:15:00 - 05:37:30
05:37:30 - 06:00:00
New York AM Session
06:00:00 - 06:22:30
06:22:30 - 06:45:00
06:45:00 - 07:07:30
07:07:30 - 07:30:00
07:30:00 - 07:52:30 (True Session Open)
07:52:30 - 08:15:00
08:15:00 - 08:37:30
08:37:30 - 09:00:00
09:00:00 - 09:22:30
09:22:30 - 09:45:00
09:45:00 - 10:07:30
10:07:30 - 10:30:00
10:30:00 - 10:52:30
10:52:30 - 11:15:00
11:15:00 - 11:37:30
11:37:30 - 12:00:00
New York PM Session
12:00:00 - 12:22:30
12:22:30 - 12:45:00
12:45:00 - 13:07:30
13:07:30 - 13:30:00
13:30:00 - 13:52:30 (True Session Open)
13:52:30 - 14:15:00
14:15:00 - 14:37:30
14:37:30 - 15:00:00
15:00:00 - 15:22:30
15:22:30 - 15:45:00
15:45:00 - 15:37:30
15:37:30 - 16:00:00
16:00:00 - 16:22:30
16:22:30 - 16:45:00
16:45:00 - 17:07:30
17:07:30 - 18:00:00
S&P 500 E-mini Futures (30 second candles) — 22.5 Minute Cycle.
Volatility Arbitrage Spread Oscillator Model (VASOM)The Volatility Arbitrage Spread Oscillator Model (VASOM) is a systematic approach to capitalizing on price inefficiencies in the VIX futures term structure. By analyzing the differential between front-month and second-month VIX futures contracts, we employ a momentum-based oscillator (Relative Strength Index, RSI) to signal potential market reversion opportunities. Our research builds upon existing financial literature on volatility risk premia and contango/backwardation dynamics in the volatility markets (Zhang & Zhu, 2006; Alexander & Korovilas, 2012).
Volatility derivatives have become essential tools for managing risk and engaging in speculative trades (Whaley, 2009). The Chicago Board Options Exchange (CBOE) Volatility Index (VIX) measures the market’s expectation of 30-day forward-looking volatility derived from S&P 500 option prices (CBOE, 2018). Term structures in VIX futures often exhibit contango or backwardation, depending on macroeconomic and market conditions (Alexander & Korovilas, 2012).
This strategy seeks to exploit the spread between the front-month and second-month VIX futures as a proxy for term structure dynamics. The spread’s momentum, quantified by the RSI, serves as a signal for entry and exit points, aligning with empirical findings on mean reversion in volatility markets (Zhang & Zhu, 2006).
• Entry Signal: When RSI_t falls below the user-defined threshold (e.g., 30), indicating a potential undervaluation in the spread.
• Exit Signal: When RSI_t exceeds a threshold (e.g., 70), suggesting mean reversion has occurred.
Empirical Justification
The strategy aligns with findings that suggest predictable patterns in volatility futures spreads (Alexander & Korovilas, 2012). Furthermore, the use of RSI leverages insights from momentum-based trading models, which have demonstrated efficacy in various asset classes, including commodities and derivatives (Jegadeesh & Titman, 1993).
References
• Alexander, C., & Korovilas, D. (2012). The Hazards of Volatility Investing. Journal of Alternative Investments, 15(2), 92-104.
• CBOE. (2018). The VIX White Paper. Chicago Board Options Exchange.
• Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
• Zhang, C., & Zhu, Y. (2006). Exploiting Predictability in Volatility Futures Spreads. Financial Analysts Journal, 62(6), 62-72.
• Whaley, R. E. (2009). Understanding the VIX. The Journal of Portfolio Management, 35(3), 98-105.
Codi's Perp-Spot Basis# Perp-Spot Basis Indicator
This indicator calculates the percentage basis between perpetual futures and spot prices for crypto assets. It is inspired by the original concept from **Krugermacro**, with the added improvement of **automatic detection of the asset pairs** based on the current chart symbol. This enhancement makes it faster and easier to apply across different assets without manual configuration.
## How It Works
The indicator compares the perpetual futures price (e.g., `BTCUSDT.P`) to the spot price (e.g., `BTCUSDT`) on Binance. The difference is expressed as a percentage: (Perp - Spot) / Spot * 100
The results are displayed in a color-coded graph:
- **Blue (Positive Basis):** Perpetual futures are trading at a premium, indicating **bullish sentiment** among derivatives traders.
