[tradinghook] - Renko Trend Reversal Strategy V2Title: Renko Trend Reversal Strategy
Short Title: - Renko TRS
> Special thanks to for manually calculating `renkoClose` and `renkoOpen` values in order to remove the infamous repaint issue
Description:
The Renko Trend Reversal Strategy ( - Renko TRS) is a powerful and original trading approach designed to identify trend reversals in financial markets using Renko charts. Renko charts differ from traditional time-based charts, as they focus solely on price movements and ignore time, resulting in a clearer representation of market trends. This strategy leverages Renko charts in conjunction with the Average True Range (ATR) to capture trend reversals with high precision and effectiveness.
Key Concepts:
Renko Charts: Renko charts are unique chart types that only plot price movements beyond a predefined brick size, ignoring time and noise. By doing so, they provide a more straightforward depiction of market trends, eliminating insignificant price fluctuations and making it easier to spot trend reversals.
Average True Range (ATR): The strategy utilizes the ATR indicator, which measures market volatility and provides valuable insights into potential price movements. By setting the brick size of the Renko chart based on the ATR, the strategy adapts to changing market conditions, ensuring optimal performance across various instruments and timeframes.
How it Works:
The Renko Trend Reversal Strategy is designed to identify trend reversal points and generate buy or sell signals based on the following principles:
Renko Brick Generation: The strategy calculates the ATR over a user-defined period (ATR Length) and utilizes this value to determine the size of Renko bricks. Larger ATR values result in bigger bricks, capturing higher market volatility, while smaller ATR values create smaller bricks for calmer market conditions.
Buy and Sell Signals: The strategy generates buy signals when the Renko chart's open price crosses below the close price, indicating a potential bullish trend reversal. Conversely, sell signals are generated when the open price crosses above the close price, suggesting a bearish trend reversal. These signals help traders identify potential entry points to capitalize on market movements.
Stop Loss and Take Profit Management: To manage risk and protect profits, the strategy incorporates dynamic stop-loss and take-profit levels. The stop-loss level is calculated as a percentage of the Renko open price, ensuring a fixed risk amount for each trade. Similarly, the take-profit level is set as a percentage of the Renko open price to secure potential gains.
How to Use:
Inputs: Before using the strategy, traders can customize several parameters to suit their trading preferences. These inputs include the ATR Length, Stop Loss Percentage, Take Profit Percentage, Start Date, and End Date. Adjusting these settings allows users to optimize the strategy for different market conditions and risk tolerances.
Chart Setup: Apply the - Renko TRS script to your desired financial instrument and timeframe on TradingView. The Renko chart will dynamically adjust its brick size based on the ATR Length parameter.
Buy and Sell Signals: The strategy will generate green "Buy" labels below bullish reversal points and red "Sell" labels above bearish reversal points on the Renko chart. These labels indicate potential entry points for long and short trades, respectively.
Risk Management: The strategy automatically calculates stop-loss and take-profit levels based on the user-defined percentages. Traders can ensure proper risk management by using these levels to protect their capital and secure profits.
Backtesting and Optimization: Before implementing the strategy live, traders are encouraged to backtest it on historical data to assess its performance across various market conditions. Adjust the input parameters through optimization to find the most suitable settings for specific instruments and timeframes.
Conclusion:
The - Renko Trend Reversal Strategy is a unique and versatile tool for traders looking to identify trend reversals with greater accuracy. By combining Renko charts and the Average True Range (ATR) indicator, this strategy adapts to market dynamics and provides clear entry and exit signals. Traders can harness the power of Renko charts while effectively managing risk through stop-loss and take-profit levels. Before using the strategy in live trading, backtesting and optimization will help traders fine-tune the parameters for optimal performance. Start exploring trend reversals with the - Renko TRS and take your trading to the next level.
(Note: This description is for illustrative purposes only and does not constitute financial advice. Traders are advised to thoroughly test the strategy and exercise sound risk management practices when trading in real markets.)
Komut dosyalarını "tradingview+筹码结构" için ara
Multi-Timeframe Trend Detector [Alifer]Here is an easy-to-use and customizable multi-timeframe visual trend indicator.
The indicator combines Exponential Moving Averages (EMA), Moving Average Convergence Divergence (MACD), and Relative Strength Index (RSI) to determine the trend direction on various timeframes: 15 minutes (15M), 30 minutes (30M), 1 hour (1H), 4 hours (4H), 1 day (1D), and 1 week (1W).
EMA Trend : The script calculates two EMAs for each timeframe: a fast EMA and a slow EMA. If the fast EMA is greater than the slow EMA, the trend is considered Bullish; if the fast EMA is less than the slow EMA, the trend is considered Bearish.
MACD Trend : The script calculates the MACD line and the signal line for each timeframe. If the MACD line is above the signal line, the trend is considered Bullish; if the MACD line is below the signal line, the trend is considered Bearish.
RSI Trend : The script calculates the RSI for each timeframe. If the RSI value is above a specified Bullish level, the trend is considered Bullish; if the RSI value is below a specified Bearish level, the trend is considered Bearish. If the RSI value is between the Bullish and Bearish levels, the trend is Neutral, and no arrow is displayed.
Dashboard Display :
The indicator prints arrows on the dashboard to represent Bullish (▲ Green) or Bearish (▼ Red) trends for each timeframe.
You can easily adapt the Dashboard colors (Inputs > Theme) for visibility depending on whether you're using a Light or Dark theme for TradingView.
Usage :
You can adjust the indicator's settings such as theme (Dark or Light), EMA periods, MACD parameters, RSI period, and Bullish/Bearish levels to adapt it to your specific trading strategies and preferences.
Disclaimer :
This indicator is designed to quickly help you identify the trend direction on multiple timeframes and potentially make more informed trading decisions.
You should consider it as an extra tool to complement your strategy, but you should not solely rely on it for making trading decisions.
Always perform your own analysis and risk management before executing trades.
The indicator will only show a Dashboard. The EMAs, RSI and MACD you see on the chart image have been added just to demonstrate how the script works.
DETAILED SCRIPT EXPLANATION
INPUTS:
theme : Allows selecting the color theme (options: "Dark" or "Light").
emaFastPeriod : The period for the fast EMA.
emaSlowPeriod : The period for the slow EMA.
macdFastLength : The fast length for MACD calculation.
macdSlowLength : The slow length for MACD calculation.
macdSignalLength : The signal length for MACD calculation.
rsiPeriod : The period for RSI calculation.
rsiBullishLevel : The level used to determine Bullish RSI condition, when RSI is above this value. It should always be higher than rsiBearishLevel.
rsiBearishLevel : The level used to determine Bearish RSI condition, when RSI is below this value. It should always be lower than rsiBullishLevel.
