Multiple Indicators Screener v2After taking the approval of Mr. QuantNomad
Multiple Indicators Screener by QuantNomad
New lists have been modified and added
Built-in indicators:
RSI (Relative Strength Index): Provides trading opportunities based on overbought or oversold market conditions.
MFI (Cash Flow Index): Measures the flow of cash into or from assets, which helps in identifying buying and selling areas.
Williams Percent Range (WPR): Measures how high or low the price has been in the last time period, giving signals of periods of saturation.
Supertrend: Used to determine market direction and potential entry and exit locations.
Volume Change Percentage: Provides an analysis of the volume change percentage, which helps in identifying demand and supply changes for assets.
How to use:
Users can choose which symbols they want to monitor and analyze using a variety of built-in indicators.
The indicator provides visual signals that help traders identify potential trading opportunities based on the selected settings.
RSI in purple = buy weak liquidity (safe entry).
MFI in yellow = Liquidity
WPR in blue = RSI, MFI and WPR in oversold areas for all.
Allows users to customize the display locations and appearance of the cursor to their personal preferences.
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
=========================================================================
فاحص لمؤشرات متعددة مع مخرجات جدول شاملة لتسهيل مراقبة الكثير من العملات تصل الى 99 في وقت واحد
بختصر الشرح
ظهور اللون البنفسجي يعني كمية الشراء ضعف السيولة .
ظهور اللون الازرق جميع المؤشرات وصلة الى مرحلة التشبع البيعي ( دخول آمن )
ظهور اللون الاصفر يعني السيولة ضعفين الشراء ( عكس اتجاه قريب ) == ركزو على هاللون خصوصا مع عملات الخفيفة
"demand"に関するスクリプトを検索
Price alert multi symbols (Miu)This indicator won't plot anything to the chart.
Please follow steps below to set your alarms based on multiple symbols' prices:
1) Add indicator to the chart
2) Go to settings
3) Check symbols you want to receive alerts (choose up to 8 different symbols)
4) Set price for each symbol
5) Once all is set go back to the chart and click on 3 dots to set alert in this indicator, rename your alert and confirm
6) You can remove indicator after alert is set and it'll keep working as expected
What does this indicator do?
This indicator will generate alerts based on following conditions:
- If price set is met for any symbol
Once condition is met it will send an alert with the following information:
- Symbol name (e.g: BTC, ETH, LTC)
- Price reached
This script requests current price for each symbol through request.security() built-in function. It also requests amount of digits (mintick) for each symbol to send alerts with correct value.
This script was developed to attend a demand from a comment in other published script.
Feel free to give feedbacks on comments section below.
Enjoy!
Smart Money Setup 05 [TradingFinder] Minor OB & Trend Proof🔵 Introduction
The "Smart Money Concept" transcends the realm of mere technical trading strategies to embody a comprehensive philosophy on the dynamics of market operations. It posits that key market participants engage in price manipulation, thereby complicating the trading landscape for smaller, retail traders.
Under this doctrine, retail traders are advised to tailor their strategies in alignment with the maneuvers of "Smart Money" - essentially, the capital operated by market makers.
To this end, one should endeavor to mirror the trading patterns of these influential market participants, who are adept at navigating through the nuances of supply, demand, and overall market structure. As a proponent of Smart Money trading, these elements are pivotal in your decision-making process for trade entries.
🟣 Key Insights
The core principle of this strategy hinges on misleading other traders. A sudden market movement against the prevailing trend that results in the formation of either a lower low or a higher high, followed by a pullback where a divergence pattern emerges, sets the stage.
Subsequently, the market may form another lower low or higher high. Traders, persuaded that the market will continue along the trajectory of the new movement, are caught off-guard when the price abruptly reverses direction. Following a "Stop Hunt" of the traders' open positions, the market resumes its initial trend.
To grasp the essence of this setup, observe the following illustrations.
"Bullish Setup" :
"Bearish Setup" :
🔵 How to Use
The setups can be customized based on the desired formation period. This adjustment can be made through the indicator's price setting options, where the default period is set at 2.
Upon configuring your preferred period, the signals become actionable. Once a setup forms, the subsequent step involves waiting for the price to reach the "Order Block".
"Bullish Setup" :
"Bearish Setup" :
Smart Money Setup 04 [TradingFinder] Three Drive (Harmonic) + OB🔵 Introduction
The "Three Drive" pattern is a well-known formation in technical analysis, recognized for its ability to signal potential trend reversals in price action. Within the realm of trading, particularly in the context of "Reversal Patterns," the Three Drive pattern holds significance as a reliable indicator of shifts in market sentiment.
🟣 Bullish 3 Drive
This pattern typically manifests at a price bottom, where a sequence of lower lows suggests a prevailing negative trend. However, within the structure of the Three Drive pattern, a notable occurrence unfolds.
The second low breaches the range of the first low, followed by the third low surpassing the range of the second low. These penetrations signify a diminishing selling pressure and an emerging buying interest.
Traders often await the confirmation of the third low surpassing the second low as an entry point, with price targets set at the highs formed within the Three Drive pattern.
🟣 Bearish 3 Drive
Conversely, the Bearish Three Drive pattern emerges at a price top, characterized by a sequence of higher highs indicating an upward trend. Yet, amidst this apparent bullish momentum, a shift occurs.
The second high breaks beyond the range of the first high, succeeded by the third high exceeding the range of the second high. These breaches signify a waning buying strength and a resurgence in selling pressure.
Entry into a trade is often executed after the confirmation of the third high surpassing the second high, with targets set at the lows formed within the Three Drive pattern.
Importance :
Understanding the Three Drive pattern's significance extends beyond mere technical analysis. It bears resemblance to other established patterns, such as the Harmonic Pattern and Ending Diagonal within the Elliott Wave Theory.
Recognizing these parallels aids traders in comprehending broader market dynamics and potential price movements.
🔵 Formation of 3 Drive in Order Block Zone
The convergence of the Three Drive pattern with the concept of the Order Block Zone introduces a nuanced layer to traders' analytical approach.
In "Price Action" methodology, Order Blocks represent areas on the price chart where significant market players, such as institutional traders, have executed notable orders.
These zones often act as barriers, with price encountering resistance or support upon reaching them.
When the Three Drive pattern forms within an Order Block Zone, it signifies a confluence of market dynamics.
The completion of the pattern within this zone suggests a potential reversal in the prevailing trend, augmented by the presence of significant institutional orders.
Traders incorporate these Order Blocks into their analysis to identify probable levels where price may change direction, enhancing the reliability of their trading decisions.
🔵 How to Use :
To effectively utilize the Three Drive pattern within the Order Block Zone, traders seek alignment between the completion of the pattern and the presence of significant Order Blocks.
This convergence enhances the reliability of the pattern's signals, increasing the likelihood of successful trade outcomes.
Bullish Three Drive in Demand Zone :
Bearish Three Drive in Supply Zone :
Settings :
You can set your desired "Pivot Period" via settings for the indicator to identify setups based on it.
Smart Money Setup 03 [TradingFinder] Minor OB & Trend Proof🔵 Introduction
The "Smart Money Concept" transcends mere technical trading strategies; it embodies a comprehensive philosophy elucidating market dynamics. Central to this concept is the acknowledgment that influential market participants manipulate price actions, presenting challenges for retail traders.
As a "retail trader", aligning your strategy with the behavior of "Smart Money," primarily market makers, is paramount. Understanding their trading patterns, which revolve around supply, demand, and market structure, forms the cornerstone of your approach. Consequently, decisions to enter trades should be informed by these considerations.
🟣 Important Note
In this setup, pattern formation revolves around the robustness of the "Stop Hunt" targeting retail traders.
When this stop hunt occurs, if the price tests below the minor pivot or above the minor pivot, a "Minor Order Block" is formed.
Similarly, if the price tests below the major pivot or above the major pivot, a "Major Order Block" is formed.
Since the price hasn't successfully broken the major pivots before breaking the Top or Bottom, it can be inferred that the minor pivots formed within a leg of price movement exhibit a "Range" structure.
For a deeper comprehension of this setup, refer to the accompanying visual aids below.
Bullish Setup Details :
Bearish Setup Details :
🔵 How to Use
Upon integrating the indicator into your chart, exercise patience as you await the evolution of the trading setup.
Experiment with different trading positions by adjusting both the "Time Frame" and "Pivot Period". Typically, setups materializing over longer "Time Frames" and "Pivot Periods" carry heightened validity.
Bullish Setup Details on Chart :
Bearish Setup Details on Chart :
Within the settings, you possess the flexibility to modify the "Pivot Period" input to tailor the indicator to your preferences.
Market Structure (Intrabar) [LuxAlgo]The Market Structure (Intrabar) indicator is designed to automatically detect and highlight real-time intrabar market structures, a core component of the Smart Money Concepts methodology.
🔶 USAGE
The proposed indicator gives a detailed picture of the most recent candle lower timeframe trends, highlighting market structures within them.
This can be particularly useful to assess the price dynamic within the most recent candle. For example, we can see how pronounced a trend is by the number of opposite bullish/bearish market structures formed within the candle.
Users can select the intrabar timeframe of interest from the "Intrabar Timeframe" setting, using a timeframe significantly lower than the chart timeframe will return more intrabar candles and potentially more market structures.
🔹 Dashboard
Users have access to a dashboard returning useful statistics such as the number of formed CHoCH's and BOS's from the intrabar prices. These can be indicative of how predominant a trend is within the intrabar data or if there exist multiple trends.
