Multi Oscillator OB/OS Signals v3 - Scope TestIndicator Description: Multi Oscillator OB/OS Signals
Purpose:
The "Multi Oscillator OB/OS Signals" indicator is a TradingView tool designed to help traders identify potential market extremes and momentum shifts by monitoring four popular oscillators simultaneously: RSI, Stochastic RSI, CCI, and MACD. Instead of displaying these oscillators in separate panes, this indicator plots distinct visual symbols directly onto the main price chart whenever specific predefined conditions (typically related to overbought/oversold levels or line crossovers) are met for each oscillator. This provides a consolidated view of potential signals from these different technical tools.
How It Works:
The indicator calculates the values for each of the four oscillators based on user-defined settings (like length periods and price sources) and then checks for specific signal conditions on every bar:
Relative Strength Index (RSI):
It monitors the standard RSI value.
When the RSI crosses above the user-defined Overbought (OB) level (e.g., 70), it plots an "Overbought" symbol (like a downward triangle) above that price bar.
When the RSI crosses below the user-defined Oversold (OS) level (e.g., 30), it plots an "Oversold" symbol (like an upward triangle) below that price bar.
Stochastic RSI:
This works similarly to RSI but is based on the Stochastic calculation applied to the RSI value itself (specifically, the %K line of the Stoch RSI).
When the Stoch RSI's %K line crosses above its Overbought level (e.g., 80), it plots its designated OB symbol (like a downward arrow) above the bar.
When the %K line crosses below its Oversold level (e.g., 20), it plots its OS symbol (like an upward arrow) below the bar.
Commodity Channel Index (CCI):
It tracks the CCI value.
When the CCI crosses above its Overbought level (e.g., +100), it plots its OB symbol (like a square) above the bar.
When the CCI crosses below its Oversold level (e.g., -100), it plots its OS symbol (like a square) below the bar.
Moving Average Convergence Divergence (MACD):
Unlike the others, MACD signals here are not based on fixed OB/OS levels.
It identifies when the main MACD line crosses above its Signal line. This is considered a bullish crossover and is indicated by a specific symbol (like an upward label) plotted below the price bar.
It also identifies when the MACD line crosses below its Signal line. This is a bearish crossover, indicated by a different symbol (like a downward label) plotted above the price bar.
Visualization:
All these signals appear as small, distinct shapes directly on the price chart at the bar where the condition occurred. The shapes, their colors, and their position (above or below the bar) are predefined for each signal type to allow for quick visual identification. Note: In the current version of the underlying code, the size of these shapes is fixed (e.g., tiny) and not user-adjustable via the settings.
Configuration:
Users can access the indicator's settings to customize:
The calculation parameters (Length periods, smoothing, price source) for each individual oscillator (RSI, Stoch RSI, CCI, MACD).
The specific Overbought and Oversold threshold levels for RSI, Stoch RSI, and CCI.
The colors associated with each type of signal (OB, OS, Bullish Cross, Bearish Cross).
(Limitation Note: While settings exist to toggle the visibility of signals for each oscillator individually, due to a technical workaround in the current code, these toggles may not actively prevent the shapes from plotting if the underlying condition is met.)
Alerts:
The indicator itself does not automatically generate pop-up alerts. However, it creates the necessary "Alert Conditions" within TradingView's alert system. This means users can manually set up alerts for any of the specific signals generated by the indicator (e.g., "RSI Overbought Enter," "MACD Bullish Crossover"). When creating an alert, the user selects this indicator, chooses the desired condition from the list provided by the script, and configures the alert actions.
Intended Use:
This indicator aims to provide traders with convenient visual cues for potential over-extension in price (via OB/OS signals) or shifts in momentum (via MACD crossovers) based on multiple standard oscillators. These signals are often used as potential indicators for:
Identifying areas where a trend might be exhausted and prone to a pullback or reversal.
Confirming signals generated by other analysis methods or trading strategies.
Noting shifts in short-term momentum.
Disclaimer: As with any technical indicator, the signals generated should not be taken as direct buy or sell recommendations. They are best used in conjunction with other forms of analysis (price action, trend analysis, volume, fundamental analysis, etc.) and within the framework of a well-defined trading plan that includes risk management. Market conditions can change, and indicator signals can sometimes be false or misleading.
Indicatori di ampiezza
Transient Impact Model [ScorsoneEnterprises]This indicator is an implementation of the Transient Impact Model. This tool is designed to show the strength the current trades have on where price goes before they decay.