- **Red (Negative Basis):** Perpetual futures are trading at a discount, indicating **bearish sentiment** among derivatives traders.
This percentage basis is a core component in understanding funding rates and derivatives market dynamics. It serves as a faster proxy for funding rates, which typically lag behind real-time price movements.
---
## How to Use It
### General Concept
- **Red (Negative Basis):** Ideal to execute **longs** when derivatives traders are overly bearish.
- **Blue (Positive Basis):** Ideal to execute **shorts** when derivatives traders are overly bullish.
### Pullback Sniping
1. During an **uptrend**:
- If the basis turns **red** temporarily, it can signal an opportunity to **buy the dip**.
2. During a **downtrend**:
- If the basis turns **blue** temporarily, it can signal an opportunity to **sell the rip**.
3. Wait for the basis to **pop back** (higher in uptrend, lower in downtrend) to time entries more effectively—this often coincides with **stop runs** or **liquidations**.
### Intraday Execution
- **When price is falling**:
- If the basis is **red**, the move is derivatives-led (**normal**).
- If the basis is **blue**, spot traders are leading, and perps are offside—wait for **price dumps** before longing.
- **When price is rising**:
- If the basis is **blue**, the move is derivatives-led (**normal**).
- If the basis is **red**, spot traders are leading, and perps are offside—wait for **price pops** before shorting.
### Larger Time Frames
- **Consistently Blue Basis:** Indicates a **bull market** as derivatives traders are bullish over the long term.
- **Consistently Red Basis:** Indicates a **bear market** as derivatives traders are bearish over the long term.
---
## Improvements Over the Original
This version of the Perp-Spot Basis indicator **automatically detects the Binance perpetual futures and spot pairs** based on the current chart symbol. For example:
- If you are viewing `ETHUSDT`, it automatically references `ETHUSDT.P` for the perpetual futures pair and `ETHUSDT` for the spot pair in BINANCE.
@tk · spectral█ OVERVIEW
This script is an indicator that helps traders to identify the price difference between spot and futures of the current crypto plotted into the chart. It works in both types of markets, when the chart is plotting the crypto in spot market, it will compare with its respective futures ticker and vice-versa. If the current asset isn't a crypt ticker, the indicator will not be plotted into the chart.
█ MOTIVATION
Since crypto's derivative market is based on spot market asset's price, to calculate the arbitrage mechanisms that attempts to balance the asset price, this indicator can help traders to identify some spot and futures price divergence that can create an anomaly of funding rate and can push it to an extreme negative — or positive — rate. So, easing to track the price difference between both markets will bring more evidences to identify an artificial price move, specially in crypto assets with low market cap.
█ CONCEPT
The trading concept to use this indicator is the concept of the arbitrage machamism created by exchanges that calculates the funding rate based on spot and futures price difference that will vary from exchange to exchange. This strategy don't works alone. It needs to be aligned together with others indicators like Exponential Moving Averages, Chart Patterns, Support and Resistance, and so on... Even more confluences that you have, bigger are your chances to increase the probability for a successful trade. So, don't use this indicator alone. Compose a trading strategy and use it to improve your analysis.
█ CUSTOMIZATION
This indicator allows the trader to customize the following settings:
GENERAL
Text size
Changes the font size of price difference table to improve accessibility.
Type: string
Options: `tiny`, `small`, `normal`, `large`.
Default: `small`
Position
Changes the position of price difference table.
Type: string
Options: `top_left`, `top_center`, `top_right`, `middle_left`, `middle_center`, `middle_right`, `bottom_left`, `bottom_center`, `bottom_right`.
Default: `bottom_right`
Pair Quote
The ticker quote symbol that will be used to base the ticker comparison from spot to futures (e.g. BTCUSDT which `USDT` is the quote. ETHBTC which `BTC` is the quote).
Type: string
Default: USDT
Spectrum Color
The color of the spectrum candles. Spectrum candles are the candles of the opposite market. If the current ticker is in the spot market, the spectrum candles will be the price of the futures market.
Type: color
Default: #434651
█ FUNCTIONS
The indicator contains the following functions:
stripStarts(src, str)
Strips a defined pattern from a string.
Parameters:
src: (string) Source string
str: (string) String pattern to be stripped from start of source string.
Returns: (string) Stripped string with matched regex pattern.