🔶 DETAILS
Market structures allow determining trend continuations as well as trend reversals in the market through two distinct structures:
🔹 Change of Character (CHoCH)
A change of character (CHoCH) refers to a shift in the market behavior of a security that is driven by changes in the underlying supply and demand dynamics. CHoCH's are indicative of confirmed reversals.
🔹 Break of Structure (BoS)
The break of structure (BoS) refers to the point at which a key level of support or resistance is broken. BOS's are indicative of confirmed trend continuations.
🔶 SETTINGS
🔹Inside the Bar Market Structure
Intrabar Timeframe: Lower timeframe setting option, if set to 'Auto' the script will determine the lower timeframe based on the chart timeframe.
Intrabar Market Structure, Length: Toggles the visibility of the break of structures and change of characters. Length defines the detection length of the swing levels.
Intrabar Swing Levels: Toggles the visibility of the swing levels, including a color customization option for highs and lows.
Intrabar Statistics: Toggles the visibility of the dashboard. Some further statistical details are presented in the tooltips of the table cells
🔹 General
Market Structure Colors: Color customization option for the break of structure and change of character lines and labels.
Intrabar Candle Colors: Color customization option for intrabar candles.
Intrabar Candles Horizontal Offset: Adjusting the intrabar candles horizontal position
Dashboard: Dashboard position and size customization option
🔶 LIMITATIONS
Please note that seconds-based intervals are available for premium and professional plan holders, which implies that the seconds-based intervals usage of the indicator may not be available for all users depending on their subscription plan.
🔶 RELATED SCRIPTS
Smart-Money-Concepts
ICT-Concepts
ATR Bands (Keltner Channel), Wick and SRSI Signals [MW]Introduction
This indicator uses a novel combination of ATR Bands, candle wicks crossing the ATR upper and lower bands, and baseline, and combines them with the Stochastic SRSI oscillator to provide early BUY and SELL signals in uptrends, downtrends, and in ranging price conditions.
How it’s unique
People generally understand Bollinger Bands and Keltner Channels. Buy at the bottom band, sell at the top band. However, because the bands themselves are not static, impulsive moves can render them useless. People also generally understand wicks. Candles with large wicks can represent a change in pattern, or volatile price movement. Combining those two to determine if price is reaching a pivot point is relatively novel. When Stochastic RSI (SRSI) filtering is also added, it becomes a genuinely unique combination that can be used to determine trade entries and exits.
What’s the benefit
The benefit of the indicator is that it can help potentially identify pivots WHEN THEY HAPPEN, and with potentially minimal retracement, depending on the trader’s time window. Many indicators wait for a trend to be established, or wait for a breakout to occur, or have to wait for some form of confirmation. In the interpretation used by this indicator, bands, wicks, and SRSI cycles provide both the signal and confirmation.
It takes into account 3 elements:
Price approaching the upper or lower band or the baseline - MEANING: Price is becoming extended based on calculations that use the candle trading range.
A candle wick of a defined proportion (e.g. wick is 1/2 the size of a full candle OR candle body) crosses a band or baseline, but the body does not cross the band or baseline - MEANING: Buyers and sellers are both very active.
The Stochastic RSI reading is above 80 for SELL signals and below 20 for BUY signals - MEANING: Additional confirmation that price is becoming extended based on the current cyclic price pattern.
How to Use
SIGNALS
Buy Signals - Green(ish):
B Signal - Potential pivot up from the lower band when using the preferred multiplier
B1 Signal - Potential pivot up from the lower band when using phi * multiplier
B2 Signal - Potential pivot up from the lower band when using 1/2 * multiplier
B3 Signal - Potential pivot up from baseline
Sell Signals - Red(ish):
S Signal - Potential pivot down from the upper band when using the preferred multiplier
S1 Signal - Potential pivot down from the upper band when using
S2 Signal - Potential pivot down from the upper band when using 1/2 * multiplier
S3 Signal - Potential pivot down from the baseline
DISCUSSION
During an uptrend or downtrend, signals from the baseline can help traders identify areas where they may enter the trending move with the least amount of drawdown. In both cases, entry points can occur with baseline signals in the direction of the trend.
For example, in an uptrend (when the price is forming higher highs and higher lows, or when the baseline is rising), price tends to oscillate between the upper band and baseline. In this case, the baseline BUY signal (B3) can show an entry point.
In a downtrend (when the price is forming lower highs and lower lows, or when the baseline is falling), price tends to oscillate between the baseline and the lower band. In this case, the baseline SELL signal (S3) can show an entry point.
During consolidation, when price is ranging, price tends to oscillate between the upper and lower bands, while crossing through the baseline unperturbed. Here, entry points can occur at the upper and lower bands.
When all conditions are met at the lower band during consolidation, a BUY signal (B), can occur. This signal may also occur prior to a break out of consolidation to the upside.
When all conditions are met at the upper band during consolidation, a SELL signal (S), can occur. This signal may also occur prior to a break out of consolidation to the downside.
Additional B1, B2, and S1, and S2 signals can be displayed that use the bands based on a multiplier that is half that of the primary one, and phi (0.618) times the primary multiplier as a way to quickly check for signals occurring along different, but related, bands.
Calculations
ATR Bands, or Keltner Channels, are a technical analysis tool that are used to measure market volatility and identify overbought or oversold conditions in the trading of financial instruments, such as stocks, bonds, commodities, and currencies. ATR Bands consist of three lines plotted on a price chart:
Middle Band, Basis, or Baseline: This is typically a simple moving average (SMA) of the closing prices over a certain period. It represents the intermediate-term trend of the asset's price.
Upper Band: This is calculated by adding a certain number of ATRs to the middle band (SMA). The upper band adjusts itself with the increase in volatility.
Lower Band: This is calculated by subtracting the same number of ATRs from the middle band (SMA). Like the upper band, the lower band adjusts to changes in volatility.
The candle wick signals occur if the wick is at the specified ratio compared to either the entire candle or the candle body. The upper band, lower band, and baseline signals happen if the wick is the specified ratio of the total candle size. For the major signals for upper and lower bands, these occur when the wick extends outside of the bands while closing a candle inside of the bands. For the baseline signals, they occur if a wick crosses a baseline but closes on the other side.
Settings
CHANNEL SETTINGS
Baseline EMA Period (Default: 21): Period length of the moving average basis line.
ATR Period (Default: 21): The number of periods over which the Average True Range (ATR) is calculated.
Basis MA Type (Default: SMA): The moving average type for the basis line.
Multiplier (Default: 2.5: The deviation multiplier used to calculate the band distance from the basis line.
ADDITIONAL CHANNELS
Half of Multiplier Offset (Default: True): Toggles the display of the ATR bands that are set a distance of half of the ATR multiplier.
Quarter of Multiplier Offset (Default: false): Toggles the display of the ATR bands that are set a distance of one quarter of the ATR multiplier.
Phi (Φ) Offset (Default: false): Toggles the display of the ATR bands that are set a distance of phi (Φ) times the ATR multiplier.
WICK SETTINGS FOR CANDLE FILTERS
Wick Ratio for Bands (Default: 0.4): The ratio of wick size to total candle size for use at upper and lower bands.
Wick Ratio for Baseline (Default: 0.4): The ratio of wick size to total candle size for use at baseline.
Use Candle Body (rather than full candle size) (Default: false): Determines whether wick calculations use the candle body or the entire candle size.
VISUAL PREFERENCES - SIGNALS
Show Signals (Default: true): Allows signal labels to be shown.
Show Signals from 1/2 Band Offset (Default: false): Toggle signals originating from 1/2 offset upper and lower bands.
Show Signals from Phi (Φ) Band Offset (Default: false): Toggle signals originating from phi (Φ) offset upper and lower bands.
Show Baseline Signals (Default: false): Toggle Baseline signals.
VISUAL PREFERENCES - BANDS
Show ATR (Keltner) Bands (Default: true): Use a background color inside the Bollinger Bands.
Fill Bands (Default: true): Use a background color inside the Bollinger Bands.
STOCHASTIC SETTINGS
Use Stochastic RSI Filtering (Default: False): This will only trigger some SELL signals when the stochastic RSI is above 80, and BUY signals when below 20.
K (Default: 3): The smoothing level for the Stochastic RSI.
RSI Length (Default: 14): The period length for the RSI calculation.
Stochastic Length (Default: 8): The period length over which the stochastic calculation is performed.
Other Usage Notes and Limitations
To understand future price movement, this indicator assumes that 3 things must be known:
Evidence of a change of market structure. This can be demonstrated by increased volatility, consolidation, volume spikes (which can be tracked with the MW Volume Impulse Indicator) or, in the case of this indicator, candle wicks.
The potential cause of the change. It could be a VWAP line (which can be tracked with the Multi VWAP , and Multi VWAP from Gaps indicators), an event, an important support or resistance level, a key moving average, or many other things. This indicator assumes the ATR bands can be a cause.
The current position in the price cycle. Oscillators like the RSI, and MACD, are typical measures of price oscillation (other oscillators like the Price and Volume Stochastic Divergence indicator can also be useful). This indicator uses the Stochastic RSI oscillator to determine overbought and oversold conditions.
When evidence of the change appears, and the potential cause of the change is identified, and the price oscillation is at a favorable position for the desired trading direction, this indicator will generate a signal.
ATR Bands (or Keltner Channels) are used to determine when price might “revert to the mean”. Crossing, or being near the upper or lower band, can indicate an overbought or oversold condition, which could lead to a price reversal. By tracking the behavior of candle wicks during these events, we can see how active the battle is between buyers and sellers.
If the top of a wick is large, it may indicate that sellers are aggressively attempting to bring the price down. Conversely, if the bottom wick is large, it can indicate that buyers are actively trying to counter the price action caused by selling pressure.
