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.
Cerca negli script per "如何用wind搜索股票的发行价和份数"
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.
Yeong RRGThe code outlines a trading strategy that leverages Relative Strength (RS) and Rate of Change (RoC) to make trading decisions. Here's a detailed breakdown of the tactic described by the code:
Ticker and Period Selection: The strategy begins by selecting a stock ticker symbol and defining a period (len) for the calculations, which defaults to 14 but can be adjusted by the user.
Stock and Index Data Retrieval: It fetches the closing price (stock_close) of the chosen stock and calculates its 25-period exponential moving average (stock_ema). Additionally, it retrieves the closing price of the S&P 500 Index (index_close), used as a benchmark for calculating Relative Strength.
Relative Strength Calculation: The Relative Strength (rs) is computed by dividing the stock's closing price by the index's closing price, then multiplying by 100 to scale the result. This metric is used to assess the stock's performance relative to the broader market.
Moving RS Ratio and Rate of Change: The strategy calculates a Simple Moving Average (sma) of the RS over the specified period to get the RS Ratio (rs_ratio). It then computes the Rate of Change (roc) of this RS Ratio over the same period to get the RM Ratio (rm_ratio).
Normalization: The RS Ratio and RM Ratio are normalized using a formula that adjusts their values based on the mean and standard deviation of their respective series over the specified window. This normalization process helps in standardizing the indicators, making them easier to interpret and compare.
Indicator Plotting: The normalized RS Ratio (jdk_rs_ratio) and RM Ratio (jdk_rm_ratio) are plotted on the chart with different colors for visual analysis. A horizontal line (hline) at 100 serves as a reference point, indicating a neutral level for the indicators.
State Color Logic: The script includes a logic to determine the state color (statecolor) based on the previous state color and the current values of jdk_rs_ratio and jdk_rm_ratio. This color coding is intended to visually represent different market states: green for bullish, red for bearish, yellow for hold, and blue for watch conditions.
Signal Generation: The strategy generates buy, sell, hold, and watch signals based on the state color and the indicators' values relative to 100. For example, a buy signal is generated when both jdk_rs_ratio and jdk_rm_ratio are above 100, and the background color is set to green to reflect this bullish condition.
Trade Execution: Finally, the strategy executes trades based on the generated signals. A "BUY" trade is entered when a buy signal is present, and it is closed when a sell signal occurs.
Overall, the strategy uses a combination of RS and RoC indicators, normalized for better comparison, to identify potential buy and sell opportunities based on the stock's performance relative to the market and its momentum.
Multi Time Frame Exponential Moving Average and dasboardThis Pine script, titled "Multi Time Frame Exponential Moving Average (MTF EMA)," provides an innovative approach for traders who wish to track trends across multiple timeframes without having to switch between different charts. It combines two main features: an indicator displaying exponential moving averages (EMA) on five different time periods, as well as a compact dashboard that synthesizes this information on a single chart window.
The originality of this script lies in its ability to provide a comprehensive analysis of EMA trends across different time intervals, allowing traders to quickly and clearly understand the market dynamics without having to navigate between multiple charts. Rather than switching from one chart to another to observe trends on different time scales, traders can now consult a single dashboard to obtain all the necessary information.
The script uses exponential moving averages (EMA) to identify trends over five time periods: 5 minutes, 15 minutes, 1 hour, 4 hours, and 1 day. The values of the EMAs are calculated based on the closing prices of candles. Bullish or bearish trends are indicated by upward or downward arrows respectively, making it easy to interpret the information on the dashboard.
To use this script, traders can simply add it to their chart on the TradingView platform. They can customize the parameters of the exponential moving averages according to their preferences and choose between a dark or light theme for the dashboard. Then, they can observe trends on different time scales directly on the dashboard, enabling them to make informed trading decisions.
In summary, this script offers a practical and innovative solution for tracking trends across multiple timeframes, combining the efficiency of exponential moving averages with the convenience of a dashboard centralized on a single chart. This allows traders to save time and stay informed about market movements effectively and efficiently.
Risk Management Chart█ OVERVIEW
Risk Management Chart allows you to calculate and visualize equity and risk depend on your risk-reward statistics which you can set at the settings.
This script generates random trades and variants of each trade based on your settings of win/loss percent and shows it on the chart as different polyline and also shows thick line which is average of all trades.
It allows you to visualize and possible to analyze probability of your risk management. Be using different settings you can adjust and change your risk management for better profit in future.
It uses compound interest for each trade.
Each variant of trade is shown as a polyline with color from gradient depended on it last profit.
Also I made blurred lines for better visualization with function :
poly(_arr, _col, _t, _tr) =>
for t = 1 to _t
polyline.new(_arr, false, false, xloc.bar_index, color.new(_col, 0 + t * _tr), line_width = t)
█ HOW TO USE
Just add it to the cart and expand the window.
█ SETTINGS
Start Equity $ - Amount of money to start with (your equity for trades)
Win Probability % - Percent of your win / loss trades
Risk/Reward Ratio - How many profit you will get for each risk(depends on risk per trade %)
Number of Trades - How many trades will be generated for each variant of random trading
Number of variants(lines) - How many variants will be generated for each trade
Risk per Trade % -risk % of current equity for each trade
If you have any ask it at comments.
Hope it will be useful.
Time Candle Range HistoryThe 'Intraday Candle Range Average' indicator is designed to provide traders with insights into the average price range of intraday candles, specifically focusing on the period around 9:30 AM. By calculating the difference between the high and low of candles occurring at 9:30 AM, the indicator offers a dynamic view of market volatility during this critical time window. Users can customize parameters such as the number of days to consider for the average calculation, allowing for flexibility in analyzing short-term price movements. Additionally, the indicator offers a clear visualization of the current candle range compared to the historical average, aiding traders in identifying potential trading opportunities based on volatility patterns. Whether used independently or in conjunction with other technical analysis tools, the 'Intraday Candle Range Average' indicator empowers traders with valuable insights into intraday market dynamics.
forex_factory_utilityLibrary "forex_factory_utility"
Supporting Utility Library for the Live Economic Calendar by toodegrees Indicator; responsible for data handling, and plotting news event data.
isLeapYear()
Finds if it's currently a leap year or not.