Open Interest Chart [LuxAlgo]The Open Interest Chart displays Commitments of Traders %change of futures open interest , with a unique circular plotting technique, inspired from this publication Periodic Ellipses .
🔶 USAGE
Open interest represents the total number of contracts that have been entered by market participants but have not yet been offset or delivered. This can be a direct indicator of market activity/liquidity, with higher open interest indicating a more active market.
Increasing open interest is highlighted in green on the circular plot, indicating money coming into the market, while decreasing open interests highlighted in red indicates money coming out of the market.
You can set up to 6 different Futures Open interest tickers for a quick follow up:
🔶 DETAILS
Circles are drawn, using plot() , with the functions createOuterCircle() (for the largest circle) and createInnerCircle() (for inner circles).
Following snippet will reload the chart, so the circles will remain at the right side of the chart:
if ta.change(chart.left_visible_bar_time ) or
ta.change(chart.right_visible_bar_time)
n := bar_index
Here is a snippet which will draw a 39-bars wide circle that will keep updating its position to the right.
//@version=5
indicator("")
n = bar_index
barsTillEnd = last_bar_index - n
if ta.change(chart.left_visible_bar_time ) or
ta.change(chart.right_visible_bar_time)
n := bar_index
createOuterCircle(radius) =>
var int end = na
var int start = na
var basis = 0.
barsFromNearestEdgeCircle = 0.
barsTillEndFromCircleStart = radius
startCylce = barsTillEnd % barsTillEndFromCircleStart == 0 // start circle
bars = ta.barssince(startCylce)
barsFromNearestEdgeCircle := barsTillEndFromCircleStart -1
basis := math.min(startCylce ? -1 : basis + 1 / barsFromNearestEdgeCircle * 2, 1) // 0 -> 1
shape = math.sqrt(1 - basis * basis)
rad = radius / 2
isOK = barsTillEnd <= barsTillEndFromCircleStart and barsTillEnd > 0
hi = isOK ? (rad + shape * radius) - rad : na
lo = isOK ? (rad - shape * radius) - rad : na
start := barsTillEnd == barsTillEndFromCircleStart ? n -1 : start
end := barsTillEnd == 0 ? start + radius : end
= createOuterCircle(40)
plot(h), plot(l)
🔶 LIMITATIONS
Due to the inability to draw between bars, from time to time, drawings can be slightly off.
Bar-replay can be demanding, since it has to reload on every bar progression. We don't recommend using this script on bar-replay. If you do, please choose the lowest speed and from time to time pause bar-replay for a second. You'll see the script gets reloaded.
🔶 SETTINGS
🔹 TICKERS
Toggle :
• Enabled -> uses the first column with a pre-filled list of Futures Open Interest tickers/symbols
• Disabled -> uses the empty field where you can enter your own ticker/symbol
Pre-filled list : the first column is filled with a list, so you can choose your open interest easily, otherwise you would see COT:088691_F_OI aka Gold Futures Open Interest for example.
If applicable, you will see 3 different COT data:
• COT: Legacy Commitments of Traders report data
• COT2: Disaggregated Commitments of Traders report data
• COT3: Traders in Financial Futures report data
Empty field : When needed, you can pick another ticker/symbol in the empty field at the right and disable the toggle.
Timeframe : Commitments of Traders (COT) data is tallied by the Commodity Futures Trading Commission (CFTC) and is published weekly. Therefore data won't change every day.
Default set TF is Daily
🔹 STYLE
From middle:
• Enabled (default): Drawings start from the middle circle -> towards outer circle is + %change , towards middle of the circle is - %change
• Disabled: Drawings start from the middle POINT of the circle, towards outer circle is + OR -
-> in both options, + %change will be coloured green , - %change will be coloured red .
-> 0 %change will be coloured blue , and when no data is available, this will be coloured gray .
Size circle : options tiny, small, normal, large, huge.
Angle : Only applicable if "From middle" is disabled!
-> sets the angle of the spike:
Show Ticker : Name of ticker, as seen in table, will be added to labels.
Text - fill
• Sets colour for +/- %change
Table
• Sets 2 text colours, size and position
Circles
• Sets the colour of circles, style can be changed in the Style section.
You can make it as crazy as you want:
NSDT Custom High and Low LinesFirst, the credit for the original script to plot a High and Low between a certain time goes to developer paaax.
I took that idea, converted it to Pinescript V5, cleaned up the code, and added a few more lines so you can plot different levels based on time of day.