CALCULATIONS:
The script calculates EMAs on multiple timeframes (15-minute, 30-minute, 1-hour, 4-hour, daily, and weekly) using the request.security() function.
Similarly, the script calculates MACD values ( macdLine , signalLine ) on the same multiple timeframes using the request.security() function along with the ta.macd() function.
RSI values are also calculated for each timeframe using the request.security() function along with the ta.rsi() function.
The script then determines the EMA trends for each timeframe by comparing the fast and slow EMAs using simple boolean expressions.
Similarly, it determines the MACD trends for each timeframe by comparing the MACD line with the signal line.
Lastly, it determines the RSI trends for each timeframe by comparing the RSI values with the Bullish and Bearish RSI levels.
PLOTTING AND DASHBOARD:
Color codes are defined based on the EMA, MACD, and RSI trends for each timeframe. Green for Bullish, Red for Bearish.
A dashboard is created using the table.new() function, displaying the trend information for each timeframe with arrows representing Bullish or Bearish conditions.
The dashboard will appear in the top-right corner of the chart, showing the Bullish and Bearish trends for each timeframe (15M, 30M, 1H, 4H, 1D, and 1W) based on EMA, MACD, and RSI analysis. Green arrows represent Bullish trends, red arrows represent Bearish trends, and no arrows indicate Neutral conditions.
INFO ON USED INDICATORS:
1 — EXPONENTIAL MOVING AVERAGE (EMA)
The Exponential Moving Average (EMA) is a type of moving average (MA) that places a greater weight and significance on the most recent data points.
The EMA is calculated by taking the average of the true range over a specified period. The true range is the greatest of the following:
The difference between the current high and the current low.
The difference between the previous close and the current high.
The difference between the previous close and the current low.
The EMA can be used by traders to produce buy and sell signals based on crossovers and divergences from the historical average. Traders often use several different EMA lengths, such as 10-day, 50-day, and 200-day moving averages.
The formula for calculating EMA is as follows:
Compute the Simple Moving Average (SMA).
Calculate the multiplier for weighting the EMA.
Calculate the current EMA using the following formula:
EMA = Closing price x multiplier + EMA (previous day) x (1-multiplier)
2 — MOVING AVERAGE CONVERGENCE DIVERGENCE (MACD)
The Moving Average Convergence Divergence (MACD) is a popular trend-following momentum indicator used in technical analysis. It helps traders identify changes in the strength, direction, momentum, and duration of a trend in a financial instrument's price.
The MACD is calculated by subtracting a longer-term Exponential Moving Average (EMA) from a shorter-term EMA. The most commonly used time periods for the MACD are 26 periods for the longer EMA and 12 periods for the shorter EMA. The difference between the two EMAs creates the main MACD line.
Additionally, a Signal Line (usually a 9-period EMA) is computed, representing a smoothed version of the MACD line. Traders watch for crossovers between the MACD line and the Signal Line, which can generate buy and sell signals. When the MACD line crosses above the Signal Line, it generates a bullish signal, indicating a potential uptrend. Conversely, when the MACD line crosses below the Signal Line, it generates a bearish signal, indicating a potential downtrend.
In addition to the MACD line and Signal Line crossovers, traders often look for divergences between the MACD and the price chart. Divergence occurs when the MACD is moving in the opposite direction of the price, which can suggest a potential trend reversal.
3 — RELATIVE STRENGHT INDEX (RSI):
The Relative Strength Index (RSI) is another popular momentum oscillator used by traders to assess the overbought or oversold conditions of a financial instrument. The RSI ranges from 0 to 100 and measures the speed and change of price movements.
The RSI is calculated based on the average gain and average loss over a specified period, commonly 14 periods. The formula involves several steps:
Calculate the average gain over the specified period.
Calculate the average loss over the specified period.
Calculate the relative strength (RS) by dividing the average gain by the average loss.
Calculate the RSI using the following formula: RSI = 100 - (100 / (1 + RS))
The RSI oscillates between 0 and 100, where readings above 70 are considered overbought, suggesting that the price may have risen too far and could be due for a correction. Readings below 30 are considered oversold, suggesting that the price may have dropped too much and could be due for a rebound.
Traders often use the RSI to identify potential trend reversals. For example, when the RSI crosses above 30 from below, it may indicate the start of an uptrend, and when it crosses below 70 from above, it may indicate the start of a downtrend. Additionally, traders may look for bullish or bearish divergences between the RSI and the price chart, similar to the MACD analysis, to spot potential trend changes.
[tradinghook] - Renko Trend Reversal Strategy - Renko Trend Reversal Strategy
Short Title: - Renko TRS
Description:
The Renko Trend Reversal Strategy ( - Renko TRS) is a powerful and original trading approach designed to identify trend reversals in financial markets using Renko charts. Renko charts differ from traditional time-based charts, as they focus solely on price movements and ignore time, resulting in a clearer representation of market trends. This strategy leverages Renko charts in conjunction with the Average True Range (ATR) to capture trend reversals with high precision and effectiveness.
Key Concepts:
Renko Charts: Renko charts are unique chart types that only plot price movements beyond a predefined brick size, ignoring time and noise. By doing so, they provide a more straightforward depiction of market trends, eliminating insignificant price fluctuations and making it easier to spot trend reversals.
Average True Range (ATR): The strategy utilizes the ATR indicator, which measures market volatility and provides valuable insights into potential price movements. By setting the brick size of the Renko chart based on the ATR, the strategy adapts to changing market conditions, ensuring optimal performance across various instruments and timeframes.
How it Works:
The Renko Trend Reversal Strategy is designed to identify trend reversal points and generate buy or sell signals based on the following principles:
Renko Brick Generation: The strategy calculates the ATR over a user-defined period (ATR Length) and utilizes this value to determine the size of Renko bricks. Larger ATR values result in bigger bricks, capturing higher market volatility, while smaller ATR values create smaller bricks for calmer market conditions.
Buy and Sell Signals: The strategy generates buy signals when the Renko chart's open price crosses below the close price, indicating a potential bullish trend reversal. Conversely, sell signals are generated when the open price crosses above the close price, suggesting a bearish trend reversal. These signals help traders identify potential entry points to capitalize on market movements.
Stop Loss and Take Profit Management: To manage risk and protect profits, the strategy incorporates dynamic stop-loss and take-profit levels. The stop-loss level is calculated as a percentage of the Renko open price, ensuring a fixed risk amount for each trade. Similarly, the take-profit level is set as a percentage of the Renko open price to secure potential gains.
