Immediate Buy/Sell SignalsThe Immediate Buy/Sell Signals indicator is designed to provide real-time buy and sell signals based on a combination of Simple Moving Averages (SMA) and the Relative Strength Index (RSI). It is intended to help traders identify potential entry and exit points in the market by detecting trend reversals and momentum shifts.
Key Features:
Moving Averages:
The script uses two Simple Moving Averages (SMAs):
A fast SMA (default length: 9) that reacts quickly to price changes.
A slow SMA (default length: 21) that reacts more slowly to price changes.
The crossover of these moving averages is used to identify potential trend reversals.
Relative Strength Index (RSI):
The RSI (default length: 14) is used to measure momentum and identify overbought or oversold conditions.
The script ensures that buy signals are only generated when the RSI is not overbought (RSI < 70) and sell signals are only generated when the RSI is not oversold (RSI > 30).
Buy/Sell Signals:
Buy Signal: Triggered when the fast SMA crosses above the slow SMA and the RSI is not overbought. This indicates a potential upward trend with room for further price appreciation.
Sell Signal: Triggered when the fast SMA crosses below the slow SMA and the RSI is not oversold. This indicates a potential downward trend with room for further price depreciation.
Visualization:
The fast and slow SMAs are plotted on the chart for reference.
Buy signals are marked with a green "BUY" label below the price bar.
Sell signals are marked with a red "SELL" label above the price bar.
Alerts:
The script includes alertcondition to trigger real-time alerts when buy or sell signals are detected. Traders can set up these alerts in TradingView to receive notifications.
How It Works:
Buy Signal:
When the fast SMA crosses above the slow SMA and the RSI is below 70, a buy signal is generated. This suggests that the asset is gaining upward momentum and is not overbought.
Sell Signal:
When the fast SMA crosses below the slow SMA and the RSI is above 30, a sell signal is generated. This suggests that the asset is losing upward momentum and is not oversold.
Example:
If the fast SMA (blue line) crosses above the slow SMA (orange line) and the RSI is below 70, a green "BUY" label appears below the price bar, indicating a potential buying opportunity.
If the fast SMA (blue line) crosses below the slow SMA (orange line) and the RSI is above 30, a red "SELL" label appears above the price bar, indicating a potential selling opportunity.
Customization:
Moving Averages:
Adjust the fast_length and slow_length inputs to change the sensitivity of the moving averages.
RSI:
Adjust the rsi_length, overbought, and oversold inputs to fine-tune the momentum conditions.
Alerts:
Use the alertcondition to set up real-time alerts for buy and sell signals.
Use Case:
This script is ideal for traders who want to identify immediate buy and sell opportunities based on trend reversals and momentum shifts.
It can be used in various markets, including stocks, forex, and cryptocurrencies.
Advantages:
Combines trend-following (moving averages) and momentum (RSI) indicators for robust signal generation.
Provides clear visual signals and real-time alerts for timely decision-making.
Highly customizable to suit different trading strategies.
רצועות וערוצים
Bitcoin Log Growth Curve OscillatorThis script presents the oscillator version of the Bitcoin Logarithmic Growth Curve 2024 indicator, offering a new perspective on Bitcoin’s long-term price trajectory.
By transforming the original logarithmic growth curve into an oscillator, this version provides a normalized view of price movements within a fixed range, making it easier to identify overbought and oversold conditions.
For a comprehensive explanation of the mathematical derivation, underlying concepts, and overall development of the Bitcoin Logarithmic Growth Curve, we encourage you to explore our primary script, Bitcoin Logarithmic Growth Curve 2024, available here . This foundational script details the regression-based approach used to model Bitcoin’s long-term price evolution.