Here are links to more sophisticated research articles about Transient Impact Models than this post arxiv.org and arxiv.org
The way this tool is supposed to work in a simple way, is when impact is high price is sensitive to past volume, past trades being placed. When impact is low, it moves in a way that is more independent from past volume. In a more sophisticated system, perhaps transient impact should be calculated for each trade that is placed, not just the total volume of a past bar. I didn't do it to ensure parameters exist and aren’t na, as well as to have more iterations for optimization. Note that the value will change as volume does, as soon as a new candle occurs with no volume, the values could be dramatically different.
How it works
There are a few components to this script, so we’ll go into the equation and then the other functions used in this script.
// Transient Impact Model
transient_impact(params, price_change, lkb) =>
alpha = array.get(params, 0)
beta = array.get(params, 1)
lambda_ = array.get(params, 2)
instantaneous = alpha * volume
transient = 0.0
for t = 1 to lkb - 1
if na(volume )
break
transient := transient + beta * volume * math.exp(-lambda_ * t)
predicted_change = instantaneous + transient
math.pow(price_change - predicted_change, 2)
The parameters alpha, beta, and lambda all represent a different real thing.
Alpha (α):
Represents the instantaneous impact coefficient. It quantifies the immediate effect of the current volume on the price change. In the equation, instantaneous = alpha * volume , alpha scales the current bar's volume (volume ) to determine how much of the price change is due to immediate market impact. A larger alpha suggests that current volume has a stronger instantaneous influence on price.
Beta (β):
Represents the transient impact coefficient.It measures the lingering effect of past volumes on the current price change. In the loop calculating transient, beta * volume * math.exp(-lambda_ * t) shows that beta scales the volume from previous bars (volume ), contributing to a decaying effect over time. A higher beta indicates a stronger influence from past volumes, though this effect diminishes with time due to the exponential decay factor.
Lambda (λ):
Represents the decay rate of the transient impact.It controls how quickly the influence of past volumes fades over time in the transient component. In the term math.exp(-lambda_ * t), lambda determines the rate of exponential decay, where t is the time lag (in bars). A larger lambda means the impact of past volumes decays faster, while a smaller lambda implies a longer-lasting effect.
So in full.
The instantaneous term, alpha * volume , captures the immediate price impact from the current volume.
The transient term, sum of beta * volume * math.exp(-lambda_ * t) over the lookback period, models the cumulative, decaying effect of past volumes.
The total predicted_change combines these two components and is compared to the actual price change to compute an error term, math.pow(price_change - predicted_change, 2), which the script minimizes to optimize alpha, beta, and lambda.
Other parts of the script.
Objective function:
This is a wrapper function with a function to minimize so we get the best alpha, beta, and lambda values. In this case it is the Transient Impact Function, not something like a log-likelihood function, helps with efficiency for a high iteration count.
Finite Difference Gradient:
This function calculates the gradient of the objective function we spoke about. The gradient is like a directional derivative. Which is like the direction of the rate of change. Which is like the direction of the slope of a hill, we can go up or down a hill. It nudges around the parameter, and calculates the derivative of the parameter. The array of these nudged around parameters is what is returned after they are optimized.
Minimize:
This is the function that actually has the loop and calls the Finite Difference Gradient each time. Here is where the minimizing happens, how we go down the hill. If we are below a tolerance, we are at the bottom of the hill.
Applied
After an initial guess, we optimize the parameters and get the transient impact value. This number is huge, so we apply a log to it to make it more readable. From here we need some way to tell if the value is low or high. We shouldn’t use standard deviation because returns are not normally distributed, an IQR is similar and better for non normal data. We store past transient impact values in an array, so that way we can see the 25th and 90th percentiles of the data as a rolling value. If the current transient impact is above the 90th percentile, it is notably high. If below the 25th percentile, notably low. All of these values are plotted so we can use it as a tool.
Tool examples:
The idea around it is that when impact is low, there is room for big money to get size quickly and move prices around.
Here we see the price reacting in the IQR Bands. We see multiple examples where the value above the 90th percentile, the red line, corresponds to continuations in the trend, and below the 25th percentile, the purple line, corresponds to reversals. There is no guarantee these tools will be perfect, that is outlined in these situations, however there is clearly a correlation in this tool and trend.
This tool works on any timeframe, daily as we saw before, or lower like a two minute. The bands don’t represent a direction, like bullish or bearish, we need to determine that by interpreting price action. We see at open and at close there are the highest values for the transient impact. This is to be expected as these are the times with the highest volume of the trading day.
This works on futures as well as equities with the same context. Volume can be attributed to volatility as well. In volatile situations, more volatility comes in, and we can perceive it through the transient impact value.
Inputs
Users can enter the lookback value.
No tool is perfect, the transient impact value is also not perfect and should not be followed blindly. It is good to use any tool along with discretion and price action.