How to Use:
Inputs: Before using the strategy, traders can customize several parameters to suit their trading preferences. These inputs include the ATR Length, Stop Loss Percentage, Take Profit Percentage, Start Date, and End Date. Adjusting these settings allows users to optimize the strategy for different market conditions and risk tolerances.
Chart Setup: Apply the - Renko TRS script to your desired financial instrument and timeframe on TradingView. The Renko chart will dynamically adjust its brick size based on the ATR Length parameter.
Buy and Sell Signals: The strategy will generate green "Buy" labels below bullish reversal points and red "Sell" labels above bearish reversal points on the Renko chart. These labels indicate potential entry points for long and short trades, respectively.
Risk Management: The strategy automatically calculates stop-loss and take-profit levels based on the user-defined percentages. Traders can ensure proper risk management by using these levels to protect their capital and secure profits.
Backtesting and Optimization: Before implementing the strategy live, traders are encouraged to backtest it on historical data to assess its performance across various market conditions. Adjust the input parameters through optimization to find the most suitable settings for specific instruments and timeframes.
Conclusion:
The - Renko Trend Reversal Strategy is a unique and versatile tool for traders looking to identify trend reversals with greater accuracy. By combining Renko charts and the Average True Range (ATR) indicator, this strategy adapts to market dynamics and provides clear entry and exit signals. Traders can harness the power of Renko charts while effectively managing risk through stop-loss and take-profit levels. Before using the strategy in live trading, backtesting and optimization will help traders fine-tune the parameters for optimal performance. Start exploring trend reversals with the - Renko TRS and take your trading to the next level.
(Note: This description is for illustrative purposes only and does not constitute financial advice. Traders are advised to thoroughly test the strategy and exercise sound risk management practices when trading in real markets.)
Good Mode RSI v2► Description:
"Good Mode RSI v2" is a powerful trading strategy designed to provide informed trading decisions. This script utilizes the popular RSI (Relative Strength Index) indicator to identify potential buying and selling opportunities in the market. It goes beyond the traditional use of RSI by incorporating carefully selected parameters to enhance its effectiveness. The strategy stands out for its customized combination of RSI levels and stop-loss/take-profit thresholds, allowing for precise trade entries and exits while effectively managing risk.
► How to Use:
To utilize the "Good Mode RSI v2" strategy, follow these steps:
1. Apply the script to your desired trading instrument and timeframe in TradingView.
2. Monitor the chart for trade signals generated by the strategy.
3. When the RSI reaches the sell level of 96, a sell signal is generated. Consider placing a sell order to take advantage of potential downward price movements.
4. take-profit level at 60 to secure profits in a strong downtrend.
5. When the RSI drops below the buy level of 4, a buy signal is generated. Consider placing a buy order to enter the market at a favorable price.
6. take-profit level at 30 to secure profits in a strong uptrend.
7. Monitor the RSI indicator on the chart to stay updated on its current value and anticipate potential trade signals.
Please note that trading decisions should be made based on a comprehensive analysis of multiple factors, including market conditions, trend analysis, and risk management. The "Good Mode RSI v2" strategy can serve as a valuable tool in your trading journey, but it should be used in conjunction with your own research and analysis.
► About it:
The "Good Mode RSI v2" strategy is not a mere replication or slight modification of existing strategies or indicators. It has been carefully crafted to provide traders with an original and purposeful approach to trading using the RSI indicator. The strategy's unique configuration of RSI levels and stop-loss/take-profit thresholds allows for improved performance and profitability. Backtesting results have shown impressive metrics, including a gain factor of 2.445 and a compelling profitability of 78.07% during the testing period.
► Referrals:
If you have any questions or need further assistance with the "Good Mode RSI v2" strategy, feel free to ask. Good luck with your trading endeavors!
Average True Range Trailing Mean [Alifer]Upgrade of the Average True Range default indicator by TradingView. It adds and plots a trailing mean to show periods of increased volatility more clearly.
ATR TRAILING MEAN
A trailing mean, also known as a moving average, is a statistical calculation used to smooth out data over time and identify trends or patterns in a time series.
In our indicator, it clearly shows when the ATR value spikes outside of it's average range, making it easier to identify periods of increased volatility.
Here's how the ATR Trailing Mean (atr_mean) is calculated:
atr_mean = ta.cum(atr) / (bar_index + 1) * atr_mult
The ta.cum() function calculates the cumulative sum of the ATR over all bars up to the current bar.
(bar_index + 1) represents the number of bars processed up to the current bar, including the current one.
By dividing the cumulative ATR ta.cum(atr) by (bar_index + 1) and then multiplying it by atr_mult (Multiplier), we obtain the ATR Trailing Mean value.
If atr_mult is set to 1.0, the ATR Trailing Mean will be equal to the simple average of the ATR values, and it will follow the ATR's general trend.
However, if atr_mult is increased, the ATR Trailing Mean will react more strongly to the ATR's recent changes, making it more sensitive to short-term fluctuations.
On the other hand, reducing atr_mult will make the ATR Trailing Mean less responsive to recent changes in ATR, making it smoother and less prone to reacting to short-term volatility.
In summary, adjusting the atr_mult input allows traders to fine-tune the ATR Trailing Mean's responsiveness based on their preferred level of sensitivity to recent changes in market volatility.
IMPLEMENTATION IN A STRATEGY
You can easily implement this indicator in an existing strategy, to only enter positions when the ATR is above the ATR Trailing Mean (with Multiplier-adjusted sensitivity). To do so, add the following lines of codes.
Under Inputs:
length = input.int(title="Length", defval=20, minval=1)
atr_mult = input.float(defval=1.0, step = 0.1, title = "Multiplier", tooltip = "Adjust the sensitivity of the ATR Trailing Mean line.")
smoothing = input.string(title="Smoothing", defval="RMA", options= )
ma_function(source, length) =>
switch smoothing
"RMA" => ta.rma(source, length)
"SMA" => ta.sma(source, length)
"EMA" => ta.ema(source, length)
=> ta.wma(source, length)
This will allow you to define the Length of the ATR (lookback length over which the ATR is calculated), the Multiplier to adjust the Trailing Mean's sensitivity and the type of Smoothing to be used for the ATR.
Under Calculations:
atr= ma_function(ta.tr(true), length)
atr_mean = ta.cum(atr) / (bar_index+1) * atr_mult
This will calculate the ATR based on Length and Smoothing, and the resulting ATR Trailing Mean.
Under Entry Conditions, add the following to your existing conditions:
and atr > atr_mean
This will make it so that entries are only triggered when the ATR is above the ATR Trailing Mean (adjusted by the Multiplier value you defined earlier).