Returns: Returns True if the current year is a leap year.
daysMonth(M)
Provides the days in a given month of the year, adjusted during leap years.
Parameters:
M (int) : Month in numerical integer format (i.e. Jan=1).
Returns: Days in the provided month.
size(S, N)
Converts a size string into the corresponding Pine Script v5 format, or N times smaller/bigger.
Parameters:
S (string) : Size string: "Tiny", "Small", "Normal", "Large", or "Huge".
N (int) : Size variation, can be positive (larger than S), or negative (smaller than S).
Returns: Size string in Pine Script v5 format.
lineStyle(S)
Converts a line style string into the corresponding Pine Script v5 format.
Parameters:
S (string) : Line style string: "Dashed", "Dotted" or "Solid".
Returns: Line style string in Pine Script v5 format.
lineTrnsp(S)
Converts a transparency style string into the corresponding integer value.
Parameters:
S (string) : Line style string: "Light", "Medium" or "Heavy".
Returns: Transparency integer.
boxLoc(X, Y)
Converts position strings of X and Y into a table position in Pine Script v5 format.
Parameters:
X (string) : X-axis string: "Left", "Center", or "Right".
Y (string) : Y-axis string: "Top", "Middle", or "Bottom".
Returns: Table location string in Pine Script v5 format.
method bubbleSort_NewsTOD(N)
Performs bubble sort on a Forex Factory News array of all news from the same date, ordering them in ascending order based on the time of the day.
Namespace types: News
Parameters:
N (News ) : Forex Factory News array.
Returns: void
bubbleSort_News(N)
Performs bubble sort on a Forex Factory News array, ordering them in ascending order based on the time of the day, and date.
Parameters:
N (News ) : Forex Factory News array.
Returns: Sorted Forex Factory News array.
weekNews(N, C, I)
Creates a Forex Factory News array containing the current week's Forex Factory News.
Parameters:
N (News ) : Forex Factory News array containing this week's unfiltered Forex Factory News.
C (string ) : Currency filter array (string array).
I (color ) : Impact filter array (color array).
Returns: Forex Factory News array containing the current week's Forex Factory News.
todayNews(W, D, M)
Creates a Forex Factory News array containing the current day's Forex Factory News.
Parameters:
W (News ) : Forex Factory News array containing this week's Forex Factory News.
D (News ) : Forex Factory News array for the current day's Forex Factory News.
M (bool) : Boolean that marks whether the current chart has a Day candle-switch at Midnight New York Time.
Returns: Forex Factory News array containing the current day's Forex Factory News.
impFilter(X, L, M, H)
Creates a filter array from the User's desired Forex Facory News to be shown based on Impact.
Parameters:
X (bool) : Boolean - if True Holidays listed on Forex Factory will be shown.
L (bool) : Boolean - if True Low Impact listed on Forex Factory News will be shown.
M (bool) : Boolean - if True Medium Impact listed on Forex Factory News will be shown.
H (bool) : Boolean - if True High Impact listed on Forex Factory News will be shown.
Returns: Color array with the colors corresponding to the Forex Factory News to be shown.
curFilter(A, C1, C2, C3, C4, C5, C6, C7, C8, C9)
Creates a filter array from the User's desired Forex Facory News to be shown based on Currency.
Parameters:
A (bool) : Boolean - if True News related to the current Chart's symbol listed on Forex Factory will be shown.
C1 (bool) : Boolean - if True News related to the Australian Dollar listed on Forex Factory will be shown.
C2 (bool) : Boolean - if True News related to the Canadian Dollar listed on Forex Factory will be shown.
C3 (bool) : Boolean - if True News related to the Swiss Franc listed on Forex Factory will be shown.
C4 (bool) : Boolean - if True News related to the Chinese Yuan listed on Forex Factory will be shown.
C5 (bool) : Boolean - if True News related to the Euro listed on Forex Factory will be shown.
C6 (bool) : Boolean - if True News related to the British Pound listed on Forex Factory will be shown.
C7 (bool) : Boolean - if True News related to the Japanese Yen listed on Forex Factory will be shown.
C8 (bool) : Boolean - if True News related to the New Zealand Dollar listed on Forex Factory will be shown.
C9 (bool) : Boolean - if True News related to the US Dollar listed on Forex Factory will be shown.
Returns: String array with the currencies corresponding to the Forex Factory News to be shown.
FF_OnChartLine(N, T, S)
Plots vertical lines where a Forex Factory News event will occur, or has already occurred.
Parameters:
N (News ) : News-type array containing all the Forex Factory News.
T (int) : Transparency integer value (0-100) for the lines.
S (string) : Line style in Pine Script v5 format.
Returns: void
method updateStringMatrix(M, P, V)
Namespace types: matrix
Parameters:
M (matrix)
P (int)
V (string)
FF_OnChartLabel(N, Y, S)
Plots labels where a Forex Factory News has already occurred based on its/their impact.
Parameters:
N (News ) : News-type array containing all the Forex Factory News.
Y (string) : String that gives direction on where to plot the label (options= "Above", "Below", "Auto").
S (string) : Label size in Pine Script v5 format.
Returns: void
historical(T, D, W, X)
Deletes Forex Factory News drawings which are ourside a specific Time window.
Parameters:
T (int) : Number of days input used for Forex Factory News drawings' history.
D (bool) : Boolean that when true will only display Forex Factory News drawings of the current day.
W (bool) : Boolean that when true will only display Forex Factory News drawings of the current week.
X (string) : String that gives direction on what lines to plot based on Time (options= "Past", "Future", "Both").
Returns: void
newTable(P)
Creates a new Table object with parameters tailored to the Forex Factory News Table.
Parameters:
P (string) : Position string for the Table, in Pine Script v5 format.
Returns: Empty Forex Factory News Table.
resetTable(P, S, headTextC, headBgC)
Resets a Table object with parameters and headers tailored to the Forex Factory News Table.
Parameters:
P (string) : Position string for the Table, in Pine Script v5 format.