Order Flow Hawkes Process [ScorsoneEnterprises]This indicator is an implementation of the Hawkes Process. This tool is designed to show the excitability of the different sides of volume, it is an estimation of bid and ask size per bar. The code for the volume delta is from www.tradingview.com
Here’s a link to a more sophisticated research article about Hawkes Process than this post arxiv.org
This tool is designed to show how excitable the different sides are. Excitability refers to how likely that side is to get more activity. Alan Hawkes made Hawkes Process for seismology. A big earthquake happens, lots of little ones follow until it returns to normal. Same for financial markets, big orders come in, causing a lot of little orders to come. Alpha, Beta, and Lambda parameters are estimated by minimizing a negative log likelihood function.
How it works
There are a few components to this script, so we’ll go into the equation and then the other functions used in this script.
hawkes_process(params, events, lkb) =>
alpha = clamp(array.get(params, 0), 0.01, 1.0)
beta = clamp(array.get(params, 1), 0.1, 10.0)
lambda_0 = clamp(array.get(params, 2), 0.01, 0.3)
intensity = array.new_float(lkb, 0.0)
events_array = array.new_float(lkb, 0.0)
for i = 0 to lkb - 1
array.set(events_array, i, array.get(events, i))
for i = 0 to lkb - 1
sum_decay = 0.0
current_event = array.get(events_array, i)
for j = 0 to i - 1
time_diff = i - j
past_event = array.get(events_array, j)
decay = math.exp(-beta * time_diff)
past_event_val = na(past_event) ? 0 : past_event
sum_decay := sum_decay + (past_event_val * decay)
array.set(intensity, i, lambda_0 + alpha * sum_decay)
intensity
The parameters alpha, beta, and lambda all represent a different real thing.
Alpha (α):
Definition: Alpha represents the excitation factor or the magnitude of the influence that past events have on the future intensity of the process. In simpler terms, it measures how much each event "excites" or triggers additional events. It is constrained between 0.01 and 1.0 (e.g., clamp(array.get(params, 0), 0.01, 1.0)). A higher alpha means past events have a stronger influence on increasing the intensity (likelihood) of future events. Initial value is set to 0.1 in init_params. In the hawkes_process function, alpha scales the contribution of past events to the current intensity via the term alpha * sum_decay.
Beta (β):
Definition: Beta controls the rate of exponential decay of the influence of past events over time. It determines how quickly the effect of a past event fades away. It is constrained between 0.1 and 10.0 (e.g., clamp(array.get(params, 1), 0.1, 10.0)). A higher beta means the influence of past events decays faster, while a lower beta means the influence lingers longer. Initial value is set to 0.1 in init_params. In the hawkes_process function, beta appears in the decay term math.exp(-beta * time_diff), which reduces the impact of past events as the time difference (time_diff) increases.
Lambda_0 (λ₀):
Definition: Lambda_0 is the baseline intensity of the process, representing the rate at which events occur in the absence of any excitation from past events. It’s the "background" rate of the process. It is constrained between 0.01 and 0.3 .A higher lambda_0 means a higher natural frequency of events, even without the influence of past events. Initial value is set to 0.1 in init_params. In the hawkes_process function, lambda_0 sets the minimum intensity level, to which the excitation term (alpha * sum_decay) is added: lambda_0 + alpha * sum_decay
Alpha (α): Strength of event excitation (how much past events boost future events).
Beta (β): Rate of decay of past event influence (how fast the effect fades).
Lambda_0 (λ₀): Baseline event rate (background intensity without excitation).
Other parts of the script.
Clamp
The clamping function is a simple way to make sure parameters don’t grow or shrink too much.
ObjectiveFunction
This function defines the objective function (negative log-likelihood) to minimize during parameter optimization.It returns a float representing the negative log-likelihood (to be minimized).
How It Works:
Calls hawkes_process to compute the intensity array based on current parameters.Iterates over the lookback period:lambda_t: Intensity at time i.event: Event magnitude at time i.Handles na values by replacing them with 0.Computes log-likelihood: event_clean * math.log(math.max(lambda_t_clean, 0.001)) - lambda_t_clean.Ensures lambda_t_clean is at least 0.001 to avoid log(0).Accumulates into log_likelihood.Returns -log_likelihood (negative because the goal is to minimize, not maximize).
It is used in the optimization process to evaluate how well the parameters fit the observed event data.
Finite Difference Gradient:
This function calculates the gradient of the objective function we spoke about. The gradient is like a directional derivative. Which is like the direction of the rate of change. Which is like the direction of the slope of a hill, we can go up or down a hill. It nudges around the parameter, and calculates the derivative of the parameter. The array of these nudged around parameters is what is returned after they are optimized.
Minimize:
This is the function that actually has the loop and calls the Finite Difference Gradient each time. Here is where the minimizing happens, how we go down the hill. If we are below a tolerance, we are at the bottom of the hill.