ATR - DEFINITION AND HISTORY
The Average True Range (ATR) is a technical indicator used to measure market volatility, regardless of the direction of the price. It was developed by J. Welles Wilder and introduced in his book "New Concepts in Technical Trading Systems" in 1978. ATR provides valuable insights into the degree of price movement or volatility experienced by a financial asset, such as a stock, currency pair, commodity, or cryptocurrency, over a specific period.
ATR - CALCULATION AND USAGE
The ATR calculation involves three components:
1 — True Range (TR): The True Range is a measure of the asset's price movement for a given period. It takes into account the following factors:
The difference between the high and low prices of the current period.
The absolute value of the difference between the high price of the current period and the closing price of the previous period.
The absolute value of the difference between the low price of the current period and the closing price of the previous period.
Mathematically, the True Range (TR) for the current period is calculated as follows:
TR = max(high - low, abs(high - previous_close), abs(low - previous_close))
2 — ATR Calculation: The ATR is calculated as a Moving Average (MA) of the True Range over a specified period.
The ATR is calculated as follows:
ATR = MA(TR, length)
3 — ATR Interpretation: The ATR value represents the average volatility of the asset over the chosen period. Higher ATR values indicate higher volatility, while lower ATR values suggest lower volatility.
Traders and investors can use ATR in various ways:
Setting Stop Loss and Take Profit Levels: ATR can help determine appropriate stop-loss and take-profit levels in trading strategies. A larger ATR value might require wider stop-loss levels to allow for the asset's natural price fluctuations, while a smaller ATR value might allow for tighter stop-loss levels.
Identifying Market Volatility: A sharp increase in ATR might indicate heightened market uncertainty or the potential for significant price movements. Conversely, a decreasing ATR might suggest a period of low volatility and possible consolidation.
Comparing Volatility Between Assets: Since ATR uses absolute values, it shouldn't be used to compare volatility between different assets, as assets with higher prices will consistently have higher ATR values, while assets with lower prices will consistently have lower ATR values. However, the addition of a trailing mean makes such a comparison possible. An asset whose ATR is consistently close to its ATR Trailing Mean will have a lower volatility than an asset whose ATR continuously moves far above and below its ATR Trailing Mean. This can help traders and investors decide which markets to trade based on their risk tolerance and trading strategies.
Determining Position Size: ATR can be used to adjust position sizes, taking into account the asset's volatility. Smaller position sizes might be appropriate for more volatile assets to manage risk effectively.
Enhanced WaveTrend OscillatorThe Enhanced WaveTrend Oscillator is a modified version of the original WaveTrend. The WaveTrend indicator is a popular technical analysis tool used to identify overbought and oversold conditions in the market and generate trading signals. The enhanced version addresses certain limitations of the original indicator and introduces additional features for improved analysis and comparison across assets.
WaveTrend:
The original WaveTrend indicator calculates two lines based on exponential moving averages and their relationship to the asset's price. The first line measures the distance between the asset's price and its EMA, while the second line smooths the first line over a specific period. The result is divided by 0.015 multiplied by the smoothed difference ('d' for reference). The indicator aims to identify overbought and oversold conditions by analyzing the relationship between the two lines.
In the original formula, the rudimentary estimation factor 0.015 times 'd' fails to accomodate for approximately a quarter of the data, preventing the indicator from reaching the traditional stationary levels of +-100. This limitation renders the indicator quantitatively biased, as it relies on the user's subjective adjustment of the levels. The enhanced version replaces this factor with the standard deviation of the asset's price, resulting in improved estimation accuracy and provides a more dynamic and robust outcome, we thereafter multiply the result by 100 to achieve a more traditional oscillation.
Enhancements and Features:
The enhanced version of the WaveTrend indicator addresses several limitations of the original indicator and introduces additional features-
Dynamic Estimation: The original indicator uses an arbitrary estimation factor, while the enhanced version replaces it with the standard deviation of the asset's price. This modification provides a more dynamic and accurate estimation, adapting to the specific price characteristics of each asset.
Stationary Support and Resistance Levels: The enhanced version provides stationary key support and resistance levels that range from -150 to 150. These levels are determined based on the analysis of the indicator's data and encompass more than 95% of the indicator's values. These levels offer important reference points for traders to identify potential price reversals or significant price movements.
Comparison Across Assets: The enhanced version allows for better comparison and analysis across different assets. By incorporating the standard deviation of the asset's price, the indicator provides a more consistent and comparable interpretation of the market conditions across multiple assets.
Upon closer inspection of the modification in the enhanced version, we can observe that the resulting indicator is a smoothed variation of the Z-Score!
f_ewave(src, chlen, avglen) =>
basis = ta.ema(src, chlen)
dev = ta.stdev(src, chlen)
wave = (src - basis) / dev * 100
ta.ema(wave, avglen)
Z-Score Analysis:
The Z-Score is a statistical measurement that quantifies how far a particular data point deviates from the mean in terms of standard deviations. In the enhanced version, the calculation involves determining the basis (mean) and deviation (standard deviation) of the asset's price to calculate its Z-Score, thereafter applying a smoothing technique to generate the final WaveTrend value.
Utility:
The 𝗘𝗻𝗵𝗮𝗻𝗰𝗲𝗱 𝗪𝗧 indicator offers traders and investors valuable insights into overbought and oversold conditions in the market. By analyzing the indicator's values and referencing the stationary support and resistance levels, traders can identify potential trend reversals, evaluate market strength, and make better informed analysis.
It is important to note that this indicator should be used in conjunction with other technical analysis tools and indicators to confirm trading signals and validate market dynamics.
Credit:
The 𝗘𝗻𝗵𝗮𝗻𝗰𝗲𝗱 𝗪𝗧 indicator is a modification of the original WaveTrend Oscillator developed by @LazyBear on TradingView.
Example Charts:
RSI Trend Transform [wbburgin]The RSI Trend Transform indicator is a dual-concept indicator that transforms volume data and price data into two different RSI values, which can then be used together to determine trend strength and momentum. The volume RSI does not use any price data in its calculation - it is purely a transform from nondirectional volume into a directional indicator.
The RSI for all three RSI values (price, volume,combined average) can be plotted as either stochastic or normal. The RSI calculation is adapted for use on volume, which is why the normal ta.rsi() function is not used for the price RSI calculation; both use the same formula for indicator consistency.
How to Use the Indicator
In the examples below, the Price RSI is plotted in yellow and the Volume RSI is plotted in red (length = 200, which is why the indicator is large in these examples). The indicator can be used on any timeframe and any asset, provided volume data is provided by the vendor to TradingView.