S (string) : Size string for the Table's text, in Pine Script v5 format.
headTextC (color)
headBgC (color)
Returns: Empty Forex Factory News Table.
logNews(N, TBL, R, S, rowTextC, rowBgC)
Adds an event to the Forex Factory News Table.
Parameters:
N (News) : News-type object.
TBL (table) : Forex Factory News Table object to add the News to.
R (int) : Row to add the event to in the Forex Factory News Table.
S (string) : Size string for the event's text, in Pine Script v5 format.
rowTextC (color)
rowBgC (color)
Returns: void
FF_Table(N, P, S, headTextC, headBgC, rowTextC, rowBgC)
Creates the Forex Factory News Table.
Parameters:
N (News ) : News-type array containing all the Forex Factory News.
P (string) : Position string for the Table, in Pine Script v5 format.
S (string) : Size string for the Table's text, in Pine Script v5 format.
headTextC (color)
headBgC (color)
rowTextC (color)
rowBgC (color)
Returns: Forex Factory News Table.
timeline(N, T, F, D)
Shades Forex Factory News events in the Forex Factory News Table after they occur.
Parameters:
N (News ) : News-type array containing all the Forex Factory News.
T (table) : Forex Facory News table object.
F (color) : Color used as shading once the Forex Factory News has occurred.
D (bool) : Daily Forex Factory News flag.
Returns: Forex Factory News Table.
News
Custom News type which contains informatino about a Forex Factory News Event.
Fields:
dow (series string) : Day of the week, in DDD format (i.e. 'Mon').
dat (series string) : Date, in MMM D format (i.e. 'Jan 1').
_t (series int)
tod (series string) : Time of the day, in hh:mm 24-Hour format (i.e 17:10).
cur (series string) : Currency, in CCC format (i.e. "USD").
imp (series color) : Impact, the respective impact color for Forex Factory News Events.
ttl (series string) : Title, encoded in a custom number mapping (see the toodegrees/toodegrees_forex_factory library to learn more).
tmst (series int)
ln (series line)
itradesize /\ Silver Bullet x Macro x KillzoneThis indicator shows the best way to annotate ICT Killzones, Silver Bullet and Macro times on the chart. With the help of a new pane, it will not distract your chart and will not cause any distractions to your eye, or brain but you can see when will they happen.
The indicator also draws everything beforehand when a proper new day starts.
You can customize them how you want to show up.
Collapsed or full view?
You can hide any of them and keep only the ones you would like to.
All the colors can be customized, texts & sizes or just use shortened texts and you are also able to hide those drawings which are older than the actual day.
You should minimize the pane where the script has been automatically drawn to therefore you will have the best experience and not show any distractions.
The script automatically shows the time-based boxes, based on the New York timezone.
Killzone Time windows ( for indices ):
London KZ 02:00 - 05:00
New York AM KZ 07:00 - 10:00
New York PM KZ 13:30 - 16:00
Silver Bullet times:
03:00 - 04:00
10:00 - 11:00
14:00 - 15:00
Macro times:
02:33 - 03:00
04:03 - 04:30
08:50 - 0910
09:50 - 10:10
10:50 - 11:10
11:50 - 12:50
Backtesting ModuleDo you often find yourself creating new 'strategy()' scripts for each trading system? Are you unable to focus on generating new systems due to fatigue and time loss incurred in the process? Here's a potential solution: the 'Backtesting Module' :)
INTRODUCTION
Every trading system is based on four basic conditions: long entry, long exit, short entry and short exit (which are typically defined as boolean series in Pine Script).
If you can define the conditions generated by your trading system as a series of integers, it becomes possible to use these variables in different scripts in efficient ways. (Pine Script is a convenient language that allows you to use the integer output of one indicator as a source in another.)
The 'Backtesting Module' is a dynamic strategy script designed to adapt to your signals. It boasts two notable features:
⮞ It produces a backtest report using the entry and exit variables you define.
⮞ It not only serves for system testing but also to combine independent signals into a single system. (This functionality enables to create complex strategies and report on their success!)
The module tests Golden and Death cross signals by default, when you enter your own conditions the default signals will be neutralized. The methodology is described below.
PREPARATION
There are three simple steps to connect your own indicator to the Module.
STEP 1
Firstly, you must define entry and exit variables in your own script. Let's elucidate it with a straightforward example. Consider a system generating long and short signals based on the intersections of two moving averages. Consequently, our conditions would be as follows:
// Signals
long = ta.crossover(ta.sma(close, 14), ta.sma(close, 28))
short = ta.crossunder(ta.sma(close, 14), ta.sma(close, 28))
Now, the question is: How can we convert boolean variables into integer variables? The answer is conditional ternary block, defined as follows:
// Entry & Exit
long_entry = long ? 1 : 0
long_exit = short ? 1 : 0
short_entry = short ? 1 : 0
short_exit = long ? 1 : 0
The mechanics of the Entry & Exit variables are simple. The variable takes on a value of 1 when your trading system generates the signal and if your system does not produce any signal, variable returns 0. In this example, you see how exit signals can be generated in a trading system that only contains entry signals. If you have a system with original exit signals, you can also use them directly. (Please mind the NOTES section below).
STEP 2
To utilize the Entry & Exit variables as source in another script, they must be plotted on the chart. Therefore, the final detail to include in the script containing your trading system would be as follows:
// Plot The Output
plot(long_entry, "Long Entry", display=display.data_window, editable=false)
plot(long_exit, "Long Exit", display=display.data_window, editable=false)
plot(short_entry, "Short Entry", display=display.data_window, editable=false)
plot(short_exit, "Short Exit", display=display.data_window, editable=false)
STEP 3
Now, we are ready to test the system! Load the Backtesting Module indicator onto the chart along with your trading system/indicator. Then set the outputs of your system (Long Entry, Long Exit, Short Entry, Short Exit) as source in the module. That's it.
FEATURES & ORIGINALITY
⮞ Primarily, this script has been created to provide you with an easy and practical method when testing your trading system.
⮞ I thought it might be nice to visualize a few useful results. The Backtesting Module provides insights into the outcomes of both long and short trades by computing the number of trades and the success percentage.