When this wicking action occurs at times when price is not near the upper band, lower band, or baseline, it could indicate the presence of an important level. That could mean a nearby VWAP line, a supply or demand zone, a round price number, or a number of other factors. In any case, this wick may be the first indication of a price reversal.
Shorter baseline periods may be better for short period trading like scalping or day trading, while longer period baselines can show signals that are better suited to swing trading, or longer term investing.
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
The TradingView platform allows a maximum of 500 labels per chart. This means that if your settings allow for a lot of signals, labels for earlier ones may not appear if the total number of labels exceeds 500 for the chart.
Bollinger Band Wick and SRSI Signals [MW]Introduction
This indicator uses a novel combination of Bollinger Bands, candle wicks crossing the upper and lower Bollinger Bands and baseline, and combines them with the Stochastic SRSI oscillator to provide early BUY and SELL signals in uptrends, downtrends, and in ranging price conditions.
How it’s unique
People generally understand Bollinger Bands and Keltner Channels. Buy at the bottom band, sell at the top band. However, because the bands themselves are not static, impulsive moves can render them useless. People also generally understand wicks. Candles with large wicks can represent a change in pattern, or volatile price movement. Combining those two to determine if price is reaching a pivot point is relatively novel. When Stochastic RSI (SRSI) filtering is also added, it becomes a genuinely unique combination that can be used to determine trade entries and exits.
What’s the benefit
The benefit of the indicator is that it can help potentially identify pivots WHEN THEY HAPPEN, and with potentially minimal retracement, depending on the trader’s time window. Many indicators wait for a trend to be established, or wait for a breakout to occur, or have to wait for some form of confirmation. In the interpretation used by this indicator, bands, wicks, and SRSI cycles provide both the signal and confirmation.
It takes into account 3 elements:
Price approaching the upper or lower band or the baseline - MEANING: Price is becoming extended based on calculations that use the candle trading range.
A candle wick of a defined proportion (e.g. wick is 1/2 the size of a full candle OR candle body) crosses a band or baseline, but the body does not cross the band or baseline - MEANING: Buyers and sellers are both very active.
The Stochastic RSI reading is above 80 for SELL signals and below 20 for BUY signals - MEANING: Additional confirmation that price is becoming extended based on the current cyclic price pattern.
How to Use
SIGNALS
Buy Signals - Green(ish):
B Signal - Potential pivot up from the lower band when using the preferred multiplier
B1 Signal - Potential pivot up from baseline
Sell Signals - Red(ish):
S Signal - Potential pivot down from the upper band when using the preferred multiplier
S1 Signal - Potential pivot down from the baseline
DISCUSSION
During an uptrend or downtrend, signals from the baseline can help traders identify areas where they may enter the trending move with the least amount of drawdown. In both cases, entry points can occur with baseline signals in the direction of the trend.
For example, in an uptrend (when the price is forming higher highs and higher lows, or when the baseline is rising), price tends to oscillate between the upper band and baseline. In this case, the baseline BUY signal (B3) can show an entry point.
In a downtrend (when the price is forming lower highs and lower lows, or when the baseline is falling), price tends to oscillate between the baseline and the lower band. In this case, the baseline SELL signal (S3) can show an entry point.
During consolidation, when price is ranging, price tends to oscillate between the upper and lower bands, while crossing through the baseline unperturbed. Here, entry points can occur at the upper and lower bands.
When all conditions are met at the lower band during consolidation, a BUY signal (B), can occur. This signal may also occur prior to a break out of consolidation to the upside.
When all conditions are met at the upper band during consolidation, a SELL signal (S), can occur. This signal may also occur prior to a break out of consolidation to the downside.
Additional, B1 and S1 signals can be displayed that use the baseline as the pivot level.
Settings
SIGNALS
Show Bollinger Band Signals (Default: True): Allows signal labels to be shown.
Hide Baseline Signals (Default: False): Baseline signals are on by default. This will turn them off.
Show Wick Signals (Defau
lt: True): Displays signals when wicking occurs.
BOLLINGER BAND SETTINGS
Period length for Bollinger Band Basis (Default: 21): Length of the Bollinger Band (BB) moving average basis line.
Basis MA Type (Default: SMA): The moving average type for the BB Basis line.
Source (Default: “close”): The source of time series data.
Standard Deviation Multiplier (Default: 2.5: The deviation multiplier used to calculate the band distance from the basis line.
WICK SETTINGS FOR BOLLINGER BANDS
Wick Ratio for Bands (Default: 0.3): The ratio of wick size to total candle size for use at upper and lower bands.
Wick Ratio for Baseline (Default: 0.3): The ratio of wick size to total candle size for use at baseline.
WICK SETTINGS FOR CANDLE SIGNALS
Upper Wick Threshold (Default: 50): The percent of upper wick compared to the full candle size or candle body size.
Lower Wick Threshold (Default: 50): The percent of lower wick compared to the full candle size or candle body size.
Use Candle Body (Default: false): Toggles the use of the full candle size versus the candle body size when calculating the wick signal.
VISUAL PREFERENCES
Fill Bands (Default: true): Use a background color inside the Bollinger Bands.
Show Signals (Default: true): Toggle the Bollinger Band upper band, lower band, and baseline signals.
Show Bollinger Bands (Default: true): Show the Bollinger Bands.
STOCHASTIC SETTINGS
Use Stochastic RSI Filtering (Default: False): This will only trigger some SELL signals when the stochastic RSI is above 80, and BUY signals when below 20.
K (Default: 3): The smoothing level for the Stochastic RSI.
RSI Length (Default: 14): The period length for the RSI calculation.
Stochastic Length (Default: 8): The period length over which the stochastic calculation is performed.
Calculations
Bollinger Bands are a technical analysis tool that are used to measure market volatility and identify overbought or oversold conditions in the trading of financial instruments, such as stocks, bonds, commodities, and currencies. Bollinger Bands consist of three lines plotted on a price chart:
Middle Band, Basis, or Baseline: This is typically a simple moving average (SMA) of the closing prices over a certain period. It represents the intermediate-term trend of the asset's price.
Upper Band: This is calculated by adding a certain number of standard deviations to the middle band (SMA). The upper band adjusts itself with the increase in volatility.
Lower Band: This is calculated by subtracting the same number of standard deviations from the middle band (SMA). Like the upper band, the lower band adjusts to changes in volatility.
The candle wick signals occur if the wick is at the specified ratio compared to either the entire candle or the candle body. The upper band, lower band, and baseline signals happen if the wick is the specified ratio of the total candle size. For the major signals for upper and lower bands, these occur when the wick extends outside of the bands while closing a candle inside of the bands. For the baseline signals, they occur if a wick crosses a baseline but closes on the other side.
Other Usage Notes and Limitations
To understand future price movement, this indicator assumes that 3 things must be known:
Evidence of a change of market structure. This can be demonstrated by increased volatility, consolidation, volume spikes (which can be tracked with the MW Volume Impulse Indicator) or, in the case of this indicator, candle wicks.
The potential cause of the change. It could be a VWAP line (which can be tracked with the Multi VWAP , and Multi VWAP from Gaps indicators), an event, an important support or resistance level, a key moving average, or many other things. This indicator assumes the ATR bands can be a cause.
The current position in the price cycle. Oscillators like the RSI, and MACD, are typical measures of price oscillation (other oscillators like the Price and Volume Stochastic Divergence indicator can also be useful). This indicator uses the Stochastic RSI oscillator to determine overbought and oversold conditions.
When evidence of the change appears, and the potential cause of the change is identified, and the price oscillation is at a favorable position for the desired trading direction, this indicator will generate a signal.
ATR Bands (or Keltner Channels) are used to determine when price might “revert to the mean”. Crossing, or being near the upper or lower band, can indicate an overbought or oversold condition, which could lead to a price reversal. By tracking the behavior of candle wicks during these events, we can see how active the battle is between buyers and sellers.
If the top of a wick is large, it may indicate that sellers are aggressively attempting to bring the price down. Conversely, if the bottom wick is large, it can indicate that buyers are actively trying to counter the price action caused by selling pressure.
When this wicking action occurs at times when price is not near the upper band, lower band, or baseline, it could indicate the presence of an important level. That could mean a nearby VWAP line, a supply or demand zone, a round price number, or a number of other factors. In any case, this wick may be the first indication of a price reversal.
Shorter baseline periods may be better for short period trading like scalping or day trading, while longer period baselines can show signals that are better suited to swing trading, or longer term investing.
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
The TradingView platform allows a maximum of 500 labels per chart. This means that if your settings allow for a lot of signals, labels for earlier ones may not appear if the total number of labels exceeds 500 for the chart.
Gaps Profile [vnhilton]Note: If you get an error preventing indicator from executing due to a loop running longer than >500ms, please lower the amount of boxes shown and/or increase the minimum gap % threshold.
OVERVIEW
The Gaps Profile (GP) simply shows the remaining gaps on the chart that have yet to be closed. Gaps are created where there's a distance between the current open and the previous close. Big gaps suggest change in sentiment and volatility causing prices to pull away thereby creating gaps. Gaps can be used as pivot areas where price may attempt to close the inefficiency entirely and/or serve as supply/demand zones.
(FEATURES)
- 3 to 499 remaining up/down gaps can be displayed on the chart (furthest gaps away from price are removed to make way for new gaps)
- Minimum gap % threshold
- Ability to highlight largest or newest up/down gap
- 4 GP color themes: Mono, Up/Down, Up/Down Largest Gradients, Up/Down Newest Gradients
- GP Type: Left, Right (how it is built - overlapping gaps plotted from left/right to right/left)
- GP offset from current bar
- Box border width
- Box border style for up/down: Dashed, Dotted, Solid
- Toggles to hide border/box with ease
Order-Block Detector ICT/SMT + FVG + SignalsOrderBlock-Finder
This script shows order-blocks (OB) and fair-value-gaps (FVG). Additionaly there are entry signals for OB and FVG. The Dist-Parameter tell how many candles should exist between the beginning of the OB or FVG and the pullback.