Identifying Bullish Trends
A rising volume RSI with a rising price RSI signifies a bullish trend. Example 1:
Example 2:
You can use the combined RSI (the average of the volume RSI and the price RSI) to help with the identification of these trends:
Identifying Bearish Trends
A falling volume RSI with a falling price RSI signifies a bearish trend:
Example 2:
Settings
Source is the source of the price RSI, the volume RSI will by default use volume in its calculations. If you have other indicators on-chart, you could even use the ATR, a volatility indicator, or any nondirectional or directional indicator and transform it into the "price" RSI.
Length is both the length of the RSI and the stochastic.
The next three rows are for each RSI you can plot on the indicator: price RSI, volume RSI, and combined RSI (average of price and volume). The first checkbox plots/removes them from the chart, you can subsequently choose the type of RSI (regular or stochastic), the color of the plot, and the length of the EMA smoothing applied afterward to the plot.
Upper Band and Lower Band refer to the overbought and oversold lines, respectively.
A note about the combined RSI- you will be unable to spot divergences if the combined RSI is the only plot on the indicator, so I encourage you to use the combined RSI as a way to confirm the overall trend if you notice the price RSI and the volume RSI and trending similarly.
Spot Symbols for CryptoLibrary "CryptoSpotSymbols"
This Library has one purpose only. It generate Symbols for the Crypto Spot Market, like all the currencies pairs of most Crypto Exchanges available to TradingView.
Have a look at .find() , which is an all in one function.
Binance(basecurrency)
Generate 27 Symbols for the Spot Market of Binance.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
BinanceUS(basecurrency)
Generate seven Symbols for the Spot Market of BinanceUS.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
Bitfinex(basecurrency)
Generate 12 Symbols for the Spot Market of Bitfinex.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
bitFlyer(basecurrency)
Generate three Symbols for the Spot Market of bitFlyer.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
Bitget(basecurrency)
Generate seven Symbols for the Spot Market of Bitget.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
Bithumb(basecurrency)
Generate two Symbols for the Spot Market of Bithumb.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
bitkub(basecurrency)
Generate one Symbol for the Spot Market of bitkub.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns: THB
BitMEX(basecurrency)
Generate two Symbols for the Spot Market of BitMEX.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
bitpanda_pro(basecurrency)
Generate six Symbols for the Spot Market of bitpanda pro.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
bitrue(basecurrency)
Generate nine Symbols for the Spot Market of bitrue.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
Bitstamp(basecurrency)
Generate eight Symbols for the Spot Market of Bitstamp.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
BITTREX(basecurrency)
Generate six Symbols for the Spot Market of BITTREX.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
BTSE(basecurrency)
Generate 15 Symbols for the Spot Market of BTSE.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
BYBIT(basecurrency)
Generate five Symbols for the Spot Market of BYBIT.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
CapitalCom(basecurrency)
Generate five Symbols for the Spot Market of capital.com.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
coinbase(basecurrency)
Generate seven Symbols for the Spot Market of coinbase.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
CoinEx(basecurrency)
Generate three Symbols for the Spot Market of CoinEx.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
CurrencyCom(basecurrency)
Generate 30 Symbols for the Spot Market of currency.com.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
Delta(basecurrency)
Generate one Symbol for the Spot Market of Delta.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns: USDT
Deribit(basecurrency)
Generate two Symbols for the Spot Market of Deribit.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
easyMarkets(basecurrency)
Generate one Symbol for the Spot Market of easyMarkets.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns: USD
Eightcap(basecurrency)
Generate one Symbol for the Spot Market of Eightcap.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns: USD
ExMo(basecurrency)
Generate ten Symbols for the Spot Market of ExMo.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
FOREXcom(basecurrency)
Generate four Symbols for the Spot Market of FOREX.com.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
FXCM(basecurrency)
Generate three Symbols for the Spot Market of FXCM.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
GateIO(basecurrency)
Generate five Symbols for the Spot Market of Gate.io.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
Gemini(basecurrency)
Generate ten Symbols for the Spot Market of Gemini.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
Kraken(basecurrency)
Generate 14 Symbols for the Spot Market of Kraken.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
KuCoin(basecurrency)
Generate 13 Symbols for the Spot Market of KuCoin.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
MEXC(basecurrency)
Generate six Symbols for the Spot Market of MEXC.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
OANDA(basecurrency)
Generate one Symbol for the Spot Market of OANDA.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns: USD
OKX(basecurrency)
Generate six Symbols for the Spot Market of OKX.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
Pepperstone(basecurrency)
Generate one Symbol for the Spot Market of Pepperstone.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns: USD
phemex(basecurrency)
Generate four Symbols for the Spot Market of phemex.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
POLONIEX(basecurrency)
Generate nine Symbols for the Spot Market of POLONIEX.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
Pyth(basecurrency)
Generate three Symbols for the Spot Market of Pyth.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
Skilling(basecurrency)
Generate four Symbols for the Spot Market of Skilling.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
TimeX(basecurrency)
Generate six Symbols for the Spot Market of TimeX.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
TradeStation(basecurrency)
Generate four Symbols for the Spot Market of TradeStation.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
UpBit(basecurrency)
Generate four Symbols for the Spot Market of UpBit.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
whitebit(basecurrency)
Generate 13 Symbols for the Spot Market of whitebit.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
WOOX(basecurrency)
Generate two Symbols for the Spot Market of WOO.
Parameters:
basecurrency (simple string) : Its the Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`.
Returns:
find(exchange, basecurrency)
Generate up to 30 Symbols for the Spot Market, depending on the market picked.
Parameters:
exchange (simple string) : The name of an Exchange. Case insensitivity. Optional. Default value is `syminfo.prefix`. If something else is put in here it will return `na` values.
basecurrency (simple string) : The Basecurrency to generate the Symbols with. Optional. Default value is `syminfo.basecurrency`
Returns: 30x string as tuple
Trendilo (OPEN-SOURCE)The provided code is a custom indicator called "Trendilo" in TradingView. It helps traders identify trends in price data. The indicator calculates the percentage change of the chosen price source and applies smoothing to it. Then, it calculates the Arnaud Legoux Moving Average (ALMA) of the smoothed percentage change. The ALMA is compared to a root mean square (RMS) band, which represents the expected range of the ALMA values. Based on this comparison, the indicator determines whether the trend is up, down, or sideways. The indicator line is plotted in a color corresponding to the trend direction. The indicator also provides the option to fill the area between the indicator line and the RMS band. Additionally, users can choose to color the bars of the chart based on the trend direction. Overall, the "Trendilo" indicator helps traders visually identify trends and potential reversals in the price data.