⮞ Through the 'Trade' parameter, users can specify the market direction in which the indicator is permitted to initiate positions.
⮞ Users have the flexibility to define the date range for the test.
⮞ There are optional features allowing users to plot entry prices on the chart and customize bar colors.
⮞ The report and the test date range are presented in a table on the chart screen. The entry price can be monitored in the data window.
⮞ Note that results are based on realized returns, and the open trade is not included in the displayed results. (The only exception is the 'Unrealized PNL' result in the table.)
STRATEGY SETTINGS
The default parameters are as follows:
⮞ Initial Balance : 10000 (in units of currency)
⮞ Quantity : 10% of equity
⮞ Commission : 0.04%
⮞ Slippage : 0
⮞ Dataset : All bars in the chart
For a realistic backtest result, you should size trades to only risk sustainable amounts of equity. Do not risk more than 5-10% on a trade. And ALWAYS configure your commission and slippage parameters according to pessimistic scenarios!
NOTES
⮞ This script is intended solely for development purposes. And it'll will be available for all the indicators I publish.
⮞ In this version of the module, all order types are designed as market orders. The exit size is the sum of the entry size.
⮞ As your trading conditions grow more intricate, you might need to define the outputs of your system in alternative ways. The method outlined in this description is tailored for straightforward signal structures.
⮞ Additionally, depending on the structure of your trading system, the backtest module may require further development. This encompasses stop-loss, take-profit, specific exit orders, quantity, margin and risk management calculations. I am considering releasing improvements that consider these options in future versions.
⮞ An example of how complex trading signals can be generated is the OTT Collection. If you're interested in seeing how the signals are constructed, you can use the link below.
THANKS
Special thanks to PineCoders for their valuable moderation efforts.
I hope this will be a useful example for the TradingView community...
DISCLAIMER
This is just an indicator, nothing more. It is provided for informational and educational purposes exclusively. The utilization of this script does not constitute professional or financial advice. The user solely bears the responsibility for risks associated with script usage. Do not forget to manage your risk. And trade as safely as possible. Best of luck!
Advanced Technical Range and Expectancy Estimator [SS]Hello everyone,
This indicator is a from of momentum based probability modelling. It is derived from my own approaches to probability modelling but just simplified a bit.
How it works:
The indicator looks at various technical, including stochastics, RSI, MFI and Z-Score, to determine the likely sentiment. All of these, with the exception of Z-Score, are momentum based indicators and can alert us to likely sentiment. However, instead of us making the subjective determination ourselves as to whether the RSI or MFI or Stochastics are bullish, the indicator will look at previous instances of these occurrences, and tally the bullish and bearish follow throughs that happened. It will also calculate the average target price that was hit, under similar conditions, on the same timeframe.
The Z-Score is your "tie breaker". It is not a momentum based indicator and measures something a little different (the standard deviation and over-extension of the stock). For this reason, it provides an alternative assessment and tends to be a bit more reliable in times of low momentum.
Back-test Results:
The indicator back-tests itself over the previous 100 candles. I have limited it to 100 candles for pragmatic considerations (it has to back-test each technical individually and increasing the BT length will slow and potentially error out the indicator) as well as accuracy considerations.
One thing I have noticed in my years of trying to crack the code and develop probability models for tickers, is historical accuracy doesn't always matter because sentiment is always changing. You need to see what it has done over the most recent 100 to 200 candles.
There are two back-test windows, one for the price targets and the other for the sentiment accuracy. The most effective/most accurate will highlight green, the least effective/least accurate will highlight red:
In the image above, you can see that the most accurate predictor of sentiment is Z-Score, with a 90.32% accuracy rate over the past 100 candles.
The most accurate predictor of price is MFI, with a 60% (for bull targets) and 42% (for bear targets)accuracy rate.
Anchoring Points:
The indicator permits you to anchor by two points. The default setting is anchoring by previous candle. If you plan to use this as an oscillator, to see the current prediction for the current candle you are viewing, then you will need to leave this default setting. It will pull the data from the previous candle and give you the data for the current candle you are on.
If you are assess the likely sentiment for the next day after the day has closed off, you will want to anchor by current candle. This will take the current technicals that the day has closed off with and run the assessment for you.
Customizability
You can customize the technicals by source and length of assessment.
They are all defaulted to the traditional settings of these indicators, but if you want to customize your model to try and improve or enhance accuracy in one way or another, you are free and able to do so!
I do suggest leaving the defaults as they seem to work particular well :-).
Thresholds
Thresholds are the tolerance levels that we permit for our technical search range. If you want them to be exactly identical, then you can set it to 0. If you want it to be extremely similar, you can set it to 0.01. This will hone in on the ranges you are interest in and you can see how it affects your accuracy by reviewing the results in the back-test tables.
Keep Static Colour Option
I want to make a quick note on the "Keep Static Colour" option that is in your settings menu.
The primary table that shows you the probability and price targets change colours based on the accuracy of the assessment. This is so, if you are using a mobile device or smaller screen and can't have the back-test results open at the same time, you can see still which are the most reliable results. However, if you have the back-test tables open and you find these colour changes too distracted, you can toggle on the "Keep Static Colour" and it will resort the colour of the table to a solid white:
Show Technicals
The indicator can show you the current technical values if you are using it in place of an oscillator. Its less pivotal as its making the assessment for you, but just for your reference if you want to see what the current MFI, Z-Score or Stochastics etc. are, you have that option as well.
All Timeframes Permitted
You can view Weekly, Monthly, Hourly, 5 minute, 1 minute, its all supported!
That's the indicator in a nutshell.
Hope you enjoy and leave your questions below.
Safe trades everyone!
ICT Times [joshu]This TradingView indicator provides a comprehensive view of ICT killzones, Silver Bullet times, and ICT Macros, enhancing your trading experience.
In those time windows price either seeks liquidity or imbalances and you often find the most energetic price moves and turning points.