Order-Blocks
An order block in trading typically refers to a significant grouping of buy or sell orders at a particular price level within a financial market. These blocks of orders can influence price movement when they are executed. Here's a breakdown:
Buy Order Block: This occurs when there's a large concentration of buy orders at a specific price level. It indicates a significant interest among traders to purchase the asset if the price reaches that level.
Sell Order Block: Conversely, a sell order block happens when there's a notable accumulation of sell orders at a particular price level. This suggests that many traders are willing to sell the asset if the price reaches that level.
Impact on Price: Order blocks can influence price movement because when the market approaches these levels, the orders within the block may be triggered, leading to increased buying or selling pressure, depending on the type of block. This surge in trading activity can cause the price to either bounce off the level or break through it.
Support and Resistance: Order blocks are often associated with support and resistance levels. A buy order block may act as support, preventing the price from falling further, while a sell order block may serve as resistance, hindering upward price movement.
Fair-Value-Gap
The fair value gap in trading refers to the difference between the current market price of an asset and its calculated fair value. This concept is often used in financial markets, especially in the context of stocks and other securities. Here's a breakdown:
Market Price: The market price is the price at which an asset is currently trading in the market. It is determined by the interaction of supply and demand forces, as well as various other factors such as news, sentiment, and economic conditions.
Fair Value: Fair value represents the estimated intrinsic value of an asset based on fundamental analysis, which includes factors such as earnings, dividends, cash flow, growth prospects, and prevailing interest rates. It's essentially what an asset should be worth based on its fundamentals.
Fair Value Calculation: Analysts and investors use various methods to calculate the fair value of an asset. Common approaches include discounted cash flow (DCF) analysis, comparable company analysis (CCA), and dividend discount models (DDM), among others.
Fair Value Gap: The fair value gap is the numerical difference between the calculated fair value of an asset and its current market price. If the market price is higher than the fair value, it suggests that the asset may be overvalued. Conversely, if the market price is lower than the fair value, it indicates that the asset may be undervalued.
Trading Implications: Traders and investors often pay attention to the fair value gap to identify potential trading opportunities. If the market price deviates significantly from the fair value, it may present opportunities to buy or sell the asset with the expectation that the market price will eventually converge towards its fair value.
Heikin Ashi and Optimized Trend Tracker and PVSRA [Erebor]Heikin Ashi Candles
Let's consider a modification to the traditional “Heikin Ashi Candles” where we introduce a new parameter: the period of calculation. The traditional HA candles are derived from the open , high low , and close prices of the underlying asset.
Now, let's introduce a new parameter, period, which will determine how many periods are considered in the calculation of the HA candles. This period parameter will affect the smoothing and responsiveness of the resulting candles.
In this modification, instead of considering just the current period, we're averaging or aggregating the prices over a specified number of periods . This will result in candles that reflect a longer-term trend or sentiment, depending on the chosen period value.
For example, if period is set to 1, it would essentially be the same as traditional Heikin Ashi candles. However, if period is set to a higher value, say 5, each candle will represent the average price movement over the last 5 periods, providing a smoother representation of the trend but potentially with delayed signals compared to lower period values.
Traders can adjust the period parameter based on their trading style, the timeframe they're analyzing, and the level of smoothing or responsiveness they prefer in their candlestick patterns.
Optimized Trend Tracker
The "Optimized Trend Tracker" is a proprietary trading indicator developed by TradingView user ANIL ÖZEKŞİ. It is designed to identify and track trends in financial markets efficiently. The indicator attempts to smooth out price fluctuations and provide clear signals for trend direction.
The Optimized Trend Tracker uses a combination of moving averages and adaptive filters to detect trends. It aims to reduce lag and noise typically associated with traditional moving averages, thereby providing more timely and accurate signals.
Some of the key features and applications of the OTT include:
• Trend Identification: The indicator helps traders identify the direction of the prevailing trend in a market. It distinguishes between uptrends, downtrends, and sideways consolidations.
• Entry and Exit Signals: The OTT generates buy and sell signals based on crossovers and direction changes of the trend. Traders can use these signals to time their entries and exits in the market.
• Trend Strength: It also provides insights into the strength of the trend by analyzing the slope and momentum of price movements. This information can help traders assess the conviction behind the trend and adjust their trading strategies accordingly.
• Filter Noise: By employing adaptive filters, the indicator aims to filter out market noise and false signals, thereby enhancing the reliability of trend identification.
• Customization: Traders can customize the parameters of the OTT to suit their specific trading preferences and market conditions. This flexibility allows for adaptation to different timeframes and asset classes.
Overall, the OTT can be a valuable tool for traders seeking to capitalize on trending market conditions while minimizing false signals and noise. However, like any trading indicator, it is essential to combine its signals with other forms of analysis and risk management strategies for optimal results. Additionally, traders should thoroughly back-test the indicator and practice using it in a demo environment before applying it to live trading.
PVSRA (Price, Volume, S&R Analysis)
“PVSRA” (Price, Volume, S&R Analysis) is a trading methodology and indicator that combines the analysis of price action, volume, and support/resistance levels to identify potential trading opportunities in financial markets. It is based on the idea that price movements are influenced by the interplay between supply and demand, and analyzing these factors together can provide valuable insights into market dynamics.
Here's a breakdown of the components of PVSRA:
• Price Action Analysis: PVSRA focuses on analyzing price movements and patterns on price charts, such as candlestick patterns, trendlines, chart patterns (like head and shoulders, triangles, etc.), and other price-based indicators. Traders using PVSRA pay close attention to how price behaves at key support and resistance levels and look for patterns that indicate potential shifts in market sentiment.
• Volume Analysis: Volume is an essential component of PVSRA. Traders monitor changes in trading volume to gauge the strength or weakness of price movements. An increase in volume during a price move suggests strong participation and conviction from market participants, reinforcing the validity of the price action. Conversely, low volume during price moves may indicate lack of conviction and potential reversals.
• Support and Resistance (S&R) Analysis: PVSRA incorporates the identification and analysis of support and resistance levels on price charts. Support levels represent areas where buying interest is expected to be strong enough to prevent further price declines, while resistance levels represent areas where selling interest may prevent further price advances. These levels are often identified using historical price data, trendlines, moving averages, pivot points, and other technical analysis tools.
The PVSRA methodology combines these three elements to generate trading signals and make trading decisions. Traders using PVSRA typically look for confluence between price action, volume, and support/resistance levels to confirm trade entries and exits. For example, a bullish reversal signal may be considered stronger if it occurs at a significant support level with increasing volume.
It's important to note that PVSRA is more of a trading approach or methodology rather than a specific indicator with predefined rules. Traders may customize their analysis based on their preferences and trading style, incorporating additional technical indicators or filters as needed. As with any trading strategy, risk management and proper trade execution are essential components of successful trading with PVSRA.
The following types of moving average have been included: "SMA", "EMA", "SMMA (RMA)", "WMA", "VWMA", "HMA", "KAMA", "LSMA", "TRAMA", "VAR", "DEMA", "ZLEMA", "TSF", "WWMA". Thanks to the authors.
Thank you for your indicator “Optimized Trend Tracker”. © kivancozbilgic
Thank you for your indicator “PVSRA Volume Suite”. © creengrack
Thank you for your programming language, indicators and strategies. © TradingView
Kind regards.
© Erebor_GIT
Dark Cloud [TradingFinder] Piercing Line Reversal chart Pattern
🔵 Introduction
"Reversal candlestick patterns" are among the Japanese candlestick patterns considered as alerts for a potential change in the current price trend. It is often assumed that by identifying reversal candlestick patterns, the price trend will definitely change, either from bullish to bearish or from bearish to bullish. However, this claim is not entirely accurate, and a change in price trend does not always mean a reversal.
Nonetheless, the importance of reversal candlestick patterns remains significant. By recognizing these patterns, you can better predict changes in the trend with higher probability and make better trading decisions.
🔵 Dark Cloud
The "Dark Cloud" pattern occurs when, after an upward trend, buyers continue to drive the price up in the first candle. However, in the next candle, with sellers entering and increasing selling pressure, the price starts to decrease compared to the close of the previous candle.
This price decrease is significant enough that in the last candle, the price goes lower than the open of the previous candle, serving as a warning sign for a potential change in price trend.
The fundamental principles for the formation of the "Dark Cloud" pattern include :
1.Two candles consisting of a positive candle (first candle) and a negative candle (second candle) whose main body should be above the halfway point of the first candle's main body but does not completely cover it.
2.The color of the main body of the second candle should be opposite to the color of the main body of the first candle.
Factors affecting the strength of the "Dark Cloud" pattern include :
1.The length of the bodies of both candles, especially the second candle, which increases the strength of the pattern.
2.The gap between the two bodies can also indicate the strength of the pattern.
3.The absence of a lower shadow in the second candle also indicates the strength of the pattern.
4.If the pattern forms in a price resistance range, it has more strength.
🔵 Piercing Line
The "Piercing Line" pattern occurs when, after a downward trend, sellers decrease the price by offering their shares on the first day. However, on the next day, with buyers entering and increasing demand, the price starts to increase compared to the close of the previous day.
This increase is significant enough that in the last candle, the price goes higher than the open of the previous day, serving as a warning sign for a reversal in the price trend. Overall, this pattern is the opposite of the "Dark Cloud" pattern and occurs under a bearish trend.