8AM Vertical LineThis script is a Pine Script indicator for TradingView. It draws a vertical line on the chart at a specific hour, which can be customized by the user. The default displayed hour is set to 8 AM, but it can be adjusted using the input options.
The indicator takes into account the timezone offset specified by the user to ensure the correct hour is displayed according to their local time. The vertical line is drawn with a specified color, style, and width, which can also be customized.
The purpose of this indicator is to visually mark a specific hour on the chart, allowing traders to easily identify and reference that particular time point. It can be useful for various trading strategies or analysis that involve specific hours of the day.
RSI-CCI Fusion + AlertsThe "RSI-CCI Fusion" indicator combines the Relative Strength Index (RSI) and Commodity Channel Index (CCI) from TradingView.
RSI-CCI Fusion: Unlocking Synergies in Technical Analysis
Technical analysis plays a crucial role in understanding market dynamics and making informed trading decisions. I often rely on a combination of indicators to gain insights into price movements and identify potential trade opportunities. In the lines below, I will explore the "RSI-CCI Fusion" indicator, a powerful tool that combines the strengths of the Relative Strength Index (RSI) and the Commodity Channel Index (CCI) to provide enhanced trading insights.
1. Understanding the RSI and CCI Indicators
Before delving into the fusion of these indicators, let's briefly review their individual characteristics. The RSI is a widely used momentum oscillator that measures the speed and change of price movements. It oscillates between 0 and 100, with readings above 70 indicating overbought conditions and readings below 30 indicating oversold conditions.
On the other hand, the CCI is a versatile indicator designed to identify cyclical trends in prices. It measures the distance between the price and its statistical average, thereby providing valuable insights into overbought and oversold levels.
2. The Concept of RSI-CCI Fusion
The RSI-CCI Fusion indicator is born out of my desire to harness the collective power of the RSI and CCI. By combining these indicators, I can benefit from a more comprehensive trading signal that captures both momentum and cyclical trend dynamics.
The fusion process involves assigning weights to the RSI and CCI, creating a blended indicator that reflects their relative importance. The weighted combination ensures that both indicators contribute meaningfully to the final result.
To maintain consistency, the RSI and CCI values are standardized using the z-score technique. This normalization process brings the values to a common scale, making them directly comparable. Rescaling is then applied to bring the combined indicator back to its original scale, facilitating intuitive interpretation.
3. Interpreting the RSI-CCI Fusion Indicator
When plotting the RSI-CCI Fusion indicator on a chart, I gain valuable insights into market dynamics and potential trading opportunities. The indicator's plot typically includes dynamic upper and lower bands, which are calculated based on the indicator's standard deviation. These bands provide boundaries for evaluating overbought and oversold conditions.
When the RSI-CCI Fusion indicator crosses above the lower band, it suggests oversold conditions and potential buying opportunities. Conversely, when the indicator crosses below the upper band, it indicates overbought conditions and potential selling opportunities. I also pay attention to the baseline, which represents the neutral level and may signal potential trend reversals.
4. Utilizing Alerts for Trading Decisions
The RSI-CCI Fusion indicator can be further enhanced by incorporating alerts. These alerts notify me when the indicator generates buy or sell signals, enabling me to take prompt action. I can customize the alerts based on my preferred thresholds and timeframes.
However, it is crucial to remember that the RSI-CCI Fusion indicator should not be relied upon in isolation. To increase the robustness of my trading decisions, it is recommended to combine the indicator with other analysis techniques such as trend lines, support and resistance levels, or additional indicators. This convergence of analysis methodologies enhances the overall accuracy of my trade signals.
Conclusion: The RSI-CCI Fusion indicator represents a compelling approach to technical analysis by synergizing the strengths of the RSI and CCI. By combining momentum and cyclical trend dynamics, I gain a more comprehensive view of market conditions. The fusion of these indicators, accompanied by timely alerts, equips me with valuable insights and facilitates well-informed trading decisions.
As with any technical analysis tool, it is essential for me to backtest the RSI-CCI Fusion indicator to evaluate its performance across different market conditions and timeframes. Additionally, applying proper risk management strategies is crucial to ensure consistent and disciplined trading practices.
Inverted Relative Strength IndexUnfortunately when using the cmd + I to invert the chart, won't have the same effect on the RSI indicator. The Inverted Relative Strength Index will have the inverted RSI showing in the same direction as the chart that was inverted using the available command in TradingView. Keep in mind that when flipping the chart back to the original direction, the Inverted Relative Strength Index won't flip with it, so you'll need to go back to the regular Relative Strength Index.
Linear Regression Channel (Log)The Linear Regression Channel (Log) indicator is a modified version of the Linear Regression channel available on TradingView. It is designed to be used on a logarithmic scale, providing a different perspective on price movements.
The indicator utilizes the concept of linear regression to visualize the overall price trend in a specific section of the chart. The central line represents the linear regression calculation, while the upper and lower lines indicate a certain number of standard deviations away from the central line. These bands serve as support and resistance levels, and when prices remain outside the channel for an extended period, a potential reversal may be anticipated.
I have replaced the Pearson values with trend strength levels to enhance understanding for individuals unfamiliar with Pearson correlation.
Correlation Coefficient - DXY & XAUPublishing my first indicator on TradingView. Essentially a modification of the Correlation Coefficient indicator, that displays a 2 ticker symbols' correlation coefficient vs, the chart presently loaded.. You can modify the symbols, but the default uses DXY and XAU, which have been displaying strong negative correlation.
As with the built-in CC (Correlation Coefficient) indicator, readings are taken the same way:
Positive Correlation = anything above 0 | stronger as it moves up towards 1 | weaker as it moves back down towards 0
Negative Correlation = anything below 0 | stronger moving down towards -1 | weaker moving back up towards 0
This is primarily created to work with the Bitcoin weekly chart, for comparing DXY and Gold (XAU) price correlations (in advance, when possible). If you change the chart timeframe to something other than weekly, consider playing with the Length input, which is set to 35 by default where I think it best represents correlations with Bitcoin's weekly timeframe for DXY and Gold.
The intention is that you might be able to determine future direction of Bitcoin based on positive or negative correlations of Gold and/or the US Dollar Index. DXY has been making peaks and valleys prior to Bitcoin since after March 2020 black swan event, where it peaked just after instead. In the future, it may flip over again and Bitcoin may hit major highs or lows prior to DXY, again. So, keep an eye on the charts for all 3, as well as the indicator correlations.