Features:
Automatic Adaptation: The ICT killzones intelligently adapt to the specific chart you are using. For Forex charts, it follows the ICT Forex times:
Asia: 2000-0000
London: 0200-0500
New York: 0700-1000
London Close: 1000-1200
For other charts, it uses the following session times:
Asia: 2000-0000
London: 0200-0500
New York AM: 0830-1100
New York PM: 1330-1600
Silver Bullet Times:
0300-0400
1000-1100
1400-1500
How to Use:
Simply apply the indicator to your chart, and the session boxes and Silver Bullet times will be plotted automatically.
Monthly beta (5Y monthly) with multi-timeframe supportThe PROPER way to calculate beta for a stock using monthly price returns . None of this nonsense using daily returns and sliding windows as done by other scripts...
Works on any timeframe.
This script has been checked against 100s of stocks on Yahoo finance and Zacks research data and matches 100% (some rounding error as this script is kept updated live on unconfirmed monthly bars).
You can check for yourself:
Zacks fundamentals - beta
The script calculates beta using the Variance-Covariance Method as described on Investopedia
How to calculate Beta
Purchasing Managers Index (PMI)The Purchasing Managers Index (PMI) is a widely recognized economic indicator that provides crucial insights into the health and performance of an economy's manufacturing and services sectors. This index is a vital tool for anticipating economic developments and trends, offering an early warning system for changes in these sectors.
The PMI is calculated based on surveys conducted among purchasing managers in various businesses and organizations. These managers are asked about their perceptions of current business conditions and their expectations for future economic activity within their sectors. The responses are then compiled and used to calculate the PMI value.
A PMI value above 50 typically indicates that the manufacturing or services sector is expanding, suggesting a positive economic outlook. Conversely, a PMI value below 50 suggests contraction, which may be an early indication of economic challenges or a potential recession.
In summary, the Purchasing Managers Index (PMI) is an essential economic indicator that assesses the health of manufacturing and services sectors by surveying purchasing managers' opinions. It serves as an early warning system for changes in economic activity and is a valuable tool for forecasting economic trends and potential crises.
This code combines the Purchasing Managers Index (PMI) data with two Simple Moving Averages (SMA) and some visual elements.
Let's break down how this indicator works:
1. Loading PMI Data:
The indicator loads data for the "USBCOI" symbol, which represents the PMI data. It fetches the monthly closing prices of this symbol.
2. Calculating Moving Averages:
Two Simple Moving Averages (SMAs) are calculated based on the PMI data. The first SMA, sma_usbcoi, has a length defined by the input parameter (default: 2). The second SMA, sma2_usbcoi, has a different length defined by the second input parameter (default: 14).
3. Color Coding and Thresholds:
The line color of the PMI plot is determined based on the value of the PMI. If the PMI is above 52, the color is teal; if it's below 48, the color is red; otherwise, it's gray. These threshold values are often used to identify specific conditions in the PMI data.
4. Crossing Indicator:
A key feature of this indicator is to determine if the PMI crosses the first SMA (sma_usbcoi) from top to bottom while also being above the value of 52. This is indicated by the crossedUp variable. This condition suggests a specific situation where the PMI crosses a short-term moving average while indicating strength (above 52).
5. Visual Elements:
A "💀" skull emoji is defined as skullEmoji.
The PMI is plotted on the chart with color coding based on its value, as described earlier.
The two SMAs are also plotted on the chart.
When the crossedUp condition is met (PMI crosses the first SMA from top to bottom while above 52), a skull emoji (indicating potential danger) is plotted at the top of the indicator window.
Realized Profit & Loss [BigBeluga]The Realized Loss & Profit indicator aims to find potential dips and tops in price by utilizing the security function syminfo.basecurrency + "_LOSSESADDRESSES".
The primary objective of this indicator is to present an average, favorable buying/selling opportunity based on the number of people currently in profit or loss.
The script takes into consideration the syminfo.basecurrency, so it should automatically adapt to the current coin.
🔶 USAGE
Users have the option to enable the display of either Loss or Profit, depending on their preferred visualization.
Examples of displaying Losses:
Example of displaying Profits:
🔶 CONCEPTS
The concept aims to assign a score to the data in the ticker representing the realized losses. This score will provide users with an average of buying/selling points that are better to the typical investor.
🔶 SETTINGS
Users have complete control over the script settings.
🔹 Calculation
• Profit: Display people in profit on an average of the selected length.
• Loss: Display people in loss on an average of the selected length.
🔹 Candle coloring
• True: Color the candle when data is above the threshold.
• False: Do not color the candle.
🔹 Levels
- Set the level of a specific threshold.
• Low: Low losses (green).
• Normal: Low normal (yellow).
• Medium: Low medium (orange).
• High: Low high (red).
🔹 Z-score Length: Length of the z-score moving window.
🔹 Threshold: Filter out non-significant values.
🔹 Histogram width: Width of the histogram.
🔹 Colors: Modify the colors of the displayed data.
🔶 LIMITATIONS
• Since the ticker from which we obtain data works only on the daily timeframe, we are
restricted to displaying data solely from the 1D timeframe.
• If the coin does not have any realized loss data, we can't use this script.
InteliTrend StableFXThis appealing little tool is a derivation of the CCI indicator and was developed in 2023 by Mario Jemic for MT4. It has additional settings that the conventional CCI indicator does not have. Furthermore, it is combined with moving averages to create signals. This is lines crossing confirmation type indicator. Look for the orange line to cross the moving average (red line).
Differences from the original:
1. Though it was coded in 2023, the original is for people who are still running Windows 95 and would like to do technical analysis on MT4.
2. The original had an additional stochastic moving average that was not particularly useful and made the indicator busy.
3. All of the moving average options have been ported over with 2 additional choices. (Hull and Arnaud Legoux added).
4. The default options are set as the tweaks that were discovered by StoneHill Forex (stonehillforex.com). You can also download the original from them.
I will probably add a few more features and options in the near future such as visuals for crossovers etc.
Enjoy!
d1g1talshad0w
ICT Killzones + Pivots [TFO]Designed with the help of TTrades and with inspiration from the ICT Everything indicator by coldbrewrosh, the purpose of this script is to identify ICT Killzones while also storing their highs and lows for future reference, until traded through.