Applied
After an initial guess the parameters are optimized with a mix of bid and ask levels to prevent some over-fitting for each side while keeping some efficiency. We initialize two different arrays to store the bid and ask sizes. After we optimize the parameters we clamp them for the calculations. We then get the array of intensities from the Hawkes Process of bid and ask and plot them both. When the bids are greater than the ask it represents a bullish scenario where there are likely to be more buy than sell orders, pushing up price.
Tool examples:
The idea is that when the bid side is more excitable it is more likely to see a bullish reaction, when the ask is we see a bearish reaction.
We see that there are a lot of crossovers, and I picked two specific spots. The idea of this isn’t to spot crossovers but avoid chop. The values are either close together or far apart. When they are far, it is a classification for us to look for our own opportunities in, when they are close, it signals the market can’t pick a direction just yet.
The value works just as well on a higher timeframe as on a lower one. Hawkes Process is an estimate, so there is a leading value aspect of it.
The value works on equities as well, here is NASDAQ:TSLA on a lower time frame with a lookback of 5.
Inputs
Users can enter the lookback value and timeframe.
No tool is perfect, the Hawkes Process value is also not perfect and should not be followed blindly. It is good to use any tool along with discretion and price action.
Trend ChannelThis is a Pine Script code written in version 6 for creating a trend channel indicator on TradingView. The indicator is called "Trend Channel" and is credited to "NachomixCrypto." Here's an explanation of what the code does:
Input Parameters
upperMult: Multiplier for the upper channel line, default is 2.0.
lowerMult: Multiplier for the lower channel line, default is -2.0.
useUpperDev: Boolean to activate/deactivate the upper deviation line. Default is false.
useLowerDev: Boolean to activate/deactivate the lower deviation line. Default is false.
showPearson: Boolean to show or hide Pearson's correlation coefficient (R). Default is true.
extendLines: Boolean to extend the channel lines to the right. Default is false.
len: Length (number of bars) to calculate the slope and deviations, default is 50.
src: Source data for the indicator, default is "close".
Line Customization Inputs
baseColor: Color for the base (middle) channel line, default is white.
upperColor: Color for the upper channel line, default is green.
lowerColor: Color for the lower channel line, default is red.
lineThickness: Thickness of the channel lines, default is 1.
Core Functions
calcSlope(): Calculates the slope (rate of change) for the given source over a specified length. It uses the least squares method to calculate the line of best fit.
slope: The rate of change.
average: The average value of the source data.
intercept: The intercept where the line crosses the Y-axis.
calcDev(): Calculates the standard deviation and Pearson's correlation coefficient (R) for the given source. It also computes the upper and lower deviations.
stdDev: Standard deviation, representing how much the data deviates from the mean.
pearsonR: Pearson's correlation coefficient, which measures the linear correlation between the source data and the regression line.
upDev: Upper deviation (difference from the highest value).
dnDev: Lower deviation (difference from the lowest value).
Main Logic
The code then calculates the upper and lower channel lines based on the calculated slope, intercept, and deviations.
Upper and lower start prices are adjusted using the multipliers and deviations, either based on the user inputs or the standard deviation.
Base, upper, and lower lines are drawn on the chart using the calculated prices. These lines represent the trend channel.
Pearson's R Label
The Pearson's R value is displayed as a label on the chart if showPearson is true. It is positioned at the lowest point between the upper and lower lines.
Debugging Plot
A small debugging circle is plotted above the bar to indicate whether the Pearson's R is valid and being calculated.
Final Notes
The trend channel dynamically adjusts based on price action and can be extended for future price movements.
The Pearson's R value gives an indication of how well the regression line fits the price data.
Clean Signal StrategyVersion: Pine Script v6
Type: Trend-Following Strategy
Best Used On: Intraday and Swing Timeframes
Built For: Clear, actionable buy/sell signals with visual lines for entries, targets, and stop loss.
Strategy Overview
The Clean Signal Strategy is designed to provide traders with crystal-clear buy/sell signals while reducing chart noise. It combines reliable indicators like EMA, VWAP, MACD, and ATR to identify high-probability trend-based trades.
The strategy runs in the background, only showing actionable signals when all conditions align, making it beginner-friendly and visually clean.
Indicators Used
EMA 9 & EMA 20 – Determines short-term momentum and trend direction.
VWAP (Volume-Weighted Average Price) – Confirms institutional interest and value area.
MACD Histogram – Confirms momentum direction.
Previous Day’s High/Low – Validates breakout or breakdown conditions.
ATR (14) – Used to set dynamic stop loss and targets.
