VIX Differential(Melon)Simple indy that measures the difference between VIX9D and VIX to try assessing short-term market sentiment. I've liked this recently as a big clue for market bottom reversals.
Sentiment
Percent Change HistogramThis indicator shows you percent changes in a super visual way using a color-coded histogram.
Here's how the colors work:
🟩 Dark green = percent change is growing stronger
🟢 Light green = still positive but losing steam
🟥 Dark red = getting more negative
🔴 Light red = negative but improving
The cool part? You can set any lookback period you want. For example:
24 periods on 1H chart = last 24 hours
30 periods on daily = last month
7 periods on daily = last week
Pro tip: You're not locked to your chart's timeframe! Want to see monthly changes while trading on 5min?
No problem.
You can even stack multiple indicators to watch different intervals simultaneously (daily, weekly, monthly) - super helpful for multi-timeframe analysis.
Perfect for spotting momentum shifts across different timeframes without switching between charts.
Intraday ORB Breakout IndicatorThis is an intraday indicator works in a 15-minute timeframe.
Timeframe - 15 min
IB Range - 1-hour range after the market opens in India (i.e. 9.15 to 10.15 AM range)
If the price shows a breakout of IB High or a breakdown of IB low and the breakout/breakdown candle has less than 20% of the wick (selling wick in breakout and buying wick in breakdown) in a 15-minute chart, then it will set a flag or alert mechanism on the chart with 'Long' or 'Short' terms. It also marks the IB range (9.15 to 10.15 AM range) with two simple lines.
Traders should wait for the break of the high of the breakout candle or the low of the breakdown candle to take their trades. Besides, one should follow proper risk management rules when making trades.
// Disclaimer: This indicator is for educational purposes only.
// I am not responsible for any financial losses incurred from its use.
Intraday ORB Breakout IndicatorThis is only applicable to intraday trading in 15 minutes timeframe.
It highlights the 1-hour range in Indian markets i.e. 9.15 AM to 10.15 AM.
If the price shows a breakout of a 1-hour High or a breakdown of a 1-hour low and the breakout/breakdown candle has less than 20% of the wick (selling wick in breakout and buying wick in breakdown) in the 15-minute chart, then it will set an alert 'Long' or 'Short' on the chart.
However, to take a trade, one must wait for the break of the high of the breakout candle for a long trade or a break of the low of the breakdown candle for a short trade. Besides, one should follow proper risk management rules to manage their trades.
Auto-Adjusting Kalman Filter by TenozenNew year, new indicator! Auto-Adjusting Kalman Filter is an indicator designed to provide an adaptive approach to trend analysis. Using the Kalman Filter (a recursive algorithm used in signal processing), this algo dynamically adjusts to market conditions, offering traders a reliable way to identify trends and manage risk! In other words, it's a remaster of my previous indicator, Kalman Filter by Tenozen.
What's the difference with the previous indicator (Kalman Filter by Tenozen)?
The indicator adjusts its parameters (Q and R) in real-time using the Average True Range (ATR) as a measure of market volatility. This ensures the filter remains responsive during high-volatility periods and smooth during low-volatility conditions, optimizing its performance across different market environments.
The filter resets on a user-defined timeframe, aligning its calculations with dominant trends and reducing sensitivity to short-term noise. This helps maintain consistency with the broader market structure.
A confidence metric, derived from the deviation of price from the Kalman filter line (measured in ATR multiples), is visualized as a heatmap:
Green : Bullish confidence (higher values indicate stronger trends).
Red : Bearish confidence (higher values indicate stronger trends).
Gray : Neutral zone (low confidence, suggesting caution).
This provides a clear, objective measure of trend strength.
How it works?
The Kalman Filter estimates the "true" price by filtering out market noise. It operates in two steps, that is, prediction and update. Prediction is about projection the current state (price) forward. Update is about adjusting the prediction based on the latest price data. The filter's parameters (Q and R) are scaled using normalized ATR, ensuring adaptibility to changing market conditions. So it means that, Q (Process Noise) increases during high volatility, making the filter more responsive to price changes and R (Measurement Noise) increases during low volatility, smoothing out the filter to avoid overreacting to minor fluctuations. Also, the trend confidence is calculated based on the deviation of price from the Kalman filter line, measured in ATR multiples, this provides a quantifiable measure of trend strength, helping traders assess market conditions objectively.
How to use?
Use the Kalman Filter line to identify the prevailing trend direction. Trade in alignment with the filter's slope for higher-probability setups.
Look for pullbacks toward the Kalman Filter line during strong trends (high confidence zones)
Utilize the dynamic stop-loss and take-profit levels to manage risk and lock in profits
Confidence Heatmap provides an objective measure of market sentiment, helping traders avoid low-confidence (neutral) zones and focus on high-probability opportunities
Guess that's it! I hope this indicator helps! Let me know if you guys got some feedback! Ciao!
SPDR Sectors█ OVERVIEW
This script is an interactive and customizable SPDR Sectors Indicator designed to monitor and analyze the performance of the 11 main sectors of the S&P 500 using sector-specific ETFs. The script provides a dynamic table for tracking daily or periodic sector movements, making it an essential tool for traders, analysts, and investors implementing sector rotation strategies.
█ DEFINITIONS
SPDR Sectors ETFs are exchange-traded funds managed by State Street Global Advisors that divide the S&P 500 into the following 11 sectors:
- Communication Services (XLC)
- Consumer Discretionary (XLY)
- Consumer Staples (XLP)
- Energy (XLE)
- Financials (XLF)
- Health Care (XLV)
- Industrials (XLI)
- Materials (XLB)
- Real Estate (XLRE)
- Technology (XLK)
- Utilities (XLU)
These ETFs aim to replicate the performance of their respective sectors as defined by the Global Industry Classification Standard (GICS). The funds are periodically rebalanced to match changes in the S&P 500, offering an accurate reflection of sectoral trends.
█ INDICATOR
The script provides a table displaying the ticker and its corresponding sector name in official GICS terminology, using the SPDR official color. Additionally, it shows the percentage performance, calculated daily for intraday charts or according to the chart's time frame.
The table can be sorted in ascending or descending order, based on either performance or the weight of the ETFs in the S&P 500, which can be manually updated using data retrieved from www.sectorspdrs.com
Directional Cycle Indicator (DCI) with True Apex/Nadir CyclesAn indication where the cycle goes over 0 it means it goes up and it's probably time to sell and give you the apex .When under zero and when it's it is in the nadir then it's time to buy , that's it
EMA Crossover with 50 EMA Filter50-period EMA: We added the 50-period EMA as the filterEMA variable.
Buy and Sell Conditions: The buy signal is generated only if the 8-period and 16-period EMAs both cross above each other and are above the 50-period EMA. Similarly, the sell signal is generated when the 8-period and 16-period EMAs cross below each other and are below the 50-period EMA.
Plotting: The 50-period EMA is also plotted on the chart (in orange).
This strategy will ensure that the buy signals are only triggered when the trend is considered "bullish" (both EMAs above the 50 EMA) and sell signals when the trend is "bearish" (both EMAs below the 50 EMA).
You can set up alerts for both buy and sell conditions using the alertcondition() function.
Let me know if you need further adjustments!
NOTE :- Applicable only for banknifty
Candle Emotion Index (CEI) StrategyThe Candle Emotion Index (CEI) Strategy is an innovative sentiment-based trading approach designed to help traders identify and capitalize on market psychology. By analyzing candlestick patterns and combining them into a unified metric, the CEI Strategy provides clear entry and exit signals while dynamically managing risk. This strategy is ideal for traders looking to leverage market sentiment to identify high-probability trading opportunities.
How It Works
The CEI Strategy is built around three core oscillators that reflect key emotional states in the market:
Indecision Oscillator . Measures market uncertainty using patterns like Doji and Spinning Tops. High values indicate hesitation, signaling potential turning points.
Fear Oscillator . Tracks bearish sentiment through patterns like Shooting Star, Hanging Man, and Bearish Engulfing. Helps identify moments of intense selling pressure.
Greed Oscillator . Detects bullish sentiment using patterns like Marubozu, Hammer, Bullish Engulfing, and Three White Soldiers. Highlights periods of strong buying interest.
These oscillators are averaged into the Candle Emotion Index (CEI):
CEI = (Indecision + Fear + Greed) / 3
This single value quantifies overall market sentiment and drives the strategy’s trading decisions.
Key Features
Sentiment-Based Trading Signals . Long Entry: Triggered when the CEI crosses above a lower threshold (e.g., 0.1), indicating increasing bullish sentiment. Short Entry: Triggered when the CEI crosses above a higher threshold (e.g., 0.2), signaling rising bearish sentiment.
Volume Confirmation . Trades are validated only if volume exceeds a user-defined multiplier of the average volume over the lookback period. This ensures entries are backed by significant market activity.
Break-Even Recovery Mechanism . If a trade moves into a loss, the strategy attempts to recover to break-even instead of immediately exiting at a loss. This feature provides flexibility, allowing the market to recover while maintaining disciplined risk management.
Dynamic Risk Management . Maximum Holding Period: Trades are closed after a user-defined number of candles to avoid overexposure to prolonged uncertainty. Profit-Taking Conditions: Positions are exited when favorable price moves are confirmed by increased volume, locking in gains. Loss Threshold: Trades are exited early if the price moves unfavorably beyond a set percentage of the entry price, limiting potential losses.
Cooldown Period . After a trade is closed, a cooldown period prevents immediate re-entry, reducing overtrading and improving signal quality.
Why Use This Strategy?
The CEI Strategy combines advanced sentiment analysis with robust trade management, making it a powerful tool for traders seeking to understand market psychology and identify high-probability setups. Its unique features, such as the break-even recovery mechanism and volume confirmation, add an extra layer of discipline and reliability to trading decisions.
Best Practices
Combine with Other Indicators . Use trend-following tools (e.g., moving averages, ADX) and momentum oscillators (e.g., RSI, MACD) to confirm signals.
Align with Key Levels . Incorporate support and resistance levels for refined entries and exits.
Multi-Market Compatibility . Apply this strategy to forex, crypto, stocks, or any asset class with strong volume and price action.
Grid Trading with RSI and Fibonacci SLThis script implements a grid trading strategy that buys when the "AI" confidence is high and the RSI is oversold, and sells when the "AI" confidence is high and the RSI is overbought.
It uses a Fibonacci-based stop-loss and adjusts the grid levels and trade size after each trade.
The "AI" is a very simple rule-based system, not actual artificial intelligence. The script also plots the RSI, AI confidence, grid price, and stop-loss level on the chart.
It's important to thoroughly backtest and understand the risks associated with grid trading strategies before using them with real capital.
CryptoMitchX Memecoin ShorterUpdate for "CryptoMitchX Memecoin Shorter" Indicator
New Features & Improvements:
Conditional Hiding of Recommendations:
SHORT Recommendations: These are now hidden when the RSI (Relative Strength Index) falls below 30, preventing signals during potentially oversold conditions.
Take Profit Recommendations: Hidden when the RSI goes above 60, avoiding signals in potentially overbought market conditions.
Refined Alert System:
Alerts for both SHORT and Take Profit signals now only trigger when the RSI conditions are met, ensuring more targeted notifications.
Code Optimization:
The script has been updated to address scope-related errors, improving its reliability and performance on the TradingView platform.
Technical Details:
RSI Implementation: The RSI is calculated with a 14-period length to determine market momentum.
Conditional Plotting: Instead of using direct conditional statements inside plotting functions, we now use boolean variables to control which signals are plotted, avoiding local scope issues.
Signal Tracking: Continues to track consecutive signals, but now with the added condition of RSI thresholds for more nuanced trading signals.
Usage:
Users will see a cleaner chart with signals only appearing when they are most relevant according to RSI levels, reducing false signals and improving the overall trading strategy experience.
I nstallation:
Simply update or replace the existing indicator script with this new version in your TradingView Pine Script editor.
Known Issues & Limitations:
This update does not include real sentiment analysis due to the limitations of Pine Script in accessing external data. The sentiment is simulated based on price volatility and direction.
Feedback:
We're eager to hear your feedback on these changes. If you encounter any issues or have suggestions for further improvements, please let us know.
Memecoin Shorter Indicator by CryptoMitchXMemecoin Shorter Indicator by CryptoMitchX
Introducing the "Memecoin Shorter Indicator" designed for traders looking to capitalize on the volatile nature of memecoins. This is built on the concept that MemeCoins can't sustain their rallies and that profits move into safer cryptocurrencies like Bitcoin or Stablecoins.
This indicator combines momentum, volume, and sentiment analysis to signal shorting opportunities with a cap at two consecutive signals to manage risk effectively.
Key Features:
Momentum Analysis: Uses Simple Moving Averages (SMA) to detect when the short-term trend crosses below the long-term trend, indicating potential downward momentum.
Volume Spike Detection: Identifies significant volume increases that could signify a reversal or continuation of a downtrend.
Simulated Sentiment Analysis: Monitors price volatility to simulate sentiment, suggesting "Take Profit" when conditions hint at negative market sentiment.
How to Use:
SHORT: The indicator marks "SHORT" on the chart when conditions are met to initiate a short position. This happens when negative momentum, volume spikes, or simulated negative sentiment are combined.
Take Profit: Signals to take profit after initiating a short position, again limited to two consecutive signals.