Currently, we've moved back into negative correlation between Bitcoin and DXY, and positive correlation with Bitcoin and Gold:
Negative Correlation b/w Bitcoin and DXY - if DXY moves up, Bitcoin likely moves down, or if DXY moves down, Bitcoin likely moves up (or if Bitcoin were to move first before DXY, as it did on March 2020, instead)
Positive Correlation b/w Bitcoin and Gold - Bitcoin and Gold will likely move up or down with each other.
DXY is represented by the green histogram and label, Gold is represented by the yellow histogram and label. Again, you can modify the tickers you want to check against, and you can modify the colors for their histograms / labels.
The inspiration from came from noticing areas of same date or delayed negative correlation between Bitcoin and DXY, here is one of my most recent posts about that:
Please let me know if you have any questions, or would like to see updates to the indicator to make it easier to use or add more useful features to it.
I hope this becomes useful to you in some way. Thank you for your support!
Cheers,
dudebruhwhoa :)
Pattern Forecast (Expo)█ Overview
The Pattern Forecast indicator is a technical analysis tool that scans historical price data to identify common chart patterns and then analyzes the price movements that followed these patterns. It takes this information and projects it into the future to provide traders with potential price actions that may occur if the same pattern is identified in real-time market data. This projection helps traders to understand the possible outcomes based on the previous occurrences of the pattern, thereby offering a clearer perspective of the market scenario. By analyzing the historical data and understanding the subsequent price movements following the appearance of a specific pattern, the indicator can provide valuable insights into potential future market behavior.
█ Calculations
The indicator works by scanning historical price data for various candlestick patterns. It includes all in-built TradingView patterns, credit to TradingView that has coded them.
Essentially, the indicator takes the historical price moves that followed the pattern to forecast what might happen next.
█ Example
In this example, the algorithm is set to search for the Inverted Hammer Bullish candlestick pattern. If the pattern is found, the historical outcome is then projected into the future. This helps traders to understand how the past pattern evolved over time.
█ How to use
Providing traders with a comprehensive understanding of historical patterns and their implications for future price action allows them to assess the likelihood of specific market scenarios objectively. For example, suppose the pattern forecast indicator suggests that a particular pattern is likely to lead to a bullish move in the market. A trader might consider going long if the same pattern is identified in the real-time market. Similarly, a trader might consider shorting the asset if the indicator suggests a bearish move is likely, if the same pattern is identified in the real-time market.
█ Settings
Pattern
Select the pattern that the indicator should scan for. All inbuilt TradingView patterns can be selected.
Forecast Candles
Number of candles to project into the future.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Digital Root 9 Time HighlightsTitle: Digital Root 9 Indicator
Description: The Digital Root 9 Indicator is a custom TradingView tool that identifies all times in which the digital root of the current time is 9. The digital root is calculated by summing the digits of the current time and then continuing to sum the resulting digits until a single digit is obtained. For instance, the time 3:33 has a digital root of 9 because 3+3+3=9.
What sets the Digital Root 9 Indicator apart from other TradingView indicators is its focus on identifying times with a numerological significance. It is particularly useful for traders who incorporate numerology into their trading strategies and are looking for a tool that highlights these significant times.
To use the Digital Root 9 Indicator, simply add it to your TradingView chart. The indicator will highlight all times when the digital root of the current time is 9, allowing you to see at a glance which times have numerological significance. You can customize the indicator's color scheme and other settings to suit your preferences.
The Digital Root 9 Indicator is intended to help traders identify times when the potential for luck and prosperity is heightened according to numerology. However, it should not be used as the sole basis for making trading decisions. It is important to conduct thorough analysis and risk management before making any trades.
The Digital Root 9 Indicator is suitable for use in any market condition and time frame.
Daily Gaps & Trapped PositionsThis script builds substantially upon the default Gaps script provided by Tradingview. Functionality was added to allow users to decide what price from the previous session is used to determine a daily gap, added support for showing gaps across all timeframes up to the daily time frame, and also allow gaps to be shown even with ETH enabled on the chart. This script provides support across normal securities, futures, and also crypto.
Users can decide between the following selections to determine if a daily gap has formed:
- Previous Session Close
- Previous Session High/Low
- Last RTH Candle High/Low
The other larger piece that was added is something called trapped positions or what some folks familiar with Market Profile would call "single prints". They could also be considered FVGs but they are a specific subset of FVGs as these must from above or below the current session's high/low.
Single prints form above or below a current session's high/low and can be considered an area where price has moved too fast in that area and price will most likely return to these areas at a later point in time. In some teachings, these are also looked at as "trapped shorts" (lighter blue box color) or "trapped supply" (yellow orange box color) which creates an area where there will be potential support (trapped shorts) or resistance (trapped supply) when this area is revisited in the future. Adding these to your chart will simply provide additional areas of interest where you may see buying or selling.
Both gaps and trapped positions have the following options:
- Show only active gaps/trapped positions. Selecting this will only show areas where price has not completely traded through the box.
- Close gaps/trapped positions partially. If this is selected, it will reduce the box size as price is traded through the area. If it is not selected, the box will only disappear once price has traded through the entire box completely.
There are some additional settings that allow you to tailor how many boxes show up on the chart. These settings are as follows:
- Max number of boxes. This setting will only plot up to this number of gaps/trapped positions.
- Minimum Deviation. This will prevent gaps/trapped positions from showing if they are too small relative to average across that last 14 periods.
- Limit Max Box Trail Length (bars). If checkbox is selected, the box will stop being extended after X number of bars given in this input.
FRAMA and Candlestick Patterns [CSM]FRAMA (Fractal Adaptive Moving Average) is a technical analysis indicator that adapts its smoothing period according to the market's volatility, allowing it to provide accurate signals in all market conditions. This indicator script plots the FRAMA on a chart and generates buy and sell signals based on the FRAMA and candlestick patterns. It also includes an option to filter signals based on bullish and bearish engulfing patterns.
To detect candlestick patterns, the script imports the "BankNifty_CSM" library from the creator's public library on TradingView. The FRAMA calculation is done using a loop that iterates over the last "length" number of bars, with the smoothing factor adjusted based on the "fracDim" parameter.
The buy and sell signals are generated based on the position of the current price relative to the FRAMA line. If the "engulfing" parameter is set to true, the signals are further filtered based on bullish and bearish engulfing patterns.
Overall, this script combines various technical indicators and candlestick pattern recognition to provide a complete trading strategy. However, as with any trading strategy, it should be thoroughly backtested and evaluated before using it in a live trading environment.
Custom Group Financials [Technimentals]This script allows the user to build custom groups and combine the same financial data from 40 different symbols simultaneously and plot it data as a total or as an average.
By default, the top 40 symbols in the QQQ are used. Between them they account for the majority of the index. This is a good workaround for the lack of ETF financial data in TradingView.