The fundamental principles for the formation of the "Piercing Line" pattern include :
1.Two candles consisting of a negative candle (first candle) and a positive candle (second candle) whose main body should be above the halfway point of the first candle's main body but does not completely cover it.
2.The color of the main body of the second candle should be opposite to the color of the main body of the first candle.
Factors affecting the strength of the "Piercing Line" pattern include :
1.The length of the bodies of both candles, especially the second candle, which increases the strength of the pattern.
2.The gap between the two bodies can also indicate the strength of the pattern.
3.The absence of an upper shadow in the second candle also indicates the strength of the pattern.
4.If the pattern forms in a price support range, it has more strength.
🔵 How to Use
The "green circle" symbol corresponds to the "Strong Piercing Line" signal, the "blue triangle" symbol corresponds to the "Weak Piercing Line" signal, the "red circle" symbol corresponds to the "Strong Dark Cloud" signal, and the "red triangle" symbol corresponds to the "Weak Dark Cloud" signal.
🔵 Setting
Using the "Show Dark Cloud" and "Show Piercing Line" buttons, you can enable or disable the display of Dark Cloud and Piercing Line.
Fair Value Gaps Mitigation Oscillator [LuxAlgo]The Fair Value Gaps Mitigation Oscillator is an oscillator based on the traditional Fair Value Gaps (FVGs) imbalances. The oscillator displays the current total un-mitigated values for the number of FVGs chosen by the user.
The indicator also displays each New FVG as a bar representing the current ratio of the New FVG in relation to the current un-mitigated total for its direction.
🔶 USAGE
When an FVG forms, it is often interpreted as strong market sentiment in the direction of the gap. For example, an upward FVG during an uptrend is typically seen as a confirmation of the strength and continuation of the trend, as it indicates that buyers are willing to purchase at higher prices without much resistance, suggesting strong demand and positive sentiment.
By analyzing the mitigation (or lack thereof), we can visualize the increase of directional strength in a trend. This is where the proposed oscillator is useful.
🔶 DETAILS
The oscillator's values are expressed as Percentages (%). Each FVG is allocated 100% of the total of its width with a max potential value of 100 and minimum potential value of 0.
Based on the "FVG Lookback" Input, the FVGs are scaled to fit within the range of +1 to -1. Using a higher "FVG Lookback" value will allow you to get indications of longer-term trends.
A higher value of the normalized bullish FVG areas suggest a stronger and cleaner uptrend, while lower values of the bearish the normalized bullish FVG areas suggest a stronger and cleaner downtrend.
+1 or -1 indicates that there is a Full Lookback of FVGs, and each one is fully un-mitigated, and the opposite direction of FVGs is entirely Mitigated.
When the price closes over/under or within an FVG it begins to get mitigated, when this happens the % of mitigation is subtracted from the total.
When a New FVG is formed, a Histogram bar is created representing the ratio of the current FVG's width to the total width off all un-mitigated FVGs.
The entire bar represents 100% of total un-mitigated FVG Width.
The filled area represents the current FVG's width relative to the whole.
A 50% hash mark is also displayed for reference.
🔶 SETTINGS
FVG Lookback - Determines the number of FVGs (Bullish and Bearish Pairs) to keep in memory for analysis.
BAERMThe Bitcoin Auto-correlation Exchange Rate Model: A Novel Two Step Approach
THIS IS NOT FINANCIAL ADVICE. THIS ARTICLE IS FOR EDUCATIONAL AND ENTERTAINMENT PURPOSES ONLY.
If you enjoy this software and information, please consider contributing to my lightning address
Prelude
It has been previously established that the Bitcoin daily USD exchange rate series is extremely auto-correlated
In this article, we will utilise this fact to build a model for Bitcoin/USD exchange rate. But not a model for predicting the exchange rate, but rather a model to understand the fundamental reasons for the Bitcoin to have this exchange rate to begin with.
This is a model of sound money, scarcity and subjective value.
Introduction
Bitcoin, a decentralised peer to peer digital value exchange network, has experienced significant exchange rate fluctuations since its inception in 2009. In this article, we explore a two-step model that reasonably accurately captures both the fundamental drivers of Bitcoin’s value and the cyclical patterns of bull and bear markets. This model, whilst it can produce forecasts, is meant more of a way of understanding past exchange rate changes and understanding the fundamental values driving the ever increasing exchange rate. The forecasts from the model are to be considered inconclusive and speculative only.
Data preparation
To develop the BAERM, we used historical Bitcoin data from Coin Metrics, a leading provider of Bitcoin market data. The dataset includes daily USD exchange rates, block counts, and other relevant information. We pre-processed the data by performing the following steps:
Fixing date formats and setting the dataset’s time index
Generating cumulative sums for blocks and halving periods
Calculating daily rewards and total supply
Computing the log-transformed price
Step 1: Building the Base Model
To build the base model, we analysed data from the first two epochs (time periods between Bitcoin mining reward halvings) and regressed the logarithm of Bitcoin’s exchange rate on the mining reward and epoch. This base model captures the fundamental relationship between Bitcoin’s exchange rate, mining reward, and halving epoch.
where Yt represents the exchange rate at day t, Epochk is the kth epoch (for that t), and epsilont is the error term. The coefficients beta0, beta1, and beta2 are estimated using ordinary least squares regression.
Base Model Regression
We use ordinary least squares regression to estimate the coefficients for the betas in figure 2. In order to reduce the possibility of over-fitting and ensure there is sufficient out of sample for testing accuracy, the base model is only trained on the first two epochs. You will notice in the code we calculate the beta2 variable prior and call it “phaseplus”.
The code below shows the regression for the base model coefficients:
\# Run the regression
mask = df\ < 2 # we only want to use Epoch's 0 and 1 to estimate the coefficients for the base model
reg\_X = df.loc\ [mask, \ \].shift(1).iloc\
reg\_y = df.loc\ .iloc\
reg\_X = sm.add\_constant(reg\_X)
ols = sm.OLS(reg\_y, reg\_X).fit()
coefs = ols.params.values
print(coefs)
The result of this regression gives us the coefficients for the betas of the base model:
\
or in more human readable form: 0.029, 0.996869586, -0.00043. NB that for the auto-correlation/momentum beta, we did NOT round the significant figures at all. Since the momentum is so important in this model, we must use all available significant figures.
Fundamental Insights from the Base Model
Momentum effect: The term 0.997 Y suggests that the exchange rate of Bitcoin on a given day (Yi) is heavily influenced by the exchange rate on the previous day. This indicates a momentum effect, where the price of Bitcoin tends to follow its recent trend.
Momentum effect is a phenomenon observed in various financial markets, including stocks and other commodities. It implies that an asset’s price is more likely to continue moving in its current direction, either upwards or downwards, over the short term.
The momentum effect can be driven by several factors:
Behavioural biases: Investors may exhibit herding behaviour or be subject to cognitive biases such as confirmation bias, which could lead them to buy or sell assets based on recent trends, reinforcing the momentum.
Positive feedback loops: As more investors notice a trend and act on it, the trend may gain even more traction, leading to a self-reinforcing positive feedback loop. This can cause prices to continue moving in the same direction, further amplifying the momentum effect.
Technical analysis: Many traders use technical analysis to make investment decisions, which often involves studying historical exchange rate trends and chart patterns to predict future exchange rate movements. When a large number of traders follow similar strategies, their collective actions can create and reinforce exchange rate momentum.
Impact of halving events: In the Bitcoin network, new bitcoins are created as a reward to miners for validating transactions and adding new blocks to the blockchain. This reward is called the block reward, and it is halved approximately every four years, or every 210,000 blocks. This event is known as a halving.
The primary purpose of halving events is to control the supply of new bitcoins entering the market, ultimately leading to a capped supply of 21 million bitcoins. As the block reward decreases, the rate at which new bitcoins are created slows down, and this can have significant implications for the price of Bitcoin.
The term -0.0004*(50/(2^epochk) — (epochk+1)²) accounts for the impact of the halving events on the Bitcoin exchange rate. The model seems to suggest that the exchange rate of Bitcoin is influenced by a function of the number of halving events that have occurred.
Exponential decay and the decreasing impact of the halvings: The first part of this term, 50/(2^epochk), indicates that the impact of each subsequent halving event decays exponentially, implying that the influence of halving events on the Bitcoin exchange rate diminishes over time. This might be due to the decreasing marginal effect of each halving event on the overall Bitcoin supply as the block reward gets smaller and smaller.
This is antithetical to the wrong and popular stock to flow model, which suggests the opposite. Given the accuracy of the BAERM, this is yet another reason to question the S2F model, from a fundamental perspective.
The second part of the term, (epochk+1)², introduces a non-linear relationship between the halving events and the exchange rate. This non-linear aspect could reflect that the impact of halving events is not constant over time and may be influenced by various factors such as market dynamics, speculation, and changing market conditions.
The combination of these two terms is expressed by the graph of the model line (see figure 3), where it can be seen the step from each halving is decaying, and the step up from each halving event is given by a parabolic curve.
NB - The base model has been trained on the first two halving epochs and then seeded (i.e. the first lag point) with the oldest data available.
Constant term: The constant term 0.03 in the equation represents an inherent baseline level of growth in the Bitcoin exchange rate.
In any linear or linear-like model, the constant term, also known as the intercept or bias, represents the value of the dependent variable (in this case, the log-scaled Bitcoin USD exchange rate) when all the independent variables are set to zero.
The constant term indicates that even without considering the effects of the previous day’s exchange rate or halving events, there is a baseline growth in the exchange rate of Bitcoin. This baseline growth could be due to factors such as the network’s overall growth or increasing adoption, or changes in the market structure (more exchanges, changes to the regulatory environment, improved liquidity, more fiat on-ramps etc).
Base Model Regression Diagnostics
Below is a summary of the model generated by the OLS function
OLS Regression Results
\==============================================================================
Dep. Variable: logprice R-squared: 0.999
Model: OLS Adj. R-squared: 0.999
Method: Least Squares F-statistic: 2.041e+06
Date: Fri, 28 Apr 2023 Prob (F-statistic): 0.00
Time: 11:06:58 Log-Likelihood: 3001.6
No. Observations: 2182 AIC: -5997.
Df Residuals: 2179 BIC: -5980.
Df Model: 2
Covariance Type: nonrobust
\==============================================================================
coef std err t P>|t| \
\------------------------------------------------------------------------------
const 0.0292 0.009 3.081 0.002 0.011 0.048
logprice 0.9969 0.001 1012.724 0.000 0.995 0.999
phaseplus -0.0004 0.000 -2.239 0.025 -0.001 -5.3e-05
\==============================================================================
Omnibus: 674.771 Durbin-Watson: 1.901
Prob(Omnibus): 0.000 Jarque-Bera (JB): 24937.353
Skew: -0.765 Prob(JB): 0.00
Kurtosis: 19.491 Cond. No. 255.
\==============================================================================
Below we see some regression diagnostics along with the regression itself.
Diagnostics: We can see that the residuals are looking a little skewed and there is some heteroskedasticity within the residuals. The coefficient of determination, or r2 is very high, but that is to be expected given the momentum term. A better r2 is manually calculated by the sum square of the difference of the model to the untrained data. This can be achieved by the following code:
\# Calculate the out-of-sample R-squared
oos\_mask = df\ >= 2
oos\_actual = df.loc\
oos\_predicted = df.loc\
residuals\_oos = oos\_actual - oos\_predicted
SSR = np.sum(residuals\_oos \*\* 2)
SST = np.sum((oos\_actual - oos\_actual.mean()) \*\* 2)
R2\_oos = 1 - SSR/SST
print("Out-of-sample R-squared:", R2\_oos)
The result is: 0.84, which indicates a very close fit to the out of sample data for the base model, which goes some way to proving our fundamental assumption around subjective value and sound money to be accurate.
Step 2: Adding the Damping Function
Next, we incorporated a damping function to capture the cyclical nature of bull and bear markets. The optimal parameters for the damping function were determined by regressing on the residuals from the base model. The damping function enhances the model’s ability to identify and predict bull and bear cycles in the Bitcoin market. The addition of the damping function to the base model is expressed as the full model equation.
This brings me to the question — why? Why add the damping function to the base model, which is arguably already performing extremely well out of sample and providing valuable insights into the exchange rate movements of Bitcoin.
Fundamental reasoning behind the addition of a damping function:
Subjective Theory of Value: The cyclical component of the damping function, represented by the cosine function, can be thought of as capturing the periodic fluctuations in market sentiment. These fluctuations may arise from various factors, such as changes in investor risk appetite, macroeconomic conditions, or technological advancements. Mathematically, the cyclical component represents the frequency of these fluctuations, while the phase shift (α and β) allows for adjustments in the alignment of these cycles with historical data. This flexibility enables the damping function to account for the heterogeneity in market participants’ preferences and expectations, which is a key aspect of the subjective theory of value.
Time Preference and Market Cycles: The exponential decay component of the damping function, represented by the term e^(-0.0004t), can be linked to the concept of time preference and its impact on market dynamics. In financial markets, the discounting of future cash flows is a common practice, reflecting the time value of money and the inherent uncertainty of future events. The exponential decay in the damping function serves a similar purpose, diminishing the influence of past market cycles as time progresses. This decay term introduces a time-dependent weight to the cyclical component, capturing the dynamic nature of the Bitcoin market and the changing relevance of past events.
Interactions between Cyclical and Exponential Decay Components: The interplay between the cyclical and exponential decay components in the damping function captures the complex dynamics of the Bitcoin market. The damping function effectively models the attenuation of past cycles while also accounting for their periodic nature. This allows the model to adapt to changing market conditions and to provide accurate predictions even in the face of significant volatility or structural shifts.
Now we have the fundamental reasoning for the addition of the function, we can explore the actual implementation and look to other analogies for guidance —
Financial and physical analogies to the damping function:
Mathematical Aspects: The exponential decay component, e^(-0.0004t), attenuates the amplitude of the cyclical component over time. This attenuation factor is crucial in modelling the diminishing influence of past market cycles. The cyclical component, represented by the cosine function, accounts for the periodic nature of market cycles, with α determining the frequency of these cycles and β representing the phase shift. The constant term (+3) ensures that the function remains positive, which is important for practical applications, as the damping function is added to the rest of the model to obtain the final predictions.
Analogies to Existing Damping Functions: The damping function in the BAERM is similar to damped harmonic oscillators found in physics. In a damped harmonic oscillator, an object in motion experiences a restoring force proportional to its displacement from equilibrium and a damping force proportional to its velocity. The equation of motion for a damped harmonic oscillator is:
x’’(t) + 2γx’(t) + ω₀²x(t) = 0
where x(t) is the displacement, ω₀ is the natural frequency, and γ is the damping coefficient. The damping function in the BAERM shares similarities with the solution to this equation, which is typically a product of an exponential decay term and a sinusoidal term. The exponential decay term in the BAERM captures the attenuation of past market cycles, while the cosine term represents the periodic nature of these cycles.
Comparisons with Financial Models: In finance, damped oscillatory models have been applied to model interest rates, stock prices, and exchange rates. The famous Black-Scholes option pricing model, for instance, assumes that stock prices follow a geometric Brownian motion, which can exhibit oscillatory behavior under certain conditions. In fixed income markets, the Cox-Ingersoll-Ross (CIR) model for interest rates also incorporates mean reversion and stochastic volatility, leading to damped oscillatory dynamics.
By drawing on these analogies, we can better understand the technical aspects of the damping function in the BAERM and appreciate its effectiveness in modelling the complex dynamics of the Bitcoin market. The damping function captures both the periodic nature of market cycles and the attenuation of past events’ influence.
Conclusion
In this article, we explored the Bitcoin Auto-correlation Exchange Rate Model (BAERM), a novel 2-step linear regression model for understanding the Bitcoin USD exchange rate. We discussed the model’s components, their interpretations, and the fundamental insights they provide about Bitcoin exchange rate dynamics.
The BAERM’s ability to capture the fundamental properties of Bitcoin is particularly interesting. The framework underlying the model emphasises the importance of individuals’ subjective valuations and preferences in determining prices. The momentum term, which accounts for auto-correlation, is a testament to this idea, as it shows that historical price trends influence market participants’ expectations and valuations. This observation is consistent with the notion that the price of Bitcoin is determined by individuals’ preferences based on past information.
Furthermore, the BAERM incorporates the impact of Bitcoin’s supply dynamics on its price through the halving epoch terms. By acknowledging the significance of supply-side factors, the model reflects the principles of sound money. A limited supply of money, such as that of Bitcoin, maintains its value and purchasing power over time. The halving events, which reduce the block reward, play a crucial role in making Bitcoin increasingly scarce, thus reinforcing its attractiveness as a store of value and a medium of exchange.
The constant term in the model serves as the baseline for the model’s predictions and can be interpreted as an inherent value attributed to Bitcoin. This value emphasizes the significance of the underlying technology, network effects, and Bitcoin’s role as a medium of exchange, store of value, and unit of account. These aspects are all essential for a sound form of money, and the model’s ability to account for them further showcases its strength in capturing the fundamental properties of Bitcoin.
The BAERM offers a potential robust and well-founded methodology for understanding the Bitcoin USD exchange rate, taking into account the key factors that drive it from both supply and demand perspectives.
In conclusion, the Bitcoin Auto-correlation Exchange Rate Model provides a comprehensive fundamentally grounded and hopefully useful framework for understanding the Bitcoin USD exchange rate.
ZigZag LibraryThis is yet another ZigZag library.
🔵 Key Features
1. Lightning-Fast Performance : Optimized code ensures minimal lag and swift chart updates.
2. Real-Time Swing Detection : No more waiting for swings to finalize! This library continuously identifies the latest swing formation.
3. Amplitude-Aware : Discover significant swings earlier, even if they haven't reached the standard bar length.
4. Customizable Visualization : Draw ZigZag on-demand using polylines for a tailored analysis experience.
Stay tuned for more features as this library is being continuously enhanced. For the latest updates, please refer to the release information.
🔵 API
// Import this library. Remember to check the latest version of this library and replace the version number below.
import algotraderdev/zigzag/1 as zz
// Initialize the ZigZag instance.
var zz.ZigZag zig = zz.ZigZag.new().init(
zz.Settings.new(
swingLen = 5,
lineColor = color.blue,
lineStyle = line.style_solid,
lineWidth = 1))
// Analyze the ZigZag using the latest bar's data.
zig.tick()
// Draw the ZigZag.
if barstate.islast
zig.draw()
SMC Fake Zones + InsideBarThis indicator is useful for whom trade with "Smart Money Concept (SMC)" strategy.
It helps SMD traders to identify fake or weak zones in the chart, So they can avoid taking position in this zones.
This indicator marks "Asia session" as well as "London and New York's Lunch Time (one hour before London and NY session starts)" zones.
It also marks Inside Bar candles which SMC trades consider as order flow. You can mark every Inside Bar or only those with opposite color via setting options.
*** As we know in SMC rules
1- Supply and Demand zones in "Asia session and Lunch Times" are fake zones for SMC trading and price will engulf them in most of times.
2- "Asia session high and low" has huge liquidity and usually price sweep that in London session.
This indicator will helps traders to visually identify those Fake zones and Asia session liquidity.
* You can change session times based on your time zone in settings.
* You can set options to show all Inside Bars or only with Opposite color in settings.
FVG Detector LibraryLibrary "FVG Detector Library"
🔵 Introduction
To save time and improve accuracy in your scripts for identifying Fair Value Gaps (FVGs), you can utilize this library. Apart from detecting and plotting FVGs, one of the most significant advantages of this script is the ability to filter FVGs, which you'll learn more about below. Additionally, the plotting of each FVG continues until either a new FVG occurs or the current FVG is mitigated.
🔵 Definition
Fair Value Gap (FVG) refers to a situation where three consecutive candlesticks do not overlap. Based on this definition, the minimum conditions for detecting a fair gap in the ascending scenario are that the minimum price of the last candlestick should be greater than the maximum price of the third candlestick, and in the descending scenario, the maximum price of the last candlestick should be smaller than the minimum price of the third candlestick.
If the filter is turned off, all FVGs that meet at least the minimum conditions are identified. This mode is simplistic and results in a high number of identified FVGs.
If the filter is turned on, you have four options to filter FVGs :
1. Very Aggressive : In addition to the initial condition, another condition is added. For ascending FVGs, the maximum price of the last candlestick should be greater than the maximum price of the middle candlestick. Similarly, for descending FVGs, the minimum price of the last candlestick should be smaller than the minimum price of the middle candlestick. In this mode, a very small number of FVGs are eliminated.
2. Aggressive : In addition to the conditions of the Very Aggressive mode, in this mode, the size of the middle candlestick should not be small. This mode eliminates more FVGs compared to the Very Aggressive mode.
3. Defensive : In addition to the conditions of the Very Aggressive mode, in this mode, the size of the middle candlestick should be relatively large, and most of it should consist of the body. Also, for identifying ascending FVGs, the second and third candlesticks must be positive, and for identifying descending FVGs, the second and third candlesticks must be negative. In this mode, a significant number of FVGs are eliminated, and the remaining FVGs have a decent quality.
4. Very Defensive : In addition to the conditions of the Defensive mode, the first and third candlesticks should not resemble very small-bodied doji candlesticks. In this mode, the majority of FVGs are filtered out, and the remaining ones are of higher quality.
By default, we recommend using the Defensive mode.
🔵 How to Use
🟣 Parameters
To utilize this library, you need to provide four input parameters to the function.
"FVGFilter" determines whether you wish to apply a filter on FVGs or not. The possible inputs for this parameter are "On" and "Off", provided as strings.
"FVGFilterType" determines the type of filter to be applied to the found FVGs. These filters include four modes: "Very Defensive", "Defensive", "Aggressive", and "Very Aggressive", respectively exhibiting decreasing sensitivity and indicating a higher number of Fair Value Gaps (FVG).
The parameter "ShowDeFVG" is a Boolean value defined as either "true" or "false". If this value is "true", FVGs are shown during the Bullish Trend; however, if it is "false", they are not displayed.
The parameter "ShowSuFVG" is a Boolean value defined as either "true" or "false". If this value is "true", FVGs are displayed during the Bearish Trend; however, if it is "false", they are not displayed.
FVGDetector(FVGFilter, FVGFilterType, ShowDeFVG, ShowSuFVG)
Parameters:
FVGFilter (string)
FVGFilterType (string)
ShowDeFVG (bool)
ShowSuFVG (bool)
🟣 Import Library
You can use the "FVG Detector" library in your script using the following expression:
import TFlab/FVGDetectorLibrary/1 as FVG
🟣 Input Parameters
The descriptions related to the input parameters were provided in the "Parameter" section. In this section, for your convenience, the code related to the inputs is also included, and you can copy and paste it into your script.
PFVGFilter = input.string('On', 'FVG Filter', )
PFVGFilterType = input.string('Defensive', 'FVG Filter Type', )
PShowDeFVG = input.bool(true, ' Show Demand FVG')
PShowSuFVG = input.bool(true, ' Show Supply FVG')
🟣 Call Function
You can copy the following code into your script to call the FVG function. This code is based on the naming conventions provided in the "Input Parameter" section, so if you want to use exactly this code, you should have similar parameter names or have copied the "Input Parameter" values.
FVG.FVGDetector(PFVGFilter, PFVGFilterType, PShowDeFVG, PShowSuFVG)
Economic Growth Index (XLY/XLP)Keeping an eye on the macroeconomic environment is an essential part of a successful investing and trading strategy. Piecing together and analysing its complex patterns are important to detect probable changing trends. This may seem complicated, or even better left to experts and gurus, but it’s made a whole lot easier by this indicator, the Economic Growth Index (EGI).
Common sense shows that in an expanding economy, consumers have access to cash and credit in the form of disposable income, and spend it on all sorts of goods, but mainly crap they don’t need (consumer discretionary items). Companies making these goods do well in this phase of the economy, and can charge well for their products.
Conversely, in a contracting economy, disposable income and credit dry up, so demand for consumer discretionary products slows, because people have no choice but to spend what they have on essential goods. Now, companies making staple goods do well, and keep their pricing power.
These dynamics are represented in EGI, which plots the Rate of Change of the Consumer Discretionary ETF (XLY) in relation to the Consumer Staples ETF (XLP). Put simply, green is an expanding phase of the economy, and red shrinking. The signal line is the market, a smoothed RSI of the S&P500. Run this on a Daily timeframe or higher. Check it occasionally to see where the smart money is heading.
Automatic Fibonacci Retracement Golden Pocket (GP)Main info
This script automatically draws you the Fibonacci retracement level called golden pocket from the latest detected pivot point to the actual price. This level is very popular among traders because the price tends to reverse on this level pretty often. You should use this on higher timeframes 15m+.
It is good to keep in mind that this level alone is not enough, you should still have another level there to enter the trade, for example golden pocket in combination with a demand zone is pretty solid. :)
Settings
The length for pivot point calculation is available in the script settings.
You can enable inverted golden pocket (for shorts)
You can hide/show the pivot point labels
If you want any updates, just feel free to write me :)
Candlesticks Patterns [TradingFinder] Pin Bar Hammer Shooting🔵 Introduction
Truly, the title "TradingView" doesn't do justice to this excellent website, and that's why I've written about its crucial aspect. In this indicator, the identification of all candlesticks known as "Pin bars" is explored.
These candlesticks include the following:
- Hammer : A Pin bar formed at the end of a bearish trend, with its body being either bearish or bullish.
- Shooting Star : Formed at the end of a bullish trend, with its body being either bearish or bullish.
- Hanging Man : Formed during an upward trend, characterized by a candle with a lower shadow.
- Inverted Hammer : Formed during a downward trend, characterized by a candle with an upper shadow.
🟣 Important : For ease of use, we refer to these four candlestick patterns as Pin Bars and categorize them into the main friends "Bullish" and "Bearish."
🟣 Important : In all sources, Hanging Man and Inverted Hammer are referred to as "Reversal candles." However, in reality, whenever they appear after breaking a significant area (Break Out), we expect these candles to signal a continuation of the trend and confirmation in the direction of the trend.
🟣 Important : One of the best signs of market manipulation and entry by market giants is the "Ice Berg." So, it provides one of the best trading opportunities.
🔵 Reason for Creation
Many traders, especially volume traders, use Pin bars as confirmation and enter the market after their occurrence. In this indicator, all four patterns are identified and displayed in a colored candle format, using "triangle" and "circle."
When they are evident on the chart, directly or by drawing a horizontal line, they give us good alerts for reversal or continuation areas.
🔵 Information Table
1. Red circle: Pin bars formed in a downtrend.
2. Blue circle: Bullish Pin bars formed in an uptrend.
3. Black triangle: Bearish Pin bar candle in an uptrend.
4. Blue triangle: Bullish Pin bar candle in a downtrend.
🔵 Settings
Trend Detection Period: A special feature that considers smaller or larger fluctuations. If individual price waves need to be considered, use lower numbers; if the overall trend direction is desired, use larger numbers (e.g., 5-7 or higher). This precisely sets the Zigzag or Pivot format, not displayed but considered in the indicator calculation.
Trend Effect : By changing the Trend Effect status to "Off," all Pin bars, whether bullish or bearish, are displayed regardless of the current market trend. If the status remains "On," only Pin bars in the direction of the main market trend are shown.
🟣 Important : Black triangles "Number 3" and blue triangles "Number 4" displayed in the information table section, as explained in the "Information Table" section.
Show Bullish Pin Bar : When set to "Yes," displays bullish Pin bars; when set to "No," does not display them.
Show Bearish Pin Bar : When set to "Yes," allows the display of bearish Pin bars; when set to "No," does not display them.
Bullish Pin Bar Setting : Using the "Ratio Lower Shadow to Body" and "Ratio Lower Shadow to Higher Shadow" settings, you can customize your bullish Pin bar candles. Larger numbers impose stricter conditions for identifying bullish Pin bars.
Bearish Pin Bar Setting : Using the "Ratio Higher Shadow to Body" and "Ratio Higher Shadow to Lower Shadow" settings, you can customize your bearish Pin bar candles. Larger numbers impose stricter conditions for identifying bearish Pin bars.
Show Info Table : Allows the display or non-display of the information table (located at the bottom of the page and on the right side).
🔵 How to Use
At the end of a downtrend, look for "Hammer" candles, easily identified one by one.
To identify the "Shooting Star" candle pattern at the end of an uptrend; expect a price reversal in the downtrend.
For trades in the downward direction, wait for the formation of an "Inverted Hammer" Pin bar.
And finally, in an uptrend, where a "Hanging Man" candle can form.
🔵 Features
For better visualization, triangles and circles are used above the candles, but they can be easily removed. All Pin bars are displayed in color with the following meanings:
- Black-bodied candle: Inverted Hammer
- Turquoise blue candle: Hammer
- Pink candle: Hanging Man
- Red candle: Shooting Star
🟣 Important : The capability to detect the powerful two-candle pattern "Tweezer Top" at the end of an uptrend emerges by forming two "Shooting Star" candles side by side.
Similarly, the two-candle pattern "Tweezer Bottom" is created at the end of a downtrend with the formation of two "Hammer" candles side by side. To identify the "Tweezer" pattern, make sure the settings in the "Trend Effect" section are set to "Off."
🟣 Auxiliary Indicators
During the start of trading sessions such as Asia, London, and New York, where the highest liquidity exists, alongside this indicator, you can use the Trading Sessions indicator.
Sessions
The combination of Order Blocks "-OB" and "+OB" with candles is one of the best trading methods. The indicator that identifies order blocks, along with this indicator, can yield remarkable results in the success of Pin bar candles.
Order Blocks Finder
The trading toolset "TFlab" presents this indicator. To benefit from all indicators, we invite you to visit our page " TFlab Scripts ".
Portfolio Management [TrendX_]Portfolio Management is a powerful tool that helps you create and manage your own portfolio of stocks, based on your risk and return preferences.
*** Note: You should select the appropriate index for each stock as the benchmark to compare your portfolio’s performance.
*** Note: You should apply the indicator to the same chart as the benchmark, so that it can capture the historical trends of all the 10 stocks in your portfolio.
USAGE
Analyze your portfolio’s return factor, which shows the compound annual growth rate (CAGR) of each stock and the portfolio as a whole, as well as the weight of each stock in the portfolio.
The Weighting approach contains 2 options, Equal and Growth-based method:
Customize your portfolio by selecting up to 10 stocks from a wide range of markets and sectors:
Compare your portfolio’s performance with a benchmark of your choice, which is the S&P500 by default setting.
Evaluate your portfolio’s risk factor, which includes the capital asset pricing model (CAPM), the portfolio beta, and the Sharpe ratio of both the portfolio and the benchmark:
- CAPM is a model that calculates the expected return of the portfolio based on its risk and the risk-free rate of return.
- Portfolio beta is a measure of how sensitive the portfolio is to the movements of the benchmark. A beta of 1 means the portfolio moves in sync with the benchmark, a beta of less than 1 means the portfolio is less volatile than the benchmark, and a beta of more than 1 means the portfolio is more volatile than the benchmark.
- Sharpe ratio measures how much excess return the portfolio generates per unit of risk. It is calculated by subtracting the risk-free rate of return from the portfolio’s return, and dividing by the portfolio’s standard deviation. A higher Sharpe ratio means the portfolio has a better risk-adjusted return. A Sharpe ratio of more than 1 is considered good, a Sharpe ratio of more than 2 is considered very good, and a Sharpe ratio of more than 3 is considered excellent .
Adjust your portfolio’s rebalancing strategy, which determines when and how to change the weight of each stock in the portfolio to optimize your return and risk objectives. The tool also suggests a default hedging-stock asset, which is the US dollar interpreted through the dollar index (DXY):
- The dollar index is a measure of the value of the US dollar relative to a basket of other major currencies. It is often used as a proxy for the global economic sentiment and the demand for safe-haven assets. A rising dollar index means the US dollar is strengthening, which may indicate a bearish outlook for the stock market. A falling dollar index means the US dollar is weakening, which may indicate a bullish outlook for the stock market.
- The rebalancing strategy suggest increasing the weight of the hedging-stock asset when the dollar index is under positive supertrend condition, and decreasing the weight of the hedging-stock asset when the dollar index is in the downward supertrend. This way, you can hedge against the adverse effects of the stock market fluctuations on your portfolio, simply you can just cash out at the suggested hedging weight.
CONCLUSION
Investors can gain a deeper insight into their portfolio’s performance, risk, and potential, and make informed decisions to achieve their financial goals with confidence and ease.
DISCLAIMER
The results achieved in the past are not all reliable sources of what will happen in the future. There are many factors and uncertainties that can affect the outcome of any endeavor, and no one can guarantee or predict with certainty what will occur.
Therefore, you should always exercise caution and judgment when making decisions based on past performance.
IBIT Premium to CoinbaseThe BTC ETF premium indicator for TradingView is a specialized tool designed to measure and visualize the premium or discount of the iShares Bitcoin Trust (IBIT), an investment vehicle that holds Bitcoin, relative to the actual price of Bitcoin on the Coinbase exchange. This indicator can be particularly insightful for traders interested in the BTC securities market and those analyzing the demand for Bitcoin as reflected by institutional investment products.
#### Description:
The BTC ETF premium indicator in TradingView leverages an advanced Pine Script algorithm to calculate the premium (or discount) percentage of IBIT compared to the spot price of Bitcoin (BTC/USD) on Coinbase. The premium is a critical insight that reflects market sentiment and potentially arbitrage opportunities between the trust's share price and the underlying cryptocurrency asset.
Here's how the indicator works:
1. **Calculation Methodology:**
- **Implied Bitcoin Price of IBIT:** We determine the implied price of Bitcoin within IBIT by dividing the IBIT closing price by the known ratio of Bitcoin per share.
- **IBIT Premium to Coinbase:** The percentage premium is then calculated as:
$$\text{IBIT Premium} = \frac{(\text{Implied Bitcoin Price of IBIT } - \text{Actual Bitcoin Price on Coinbase})}{\text{Actual Bitcoin Price on Coinbase}} \times 100$$
- This calculation is performed using the closing prices on a per-minute basis to ensure timely and accurate analysis.
2. **Visualization:** The indicator plots the premium as a step line chart, making it easy to visualize changes over time. A dynamic label accompanies the plot, displaying the implied Bitcoin price, the actual percentage premium or discount, and whether the premium is trending up or down compared to the previous day's value.
3. **Usage Scenario:** Traders can use this indicator to monitor the live premium 24/7 and analyze how it behaves during different market conditions, including when the equity market, where IBIT is traded, is closed.
#### Additional Features:
- **Color-Coding:** The premium is color-coded in green when positive (premium) and in red when negative (discount), aiding quick visual assessment.
- **Zero-Line Reference:** A horizontal line is drawn at zero to easily identify when IBIT is trading at par with the spot price of Bitcoin.
- **Real-Time Label Updates:** The label updates in real time with the latest premium/discount information and includes an arrow to signify the trend direction.
#### Access and Usage:
The indicator can be favorited or added to your TradingView charts. You are also welcome to use the source code as a foundation for further customization to suit your trading strategies.
#### Notes:
Please consider that the IBIT has specific trading hours, and the indicator can show live changes even when its market is closed, which might lead to discrepancies from official static data. For best performance, use this indicator alongside the IBIT candlestick chart on TradingView.
GBTC Premium to CoinbaseThe BTC ETF premium indicator for TradingView is a specialized tool designed to measure and visualize the premium or discount of the Grayscale Bitcoin Trust (GBTC), an investment vehicle that holds Bitcoin, relative to the actual price of Bitcoin on the Coinbase exchange. This indicator can be particularly insightful for traders interested in the BTC securities market and those analyzing the demand for Bitcoin as reflected by institutional investment products.
#### Description:
The BTC ETF premium indicator in TradingView leverages an advanced Pine Script algorithm to calculate the premium (or discount) percentage of GBTC compared to the spot price of Bitcoin (BTC/USD) on Coinbase. The premium is a critical insight that reflects market sentiment and potentially arbitrage opportunities between the trust's share price and the underlying cryptocurrency asset.
Here's how the indicator works:
1. **Calculation Methodology:**
- **Implied Bitcoin Price of GBTC:** We determine the implied price of Bitcoin within GBTC by dividing the GBTC closing price by the known ratio of Bitcoin per share.
- **GBTC Premium to Coinbase:** The percentage premium is then calculated as:
$$\text{GBTC Premium} = \frac{(\text{Implied Bitcoin Price of GBTC} - \text{Actual Bitcoin Price on Coinbase})}{\text{Actual Bitcoin Price on Coinbase}} \times 100$$
- This calculation is performed using the closing prices on a per-minute basis to ensure timely and accurate analysis.
2. **Visualization:** The indicator plots the premium as a step line chart, making it easy to visualize changes over time. A dynamic label accompanies the plot, displaying the implied Bitcoin price, the actual percentage premium or discount, and whether the premium is trending up or down compared to the previous day's value.
3. **Usage Scenario:** Traders can use this indicator to monitor the live premium 24/7 and analyze how it behaves during different market conditions, including when the equity market, where GBTC is traded, is closed.
#### Additional Features:
- **Color-Coding:** The premium is color-coded in green when positive (premium) and in red when negative (discount), aiding quick visual assessment.
- **Zero-Line Reference:** A horizontal line is drawn at zero to easily identify when GBTC is trading at par with the spot price of Bitcoin.
- **Real-Time Label Updates:** The label updates in real time with the latest premium/discount information and includes an arrow to signify the trend direction.
#### Access and Usage:
The indicator can be favorited or added to your TradingView charts. You are also welcome to use the source code as a foundation for further customization to suit your trading strategies.
#### Notes:
Please consider that the GBTC has specific trading hours, and the indicator can show live changes even when its market is closed, which might lead to discrepancies from official static data. For best performance, use this indicator alongside the GBTC candlestick chart on TradingView.