✅ Buy Signal Criteria
A Buy signal is triggered when:
Price is above EMA 9, EMA 20, and VWAP
MACD Histogram is positive (momentum bullish)
Current price breaks previous day’s high
📍 When a buy signal occurs:
Green candle is painted
Entry, Stop Loss, and Targets 1-3 lines are drawn
Labels appear at the right end of each line
❌ Sell Signal Criteria
A Sell signal is triggered when:
Price is below EMA 9, EMA 20, and VWAP
MACD Histogram is negative (momentum bearish)
Current price breaks previous day’s low
📍 When a sell signal occurs:
Red candle is painted
Entry, Stop Loss, and Targets 1-3 lines are drawn
Labels appear at the right end of each line
⏸️ Neutral/Sideways Zones
If conditions for neither buy nor sell are met, the chart paints gray candles.
This helps traders avoid false entries and stay disciplined.
📋 On-Chart Signal Table
The strategy includes a floating table showing:
Current signal: Buy, Sell, or Neutral
Explanation of the signal based on indicator conditions
Real-time values of all key indicators: EMA9, EMA20, VWAP, MACD Hist, ATR, and previous high/low
This makes it easy to understand why a signal was triggered.
🎯 Target and Stop Loss Logic
Stop Loss: 1× ATR from entry
Target 1: 1× ATR
Target 2: 2× ATR
Target 3: 3× ATR
📌 Highlights
Clear visual lines and labels for easy understanding
No clutter — all signals and analysis are background-powered
Strong risk-reward based on volatility
Best used in trending markets or after consolidation breaks
These levels adjust dynamically based on market volatility, offering flexible trade management.
⚠️ Disclaimer
This strategy is for educational purposes only. Always do your own research before trading or investing.
Daily Time Range HighlightThis Pine Script code creates a TradingView indicator that allows users to highlight a specific time range on a chosen day of the week. It draws a customizable colored box on the price chart, spanning from the session's start to end and covering the highest high and lowest low within that period. Users can enable or disable the highlighting, select the day of the week and time range, and customize the appearance of the highlight box through the indicator's settings.
JACK Pivot Breakout StrategyThis script is quite robust and includes comprehensive logic for pivot breakouts, EMA analysis, and support/resistance breaks.
Apply this script to TradingView or similar charting platforms to visualize pivot points, EMAs, and support/resistance lines.
Adjust the parameters (slPips, tpPips, etc.) to suit your trading style and risk tolerance.
Monitor the generated alerts for actionable trading opportunities.
Multi-TF Fibonacci Divergence StrategyChart Beast 3
The 1 hour and 4 hour time frame must be above the 200 Exponential Moving average for buy trades, and below the 200 Exponential Moving Average for sell trades.
Price on the previous day's daily candle must have closed above the candle before its body and wick for buys and below it for sells. (Example: Today is Monday and price has not yet closed, fridays daily candle closed above the thursday candles body and wick for buys and below it for sells)
Price on The 15 minute time frame must retrace past the 50% level on the fibonacci indicator. Price must not close beyond the 78.6% level on the fibonacci indicator. (on the 5 minute time frame, 15 minute time frame, 1 hour time frame, 4 hour time frame.)
Price on the 15 minute time frame must have retraced to the -27% or -61.8 levels on the fibonacci indicator. (Price must not close beyond the 78.6% fibonacci level on the hourly time frame)
Price on the 15 minute time frame or the 5 minute time frame must show bullish divergence once price has touched the -27% or -61.8% fibonacci level for buys and bearish divergence for sells.
Provide alerts when these conditions have been met. (ONLY in the session of the asset that's being traded)
Do not add lines to the chart, provide an option to turn on and off the past alerts that meet these conditions.
Make it visually appealing on the charts and easy to understand.
RSI Strategy with Backtestingupgraded RSI Strategy with strategy backtesting support included. It places trades when RSI crosses below the oversold level (Buy) and above the overbought level (Sell), and includes adjustable take-profit and stop-loss inputs for more realistic simulation.
ICT & SMC Multi-Timeframe by [KhedrFX]Transform your trading experience with the ICT & SMC Multi-Timeframe by indicator. This innovative tool is designed for traders who want to harness the power of multi-timeframe analysis, enabling them to make informed trading decisions based on key market insights. By integrating concepts from the Inner Circle Trader (ICT) and Smart Money Concepts (SMC), this indicator provides a comprehensive view of market dynamics, helping you identify potential trading opportunities with precision.
Key Features
- Multi-Timeframe Analysis: Effortlessly switch between various timeframes (5 minutes, 15 minutes, 30 minutes, 1 hour, 4 hours, daily, and weekly) to capture the full spectrum of market movements.
- High and Low Levels: Automatically calculates and displays the highest and lowest price levels over the last 20 bars, highlighting critical support and resistance zones.
- Market Structure Visualization: Identifies the last swing high and swing low, allowing you to recognize current market trends and potential reversal points.
- Order Block Detection: Detects significant order blocks, pinpointing areas of strong buying or selling pressure that can indicate potential market reversals.
- Custom Alerts: Set alerts for when the price crosses above or below identified order block levels, enabling you to act swiftly on trading opportunities.
How to Use the Indicator
1. Add the Indicator to Your Chart
- Open TradingView.
- Click on the "Indicators" button at the top of the screen.
- Search for "ICT & SMC Multi-Timeframe by " in the search bar.
- Click on the indicator to add it to your chart.
2. Select Your Timeframe
- Use the dropdown menu to choose your preferred timeframe (5, 15, 30, 60, 240, D, W) for analysis.
3. Interpret the Signals
- High Level (Green Line): Represents the highest price level over the last 20 bars, acting as a potential resistance level.
- Low Level (Red Line): Represents the lowest price level over the last 20 bars, acting as a potential support level.
- Last Swing High (Blue Cross): Indicates the most recent significant high, useful for identifying potential reversal points.
- Last Swing Low (Orange Cross): Indicates the most recent significant low, providing insight into market structure.
- Order Block High (Purple Line): Marks the upper boundary of a detected order block, suggesting potential selling pressure.
- Order Block Low (Yellow Line): Marks the lower boundary of a detected order block, indicating potential buying pressure.
4. Set Alerts
- Utilize the alert conditions to receive notifications when the price crosses above or below the order block levels, allowing you to stay informed about potential trading opportunities.
5. Implement Risk Management
- Always use proper risk management techniques. Consider setting stop-loss orders based on the identified swing highs and lows or the order block levels to protect your capital.
Conclusion
The ICT & SMC Multi-Timeframe by indicator is an essential tool for traders looking to enhance their market analysis and decision-making process. By leveraging multi-timeframe insights, market structure visualization, and order block detection, you can navigate the complexities of the market with confidence. Start using this powerful indicator today and take your trading to the next level.
⚠️ Trade Responsibly
This tool helps you analyze the market, but it’s not a guarantee of profits. Always do your own research, manage risk, and trade with caution.
Shan AlertsKey Features:
ATR-Based Trailing Stop:
Uses Average True Range (ATR) to determine stop distance
Adjustable multiplier (1.0 by default) for sensitivity
Configurable ATR period (10 by default)
Flexible Price Source:
Can use either regular candles or Heikin-Ashi candles
Toggle with the "Use Heikin-Ashi Candles" input
Visual Elements:
Plots the trailing stop line in orange
Shows BUY/SELL labels (configurable)
Colors bars green/red based on position
Trading Signals:
Generates BUY signals when price crosses above the trailing stop
Generates SELL signals when price crosses below the trailing stop
Includes alert conditions for both signals
Debug Information:
Shows current stop value and position on the last bar
Forex Majors - Stochastic Signals‘How will the price change and where will the market go next?’ - is a question that all traders and long-term investors are concerned about. Many spend years trying different trading approaches and only lose time and money. The author offers his own analytical method VPA, with the help of which you will be able to confidently predict the market direction, and your decisions to buy or sell will be based on logic and analysis of the price-volume relationship.
Translated with DeepL.com (free version)
Moving Average ExponentialICHI+EmA
You can change the length of the EMA as it is suitable for you
And also you change the numbers of ichi for your own stratagy this indicator is mixture of these two hope you enjoy it
Highs/Lows des Sessions - Paris TimeThis indicator represents the different sessions (London, NY and Asia), at french hours, on the index market.
Highs/Lows des Sessions - Paris TimeThis indicator represents the different sessions of the indexes (S&P and NASDAQ), including Asian, London and New-York at french hour, Paris.
Sahid Strategy v2This script identifies potential buy/sell signals using:
Pivot Points - Detects swing highs/lows (price reversals)
Confirmation Filters - Reduces false signals using:
RSI (momentum)
Moving Average (trend direction)
Optional MACD (trend confirmation)
Key Features
Signal Type Trigger Conditions
BUY - Price makes a swing low (pivot)
Copy
- RSI ≤ 30 (oversold)
- Price above trend MA
- MACD bullish (optional) |
| SELL | - Price makes a swing high (pivot)
- RSI ≥ 70 (overbought)
- Price below trend MA
- MACD bearish (optional) |
Visual Signals
Green "BUY" labels below price bars
Red "SELL" labels above price bars
Purple trend line (20-period EMA/SMA)
Orange/blue circles showing raw pivot points
Optional Tools
Debug Table (top-right): Shows real-time:
RSI value
Price vs MA position
MACD status
Alerts - Triggers audible/visual notifications
Customization
Adjust in settings:
Pivot sensitivity (left/right bars)
RSI levels (30/70 by default)
MA type/length (20-period EMA/SMA)
Toggle MACD filter on/off
Best For: Swing trading in trending markets (1H-4H timeframes). Signals appear faster than classic pivot strategies but still require confirmation from other analysis tools.
TRIX Strategy)trix strategy with rsi
this is a winning strategy if used with good setting can get 140 pesent roi per year
this is true i have done that with this strategy jast play with the setting to get the best result
EMA Crossover 9/21 📈 **EMA Crossover Signal Line**
Created by **Ahmet AKSOY (tugeday)**
This indicator visualizes the crossover between two EMAs using a single dynamic-colored line.
✅ **How it works:**
- The script calculates two EMAs: a short-period EMA and a long-period EMA.
- Only the **short EMA line** is displayed on the chart.
- When the short EMA **crosses above** the long EMA (bullish crossover), the line color turns **green**.
- When the short EMA **crosses below** the long EMA (bearish crossover), the line color turns **red**.
- The line color remains based on the last crossover signal.
🎛️ **Customizable Inputs:**
- Short EMA period (default: 9)
- Long EMA period (default: 21)
All EMA periods can be adjusted from the settings panel, allowing traders to fine-tune the indicator to match their strategy.
Simple, clean, and effective.
Developed by **Ahmet AKSOY (tugeday)** — enjoy and trade smart!
BTC Trading RobotOverview
This Pine Script strategy is designed for trading Bitcoin (BTC) by placing pending orders (BuyStop and SellStop) based on local price extremes. The script also implements a trailing stop mechanism to protect profits once a position becomes sufficiently profitable.
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Inputs and Parameter Setup
1. Trading Profile:
o The strategy is set up specifically for BTC trading.
o The systemType input is set to 1, which means the strategy will calculate trade parameters using the BTC-specific inputs.
2. Common Trading Inputs:
o Risk Parameters: Although RiskPercent is defined, its actual use (e.g., for position sizing) isn’t implemented in this version.
o Trading Hours Filter:
SHInput and EHInput let you restrict trading to a specific hour range. If these are set (non-zero), orders will only be placed during the allowed hours.
3. BTC-Specific Inputs:
o Take Profit (TP) and Stop Loss (SL) Percentages:
TPasPctBTC and SLasPctBTC are used to determine the TP and SL levels as a percentage of the current price.
o Trailing Stop Parameters:
TSLasPctofTPBTC and TSLTgrasPctofTPBTC determine when and by how much a trailing stop is applied, again as percentages of the TP.
4. Other Parameters:
o BarsN is used to define the window (number of bars) over which the local high and low are calculated.
o OrderDistPoints acts as a buffer to prevent the entry orders from being triggered too early.
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Trade Parameter Calculation
• Price Reference:
o The strategy uses the current closing price as the reference for calculations.
• Calculation of TP and SL Levels:
o If the systemType is set to BTC (value 1), then:
Take Profit Points (Tppoints) are calculated by multiplying the current price by TPasPctBTC.
Stop Loss Points (Slpoints) are calculated similarly using SLasPctBTC.
A buffer (OrderDistPoints) is set to half of the take profit points.
Trailing Stop Levels:
TslPoints is calculated as a fraction of the TP (using TSLTgrasPctofTPBTC).
TslTriggerPoints is similarly determined, which sets the profit level at which the trailing stop will start to activate.
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Time Filtering
• Session Control:
o The current hour is compared against SHInput (start hour) and EHInput (end hour).
o If the current time falls outside the allowed window, the script will not place any new orders.
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Entry Orders
• Local Price Extremes:
o The strategy calculates a local high and local low using a window of BarsN * 2 + 1 bars.
• Placing Stop Orders:
o BuyStop Order:
A long entry is triggered if the current price is less than the local high minus the order distance buffer.
The BuyStop order is set to trigger at the level of the local high.
o SellStop Order:
A short entry is triggered if the current price is greater than the local low plus the order distance buffer.
The SellStop order is set to trigger at the level of the local low.
Note: Orders are only placed if there is no current open position and if the session conditions are met.
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Trailing Stop Logic
Once a position is open, the strategy monitors profit levels to protect gains:
• For Long Positions:
o The script calculates the profit as the difference between the current price and the average entry price.
o If this profit exceeds the TslTriggerPoints threshold, a trailing stop is applied by placing an exit order.
o The stop price is set at a distance below the current price, while a limit (profit target) is also defined.
• For Short Positions:
o The profit is calculated as the difference between the average entry price and the current price.
o A similar trailing stop exit is applied if the profit exceeds the trigger threshold.
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Summary
In essence, this strategy works by:
• Defining entry levels based on recent local highs and lows.
• Placing pending stop orders to enter the market when those levels are breached.
• Filtering orders by time, ensuring trades are only taken during specified hours.
• Implementing a trailing stop mechanism to secure profits once the trade moves favorably.
This approach is designed to automate BTC trading based on price action and dynamic risk management, although further enhancements (like dynamic position sizing based on RiskPercent) could be added for a more complete risk management system.
TREND and ZL FLOWThis PineScript combines two technical indicators—T3 Slow Trend Histogram and Zero Lag Moving Average to analyze market trends and potential reversals.
Giving credit to original authors of their original indicators: RedKTrader and Bjorgum
I have combined these into one indicator showing when trend is best to be trading...
When all lines are showing Green you are in a buying pressure market.
When all are lines are showing Red then you are in a selling pressure market.
T3 Slow Trend Histogram (Bjorgum):
A smoothed moving average (T3) is calculated using a recursive EMA (Exponential Moving Average) process with a length of 8 and a smoothing factor (b = 0.7). Six layers of EMAs are computed (xe1 to xe6) and combined with weighted coefficients (c1 to c4) to generate the final T3 value (nT3Average).
The histogram visually represents the T3’s momentum: green bars indicate upward momentum (T3 rising) and red bars signal downward momentum (T3 falling). This helps identify trend strength and direction.
ZL Flow (Zero-Lag Moving Average RedKTrader ):
A double-smoothed WMA (Weighted Moving Average) with a length of 9 and smoothing factor of 2 is applied to the price. The final ZLMA line is derived using a formula (2 * priceMA - ta.wma(priceMA, length)) to reduce lag.
The ZLMA line changes color (bright green for upward, red for downward) based on its direction.
Together, the T3 histogram tracks trend dynamics, while the ZL Flow provides early reversal signals, offering a dual approach to trend analysis and trade timing. The script is ideal for traders seeking confirmation of momentum shifts and zero-lag responsiveness.
5M Pro Toolkit Ultimate by dnnfafx🎯 Script Purpose
This script is a multi-indicator trading toolkit designed for use on the 5-minute chart (5M timeframe). It combines trend filters, momentum indicators, volume spikes, support/resistance levels, and candlestick pattern detection to assist in technical analysis and provide potential confluence signals for entries.
📌 Main Components
1. User Inputs
Allows users to customize key indicator settings:
EMA lengths (Short and Long)
RSI period
MACD parameters (fast, slow, signal)
Volume spike multiplier
Pivot left/right bar count
2. Trend Filter: EMA 50 and EMA 200
pine
Salin
Edit
emaShort = ta.ema(close, emaShortLen)
emaLong = ta.ema(close, emaLongLen)
Determines the trend direction.
EMA 50 (orange) and EMA 200 (blue) are plotted on the main chart.
3. RSI (Relative Strength Index)
pine
Salin
Edit
rsi = ta.rsi(close, rsiLen)
Measures price momentum.
Horizontal lines at 70 (Overbought) and 30 (Oversold) for quick reference.
4. MACD Histogram
pine
Salin
Edit
= ta.macd(close, macdFast, macdSlow, macdSignal)
macdHist = macdLine - signalLine
Plots the MACD histogram as vertical bars.
Useful for identifying trend strength and potential reversals.
5. Volume Spike Detection
pine
Salin
Edit
volSpike = volume > volMA * volMultiplier
Detects significant volume surges compared to the 20-period volume average.
Displays a red triangle below the candle when a spike occurs.
6. Support & Resistance (Pivot High/Low)
pine
Salin
Edit
pivotHigh = ta.pivothigh(high, pivotLeft, pivotRight)
pivotLow = ta.pivotlow(low, pivotLeft, pivotRight)
Automatically detects local highs (resistance) and lows (support) using pivot logic.
Resistance lines in red, Support lines in green.
7. Candlestick Pattern Detection
Identifies four popular patterns:
Bullish Engulfing (green label "Engulf" below the bar)
Bearish Engulfing (red label "Engulf" above the bar)
Hammer (lime triangle)
Shooting Star (fuchsia triangle)
8. Confluence Entry Logic (Incomplete)
pine
Salin
Edit
buyCond = rsi
This section is currently incomplete.
It's likely intended to define a buy condition based on the confluence of RSI, MACD, EMA trend, volume spike, and candlestick patterns.
🧩 Conclusion
This toolkit is an all-in-one solution for intraday 5-minute trading, combining trend, momentum, volume, price action, and pattern recognition. While the entry logic (buyCond) is not yet finished, the structure is well laid out and can serve as the foundation for a manual or automated trading strategy.