There are 5 Killzones / sessions whose times and labels can all be changed to one's liking. Some prefer slight alterations to traditional ICT Killzones, or use different time windows altogether. Either way, the sessions are fully customizable. The sessions will auto fit to keep track of the highs and lows made during their respective times, and these pivots will be extended until they are invalidated.
There are also 4 optional Open Price lines and 4 vertical Timestamps, where the user can change the time and style of each one as well.
To help maintain a clean chart, we can implement a Cutoff Time where all drawings will stop extending past a certain point. The indicator will apply this logic by default, as it can get messy with multiple drawings starting and stopping throughout the day at different times.
Given the amount of interest I've received about this indicator, I intend to leave it open to suggestions for further improvements. Let me know what you think & what you want to see added!
RSI Dot Party - All Lengths From 1 To 120The RSI Dot Party indicator displays all RSI lengths from 1 to 120 as different colored dots on the chart.
🔶 Purpose
Show the reversal point of price action to time entries and exits.
🔶 USAGE
When a dot displays it is a indication of the reversal of the price/trend. The larger the dot the more likely it is to reverse.
The Default settings generates dots for extreme cases where the RSI is over = 90 or under = 10 for every RSI length in the range of 1-120.
Example if the RSI of length 1 or 2 or 3 or 4 or ... or 15 or 16 or 17 or ... or 80 or 81 or 82 or ... if any of does RSI crosses a boundary a dot is shown.
A boundary is the over/under the RSI oscillates in.
Customize the settings until the dots match up with the high and lows of past price action.
🔶 SETTINGS
🔹 Source
Source 1: Is the First Source RSI is calculated from
Source 2: Is the Second Source RSI is calculated from
🔹 Meta Settings
Hours back to draw: To speed up the script calculate it only draws a set number of hours back, default is 300 hours back in time to draw then it cuts off.
Show Dots: Show or disable dots
Show Bar Color: Color the bars for each RSI incident
Filter Cross: Filters and only shows dots when the RSI crosses above or bellow a boundary. If not all candles above or bellow the boundaries will display a dot.
Dots Location Absolute: Instead of showing the dots above or bellow the candle, the dots will show up on the top and bottom of the window.
🔹 7 RSI Groups
There are a total of 7 RSI colors.
Range Very Tiny: Default Color Green
Range Tiny: Default Color Purple
Range Small: Default Color Yellow
Range Normal: Default Color Red
Range Large: Default Color Blue
Range Huge: Default Color Dark Purple
Range Very Huge: Default Color White
🔹 RSI Group Settings
Hi/Low Color: Change the Color of that group.
Start/End: The Start and End range of this RSI color. Example if start = 5 and end = 10 the RSI of 5,6,7,8,9,10 will be displayed on the chart for that color, if any of does RSI goes above or bellow the boundary a dot is displayed on that candle.
Delay: The RSI needs to be above or bellow a boundary for x number of candles before displaying a dot. For example if delay = 2 and the RSI is over = 70 for 2 candles then it will display a dot.
Under/Over: Boundaries that indicate when to draw a dot, if over = 70 and RSI crosses above 70 a dot is displayed.
🔹 Show
Section that allows you to disable RSI grounds you dont want to see, this also removes them from the alert signal generated.
Show Low: Show or disable Low RSI dots
Show High: Show or disable High RSI dots
🔶 ALERTS
Alert for all New RSIs Dots Created in real time
The alert generated depends on what groups are showing or not, if the green group is disabled for example the alert will not be generated.
🔶 Warning
When a dot shows up it can continue moving. For example if a purple dot shows itself above a 15 minute candle, if that candle/price continue to extend up the dot will move up with it.
Dots can also disappear occasionally if the RSI moves in and out of a boundary within that candles life span.
🔶 Community
I hope you guys find this useful, if you have any questions or feature requests leave me a comment! Take care :D
RelativeValue█ OVERVIEW
This library is a Pine Script™ programmer's tool offering the ability to compute relative values, which represent comparisons of current data points, such as volume, price, or custom indicators, with their analogous historical data points from corresponding time offsets. This approach can provide insightful perspectives into the intricate dynamics of relative market behavior over time.
█ CONCEPTS
Relative values
In this library, a relative value is a metric that compares a current data point in a time interval to an average of data points with corresponding time offsets across historical periods. Its purpose is to assess the significance of a value by considering the historical context within past time intervals.
For instance, suppose we wanted to calculate relative volume on an hourly chart over five daily periods, and the last chart bar is two hours into the current trading day. In this case, we would compare the current volume to the average of volume in the second hour of trading across five days. We obtain the relative volume value by dividing the current volume by this average.
This form of analysis rests on the hypothesis that substantial discrepancies or aberrations in present market activity relative to historical time intervals might help indicate upcoming changes in market trends.
Cumulative and non-cumulative values
In the context of this library, a cumulative value refers to the cumulative sum of a series since the last occurrence of a specific condition (referred to as `anchor` in the function definitions). Given that relative values depend on time, we use time-based conditions such as the onset of a new hour, day, etc. On the other hand, a non-cumulative value is simply the series value at a specific time without accumulation.
Calculating relative values
Four main functions coordinate together to compute the relative values: `maintainArray()`, `calcAverageByTime()`, `calcCumulativeSeries()`, and `averageAtTime()`. These functions are underpinned by a `collectedData` user-defined type (UDT), which stores data collected since the last reset of the timeframe along with their corresponding timestamps. The relative values are calculated using the following procedure:
1. The `averageAtTime()` function invokes the process leveraging all four of the methods and acts as the main driver of the calculations. For each bar, this function adds the current bar's source and corresponding time value to a `collectedData` object.
2. Within the `averageAtTime()` function, the `maintainArray()` function is called at the start of each anchor period. It adds a new `collectedData` object to the array and ensures the array size does not exceed the predefined `maxSize` by removing the oldest element when necessary. This method plays an essential role in limiting memory usage and ensuring only relevant data over the desired number of periods is in the calculation window.
3. Next, the `calcAverageByTime()` function calculates the average value of elements within the `data` field for each `collectedData` object that corresponds to the same time offset from each anchor condition. This method accounts for cases where the current index of a `collectedData` object exceeds the last index of any past objects by using the last available values instead.