Normalization Process
The core principle behind this oscillator lies in the normalization of Bitcoin’s price relative to the upper and lower regression boundaries. By applying Min-Max Normalization, we effectively scale the price into a bounded range, facilitating clearer trend analysis. The normalization follows the formula:
normalized price = (upper regresionline − lower regressionline) / (price − lower regressionline)
This transformation ensures that price movements are always mapped within a fixed range, preventing distortions caused by Bitcoin’s exponential long-term growth. Furthermore, this normalization technique has been applied to each of the confidence interval lines, allowing for a structured and systematic approach to analyzing Bitcoin’s historical and projected price behavior.
By representing the logarithmic growth curve in oscillator form, this indicator helps traders and analysts more effectively gauge Bitcoin’s position within its long-term growth trajectory while identifying potential opportunities based on historical price tendencies.
Buy/Sell Reversal SignalsThe Buy/Sell Reversal Signals indicator is designed to identify potential buy and sell opportunities based on price reversals. It uses a moving average crossover strategy to detect changes in trend direction.
MACD Killer Indicator with SuperTrend and RSIThe "MACD Killer Indicator with SuperTrend and RSI" is a comprehensive trading tool designed for technical analysis on TradingView. This script incorporates three powerful indicators: the MACD (Moving Average Convergence Divergence), SuperTrend, and RSI (Relative Strength Index) to generate buy and sell signals.
MACD is used to determine the momentum of the asset, signaling entry points when the MACD line crosses above the signal line.
The SuperTrend adds a layer of trend detection, ensuring that trades are executed in the direction of the prevailing trend, indicated by the SuperTrend line's color (green for uptrend, red for downtrend).
RSI is employed to filter out overbought conditions, limiting buy signals when RSI is below 73.
This indicator effectively mitigates consecutive signals of the same type, helping traders avoid false entries and exits. The visual elements, including clearly marked buy and sell signals and background color changes, enhance the user experience, making it easier to spot actionable trade opportunities on the charts.
Dan BollingerThis Strategy is using a 3 different Bollinger bands
It gives a signal when the candlestick is outside the bands
Dip Indicator with EMAs and TWAPTwap and Ema crossing with Bands, when price is near low band and cross the Twap line from below we can go for long, opposite is for short. Keep eyes on ema crossing for double confirmation.
Dan The Man BollingerThis is a Bollinger band strategy that use 3 different bands.
It Use the 20 120 and 240 band
It gives you a sell or a buy signal outside the Bollinger bands
Desvio PadrãoEste indicador trabalha com desvio padrão do dia. Baseado em cálculos matemáticos!
by joao laudir
IU Imbalance Trend StrategyIU Imbalance Trend Strategy
The IU Imbalance Trend Strategy is a trend-following strategy that combines order flow imbalance, trend filtering, and RSI-based momentum confirmation to generate long and short trading signals.
User Inputs:
- Imbalance Length (Default: 10) – Defines the lookback period for calculating order flow imbalance.
- Trend Length (Default: 50) – Determines the moving average period for identifying bullish and bearish trends.
- RSI Length (Default: 14) – Sets the period for the Relative Strength Index (RSI) calculation.
How It Works:
1. Order Flow Score: The strategy calculates an imbalance score based on the highest and lowest close prices over a set period, helping to identify potential shifts in market direction.
2. Trend Filter: A dynamic trend filter is applied using a moving average and ATR to detect bullish and bearish market conditions.
3. RSI Confirmation: A momentum filter using RSI ensures trades are taken only when momentum supports the trend.
Long Entry Conditions:
- Order Flow Score is positive (indicating bullish imbalance).
- Price is above the Bull Trend Line (uptrend confirmation).
- RSI is above 50 (momentum supports buying).
- No active long trade (prevents duplicate entries).
Short Entry Conditions:
- Order Flow Score is negative (indicating bearish imbalance).
- Price is below the Bear Trend Line (downtrend confirmation).
- RSI is below 50 (momentum supports selling).
- No active short trade (prevents duplicate entries).
Additional Features:
- Trend Bands: Visual representation of bullish and bearish trend zones.
- Entry Signals: Green and red labels indicate long and short trade opportunities.
- Alerts: Get notified when a long or short entry is triggered.
Peak Reaction Zones [BigBeluga]Peak Reaction Zones is an advanced Smart Money Concept (SMC) indicator that identifies the most recent swing high and swing low zones, helping traders determine premium and discount areas for optimal trade positioning.
🔵 Key Features:
Swing High & Low Zones:
Automatically detects the latest swing high and swing low levels.
Helps traders identify key reaction points where price is likely to respond.
Premium & Discount Concept:
The high zone represents a premium area, where price is overextended and may reverse.
The low zone represents a discount area, where price is undervalued and may bounce.
The midline dynamically marks the equilibrium of the range.
Adjustable Zone Width:
Users can fine-tune the width of the zones to match their trading style.
Wider zones capture broader reaction ranges, while narrower zones focus on precise levels.
Zone Retest Signals:
Blue markers appear when price retests the lower reaction zone, signaling potential support.
Orange markers appear when price retests the upper reaction zone, indicating possible resistance.
Price Labels for Key Levels:
Displays the price value of the swing high, swing low, and midline for quick reference.
Helps traders recognize major reaction points at a glance.
🔵 Usage:
Smart Money Trading: Utilize the premium and discount concept to align trades with institutional order flow.
Zone Reactions: Watch for price tests of reaction zones and use the retest signals to confirm potential reversals.
Midline Confirmation: If price holds above or below the midline, it can indicate directional bias.
Scalping & Swing Trading: Short-term traders can look for zone rejections, while swing traders can use the levels for trend continuation setups.
Peak Reaction Zones is a must-have tool for traders looking to trade with Smart Money Concepts, allowing for precise entries and exits based on key liquidity areas and market structure.
EMA Crossover v.1This TradingView indicator tracks the crossover of two Exponential Moving Averages (EMAs) and provides visual and alert-based signals for buy and sell opportunities. When EMA 1 crosses above EMA 2, the lines and background turn green, indicating a bullish trend. When EMA 1 crosses below EMA 2, they turn red, signaling a bearish trend. The colors and opacity are customizable through the settings.
Moving Average Crossover Strategy v6 liderbsСтратегия на основе пересечения скользящих средних в Pine Script версии 6
Power Law Below is a detailed, line-by-line explanation in English of the Pine Script (TradingView) code. It uses Pine Script v6 syntax.
---
```pine
//@version=6
indicator("Power Law", overlay=true)
```
1. `//@version=6`
- Declares that this script uses Pine Script version 6. It must appear on the very first line.
2. `indicator("Power Law", overlay=true)`
- Defines this script as an indicator named **"Power Law"**.
- `overlay=true` means this indicator is plotted on the main chart (the price chart) rather than in a separate pane.
---
```pine
// Days X-Axis Value
start = time == timestamp(2010, 7, 18, 0, 0)
days = request.security("INDEX:BTCUSD", 'D', ta.barssince(start))
offset = 561 // days between 2009/1/1 and "start"
d = days + offset
```
1. `start = time == timestamp(2010, 7, 18, 0, 0)`
- Checks if the current bar’s `time` equals July 18, 2010 at 00:00. This returns a boolean value (`true` or `false`).
- It’s mainly used together with `ta.barssince(start)` to calculate the number of bars elapsed since this “start” date.
2. `days = request.security("INDEX:BTCUSD", 'D', ta.barssince(start))`
- `request.security()` lets the script request data from another symbol or another timeframe—in this case, `"INDEX:BTCUSD"` on the Daily (`'D'`) timeframe.
- The third argument, `ta.barssince(start)`, is a built-in function in Pine that counts how many bars have passed since `start` was `true`. In this script, it effectively measures how many daily bars have elapsed since July 18, 2010.
- The result is assigned to `days`, indicating “the count of daily bars between July 18, 2010 and the most recent daily bar in the BTC index.”
3. `offset = 561`
- A user-defined number. The comment states it’s the number of days between January 1, 2009, and the “start” date (July 18, 2010). It is used to calibrate or shift the day count.
4. `d = days + offset`
- Adds the offset to `days`, giving a final day-count-like value (`d`) that the script uses later in the power-law calculations.
---
```pine
a = input(-17.668, "Power Law Intercept", group="Power Law Settings")
b = input(5.926, "Power Law Slope", group="Power Law Settings")
```
- These lines define two adjustable parameters `a` and `b` using `input()`, making them editable via the indicator’s settings.
- `a` (the intercept) is labeled “Power Law Intercept.”
- `b` (the slope) is labeled “Power Law Slope.”
- `group="Power Law Settings"` puts them into a named group in the settings dialog.
---
```pine
price_power_law_0 = math.pow(10, a + b*math.log10(d))
price_power_law_1 = math.pow(10, a + b*math.log10(d + 1*365))
price_power_law_2 = math.pow(10, a + b*math.log10(d + 2*365))
price_power_law_3 = math.pow(10, a + b*math.log10(d + 3*365))
price_power_law_4 = math.pow(10, a + b*math.log10(d + 4*365))
price_power_law_5 = math.pow(10, a + b*math.log10(d + 5*365))
```
- These lines each calculate a “power law” price value:
\
- `d` is the base day count.
- `math.log10(...)` takes the base-10 logarithm.
- `a` is the intercept; `b` is the slope in the power-law model.
- Adding `(1*365), (2*365), ...` to `d` suggests forecasts or curves 1 year, 2 years, etc. beyond the baseline.
- `math.pow(10, ... )` is simply 10 raised to the power of `(a + b * log10(...))`.
---
```pine
// Use a valid 6-digit color code (e.g. #FFFFAA) or 8-digit (e.g. #FFFFAA80)
p0 = plot(price_power_law_0, color=#FFFFAA, title="Power Law", linewidth=1)
p1 = plot(price_power_law_1, title="Power Law 1", linewidth=1, color=bar_index % 2 == 0 ? #FFFFAA : #000000)
p2 = plot(price_power_law_2, title="Power Law 2", linewidth=1, color=bar_index % 2 == 0 ? #FFFFAA : #000000)
p3 = plot(price_power_law_3, title="Power Law 3", linewidth=1, color=bar_index % 2 == 0 ? #FFFFAA : #000000)
p4 = plot(price_power_law_4, title="Power Law 4", linewidth=1, color=bar_index % 2 == 0 ? #FFFFAA : #000000)
p5 = plot(price_power_law_5, title="Power Law 5", linewidth=1, color=bar_index % 2 == 0 ? #FFFFAA : #000000)
```
1. The script plots six lines (from `price_power_law_0` to `price_power_law_5`).
2. `color=#FFFFAA`
- A 6-digit hex color (`#RRGGBB`) that sets the line’s color.
3. `color=bar_index % 2 == 0 ? #FFFFAA : #000000`
- A conditional color assignment: if `bar_index % 2 == 0`, the color is `#FFFFAA`, otherwise it is `#000000`. This makes line colors alternate depending on the bar index.
4. `linewidth=1` sets the thickness of each line.
5. `title="Power Law X"` sets each line’s label in the chart’s legend.
---
## How It Works
- The script calculates how many daily bars have passed since July 18, 2010 (plus a manual offset of 561 days).
- It then applies a power-law formula for various offsets (`+ 1*365`, etc.), each representing a different curve.
- Finally, it plots these six curves on the main chart, showing potential price trajectories or “power-law” relationships for Bitcoin’s historical data (taken from `"INDEX:BTCUSD"` on a daily timeframe).
## Important Notes
1. **Color Codes**
- Must be valid 6-digit or 8-digit hex codes (e.g. `#FFFFAA` or `#FFFFAA80`). Otherwise, you’ll get a syntax error.
2. **`request.security()`**
- Fetching data from `"INDEX:BTCUSD"` on a daily timeframe. If your chart is on another symbol or timeframe, the script still references the daily bars from that index, which can lead to alignment differences.
3. **Logarithms**
- Make sure `d` (or `d + n*365`) never becomes zero or negative, otherwise `math.log10()` will fail. If your script tries to log10(0) or a negative number, you’ll get an error.
4. **Conceptual Use**
- This script’s logic is specific to modeling Bitcoin’s price over time using a power-law approach. You can change the `start` date, the offset, or the intercept/slope inputs to adapt the script for different data sources or fitting strategies.
---
**In summary,** this script draws several power-law curves on the chart based on a reference date (July 18, 2010) and an offset, presumably chosen to align with Bitcoin’s historical timeline. By adjusting `a` (the intercept) and `b` (the slope), you can fine-tune how these curves fit the historical data.
RocketScience: Instantaneous BBTrading Three Pushes
The three pushes pattern is a trading strategy used to identify potential trend reversals. It involves observing three consecutive price movements (pushes) in one direction, followed by a reversal. The push starts with an impulse (make sure to know what an impulse is), and is confirmed with a low (bullish) testing the median or lower. The pattern is often seen on chart trading and can be applied to various markets, including stocks, forex, and commodities. Look at the arrows. The first push is confirmed by the lows at the median or lower...we count one. The second push extended, and then retraced to the median. This last third push is waiting for a retracement. At this point walk the band. Walking a band is waiting for the price to reach the median...to not exit prematurely.
To trade the three pushes pattern, traders should:
Identify the three pushes: Look for three consecutive price movements in one direction.
Confirm the pattern: Ensure the third push is followed by a reversal in price.
Set entry and exit points: Enter the trade after the third push and exit when the price reverses or reaches a predetermined target.
Trading Inner Quarters
Inner quarters theory is a concept used by traders to identify key support and resistance levels based on whole numbers and quarter points. Notice the chart, the upper inner range is resistance...it is bought through and "stood" on during child retracements. The theory suggests that banks, institutions, and countries use these levels to transact with foreign currencies, making them significant areas of price action.
To trade inner quarters, traders should:
Identify the inner quarters: define by the inner color-fill range.
Look for support and resistance: Identify key levels where the price has previously reversed or consolidated...usually a price reaction near the support or resistance.
Use these levels for entry and exit points: Enter trades at support levels and exit at resistance levels, or vice versa.
Dual MA CrossoverThis script does the following:
1. We define the indicator with the name “Dual MA Crossover” and set it to overlay on the chart.
2. Two user inputs are created for the fast and slow moving average lengths, with default values of 10 and 100 respectively.
3. We calculate the simple moving averages (SMA) using the `ta.sma()` function.
4. The moving averages are plotted on the chart using different colors.
5. Crossover and crossunder conditions are detected using `ta.crossover()` and `ta.crossunder()` functions.
6. Labels are created at the crossover points:
• A “BUY” label is placed below the candle when the fast MA crosses above the slow MA.
• A “SELL” label is placed above the candle when the fast MA crosses below the slow MA.
7. The labels are set to have white text as requested, with green background for buy signals and red for sell signals.
ATR/CCI Adaptive Trend BandsATR/CCI Trend Bands is a dynamic trend-following indicator that combines the power of the Average True Range (ATR) and Commodity Channel Index (CCI) to create adaptive support and resistance bands. The indicator plots upper and lower trend bands based on ATR deviations while using CCI to confirm trend direction. The bands visually highlight areas of trend strength and potential reversals, helping traders identify key price zones."
🔹 Key Features:
✅ ATR-Based Trend Bands – Dynamically adjust to market volatility.
✅ CCI Confirmation – Determines whether price is in an uptrend or downtrend.
✅ Color-Coded Trendline – Blue for bullish trends, red for bearish trends.
✅ Shaded Support & Resistance Zones – Red upper bands (resistance), blue lower bands (support).
✅ Customizable Parameters – ATR length, multipliers, and CCI period can be adjusted.
🔹 How to Use:
Trend Trading: Follow the bands to ride trends with confidence.
Breakout Confirmation: Watch for price breaking above/below the bands for potential strong moves.
Reversal Trading: Use the shaded zones as dynamic support and resistance levels.
This indicator is suitable for all timeframes and markets and is designed to be a versatile tool for both trend-followers and breakout traders. 🚀📈
Price-Aligned Trend IndicatorPrice-Aligned Trend IndicatoPrice-Aligned Trend IndicatoPrice-Aligned Trend IndicatoPrice-Aligned Trend Indicato
[COG]StochRSI Zenith📊 StochRSI Zenith
This indicator combines the traditional Stochastic RSI with enhanced visualization features and multi-timeframe analysis capabilities. It's designed to provide traders with a comprehensive view of market conditions through various technical components.
🔑 Key Features:
• Advanced StochRSI Implementation
- Customizable RSI and Stochastic calculation periods
- Multiple moving average type options (SMA, EMA, SMMA, LWMA)
- Adjustable signal line parameters
• Visual Enhancement System
- Dynamic wave effect visualization
- Energy field display for momentum visualization
- Customizable color schemes for bullish and bearish signals
- Adaptive transparency settings
• Multi-Timeframe Analysis
- Higher timeframe confirmation
- Synchronized market structure analysis
- Cross-timeframe signal validation
• Divergence Detection
- Automated bullish and bearish divergence identification
- Customizable lookback period
- Clear visual signals for confirmed divergences
• Signal Generation Framework
- Price action confirmation
- SMA-based trend filtering
- Multiple confirmation levels for reduced noise
- Clear entry signals with customizable display options
📈 Technical Components:
1. Core Oscillator
- Base calculation: 13-period RSI (adjustable)
- Stochastic calculation: 8-period (adjustable)
- Signal lines: 5,3 smoothing (adjustable)
2. Visual Systems
- Wave effect with three layers of visualization
- Energy field display with dynamic intensity
- Reference bands at 20/30/50/70/80 levels
3. Confirmation Mechanisms
- SMA trend filter
- Higher timeframe alignment
- Price action validation
- Divergence confirmation
⚙️ Customization Options:
• Visual Parameters
- Wave effect intensity and speed
- Energy field sensitivity
- Color schemes for bullish/bearish signals
- Signal display preferences
• Technical Parameters
- All core calculation periods
- Moving average types
- Divergence detection settings
- Signal confirmation criteria
• Display Settings
- Chart and indicator signal placement
- SMA line visualization
- Background highlighting options
- Label positioning and size
🔍 Technical Implementation:
The indicator combines several advanced techniques to generate signals. Here are key components with code examples:
1. Core StochRSI Calculation:
// Base RSI calculation
rsi = ta.rsi(close, rsi_length)
// StochRSI transformation
stochRSI = ((ta.highest(rsi, stoch_length) - ta.lowest(rsi, stoch_length)) != 0) ?
(100 * (rsi - ta.lowest(rsi, stoch_length))) /
(ta.highest(rsi, stoch_length) - ta.lowest(rsi, stoch_length)) : 0
2. Signal Generation System:
// Core signal conditions
crossover_buy = crossOver(sk, sd, cross_threshold)
valid_buy_zone = sk < 30 and sd < 30
price_within_sma_bands = close <= sma_high and close >= sma_low
// Enhanced signal generation
if crossover_buy and valid_buy_zone and price_within_sma_bands and htf_allows_long
if is_bullish_candle
long_signal := true
else
awaiting_bull_confirmation := true
3. Multi-Timeframe Analysis:
= request.security(syminfo.tickerid, mtf_period,
)
The HTF filter looks at a higher timeframe (default: 4H) to confirm the trend
It only allows:
Long trades when the higher timeframe is bullish
Short trades when the higher timeframe is bearish
📈 Trading Application Guide:
1. Signal Identification
• Oversold Opportunities (< 30 level)
- Look for bullish crosses of K-line above D-line
- Confirm with higher timeframe alignment
- Wait for price action confirmation (bullish candle)
• Overbought Conditions (> 70 level)
- Watch for bearish crosses of K-line below D-line
- Verify higher timeframe condition
- Confirm with bearish price action
2. Divergence Trading
• Bullish Divergence
- Price makes lower lows while indicator makes higher lows
- Most effective when occurring in oversold territory
- Use with support levels for entry timing
• Bearish Divergence
- Price makes higher highs while indicator shows lower highs
- Most reliable in overbought conditions
- Combine with resistance levels
3. Wave Effect Analysis
• Strong Waves
- Multiple wave lines moving in same direction indicate momentum
- Wider wave spread suggests increased volatility
- Use for trend strength confirmation
• Energy Field
- Higher intensity in trading zones suggests stronger moves
- Use for momentum confirmation
- Watch for energy field convergence with price action
The energy field is like a heat map that shows momentum strength
It gets stronger (more visible) when:
Price is in oversold (<30) or overbought (>70) zones
The indicator lines are moving apart quickly
A strong signal is forming
Think of it as a "strength meter" - the more visible the energy field, the stronger the potential move
4. Risk Management Integration
• Entry Confirmation
- Wait for all signal components to align
- Use higher timeframe for trend direction
- Confirm with price action and SMA positions
• Stop Loss Placement
- Consider placing stops beyond recent swing points
- Use ATR for dynamic stop calculation
- Account for market volatility
5. Position Management
• Partial Profit Taking
- Consider scaling out at overbought/oversold levels
- Use wave effect intensity for exit timing
- Monitor energy field for momentum shifts
• Trade Duration
- Short-term: Use primary signals in trading zones
- Swing trades: Focus on divergence signals
- Position trades: Utilize higher timeframe signals
⚠️ Important Usage Notes:
• Avoid:
- Trading against strong trends
- Relying solely on single signals
- Ignoring higher timeframe context
- Over-leveraging based on signals
Remember: This tool is designed to assist in analysis but should never be used as the sole decision-maker for trades. Always maintain proper risk management and combine with other forms of analysis.
Automatic Linear Trend Channel sandyAutomatic Linear Trend Channel with Signals
This indicator combines linear regression trends with dynamic standard deviation channels to identify market trends and potential trading opportunities.
Key Features:
- Automatically detects trend changes using 100-period moving average
- Creates dynamic channels based on linear regression and standard deviation
- Shows both standard and real-time channel options
- Generates buy/sell signals based on channel breakouts and trend changes
- Customizable standard deviation factor for channel width
- Color-coded channels (green for uptrend, red for downtrend)
Trading Signals:
Buy Signals (Green Triangles):
- Trend changes to bullish
- Price breaks above upper band in downtrend
- Price bounces off lower band in uptrend
Sell Signals (Red Triangles):
- Trend changes to bearish
- Price breaks below lower band in uptrend
- Price bounces off upper band in downtrend
Settings:
- Standard Deviation Factor: Adjusts channel width
- Offset: Fine-tunes signal generation
- Channel Display: Choose between standard, real-time, or both channels
- Show Trade Signals: Toggle signal display
Perfect for swing trading and trend following strategies across any timeframe.
Multi-Coin Zero Lag Scanner - Alex PlayerThis code is to work with the great "Zero Lag Trend Signals (MTF) " - it scans the top 100 coins, (you can select different lists in settings), and tells you if the market is BULLISH or BEARISH and all time frames, allowing you to take entries with the knowledge that the market is not going down. Plus saves time scanning each coin manually. This is FREE, but donations from profits welcome :) 0x1BdBdD3C6cE7Cd8bA32EaE1B784B81b58d22CBA8