Published open source like the original.
The example shown has:
Blue - plotting from the start of the Futures Asian session to the start of the Futures USA Session. (6:00PM - 9:30AM Eastern)
Yellow - plotting from the start of the Futures Europe session to the start of the Futures USA Session. (3:00AM - 9:30AM Eastern)
Green - plotting from the start of the Futures US Premarket session to the start of the Futures USA Session. (8:00AM - 9:30AM Eastern)
These are great levels to use for breakouts and/or support and resistance.
Combine these levels with the 5 min Open Range levels, as you have some good trades.
Each of the three sessions have individual start and end times that can be modified by the trader, so you can easily mark off important areas for your style of trading.
MicroStrategy MetricsA script showing all the key MSTR metrics. I will update the script every time degen Saylor sells some more office furniture to buy BTC.
All based around valuing MSTR, aside from its BTC holdings. I.e. the true market cap = enterprise value - BTC holdings. Hence, you're left with the value of the software business + any premium/discount decided by investors.
From this we can derive:
- BTC Holdings % of enterprise value
- Correlation to BTC (in this case we use CME futures...may change this)
- Equivalent Share Price (true market cap divided by shares outstanding)
- P/E Ratio (equivalent share price divided by quarterly EPS estimates x 4)
- Price to FCF Ratio (true market cap divided by FCF (ttm))
- Price to Revenue (^ but with total revenue (ttm))
Open Interest Auto SpaceManBTCOpen Interest Auto SpaceManBTC
This is an extension to the script, it aims to provide the data in a less hands on way by providing the basis for automatic calculation on which symbol the data is being pulled from.
Changelog:
Automatic Data retrieval on a percoin basis.
Ability to hide or show symbol.
Coloring choices for the user.
BTC Contango IndexInspired by a Twitter post by Byzantine General:
This is a script that shows the contango between spot and futures prices of Bitcoin to identify overbought and oversold conditions. Contango and backwardation are terms used to define the structure of the forward curve. When a market is in contango, the forward price of a futures contract is higher than the spot price. Conversely, when a market is in backwardation, the forward price of the futures contract is lower than the spot price.
The aggregate prices on top exchanges are taken and then averaged to obtain a Spot Average and a Futures Average. The script then plots (Futures Average/Spot Average) - 1 to illustrate the percent difference (contango) between spot and futures prices of Bitcoin.
When in contango, Bitcoin may be overbought.
When in backwardation, Bitcoin may be oversold.
Weis Pip Wave jayyWhat you see here is the Weis pip wave. The Weis pip wave shows how far in price a Weis wave has traveled through the duration of a Weis wave. The Weis pip wave is used in combination with the Weis cumulative volume wave. The two waves must be set to the same "wave size" and using the same method as described by Weis.
Using the traditional Weis method simply enter the desired wave size in the box "Select Weis Wave Size". In the example shown, it is set to 5 points. Each wave for each security and each timeframe requires its own wave size. Although not the traditional method a more automatic way to set wave size would be to use ATR. This is not the true Weis method but it does give you similar waves and, importantly, without the hassle of selecting a wave size for every chart. Once the Weis wave size is set then the pip wave will be shown.
I have put a zigzag of a 5 point Weis wave on the above bar chart. I have added it to allow your eye to get a better appreciation for Weis wave pivot points. You will notice that the wave is not in straight lines connecting wave tops to bottoms this is a function of the limitations of Pinescript version 1. This script would need to be in version 4 to allow straight lines. I will elaborate on the Weis pip zigzag script.
What is a Weis wave? David Weis has been recognized as a Wyckoff method analyst he has written two books one of which, Trades About to Happen, describes the evolution of the now popular Weis wave. The method employed by Weis is to identify waves of price action and to compare the strength of the waves on characteristics of wave strength. Chief among the characteristics of strength is the cumulative volume of the wave. There are other markers that Weis uses as well for example how the actual price difference between the start of the Weis wave from start to finish. Weis also uses time, particularly when using a Renko chart. Weis specifically uses candle/bar closes to define all wave action.
David Weis did a futures.io video which is a popular source of information about his method.