4. For cumulative calculations, the `averageAtTime()` function utilizes the `isCumulative` boolean parameter. If true, the `calcCumulativeSeries()` function will track the running total of the source data from the last bar where the anchor condition was met, providing a cumulative sum of the source values from one anchor point to the next.
To summarize, the `averageAtTime()` function continually stores values with their corresponding times in a `collectedData` object for each bar in the anchor period. When the anchor resets, this object is added to a larger array. The array's size is limited by the specified number of periods to be averaged. To correlate data across these periods, time indexing is employed, enabling the function to compare corresponding points across multiple periods.
█ USING THIS LIBRARY
The library simplifies the complex process of calculating relative values through its intuitive functions. Follow the steps below to use this library in your scripts.
Step 1: Import the library and declare inputs
Import the library and declare variables based on the user's input. These can include the timeframe for each period, the number of time intervals to include in the average, and whether the calculation uses cumulative values. For example:
//@version=5
import TradingView/RelativeValue/1 as TVrv
indicator("Relative Range Demo")
string resetTimeInput = input.timeframe("D")
int lengthInput = input.int(5, "No. of periods")
Step 2: Define the anchor condition
With these inputs declared, create a condition to define the start of a new period (anchor). For this, we use the change in the time value from the input timeframe:
bool anchor = timeframe.change(resetTimeInput)
Step 3: Calculate the average
At this point, one can calculate the average of a value's history at the time offset from the anchor over a number of periods using the `averageAtTime()` function. In this example, we use True Range (TR) as the `source` and set `isCumulative` to false:
float pastRange = TVrv.averageAtTime(ta.tr, lengthInput, anchor, false)
Step 4: Display the data
You can visualize the results by plotting the returned series. These lines display the non-cumulative TR alongside the average value over `lengthInput` periods for relative comparison:
plot(pastRange, "Past True Range Avg", color.new(chart.bg_color, 70), 1, plot.style_columns)
plot(ta.tr, "True Range", close >= open ? color.new(color.teal, 50) : color.new(color.red, 50), 1, plot.style_columns)
This example will display two overlapping series of columns. The green and red columns depict the current TR on each bar, and the light gray columns show the average over a defined number of periods, e.g., the default inputs on an hourly chart will show the average value at the hour over the past five days. This comparative analysis aids in determining whether the range of a bar aligns with its typical historical values or if it's an outlier.
█ NOTES
• The foundational concept of this library was derived from our initial Relative Volume at Time script. This library's logic significantly boosts its performance. Keep an eye out for a forthcoming updated version of the indicator. The demonstration code included in the library emulates a streamlined version of the indicator utilizing the library functions.
• Key efficiencies in the data management are realized through array.binary_search_leftmost() , which offers a performance improvement in comparison to its loop-dependent counterpart.
• This library's architecture utilizes user-defined types (UDTs) to create custom objects which are the equivalent of variables containing multiple parts, each able to hold independent values of different types . The recently added feature was announced in this blog post.
• To enhance readability, the code substitutes array functions with equivalent methods .
Look first. Then leap.
█ FUNCTIONS
This library contains the following functions:
calcCumulativeSeries(source, anchor)
Calculates the cumulative sum of `source` since the last bar where `anchor` was `true`.
Parameters:
source (series float) : Source used for the calculation.
anchor (series bool) : The condition that triggers the reset of the calculation. The calculation is reset when `anchor` evaluates to `true`, and continues using the values accumulated since the previous reset when `anchor` is `false`.
Returns: (float) The cumulative sum of `source`.
averageAtTime(source, length, anchor, isCumulative)
Calculates the average of all `source` values that share the same time difference from the `anchor` as the current bar for the most recent `length` bars.
Parameters:
source (series float) : Source used for the calculation.
length (simple int) : The number of reset periods to consider for the average calculation of historical data.
anchor (series bool) : The condition that triggers the reset of the average calculation. The calculation is reset when `anchor` evaluates to `true`, and continues using the values accumulated since the previous reset when `anchor` is `false`.
isCumulative (simple bool) : If `true`, `source` values are accumulated until the next time `anchor` is `true`. Optional. The default is `true`.
Returns: (float) The average of the source series at the specified time difference.
David Varadi Intermediate OscillatorThe David Varadi Intermediate Oscillator (DVI) is a composite momentum oscillator designed to generate trading signals based on two key factors: the magnitude of returns over different time windows and the stretch, which measures the relative number of up versus down days. By combining these factors, the DVI aims to provide a reliable and objective assessment of market trends and momentum.
Methodology:
To calculate the DVI, a specific formula is applied. The magnitude component involves averaging smoothed returns over various lengths, weighted according to user-defined parameters. This calculation helps determine the magnitude of price changes. The stretch component follows a similar process, averaging smoothed returns over different lengths to gauge market momentum. Users have the flexibility to adjust the weights and lengths to suit their trading preferences and styles.
Utility:
The DVI offers versatility in its applications. It can be used for both momentum trading and trend analysis due to its smooth and consistent signals. Unlike some other oscillators, the DVI provides longer and uncorrelated signals, allowing traders to effectively combine trend-following and mean-reversion strategies. For example, the DVI is adept at identifying overbought levels above the 200-day moving average, serving as a useful tool for determining exit points during price strength and even potential shorting opportunities. Traders can develop simple trading systems based on the DVI, buying above the 200-day moving average and selling when the DVI exceeds a specified threshold. Conversely, they can consider short positions below the 200-day moving average and cover when the DVI falls below a specific threshold. The DVI's objective approach to analyzing market momentum makes it a valuable resource for traders seeking to identify trading opportunities.
Key Features:
Bar coloring: based on Trend, Extremeties or Reversions
Reversions: Potential reversal points marked with triangles above\below oscillator
Extremity Hues: Highlighting oxcillator reaching traditional OB\OS levels
Example Charts:
bar viewBar view is a simple script to show other higher time frame windows while you are focusing on lower time for precise decision making.
For example you are currently operating at 1 minute time frame and you want to see other bars on higher time frames e.g. 5 minute, 15 minutes etc.
Feel free to add multiple bar view to see different time frames.