This functions much like any other financial indicator. You choose the financial data and period:
FY = Financial Year
FQ = Financial Quarter
TTM = Trailing Twelve Months
Bare in mind that some data only exists in FY data.
Thanks to @LucF for writing most of this code!
Enjoy!
EMA bridge and dashboard with color coding.
Summary:
This is a custom moving average indicator script that calculates and plots different Exponential Moving Averages (EMAs) based on user-defined input values. The script also displays MACD and RSI, and provides a table that displays the current trend of the market in a color-coded format.
Explanation:
- The script starts by defining the name of the indicator and the different inputs that the user can customize.
- The inputs include bridge values for three different EMAs (high, close, and low), and four other EMAs (5, 50, 100, and 200).
- The script assigns values to these inputs using the `ta.ema()` function.
- Additionally, the script calculates EMAs for higher timeframes (3m, 5m, 15m, and 30m).
- The script then plots the EMAs on the chart using different colors and line widths.
- The script defines conditions for going long or short based on the crossover of two EMAs.
- It plots triangles above or below bars to indicate the crossover events.
- The script also calculates and displays the RSI and MACD of the asset.
- Finally, the script creates a table that displays the current trend of the market in a color-coded format. The table can be positioned on the top, middle, or bottom of the chart and on the left, center, or right side of the chart.
Parameters:
- i_ema_h: Bridge value for high EMA (default=34)
- i_ema_c: Bridge value for close EMA (default=34)
- i_ema_l: Bridge value for low EMA (default=34)
- i_ema_5: Value for 5-period EMA (default=5)
- i_ema_50: Value for 50-period EMA (default=50)
- i_ema_100: Value for 100-period EMA (default=100)
- i_ema_200: Value for 200-period EMA (default=200)
- i_f_ema: Value for fast EMA used in MACD calculation (default=9)
- i_s_ema: Value for slow EMA used in MACD calculation (default=21)
- fastInput: Value for fast length used in MACD calculation (default=7)
- slowInput: Value for slow length used in MACD calculation (default=14)
- tableYposInput: Vertical position of the table (options: top, middle, bottom; default=middle)
- tableXposInput: Horizontal position of the table (options: left, center, right; default=right)
- bullColorInput: Color of the table cell for a bullish trend (default=green)
- bearColorInput: Color of the table cell for a bearish trend (default=red)
- neutColorInput: Color of the table cell for a neutral trend (default=white)
- neutColorLabelInput: Color of the label for neutral trend in the table (default=fuchsia)
Usage:
To use this script, simply copy and paste it into the Pine Editor on TradingView. You can then customize the input values to your liking or leave them at their default values. Once you have added the script to your chart, you can view the EMAs, MACD, RSI, and trend table on the chart. The trend table provides a quick way to assess the current trend of the market at a glance.
BTCUSD Price prediction based on central bank liquidityIn recent months the idea that Bitcoin prices are increasingly linked to liquidity provided by central banks has gained strength. Multiple opinion leaders in the bitcoin space have shared their thoughts to explain why this is happening and why it makes sense. Some of these people I'm talking about are Preston Pysh, Dr. Jeff Ross, Steven McClurg, Lynn Alden among others.
The reality is that the correlation between market liquidity, measured as Assets held by the Federal Reserve, Bank of Japan and European Central bank, and Bitcoin prices is high. This made me wonder whether a regression between "market liquidity" and BTCUSD prices made sense in order to understand where Bitcoin prices are in relation to the liquidity in the market. After several trials I ended up fitting a polynomial regression of degree 5 between Market Liquidity and BTCUSD prices since 2013. This regression resulted in r-squared value of 90.93%. I initially visualized the results in python notebooks but then I thought it would be cool to be able to see them in real-time in tradingview.
That's where this script comes handy...
This script takes the coefficients and intercept from the polynomial regression I built and applies them to the "market_liquidity" index. In addition, it adds upper and lower bound lines to the prediction based on a 95% confidence interval. As you will see, particularly since 2020, the price of bitcoin has rarely been above or below the lines representing the 95% confidence interval. When price has actually crossed these lines it's been in moments where Bitcoin was highly overbought or oversold. Therefore this indicator could be used to understand when it's a good moment to enter or exit the market based on central bank fundamentals.
Here's the detailed step-by-step description of what the script does
1) It defines the coefficients obtained from running the regression betweeen "market liquidity" and BTCUSD. Market liquidity is defined as:
Market liquidity = FRED:WALCL + FX_IDX:JPYUSD*FRED:JPNASSETS + FX:EURUSD*FRED:ECBASSETSW - FRED:RRPONTSYD - FRED:WTREGEN
2) It defines a scale factor. The reason for this is that coefficients from the regression are very small numbers, given the huge numbers of the value of assets held by central banks. Pinescript doesn't support numbers with many decimals and rounds them to 0, so the coefficients had to be scaled up in order to be able to calculate the regression results.
3) It calculates market liquity with the formula defined above. Market liquidity is calculated in US Dollars.
4) It calculates the predicted BTCUSD price based on the coefficients and the market liquidity values.
5) It scales down the values by the same factor used to scale the coefficients up
6) It defines the standard deviation of the "potential_btcusd_price_scaled" and the actual BTCUSD prices.
7) It defines upper and lower bounds to the BTCUSD price prediction using a z-score of 1.96, which is equivalent to 95% confidence interval.
8) Lastly it plots the BTCUSD price prediction (orange) and the upper (red) and lower(green) confidence intervals.
The script can be updated as the correlation of BTCUSD to central bank assets changes (the slope values can be updated).
How to use it:
When actual BTCUSD price (blue line in the chart) crosses over the red line (upper bound) or crosses under the green line (lower bound) it should be taken as a sign that the price of BTCUSD may be overvalued or undervalued based on the value of assets held by major central banks.
comm_idxThis script displays information about the components of the Goldman Sachs Commodity Index. The index is based on futures contracts in the categories of agricultural products, softs commodities, livestock, energies, industrial metals, and precious metals. The statistics displayed in the table are:
change: 1-day % change
from ma: the % change from a moving average
corr idx: correlation of the contract to the GSCI
The lengths for the moving average and correlation statistic can be set using the inputs.
See the script source for the symbols used for each commodity. Although most of the symbols correspond to the actual futures contract used to compute the index, LME contracts are not available on tradingview. Hence, corresponding HKEX contracts are used for the industrial metals.
CVD - Cumulative Volume Delta Candles (old version)An old session of CVD from Tradingview. I noticed that the latest version of CVD has errors in calculations between different timeframes and with other similar indicators by other authors.