Cheers jayy
PS This script was published a day ago, however, I had included some links to the website of a person that uses Weis pip waves and also a dropbox link that contains the Weis wave chart for May 27, 2020, published by David Weis. Providing those links is against TV policy and so the script was hidden by TV. This is the identical script with the identical settings but without the offending links. If you want to see the pip Weis method in practice then search Weis pip wave. I have absolutely no affiliation. If you want to see Weis chart in pdf then message me and I will give a link or the Weis pdf. Why would you want to see the Weis chart for May 27, 2020? Merely to confirm the veracity of my algorithm. You could compare my chart () from the same period to the Weis chart. Both waves are for the ES!1 4 hour chart and both for a wave size of 5.
ADX Volatility Moving AverageThe ADXVMA is a volatility based moving average with the volatility being determined by the value of the ADX. The ADXVMA provides levels of support during uptrends and resistance during downtrends. Original NT indicator by Fat Tails on futures.io, just ported it to pinescript
Fibonacci BandsCreates bands based on Fibonacci numbers and the SMA.
Based on indicator by Big Mike on futures.io
How to trade
- Best to use in ranging market conditions
- Place on two different time frames eg. 15 and 55 min.
- Take trades off either short or long term chart.
- Best trades occur when both charts show same trigger/condition.
- Trades are short term reversals in direction of major trend on longer term chart unless you expect a trend reversal.
- Determine which band is the limiting band for the volatility of the instrument.
- When the market closes outside of the limiting band then returns inside, take a long/short one tick above/below the high/low of the previous bar.
- Place stop below/above the low/high of the the recent swing low/high.
- Set targets at opposite band of chart
_CM_COT Commercial Net Interest_Upper_V1Overview.
-This is the Beginning of a Educational Series from Jake Bernstein to the TradingView Community.
-Many Traders use the COT Data Incorrectly.
-Jake Discovered if You Look at the Net Commercials and Take Note When Commercials net Buying is Either At All Time Highs, Or Net Buying = Longest Period of Buying Look for an Extreme Move To the Upside.
-In The Future We Will Show Precise Entry Signals…But a Basic Entry Signal Is When Commercials Go From Net Long to Net Short.
-Full Credit in Methodology goes to Jake Bernstein at www.Trade-Futures.com and www.2Chimps.net
Thought Process:
-Commercials Represent Large (Typically Billion Dollar) Companies.
-Take Note - When Commercials Are Buying at Record High
-Take Note - When Commercials Are Buying For Record Long Periods of Time
***Note…Commercials Can Buy For Extended Periods Dollar Cost Averaging…
***Basic Entry Listed In Overview.
***More Precise Entries Will Be Introduced Soon.
Indicator Shows Net Commercials
-Full Credit goes to Greeny for Creating Original Code. I only made slight modifications.
Modifications include
-Added Ability to Plot Text Entries when Commercials Switch From Net Long To Short
-Added Optional Background Highlighting when Commercials Switch from Long to Short
-Added Optional Alert Capability If Commercials Go From Net Long to Short
***Additional Indicators and Updates Coming Soon
***Link To Lower Indicator:
_CM_COT Commercial Net Interest_V1Overview.
-This is the Beginning of a Educational Series from Jake Bernstein to the TradingView Community.
-Many Traders use the COT Data Incorrectly.
-Jake Discovered if You Look at the Net Commercials and Take Note When Commercials net Buying is Either At All Time Highs, Or Net Buying = Longest Period of Buying Look for an Extreme Move To the Upside.
-In The Future We Will Show Precise Entry Signals…But a Basic Entry Signal Is When Commercials Go From Net Long to Net Short.
-Full Credit in Methodology goes to Jake Bernstein at www.Trade-Futures.com and www.2Chimps.net
Thought Process:
-Commercials Represent Large (Typically Billion Dollar) Companies.
-Take Note - When Commercials Are Buying at Record High
-Take Note - When Commercials Are Buying For Record Long Periods of Time
***Note…Commercials Can Buy For Extended Periods Dollar Cost Averaging…
***Basic Entry Listed In Overview.
***More Precise Entries Will Be Introduced Soon.
Indicator Shows Net Commercials
-Full Credit goes to Greeny for Creating Original Code. I only made slight modifications.
Modifications include
-Took Off Net Long and Short Individual Plots
-Added Optional Background Highlighting when Commercials Switch from Long to Short
-Added Optional Alert Capability If Commercials Go From Net Long to Short
-Ability to Show INVERSE - This makes it Easier for some Traders to See…Since the Signals look similar to MacD/RSI Type Indicators.
***Additional Indicators and Updates Coming Soon
***Link To Upper Indicator:
