Impulse MACD enhancedThis indicator is designed to provide robust trade entry signals by combining multiple technical filters. Here’s a summary of its key components:
Impulse MACD Calculation:
Uses a Zero-Lag EMA (ZLEMA) based approach to generate a momentum indicator (with a signal line and histogram) that identifies shifts in market momentum.
Simulated Higher Timeframe (HTF) Trend Filter:
Computes an SMA over a multiplied period to simulate a higher timeframe trend. It requires the price to be in line with this broader trend before signaling an entry.
RSI Filter:
Ensures that for bullish entries the RSI is above a set threshold (indicating momentum) and for bearish entries it’s below a threshold.
ADX Filter:
Uses a manually calculated ADX to confirm that the market is in a strong trend (ADX > 30) to reduce false signals in weakly trending or sideways markets.
Volume Filter:
Compares the current volume to a 20‑bar SMA of volume, requiring volume to be significantly higher (by a user-defined percentage) to confirm the strength of the move.
VWAP Confirmation:
Uses the Volume-Weighted Average Price as an extra layer of confirmation: bullish signals require the price to be above VWAP, bearish signals below.
Optional Long-Term & Short-Term MA Filters:
These filters can be enabled to ensure the price is trading above (or below) longer-term and shorter-term moving averages, further aligning the trade with the prevailing trend.
ATR Volatility Filter:
Checks that volatility (as measured by the ATR relative to price) is below a maximum threshold, which helps avoid taking trades in overly volatile conditions.
Price Action Filter:
Ensures that for a bullish signal the current close is above the highest high over a specified lookback period (and vice versa for bearish), indicating a clear breakout.
Signal Throttling:
Signals are limited to one every 10 bars to prevent excessive trading.
When all these conditions are met, the indicator outputs an entry signal for either a bullish or bearish trade.
This multi-filter approach aims to increase win rate by reducing false signals and aligning trades with strong, confirmed trends while filtering out noise.
Cerca negli script per "entry"
3 Red / 3 Green Strategy with Volatility CheckStrategy Name: 3 Red / 3 Green Strategy with Volatility Check by AlgoTradeKit
Overview
This long-only strategy is designed for daily bars on NASDAQ (or similar instruments) and combines simple price action with a volatility filter. It “tells it like it is” – enter when the market shows weakness, but only in sufficiently volatile conditions, and exit either on signs of a reversal or after a set number of days.
Entry Conditions
- Price Action :
Enter a long position when there are 3 consecutive red days (each day's close is below its open).
- Volatility Filter :
The entry is allowed only if the current ATR (Average True Range) calculated over the specified ATR Period (default 12) is greater than its 30-day simple moving average. This ensures the market has enough volatility to justify the trade.
Exit Conditions
- Reversal Signal :
Exit the long position when 3 consecutive green days occur (each day's close is above its open), signaling a potential reversal.
- Time Limit :
Regardless of market conditions, any open trade is closed if it reaches the Maximum Trade Duration (default 22 days). This helps limit exposure during stagnant or unfavorable market conditions.
- You can toggle the three-green-day exit if you want to isolate the time-based exit.
Input Parameters
- Maximum Trade Duration (days): Default is 22 days.
- ATR Period: Default is 12.
- Use 3 Green Days Exit: Toggle to enable or disable the three-green-day exit condition.
How It Works
1. Entry: The strategy monitors daily price action for 3 consecutive down days. When this occurs and if the market is volatile enough (current ATR > 30-day ATR average), it opens a long position.
2. Exit: The position is closed if the price action reverses with 3 consecutive up days or if the trade has been open for the maximum allowed duration - i.e. use it on daily chart.
Risk Management
- The built-in maximum trade duration prevents trades from lingering too long in a non-trending or consolidating market.
- The volatility filter helps ensure that trades are only taken when there is sufficient price movement, potentially increasing the odds of a meaningful move.
Disclaimer
This strategy is provided “as is” without any warranties. It is essential to backtest and validate the performance on your specific instrument and market conditions before deploying live capital. Trading involves significant risk, and you should adjust parameters to match your risk tolerance.
Test and tweak this strategy to see if it fits your trading style and market conditions. Happy trading!
Balance of Power for US30 4H [PineIndicators]The Balance of Power (BoP) Strategy is a momentum-based trading system for the US30 index on a 4-hour timeframe. It measures the strength of buyers versus sellers in each candle using the Balance of Power (BoP) indicator and executes trades based on predefined threshold crossovers. The strategy includes dynamic position sizing, adjustable leverage, and visual trade tracking.
⚙️ Core Strategy Mechanics
Positive values indicate buying strength.
Negative values indicate selling strength.
Values close to 1 suggest strong bullish momentum.
Values close to -1 indicate strong bearish pressure.
The strategy uses fixed threshold crossovers to determine trade entries and exits.
📌 Trade Logic
Entry Conditions
Long Entry: When BoP crosses above 0.8, signaling strong buying pressure.
Exit Conditions
Position Close: When BoP crosses below -0.8, indicating a shift to selling pressure.
This threshold-based system filters out low-confidence signals and focuses on high-momentum shifts.
📏 Position Sizing & Leverage
Leverage: Adjustable by the user (default = 5x).
Risk Management: Position size adapts dynamically based on equity fluctuations.
📊 Trade Visualization & History Tracking
Trade Markers:
"Buy" labels appear when a long position is opened.
"Close" labels appear when a position is exited.
Trade History Boxes:
Green for profitable trades.
Red for losing trades.
These elements provide clear visual tracking of past trade execution.
⚡ Usage & Customization
1️⃣ Apply the script to a US30 4H chart in TradingView.
2️⃣ Adjust leverage settings as needed.
3️⃣ Review trade signals and historical performance with visual markers.
4️⃣ Enable backtesting to evaluate past performance.
This strategy is designed for momentum-based trading and is best suited for volatile market conditions.
[SHORT ONLY] ATR Sell the Rip Mean Reversion Strategy█ STRATEGY DESCRIPTION
The "ATR Sell the Rip Mean Reversion Strategy" is a contrarian system that targets overextended price moves on stocks and ETFs. It calculates an ATR‐based trigger level to identify shorting opportunities. When the current close exceeds this smoothed ATR trigger, and if the close is below a 200-period EMA (if enabled), the strategy initiates a short entry, aiming to profit from an anticipated corrective pullback.
█ HOW IS THE ATR SIGNAL BAND CALCULATED?
This strategy computes an ATR-based signal trigger as follows:
Calculate the ATR
The strategy computes the Average True Range (ATR) using a configurable period provided by the user:
atrValue = ta.atr(atrPeriod)
Determine the Threshold
Multiply the ATR by a predefined multiplier and add it to the current close:
atrThreshold = close + atrValue * atrMultInput
Smooth the Threshold
Apply a Simple Moving Average over a specified period to smooth out the threshold, reducing noise:
signalTrigger = ta.sma(atrThreshold, smoothPeriodInput)
█ SIGNAL GENERATION
1. SHORT ENTRY
A Short Signal is triggered when:
The current close is above the smoothed ATR signal trigger.
The trade occurs within the specified trading window (between Start Time and End Time).
If the EMA filter is enabled, the close must also be below the 200-period EMA.
2. EXIT CONDITION
An exit Signal is generated when the current close falls below the previous bar’s low (close < low ), indicating a potential bearish reversal and prompting the strategy to close its short position.
█ ADDITIONAL SETTINGS
ATR Period: The period used to calculate the ATR, allowing for adaptability to different volatility conditions (default is 20).
ATR Multiplier: The multiplier applied to the ATR to determine the raw threshold (default is 1.0).
Smoothing Period: The period over which the raw ATR threshold is smoothed using an SMA (default is 10).
Start Time and End Time: Defines the time window during which trades are allowed.
EMA Filter (Optional): When enabled, short entries are only executed if the current close is below the 200-period EMA, confirming a bearish trend.
█ PERFORMANCE OVERVIEW
This strategy is designed for use on the Daily timeframe, targeting stocks and ETFs by capitalizing on overextended price moves.
It utilizes a dynamic, ATR-based trigger to identify when prices have potentially peaked, setting the stage for a mean reversion short entry.
The optional EMA filter helps align trades with broader market trends, potentially reducing false signals.
Backtesting is recommended to fine-tune the ATR multiplier, smoothing period, and EMA settings to match the volatility and behavior of specific markets.
Crypto Scanner v4This guide explains a version 6 Pine Script that scans a user-provided list of cryptocurrency tokens to identify high probability tradable opportunities using several technical indicators. The script combines trend, momentum, and volume-based analyses to generate potential buying or selling signals, and it displays the results in a neatly formatted table with alerts for trading setups. Below is a detailed walkthrough of the script’s design, how traders can interpret its outputs, and recommendations for optimizing indicator inputs across different timeframes.
## Overview and Key Components
The script is designed to help traders assess multiple tokens by calculating several indicators for each one. The key components include:
- **Input Settings:**
- A comma-separated list of symbols to scan.
- Adjustable parameters for technical indicators such as ADX, RSI, MFI, and a custom Wave Trend indicator.
- Options to enable alerts and set update frequencies.
- **Indicator Calculations:**
- **ADX (Average Directional Index):** Measures trend strength. A value above the provided threshold indicates a strong trend, which is essential for validating momentum before entering a trade.
- **RSI (Relative Strength Index):** Helps determine overbought or oversold conditions. When the RSI is below the oversold level, it may present a buying opportunity, while an overbought condition (not explicitly part of this setup) could suggest selling.
- **MFI (Money Flow Index):** Similar in concept to RSI but incorporates volume, thus assessing buying and selling pressure. Values below the designated oversold threshold indicate potential undervaluation.
- **Wave Trend:** A custom indicator that calculates two components (WT1 and WT2); a crossover where WT1 moves from below to above WT2 (particularly near oversold levels) may signal a reversal and a potential entry point.
- **Scanning and Trading Zone:**
- The script identifies a *bullish setup* when the following conditions are met for a token:
- ADX exceeds the threshold (strong trend).
- Both RSI and MFI are below their oversold levels (indicating potential buying opportunities).
- A Wave Trend crossover confirms near-term reversal dynamics.
- A *trading zone* condition is also defined by specific ranges for ADX, RSI, MFI, and a limited difference between WT1 and WT2. This zone suggests that the token might be in a consolidation phase where even small moves may be significant.
- **Alerts and Table Reporting:**
- A table is generated, with each row corresponding to a token. The table contains columns for the symbol, ADX, RSI, MFI, WT1, WT2, and the trading zone status.
- Visual cues—such as different background colors—highlight tokens with a bullish setup or that are within the trading zone.
- Alerts are issued based on the detection of a bullish setup or entry into a trading zone. These alerts are limited per bar to avoid flooding the trader with notifications.
## How to Interpret the Indicator Outputs
Traders should use the indicator values as guidance, verifying them against their own analysis before making any trading decision. Here’s how to assess each output:
- **ADX:**
- **High values (above threshold):** Indicate strong trends. If other indicators confirm an oversold condition, a trader may consider a long position for a corrective reversal.
- **Low values:** Suggest that the market is not trending strongly, and caution should be taken when considering entry.
- **RSI and MFI:**
- **Below oversold levels:** These conditions are traditionally seen as signals that an asset is undervalued, potentially triggering a bounce.
- **Above typical resistance levels (not explicitly used here):** Would normally caution a trader against entering a long position.
- **Wave Trend (WT1 and WT2):**
- A crossover where WT1 moves upward above WT2 in an oversold environment can signal the beginning of a recovery or reversal, thereby reinforcing buy signals.
- **Trading Zone:**
- Being “in zone” means that the asset’s current values for ADX, RSI, MFI, and the closeness of the Wave Trend lines indicate a period of consolidation. This scenario might be suitable for both short-term scalping or as an early exit indicator, depending on further market analysis.
## Timeframe Optimization Input Table
Traders can optimize indicator inputs depending on the timeframe they use. The following table provides a set of recommended input values for various timeframes. These values are suggestions and should be adjusted based on market conditions and individual trading styles.
Timeframe ADX RSI MFI ADX RSI MFI WT Channel WT Average
5-min 10 10 10 20 30 20 7 15
15-min 12 12 12 22 30 20 9 18
1-hour 14 14 14 25 30 20 10 21
4-hour 16 16 16 27 30 20 12 24
1-day 18 18 18 30 30 20 14 28
Adjust these parameters directly in the script’s input settings to match the selected timeframe. For shorter timeframes (e.g., 5-min or 15-min), the shorter lengths help filter high-frequency noise. For longer timeframes (e.g., 1-day), longer input values may reduce false signals and capture more significant trends.
## Best Practices and Usage Tips
- **Token Limit:**
- Limit the number of tokens scanned to 10 per query line. If you need to scan more tokens, initiate a new query line. This helps manage screen real estate and ensures the table remains legible.
- **Confirming Signals:**
- Use this script as a starting point for identifying high potential trades. Each indicator’s output should be used to confirm your trading decision. Always cross-reference with additional technical analysis tools or market context.
- **Regular Review:**
- Since the script updates the table every few bars (as defined by the update frequency), review the table and alerts regularly. Market conditions change rapidly, so timely decisions are crucial.
## Conclusion
This Pine Script provides a comprehensive approach for scanning multiple cryptocurrencies using a combination of trend strength (ADX), momentum (RSI and MFI), and reversal signals (Wave Trend). By using the provided recommendation table for different timeframes and limiting the tokens to 20 per query line (with a maximum of four query lines), traders can streamline their scanning process and more effectively identify high probability tradable tokens. Ultimately, the outputs should be critically evaluated and combined with additional market research before executing any trades.
Candlesticks Not Touching EMA 3 & EMA 5 ScannerCandlesticks Not Touching EMA 3 & EMA 5 Scanner
Short Title: EMA Scanner
Overview
This indicator scans for candlesticks that do not touch the EMA 3 and EMA 5, highlighting potential trading opportunities where price action is significantly distanced from these moving averages. It identifies momentum-based entries and helps traders spot strong trends.
How It Works
It checks if the candle's high and low are completely above or below both EMAs (3 & 5).
It ensures that the distance between the candle and EMA 5 is at least a user-defined multiple of the candle range.
When a valid candle is detected, a triangle marker appears below (for long trades) or above (for short trades).
Trade Execution Strategy
Entry:
Long Entry → Break of the candle’s high
Short Entry → Break of the candle’s low
Stop Loss:
Long SL → Low of the same candle
Short SL → High of the same candle
Target: EMA 5
Additional Features
✅ Plots EMA 3 (Blue) and EMA 5 (Red) for reference
✅ Marks potential long and short trades with arrows
✅ Detects & plots when Target or Stop Loss is hit
✅ Alerts for valid signals, target hits, and stop loss hits
Best Use Cases
🔹 Suitable for intraday & swing traders looking for momentum-based trades
🔹 Works well in trending markets
🔹 Helps identify mean-reversion & breakout opportunities
🚀 Use this indicator to refine your trading setups & boost your market edge! 🚀
Daily COC Strategy with SHERLOCK WAVESThis indicator implements a unique trading strategy known as the "Daily COC (Candle Over Candle) Strategy" enhanced with "SHERLOCK WAVES" for pattern recognition. It's designed for traders looking to capitalize on specific candlestick formations with a negative risk-reward ratio, with the aim of achieving a high win rate (over 70%) through numerous trading opportunities, despite each trade having a higher risk relative to the reward.
Key Features:
Pattern Recognition: Identifies a setup based on three consecutive candles - a red candle followed by a shooting star, then an entry candle that does not break below the shooting star's low.
Negative Risk/Reward Trade Selection: Focuses on entries where the potential stop loss is greater than the take profit, banking on a high win rate to offset the individual trade's negative risk-reward ratio.
Visual Signals:
Green Label: Marks potential entry points at the high of the candle before the entry.
Green Dot: Indicates a winning trade closure.
Red Dot: Signals a losing trade closure.
Blue Circle: Warns when the current candle is within 2% of breaking above the previous candle's high, suggesting a potential setup is developing.
Green Circle: Plots the take profit level.
Red Circle: Plots the stop loss level.
Dynamic Statistics: A live updating label showing the number of trades, wins, losses, open trades, current account balance, and win percentage.
Customizable Parameters:
Risk % per Trade: Adjust the percentage of your account balance you're willing to risk on each trade.
Initial Account Balance: Set your starting balance for tracking performance.
Start Date for Strategy: Define when the strategy should start calculating from, allowing for backtesting.
Alerts:
An alert condition is set for when a potential trade setup is developing, helping traders prepare for entries.
Usage Tips:
This strategy is predicated on the idea that a high win rate can compensate for the negative risk-reward ratio of individual trades. It might not suit all market conditions or traders' risk profiles.
Use this strategy in conjunction with other analysis methods to validate trade setups.
Note: Always backtest thoroughly before applying to live markets. Consider this tool as part of a broader trading strategy, not a standalone solution. Monitor your win rate and adjust your risk management accordingly to ensure the strategy remains profitable over time.
This description now correctly explains the purpose behind the negative risk-reward ratio in the context of your trading strategy.
4 EMA & MACDThe indicator that combines Moving Average and MACD into one is very useful for providing a more complete picture of the market. Here's how it works:
Moving Average (MA): This is a trend indicator that smooths the price to show the dominant trend direction. MA helps traders determine whether the market is in an uptrend, downtrend, or sideways. For example, if the price is above the MA, it might indicate an uptrend, while if the price is below the MA, it might indicate a downtrend.
MACD (Moving Average Convergence Divergence): MACD measures market momentum and can provide entry and exit signals based on the difference between two moving averages (fast MA and slow MA). A buy signal occurs when the MACD crosses above the signal line, and a sell signal occurs when the MACD crosses below the signal line.
Combining both gives traders a more complete view:
MA provides an overview of the larger trend direction.
MACD helps identify moments when momentum supports a position for entering or exiting.
Common usage:
Entry: If the price is above the Moving Average (uptrend) and the MACD shows a buy signal (for example, MACD crossing above the signal line), it can be a signal to buy.
Exit: If the price starts moving below the MA and the MACD shows a sell signal, it can be a signal to sell or exit the position.
There is an indicator called MACD + Moving Average Cross, which combines both elements, providing stronger signals and making it easier to follow the market.
Fibonacci Extension Strt StrategyCore Logic and Steps:
Weekly Trend Identification:
Find the last significant Higher High (HH) and Lower Low (LL) or vice-versa on the Weekly timeframe.
Determine if it's an uptrend (HH followed by LL) or a downtrend (LL followed by HH).
Plot a Fibonacci Extension (or Retracement in reverse order) from the swing point determined to the other significant swing point.
Weekly Retracement Levels:
Display horizontal lines at the 0.236, 0.382, and 0.5 Fibonacci levels from the weekly extension.
Monitor price action on these levels.
Daily Confirmation:
When price hits the Fib levels, examine the Daily chart.
Look for a rejection wick (indicating the pull back is ending) on the identified weekly retracement levels.
Confirm that the price is indeed starting to continue in the direction of the original weekly trend.
Four-Hour Entry:
On the 4H timeframe, plot a new Fib Extension in the opposite direction of the weekly.
If it's an uptrend, the Fib is plotted from last swing low to its swing high. If the weekly trend was bearish the Fib will be plotted from last swing high to the swing low.
Generate an entry when price breaks the high of that candle.
Trade Management:
Entry is on the breakout of the current candle.
Stop Loss: Place the stop loss below the wick of the breakout candle.
Take Profit 1: Close 50% of the position at the 0.5 Fibonacci level. Move the stop loss to breakeven on this position.
Take Profit 2: Close another 25% of the position at the 0.236 Fib level.
Trailing Take Profit: Keep the last 25% open, using a trailing stop loss. (You'll need to define the logic for the trailing stop, e.g., trailing stop using the last high/low)
How to Use in TradingView:
Open a TradingView Chart.
Click on "Pine Editor" at the bottom.
Copy and paste the corrected Pine Script code.
Click "Add to Chart".
The indicator should now be displayed on your chart.
3 Down, 3 Up Strategy█ STRATEGY DESCRIPTION
The "3 Down, 3 Up Strategy" is a mean-reversion strategy designed to capitalize on short-term price reversals. It enters a long position after consecutive bearish closes and exits after consecutive bullish closes. This strategy is NOT optimized and can be used on any timeframes.
█ WHAT ARE CONSECUTIVE DOWN/UP CLOSES?
- Consecutive Down Closes: A sequence of trading bars where each close is lower than the previous close.
- Consecutive Up Closes: A sequence of trading bars where each close is higher than the previous close.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The price closes lower than the previous close for Consecutive Down Closes for Entry (default: 3) consecutive bars.
The signal occurs within the specified time window (between Start Time and End Time).
If enabled, the close price must also be above the 200-period EMA (Exponential Moving Average).
2. EXIT CONDITION
A Sell Signal is generated when the price closes higher than the previous close for Consecutive Up Closes for Exit (default: 3) consecutive bars.
█ ADDITIONAL SETTINGS
Consecutive Down Closes for Entry: Number of consecutive lower closes required to trigger a buy. Default = 3.
Consecutive Up Closes for Exit: Number of consecutive higher closes required to exit. Default = 3.
EMA Filter: Optional 200-period EMA filter to confirm long entries in bullish trends. Default = disabled.
Start Time and End Time: Restrict trading to specific dates (default: 2014-2099).
█ PERFORMANCE OVERVIEW
Designed for volatile markets with frequent short-term reversals.
Performs best when price oscillates between clear support/resistance levels.
The EMA filter improves reliability in trending markets but may reduce trade frequency.
Backtest to optimize consecutive close thresholds and EMA period for specific instruments.
3 Candle AlertThis is a test for integration using a webhook. I am publishing it so I can share it. Ultimately, this is what we want to do:
1. Trade Entry Rules:
Wait until at least the 3rd bar of the day (15 minutes after market open) before entering the first trade.
Order of Priority for Entry:
Look for two consecutive volume bars of the same color (the second bar must have higher volume than the first).
Look for a “price push” beyond the high or low of the day (as determined in the first 15 minutes).
2. Trading Direction:
If the volume bars are RED, I take a Long Position.
If the volume bars are GREEN, I take a Short Position.
ENIGMA Signals with Retests Select higher Time FrameENIGMA Signals with Retests – Script Description
The "ENIGMA Signals with Retests" script is a unique indicator designed for traders who prefer precision trading based on price action retests of key levels derived from higher timeframes. This tool is ideal for those employing multi-timeframe analysis strategies, helping them detect high-probability trade entries when the price interacts with significant support and resistance levels.
What Does This Script Do?
This indicator identifies key levels from a higher timeframe selected by the user (e.g., 4-hour or daily), then tracks price action on lower timeframes to provide actionable buy and sell signals when the price retests these levels. It visually plots the key levels on the chart and triggers alerts for potential trade opportunities when conditions are met.
How It Works
Key Level Detection:
The script uses custom functions to detect recent swing highs and swing lows on the selected higher timeframe (such as 4H or Daily). These levels represent potential areas of support and resistance where price reactions are likely to occur.
Multi-Timeframe Analysis:
The indicator leverages the request.security() function to retrieve price data from the user-defined higher timeframe and plots horizontal lines on the chart for the most recent swing highs and lows.
Retest-Based Signals:
Once the key levels are plotted, the script continuously monitors the price on the lower timeframe:
A Buy Signal is triggered when the price closes below a key high level and then moves back above it, indicating a potential bullish retest.
A Sell Signal is triggered when the price closes above a key low level and then moves back below it, indicating a potential bearish retest.
These retest signals are displayed as green and red arrows on the chart, helping traders identify optimal entry points.
Alerts for Retests:
The script includes built-in alert conditions that notify traders when a valid retest signal occurs. This allows traders to react promptly without constantly monitoring the chart.
How to Use the Script
Select Your Key Timeframe:
From the input settings, choose a higher timeframe that suits your trading style (e.g., 4H for intraday trading or Daily for swing trading).
Adjust Visual Preferences:
Customize the line style (solid, dashed, or dotted) and length of the plotted levels.
Toggle labels for the levels on or off as per your preference.
Trade Execution:
Once a retest signal appears on the lower timeframe, consider entering a trade in the direction of the signal. The buy signal suggests a potential long entry, while the sell signal indicates a potential short entry.
Set Alerts:
Use the alert conditions provided to get notified whenever a valid retest occurs. This helps in reducing screen time and improving trading efficiency.
Underlying Concepts
This script is grounded in the principles of support and resistance, retests, and breakout trading. By focusing on multi-timeframe key levels, it aligns with widely used trading concepts like:
Breakout and Retest: Entering trades after a confirmed breakout and successful retest of a significant level.
Swing Highs and Lows: Recognizing swing points to identify strong price reaction zones.
Multi-Timeframe Confluence: Enhancing trade probability by ensuring that the signals on lower timeframes correspond with key levels from higher timeframes.
Why This Script Is Unique
Unlike many generic trend-following or scalping indicators, "ENIGMA Signals with Retests" offers:
Precision Signals: It only provides signals when specific retest conditions are met, reducing false signals and noise.
Multi-Timeframe Customization: Users can tailor the higher timeframe to their strategy, making it versatile for various trading styles.
Alert Functionality: Alerts are integrated, allowing traders to stay updated without constantly monitoring the charts.
This script is perfect for traders looking for a systematic way to trade retests of key levels across multiple timeframes. Whether you're a scalper, day trader, or swing trader, "ENIGMA Signals with Retests" can help improve your precision and timing in the market.
4H CRT (1AM and 5AM)This TradingView script is designed to assist traders in implementing the "4-Hour Candle Ranges Theory Strategy (CRT)" by identifying key levels and setups based on the 1am and 4am (5am) 4-hour candles. This strategy is particularly effective for trading high-volatility assets such as Gold, EUR/USD, NAS100, US30, and S&P500, with US30 showing a notably high win rate. Here's how the strategy works:
Key Features:
1. Marking 1am and 4am 4-Hour Candle Ranges
- The script highlights the high and low of the 1am 4-hour candle.
- It visually tracks whether the high or low of the 1am candle is taken out by the subsequent 4-hour candle (5am).
2. Entry Setup Rules
- Primary Setup: Wait for the high or low of the 1am candle to be taken out by the 5am candle. Once this sweep occurs, wait for a Market Structure Shift (MSS) on the lower time frame (15min) to confirm your entry.
- Secondary Setup: If the 5am candle fails to take out the high or low of the 1am candle, the setup focuses on the levels formed by the 5am candle.
3. Trade Execution on 15-Minute Timeframe
- The script supports a lower time frame (15min) view to identify MSS and fine-tune entries.
4. Rinse and Repeat
- This process can be applied daily for consistent opportunities across the specified assets.
Advantages:
- Provides clear visual markers for key levels based on the 4-hour candles.
- Automates level plotting, saving traders time and reducing manual errors.
- Integrates well with the 15-minute timeframe for precise entry triggers.
- Optimized for popular trading instruments, especially US30 for a higher probability of success.
This script simplifies the application of CRT by automating the process of identifying and marking critical levels, enabling traders to focus on executing high-probability setups effectively.
Created by Hamid (poraymanfx)
Dabel MS + FVGThis script is designed to assist traders by identifying market structures, imbalances, and potential trade opportunities using Break of Structure (BOS) and Market Structure Shifts (MSS). It visually highlights imbalances in price action, key pivots, and market structure changes, providing actionable information for making trading decisions.
Key features:
Imbalances Detection: Highlights bullish and bearish price gaps (Fair Value Gaps) using colored boxes. Users can choose the line style (solid, dashed, or dotted) for imbalance midlines.
Market Structure Analysis: Tracks pivot highs and lows to identify BOS and MSS in two separate market structures with adjustable pivot strengths.
Customizable Visualization: Allows users to choose line styles, colors, and display options for both imbalances and market structures.
Alerts: Alerts traders when BOS or MSS occur, helping to monitor the market effectively.
Trading Strategy
Imbalance Trading:
Imbalances (gaps) represent areas where supply or demand was left unfilled. These gaps often act as magnet zones where the price revisits to fill.
Bullish Imbalance: Look for buying opportunities when price enters a green imbalance zone.
Bearish Imbalance: Look for selling opportunities when price enters a red imbalance zone.
Use the midline of the imbalance box as a key reference point for potential reversals.
Break of Structure (BOS) and Market Structure Shift (MSS):
BOS: Indicates a continuation of the existing trend. For example:
Bullish BOS: Look for continuation in the uptrend after a high is broken.
Bearish BOS: Look for continuation in the downtrend after a low is broken.
MSS: Suggests a potential reversal in market structure. For example:
Bullish MSS: Indicates a possible shift from a bearish to bullish market.
Bearish MSS: Indicates a potential shift from a bullish to bearish market.
Multiple Market Structures:
This script provide two sets of market structures, allowing traders to compare short-term and long-term trends.
Adjust the pivot strength to suit your trading style (lower for intraday trading, higher for swing or positional trading).
Entry and Exit:
Entry: Look for entries near imbalances or after confirmed BOS/MSS in line with the overall trend.
Exit: Place stop-loss below/above recent pivots and take profit at nearby support/resistance or imbalance zones.
For New Traders
Focus on Basics: Understand what BOS and MSS mean and how they signal trend direction or reversals.
Use Alerts: Rely on the script's alert system to catch important moments without staring at charts all day.
Start Small: Test this strategy on a demo account before using it live. You can understand it more with practice.
Adaptive Momentum Reversion StrategyThe Adaptive Momentum Reversion Strategy: An Empirical Approach to Market Behavior
The Adaptive Momentum Reversion Strategy seeks to capitalize on market price dynamics by combining concepts from momentum and mean reversion theories. This hybrid approach leverages a Rate of Change (ROC) indicator along with Bollinger Bands to identify overbought and oversold conditions, triggering trades based on the crossing of specific thresholds. The strategy aims to detect momentum shifts and exploit price reversions to their mean.
Theoretical Framework
Momentum and Mean Reversion: Momentum trading assumes that assets with a recent history of strong performance will continue in that direction, while mean reversion suggests that assets tend to return to their historical average over time (Fama & French, 1988; Poterba & Summers, 1988). This strategy incorporates elements of both, looking for periods when momentum is either overextended (and likely to revert) or when the asset’s price is temporarily underpriced relative to its historical trend.
Rate of Change (ROC): The ROC is a straightforward momentum indicator that measures the percentage change in price over a specified period (Wilder, 1978). The strategy calculates the ROC over a 2-period window, making it responsive to short-term price changes. By using ROC, the strategy aims to detect price acceleration and deceleration.
Bollinger Bands: Bollinger Bands are used to identify volatility and potential price extremes, often signaling overbought or oversold conditions. The bands consist of a moving average and two standard deviation bounds that adjust dynamically with price volatility (Bollinger, 2002).
The strategy employs two sets of Bollinger Bands: one for short-term volatility (lower band) and another for longer-term trends (upper band), with different lengths and standard deviation multipliers.
Strategy Construction
Indicator Inputs:
ROC Period: The rate of change is computed over a 2-period window, which provides sensitivity to short-term price fluctuations.
Bollinger Bands:
Lower Band: Calculated with a 18-period length and a standard deviation of 1.7.
Upper Band: Calculated with a 21-period length and a standard deviation of 2.1.
Calculations:
ROC Calculation: The ROC is computed by comparing the current close price to the close price from rocPeriod days ago, expressing it as a percentage.
Bollinger Bands: The strategy calculates both upper and lower Bollinger Bands around the ROC, using a simple moving average as the central basis. The lower Bollinger Band is used as a reference for identifying potential long entry points when the ROC crosses above it, while the upper Bollinger Band serves as a reference for exits, when the ROC crosses below it.
Trading Conditions:
Long Entry: A long position is initiated when the ROC crosses above the lower Bollinger Band, signaling a potential shift from a period of low momentum to an increase in price movement.
Exit Condition: A position is closed when the ROC crosses under the upper Bollinger Band, or when the ROC drops below the lower band again, indicating a reversal or weakening of momentum.
Visual Indicators:
ROC Plot: The ROC is plotted as a line to visualize the momentum direction.
Bollinger Bands: The upper and lower bands, along with their basis (simple moving averages), are plotted to delineate the expected range for the ROC.
Background Color: To enhance decision-making, the strategy colors the background when extreme conditions are detected—green for oversold (ROC below the lower band) and red for overbought (ROC above the upper band), indicating potential reversal zones.
Strategy Performance Considerations
The use of Bollinger Bands in this strategy provides an adaptive framework that adjusts to changing market volatility. When volatility increases, the bands widen, allowing for larger price movements, while during quieter periods, the bands contract, reducing trade signals. This adaptiveness is critical in maintaining strategy effectiveness across different market conditions.
The strategy’s pyramiding setting is disabled (pyramiding=0), ensuring that only one position is taken at a time, which is a conservative risk management approach. Additionally, the strategy includes transaction costs and slippage parameters to account for real-world trading conditions.
Empirical Evidence and Relevance
The combination of momentum and mean reversion has been widely studied and shown to provide profitable opportunities under certain market conditions. Studies such as Jegadeesh and Titman (1993) confirm that momentum strategies tend to work well in trending markets, while mean reversion strategies have been effective during periods of high volatility or after sharp price movements (De Bondt & Thaler, 1985). By integrating both strategies into one system, the Adaptive Momentum Reversion Strategy may be able to capitalize on both trending and reverting market behavior.
Furthermore, research by Chan (1996) on momentum-based trading systems demonstrates that adaptive strategies, which adjust to changes in market volatility, often outperform static strategies, providing a compelling rationale for the use of Bollinger Bands in this context.
Conclusion
The Adaptive Momentum Reversion Strategy provides a robust framework for trading based on the dual concepts of momentum and mean reversion. By using ROC in combination with Bollinger Bands, the strategy is capable of identifying overbought and oversold conditions while adapting to changing market conditions. The use of adaptive indicators ensures that the strategy remains flexible and can perform across different market environments, potentially offering a competitive edge for traders who seek to balance risk and reward in their trading approaches.
References
Bollinger, J. (2002). Bollinger on Bollinger Bands. McGraw-Hill Professional.
Chan, L. K. C. (1996). Momentum, Mean Reversion, and the Cross-Section of Stock Returns. Journal of Finance, 51(5), 1681-1713.
De Bondt, W. F., & Thaler, R. H. (1985). Does the Stock Market Overreact? Journal of Finance, 40(3), 793-805.
Fama, E. F., & French, K. R. (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96(2), 246-273.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Trend Research.
Range Channel by Atilla YurtsevenThis script creates a dynamic channel around a user-selected moving average (MA). It calculates the relative difference between price and the MA, then finds the average of the positive differences and the negative differences separately. Using these averages, it plots upper and lower bands around the MA as well as a histogram-like oscillator to show when price moves above or below the average thresholds.
How It Works
Moving Average Selection
The indicator allows you to choose among multiple MA types (SMA, EMA, WMA, Linear Regression, etc.). Depending on your preference, it calculates the chosen MA for the selected lookback period.
Relative Difference Calculation
It then computes the percentage difference between the source (typically the closing price) and the MA. (diff = (src / ma - 1) * 100)
Positive & Negative Averages
- Positive differences are averaged and represent how far the price typically moves above the MA.
- Negative differences are similarly averaged for when price moves below the MA.
Range Channel & Oscillator
- The channel is plotted around the MA using the average positive and negative differences (Upper Edge and Lower Edge).
- The “Untrended” histogram plots the difference (diff). Green bars occur when price is above the MA on average, and red bars when below. Two additional lines mark the upper and lower average thresholds on this histogram.
How to Use
Identify Overbought/Oversold Zones: The upper edge can serve as a dynamic overbought level, while the lower edge can suggest potential oversold conditions. When the histogram approaches or crosses these levels, it may signal price extremes relative to its average movement.
Trend Confirmation: Compare price action relative to the channel. If price and the histogram consistently remain above the MA and upper threshold, it could indicate a stronger bullish trend. If they remain below, it might signal a prolonged bearish trend.
Entry/Exit Timings:
- Entry: Traders can look for moments when price breaks back inside the channel from an extreme, anticipating a mean reversion.
- Exit: Watching how price interacts with these dynamic edges can help define stop-loss or take-profit points.
Because these thresholds adapt over time based on actual price behavior, they can be more responsive than fixed-percentage bands. However, like all indicators, it’s most effective when used in conjunction with other technical and fundamental tools.
Disclaimer
This script is provided for educational and informational purposes only. It does not guarantee any specific outcome or profit. Use it at your own discretion and risk.
Trade smart, stay safe.
Atilla Yurtseven
McClellan A-D Volume Integration ModelThe strategy integrates the McClellan A-D Oscillator with an adjustment based on the Advance/Decline (A-D) volume data. The McClellan Oscillator is calculated by taking the difference between the short-term and long-term exponential moving averages (EMAs) of the A-D line. This strategy introduces an enhancement where the A-D volume (the difference between the advancing and declining volume) is factored in to adjust the oscillator value.
Inputs:
• ema_short_length: The length for the short-term EMA of the A-D line.
• ema_long_length: The length for the long-term EMA of the A-D line.
• osc_threshold_long: The threshold below which the oscillator must drop for an entry signal to trigger.
• exit_periods: The number of periods after which the position is closed.
• Data Sources:
• ad_advance and ad_decline are the data sources for advancing and declining issues, respectively.
• vol_advance and vol_decline are the volume data for the advancing and declining issues. If volume data is unavailable, it defaults to na (Not Available), and the fallback logic ensures that the strategy continues to function.
McClellan Oscillator with Volume Adjustment:
• The A-D line is calculated by subtracting the declining issues from the advancing issues. Then, the volume difference is applied to this line, creating a “weighted” A-D line.
• The short and long EMAs are calculated for the weighted A-D line to generate the McClellan Oscillator.
Entry Condition:
• The strategy looks for a reversal signal, where the oscillator falls below the threshold and then rises above it again. The condition is designed to trigger a long position when this reversal happens.
Exit Condition:
• The position is closed after a set number of periods (exit_periods) have passed since the entry.
Plotting:
• The McClellan Oscillator and the threshold are plotted on the chart for visual reference.
• Entry and exit signals are highlighted with background colors to make the signals more visible.
Scientific Background:
The McClellan A-D Oscillator is a popular market breadth indicator developed by Sherman and Marian McClellan. It is used to gauge the underlying strength of a market by analyzing the difference between the number of advancing and declining stocks. The oscillator is typically calculated using exponential moving averages (EMAs) of the A-D line, with the idea being that crossovers of these EMAs indicate potential changes in the market’s direction.
The integration of A-D volume into this model adds another layer of analysis, as volume is often considered a leading indicator of price movement. By factoring in volume, the strategy becomes more sensitive to not just the number of advancing or declining stocks but also how significant those movements are based on trading volume, as discussed in Schwager, J. D. (1999). Technical Analysis of the Financial Markets. This enhanced version aims to capture stronger and more sustainable trends in the market, helping to filter out false signals.
Additionally, volume analysis is often used to confirm price movements, as described in Wyckoff, R. (1931). The Day Trading System. Therefore, incorporating the volume of advancing and declining stocks in the McClellan Oscillator offers a more robust signal for trading decisions.
VIX Spike StrategyThis script implements a trading strategy based on the Volatility Index (VIX) and its standard deviation. It aims to enter a long position when the VIX exceeds a certain number of standard deviations above its moving average, which is a signal of a volatility spike. The position is then exited after a set number of periods.
VIX Symbol (vix_symbol): The input allows the user to specify the symbol for the VIX index (typically "CBOE:VIX").
Standard Deviation Length (stddev_length): The number of periods used to calculate the standard deviation of the VIX. This can be adjusted by the user.
Standard Deviation Multiplier (stddev_multiple): This multiplier is used to determine how many standard deviations above the moving average the VIX must exceed to trigger a long entry.
Exit Periods (exit_periods): The user specifies how many periods after entering the position the strategy will exit the trade.
Strategy Logic:
Data Loading: The script loads the VIX data, both for the current timeframe and as a rescaled version for calculation purposes.
Standard Deviation Calculation: It calculates both the moving average (SMA) and the standard deviation of the VIX over the specified period (stddev_length).
Entry Condition: A long position is entered when the VIX exceeds the moving average by a specified multiple of its standard deviation (calculated as vix_mean + stddev_multiple * vix_stddev).
Exit Condition: After the position is entered, it will be closed after the user-defined number of periods (exit_periods).
Visualization:
The VIX is plotted in blue.
The moving average of the VIX is plotted in orange.
The threshold for the VIX, which is the moving average plus the standard deviation multiplier, is plotted in red.
The background turns green when the entry condition is met, providing a visual cue.
Sources:
The VIX is often used as a measure of market volatility, with high values indicating increased uncertainty in the market.
Standard deviation is a statistical measure of the variability or dispersion of a set of data points. In financial markets, it is used to measure the volatility of asset prices.
References:
Bollerslev, T. (1986). "Generalized Autoregressive Conditional Heteroskedasticity." Journal of Econometrics.
Black, F., & Scholes, M. (1973). "The Pricing of Options and Corporate Liabilities." Journal of Political Economy.
Smart DCA Strategy (Public)INSPIRATION
While Dollar Cost Averaging (DCA) is a popular and stress-free investment approach, I noticed an opportunity for enhancement. Standard DCA involves buying consistently, regardless of market conditions, which can sometimes mean missing out on optimal investment opportunities. This led me to develop the Smart DCA Strategy – a 'set and forget' method like traditional DCA, but with an intelligent twist to boost its effectiveness.
The goal was to build something more profitable than a standard DCA strategy so it was equally important that this indicator could backtest its own results in an A/B test manner against the regular DCA strategy.
WHY IS IT SMART?
The key to this strategy is its dynamic approach: buying aggressively when the market shows signs of being oversold, and sitting on the sidelines when it's not. This approach aims to optimize entry points, enhancing the potential for better returns while maintaining the simplicity and low stress of DCA.
WHAT THIS STRATEGY IS, AND IS NOT
This is an investment style strategy. It is designed to improve upon the common standard DCA investment strategy. It is therefore NOT a day trading strategy. Feel free to experiment with various timeframes, but it was designed to be used on a daily timeframe and that's how I recommend it to be used.
You may also go months without any buy signals during bull markets, but remember that is exactly the point of the strategy - to keep your buying power on the sidelines until the markets have significantly pulled back. You need to be patient and trust in the historical backtesting you have performed.
HOW IT WORKS
The Smart DCA Strategy leverages a creative approach to using Moving Averages to identify the most opportune moments to buy. A trigger occurs when a daily candle, in its entirety including the high wick, closes below the threshold line or box plotted on the chart. The indicator is designed to facilitate both backtesting and live trading.
HOW TO USE
Settings:
The input parameters for tuning have been intentionally simplified in an effort to prevent users falling into the overfitting trap.
The main control is the Buying strictness scale setting. Setting this to a lower value will provide more buying days (less strict) while higher values mean less buying days (more strict). In my testing I've found level 9 to provide good all round results.
Validation days is a setting to prevent triggering entries until the asset has spent a given number of days (candles) in the overbought state. Increasing this makes entries stricter. I've found 0 to give the best results across most assets.
In the backtest settings you can also configure how much to buy for each day an entry triggers. Blind buy size is the amount you would buy every day in a standard DCA strategy. Smart buy size is the amount you would buy each day a Smart DCA entry is triggered.
You can also experiment with backtesting your strategy over different historical datasets by using the Start date and End date settings. The results table will not calculate for any trades outside what you've set in the date range settings.
Backtesting:
When backtesting you should use the results table on the top right to tune and optimise the results of your strategy. As with all backtests, be careful to avoid overfitting the parameters. It's better to have a setup which works well across many currencies and historical periods than a setup which is excellent on one dataset but bad on most others. This gives a much higher probability that it will be effective when you move to live trading.
The results table provides a clear visual representation as to which strategy, standard or smart, is more profitable for the given dataset. You will notice the columns are dynamically coloured red and green. Their colour changes based on which strategy is more profitable in the A/B style backtest - green wins, red loses. The key metrics to focus on are GOA (Gain on Account) and Avg Cost.
Live Trading:
After you've finished backtesting you can proceed with configuring your alerts for live trading.
But first, you need to estimate the amount you should buy on each Smart DCA entry. We can use the Total invested row in the results table to calculate this. Assuming we're looking to trade on
BTCUSD
Decide how much USD you would spend each day to buy BTC if you were using a standard DCA strategy. Lets say that is $5 per day
Enter that USD amount in the Blind buy size settings box
Check the Blind Buy column in the results table. If we set the backtest date range to the last 10 years, we would expect the amount spent on blind buys over 10 years to be $18,250 given $5 each day
Next we need to tweak the value of the Smart buy size parameter in setting to get it as close as we can to the Total Invested amount for Blind Buy
By following this approach it means we will invest roughly the same amount into our Smart DCA strategy as we would have into a standard DCA strategy over any given time period.
After you have calculated the Smart buy size, you can go ahead and set up alerts on Smart DCA buy triggers.
BOT AUTOMATION
In an effort to maintain the 'set and forget' stress-free benefits of a standard DCA strategy, I have set my personal Smart DCA Strategy up to be automated. The bot runs on AWS and I have a fully functional project for the bot on my GitHub account. Just reach out if you would like me to point you towards it. You can also hook this into any other 3rd party trade automation system of your choice using the pre-configured alerts within the indicator.
PLANNED FUTURE DEVELOPMENTS
Currently this is purely an accumulation strategy. It does not have any sell signals right now but I have ideas on how I will build upon it to incorporate an algorithm for selling. The strategy should gradually offload profits in bull markets which generates more USD which gives more buying power to rinse and repeat the same process in the next cycle only with a bigger starting capital. Watch this space!
MARKETS
Crypto:
This strategy has been specifically built to work on the crypto markets. It has been developed, backtested and tuned against crypto markets and I personally only run it on crypto markets to accumulate more of the coins I believe in for the long term. In the section below I will provide some backtest results from some of the top crypto assets.
Stocks:
I've found it is generally more profitable than a standard DCA strategy on the majority of stocks, however the results proved to be a lot more impressive on crypto. This is mainly due to the volatility and cycles found in crypto markets. The strategy makes its profits from capitalising on pullbacks in price. Good stocks on the other hand tend to move up and to the right with less significant pullbacks, therefore giving this strategy less opportunity to flourish.
Forex:
As this is an accumulation style investment strategy, I do not recommend that you use it to trade Forex.
For more info about this strategy including backtest results, please see the full description on the invite only version of this strategy named "Smart DCA Strategy"
Gauti Market Maker Killzone EMA1. Identifying the Trend
Use Daily (1D) and Hourly (1H) Exponential Moving Averages (EMAs) to define the overall trend:
Bullish Trend: Both 1D and 1H EMAs are upward sloping, and the price is above these EMAs.
Bearish Trend: Both 1D and 1H EMAs are downward sloping, and the price is below these EMAs.
2. Confirmation with Higher Timeframes
Bullish Conditions:
Check 1D and 4H charts for price action above the EMA bands.
Look for price forming higher highs and higher lows or respecting support at the EMA bands.
Bearish Conditions:
Check 1D and 4H charts for price action below the EMA bands.
Look for price forming lower highs and lower lows or respecting resistance at the EMA bands.
Note: Crossover of EMAs on higher timeframes is an optional extra confirmation, but not mandatory for entry.
3. Entry Strategy
Use the 15-Minute (15M) timeframe for entries.
Entries are taken only during Killzones:
Killzones: London Open, New York Open, or other intraday key trading sessions. (Define the time ranges for these zones based on your trading hours.)
Wait for the price to touch or pull back to the EMA band during the Killzones in the direction of the overall trend:
In a bullish trend, enter long when the price touches the EMA band and shows signs of rejection or reversal.
In a bearish trend, enter short when the price touches the EMA band and shows signs of rejection or reversal.
4. Checklist for Entry
Confirm the following before entering:
1D Trend aligns with the 1H Trend.
Price Action in 1D and 4H supports the trend.
Killzone session is active.
Price is reacting to the EMA band on the 15M chart in the trend direction.
Lot Size & Risk Calculator (All Pairs)this indicator is designed to simplify and optimize risk management. It automatically calculates the ideal lot size based on your account balance, risk percentage, and defined entry and exit levels. Additionally, it includes visual tools to represent stop-loss (SL) and take-profit (TP) levels, helping you trade with precision and consistency.
WHAT IS THIS INDICATOR FOR?
This indicator is essential for traders who want to:
Maintain consistent risk in their trades.
Quickly calculate lot sizes for Forex, XAUUSD, BTCUSD, and US100.
Visualize key levels (Entry, SL, and TP) on the chart.
Monitor potential losses and gains in real time.
COMPATIBLE ASSETS
The Lot Size Calculator works with the following assets:
Forex: Standard currency pairs.
XAUUSD: Gold versus the US dollar.
BTCUSD: Bitcoin versus the US dollar.
US100: Nasdaq 100 index.
Calculations adjust automatically based on the selected asset.
TAKE-PROFIT (TP) LEVELS
The indicator allows you to define up to three take-profit levels:
TP1
TP2
TP3
.
Each level is configurable based on your exit strategy.
DASHBOARD
The dashboard is a visual tool that consolidates key information about your trade:
Account balance: Total amount available in your account.
Lot size: Calculated based on your risk and parameters.
Potential loss (SL): Amount you could lose if the price hits your stop-loss.
Potential gain (TP): Expected profit if the take-profit level is reached.
SETTINGS
The indicator offers multiple configurable options to adapt to your trading style:
Levels
Entry: Initial trade price.
Stop-Loss (SL): Maximum allowed loss level.
Take-Profit (TP): Up to three configurable levels.
Risk Management
Account balance ($): Enter your total available balance.
Risk percentage: Define how much you're willing to risk per trade
.
Visual Options
Visualization style: Choose between simple lines or visual fills.
Colors: Customize the colors of lines and labels.
Dashboard Settings
Statistics: Enable or disable key data display.
Size and position: Adjust the dashboard's size and location on the chart.
HOW TO CHANGE AN ENTRY?
Open the indicator settings in TradingView and entering the new data manually
Removing and re-adding the indicator to the chart
Scalp System# Scalp System
A premium scalping system designed specifically for 2-minute charts, combining multiple timeframe analysis with trend-based trading decisions. This indicator helps identify high-probability scalping opportunities through color-coded moving averages and their crossovers.
## Strategy Overview
### Entry Signals
- ONLY trade LONG when price is above RED line
- ONLY trade SHORT when price is below RED line
- Primary entry: BLUE/GREEN crosses
- Strong trend confirmation: YELLOW/PURPLE crosses
### Best Practices
1. Trade with the trend (follow RED line direction)
2. Wait for price pullbacks of faster lines
3. Combine crosses with support/resistance levels
4. Use smaller targets
5. Quick exits on failed breakouts
6. Monitor volume for confirmation
### Color Guide
- YELLOW: Fast trend identifier
- BLUE: Very short-term momentum (1min)
- GREEN: Short-term momentum (3min)
- RED: Trend filter
- PURPLE: Strong trend baseline
### Risk Management
- Place stops beyond the RED line
- Scale out at key levels
- Use 1:1.5 minimum risk/reward
- Avoid trading during major news
- Reduce position size in choppy markets
### Best Trading Hours
- Most effective during first 2 hours after market open
- Good opportunities during power hour (last hour)
- Avoid lunch hour chop (11:30-1:30 EST)
## Tips
- Less is more - wait for clean setups
- Respect the RED line as your trend filter
- Multiple timeframe confirmation increases success rate
- Use crosses as triggers, not absolute signals
- Practice in simulator before live trading
TFMTFM Strategy Explanation
Overview
The TFM (Timeframe Multiplier) strategy is a PineScript trading bot that utilizes multiple timeframes to identify entry and exit points.
Inputs
1. tfm (Timeframe Multiplier): Multiplies the chart's timeframe to create a higher timeframe for analysis.
2. lns (Long and Short): Enables or disables short positions.
Logic
Calculations
1. chartTf: Gets the chart's timeframe in seconds.
2. tfTimes: Calculates the higher timeframe by multiplying chartTf with tfm.
3. MintickerClose and MaxtickerClose: Retrieve the minimum and maximum closing prices from the higher timeframe using request.security.
- MintickerClose: Finds the lowest low when the higher timeframe's close is below its open.
- MaxtickerClose: Finds the highest high when the higher timeframe's close is above its open.
Entries and Exits
1. Long Entry: When the current close price crosses above MaxtickerClose.
2. Short Entry (if lns is true): When the current close price crosses below MintickerClose.
3. Exit Long: When the short condition is met (if lns is false) or when the trade is manually closed.
Strategy
1. Attach the script to a chart.
2. Adjust tfm and lns inputs.
3. Monitor entries and exits.
Example Use Cases
1. Intraday trading with tfm = 2-5.
2. Swing trading with tfm = 10-30.
Tips
1. Experiment with different tfm values.
2. Use lns to control short positions.
3. Combine with other indicators for confirmation.