Hui-Heubel Liquidity RatioThe Hui-Heubel Liquidity Ratio (lhh) is a measurement of market resiliency and liquidity. Higher values indicate a more liquid and resilient market, lower values indicate a more fragile market susceptible to volatile moves. It does not work on all tickers (for example, if something does not report volume).
Generally, you will see lhh rise when stocks sell off and fall when they are bought. Occasionally you will see scenarios where price will go up while lhh does as well, often this is a symptom of short covering.
Includes two configurable SMAs and a configurable lookback window.
Buy / Sell Fractal Algorithm with SL Line GenerationThis algorithm is designed for usage across indices.
How it works?
The algorithm uses a variation of fractals, momentum, RSI and LRSI to determine a trends direction.
The Relative Strength Index (RSI) is a momentum-based oscillator used to measure the speed (velocity) and change (magnitude) of directional price movements. It provides a visual means to monitor both the current and historical strength and weakness of a particular market. The strength or weakness is based on closing prices over the duration of a specified trading period, creating a reliable metric of price and momentum changes
Momentum in trading refers to the direction and magnitude of price. Momentum plays a key role in assessing trend strength, and it is important to know when a trend is slowing down. Less momentum does not always lead to a reversal, but it does signal that something is changing, and the trend may consolidate or reverse
Fractals are patterns within price changes which are repeated across thousands of bars. Examples of fractals include the golden ratio, PHI and the spirals of the milk way. They are quite literally a universal concept.
Basics of usage:
When a bullish trend is detected; the algorithm will generate a green "SL Line" at a calculated point, which can be interpreted as an invalidation line.
If the price goes below this line, the bullish trend is invalidated. So long as it holds, the bullish trend is true until the next detection change.
When a bearish trend is detected; the algorithm will generate a red "SL Line", at a calculated point, which can be interpreted as an invalidation line.
If the prices goes above this line, the bearish trend is invalidated. So long as it holds, the bearish trend is true until the next detection change.
When a given trend is invalidated, the SL Line turns yellow and you enter a "pause zone", where neither a bearish nor bullish trend is calculated.
This resets itself on the next trend detection.
Additional information:
I have coded my own backtest to this algorithm, along with plotting the profit / loss of each generated trade.
The profit is calculated by the difference between the open bar of the trade after a long ( or short ) and the following trade.
If we are calculating a short, the resulting value is then multiplied by -1 to get a positive integer.
For calculating a loss we take the value of the open bar of the trade that generates a long, and take the difference between this and the SL line, and similarly for short positions. The code assumes the user is placing their SL at the indicated line.
Within the input settings there are a few customisation options:
Alpha & Fractal Energy Length & Source - Should not be changed.
Highly bands crossover? - Has no visible effect whether on or off. It refers to the fractal chart which in this iteration is not visible and rather a backend mechanic.
Apply fractal energy? - Should generally be left turned on. This is a noise reduction. Disabling will result in over-trading.
Apply normalization? - Has no impact, is solely used to make the fractal values more human-readable rather than decimal format.
Offset - refers to the offset value of the SL Line generations. This should be set to a value that gives you enough breathing room, and remember to include any spreads! Default is 0.2, written in %
Trading hours - This simply gives a session input for the trading hours you want to trade within, and then colours the background green for that session. Trading 24/7 is never a wise strategy, stick to whatever is most optimal for you.
Leverage - Whatever leverage you are using. Default is x20. This will affect the profit / loss calculations accordingly.
Start equity - refers to the equity value you want to backtest with. Some assets will generate NA for this in the backtest label explained later.
Label customisation options.
Note that the backtest label is by default hidden, and appears when you hover over the black label at the current bar. When enabled to visible, it will show a large text label that may cover your chart screen more than you wish.
Alerts -
There are dozens of alert functionalities here; first are the timeframe assignments for each alert, set by default to 2hrs.
These timeframes then affect the asset you select in the corresponding setting.
In total there are 8 additional assets you can set alerts for.
Once you have assigned the timeframe and asset for an alert, you can then check the tick box for that individual alert.
Once done, you set the alert as normal through the tradingview alerts window. Remember to set "alert function calls only"
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Timers:
I have added some functionality for timers to be set, values are in minutes. These work on the exact time of placement. Do not change the extra symbol formula option.
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Note that this backtest is not intended as a replacement for tradingview backtest, nor is there a guarantee that historical results are to be replicated in the future. Trading is inherently risky.
Moonhub Cycle IndexMoonhub Cycle Index is a composite index derived from three popular technical analysis indicators: Moving Average Convergence Divergence (MACD), Schaff Trend Cycle (STC), and Detrended Price Oscillator (DPO). The indicator is designed to help identify potential trends and market sentiment by combining the unique characteristics of each indicator.
Key components of the indicator include:
Input Parameters:
COEMA Length (len_DIema): The length of the Exponential Moving Average (EMA) applied to the Custom Index. Default is set to 9.
COSMA Length (len_DIsma): The length of the Simple Moving Average (SMA) applied to the Custom Index. Default is set to 30.
Indicators:
MACD: A momentum oscillator that shows the relationship between two moving averages of a security's price. It is calculated using the difference between the 12-period and 26-period EMA, and a 9-period EMA (signal line) of the MACD.
STC: A cyclic indicator that identifies cyclical trends in the market. It is calculated using the Stochastic oscillator formula applied to the close, high, and low prices over a 10-period lookback window.
DPO: A price oscillator that eliminates the trend from price data to focus on underlying cycles. It is calculated using a custom function that shifts the price by half the length and subtracts the SMA from the shifted price.
Custom Index: The composite index is calculated by taking the average of the MACD line, STC, and DPO.
COEMA and COSMA: Exponential and Simple Moving Averages applied to the Custom Index using the lengths specified by the input parameters (len_DIema and len_DIsma).
Plots: The Custom Index, COEMA, and COSMA are plotted with different colors and line widths to visualize their interaction and provide insights into potential market trends.
This Custom Index Indicator can be useful for traders who want to analyze the market using a combination of these indicators to make more informed decisions. It can also help identify potential trends and market sentiment by combining the unique characteristics of each indicator.