Strategies and Tips for Optimization:
Backtesting and Forward Testing:
Before live trading, backtest this indicator with historical data to see how it performs over different market conditions, especially during memecoin pump-and-dump cycles.
Use forward testing in a demo account to understand real-time performance without financial risk.
Customization:
Adjust the short_sma_length and long_sma_length according to the asset's volatility. More volatile memecoins might require shorter periods for quicker signals.
Modify volume_spike_threshold to be more or less sensitive to volume changes based on the average trading volume of the asset.
Risk Management:
Since this indicator allows for two consecutive signals, set strict stop-losses to manage risk. Consider the percentage drop from your entry price where you are comfortable cutting losses.
Use this indicator in conjunction with other technical analysis tools like RSI or MACD for confirmation signals to increase the reliability of your trades.
Market Context:
Understand the broader market sentiment towards memecoins. This indicator works best in bearish or highly volatile scenarios. Keep an eye on news and social media trends that could affect memecoin prices.
Trade Sizing:
Due to the speculative nature of memecoins, consider smaller position sizes to manage potential losses. Even with only two consecutive signals, losses can accumulate quickly in volatile markets.
Exit Strategy:
Beyond taking profit on signals, consider setting a trailing stop loss or using a time-based exit strategy if the market doesn't move as expected after your entry.
Alert Utilization:
Set up alerts for both SHORT and Take Profit signals to monitor opportunities without needing constant chart watching.
Remember, trading meme coins involves high risk due to their speculative nature and susceptibility to manipulation. Always trade with what you can afford to lose and use this indicator as part of a broader trading strategy.
Note: This indicator simulates sentiment based on price action; for real sentiment analysis, external data integration would be necessary, which is beyond the scope of Pine Script in TradingView.
US10Y 63-Day Range Percentage [TomasOnMarkets]Shows the relation of US Government Bonds 10 YR Yield to risk assets like S&P500.
When yields move to the 80th percentile of their rolling 1 quarter (63 day) range, the S&P500 struggles.
The indicator chart's background is painted with red when yields move over 80th percentile. Notice how the risk assets (eg S&P500) goes down in that range.
The indicator works pretty good for the S&P500.
Not as good for bitcoin, but maybe still useful
Credits:
Tomas (@TomasOnMarkets) - x.com/TomasOnMarkets/status/1881770106356641885
Warren Pies (@WarrenPies) - x.com/WarrenPies/status/1881480249139187974
9/21 EMA_DSWThe 9 and 21 Exponential Moving Average (EMA) crossover is a popular technical indicator used by traders to identify potential buy and sell signals in the market. The 9 EMA is a shorter-term moving average, which responds more quickly to recent price movements, while the 21 EMA is a longer-term moving average that smooths out price action over a longer period. A bullish signal occurs when the 9 EMA crosses above the 21 EMA, suggesting upward momentum and a potential buying opportunity. Conversely, a bearish signal occurs when the 9 EMA crosses below the 21 EMA, indicating downward momentum and a potential selling opportunity. Traders often use this crossover in combination with other indicators, such as volume or RSI, to confirm the strength of the trend. The strategy is commonly applied in various time frames, from intraday charts to longer-term setups, and is widely used for trend-following strategies. However, it’s essential to keep in mind that the EMA crossover strategy can produce false signals in choppy or sideways markets.
Helicopter Volatility Detector v4This Indicator designed to measure market volatility specifically during reversal phases, while ignoring periods of strong trending movements. It helps traders identify when the market is experiencing frequent and significant price reversals, which are often accompanied by increased volatility.
This indicator is suitable for those who want to understand when there is high volatility in the market, such as when Jerome Powell speaks or economic data is released. It can help identify periods when large leveraged positions are likely to be liquidated.
Dynamic Ticks Oscillator Model (DTOM)The Dynamic Ticks Oscillator Model (DTOM) is a systematic trading approach grounded in momentum and volatility analysis, designed to exploit behavioral inefficiencies in the equity markets. It focuses on the NYSE Down Ticks, a metric reflecting the cumulative number of stocks trading at a lower price than their previous trade. As a proxy for market sentiment and selling pressure, this indicator is particularly useful in identifying shifts in investor behavior during periods of heightened uncertainty or volatility (Jegadeesh & Titman, 1993).
Theoretical Basis
The DTOM builds on established principles of momentum and mean reversion in financial markets. Momentum strategies, which seek to capitalize on the persistence of price trends, have been shown to deliver significant returns in various asset classes (Carhart, 1997). However, these strategies are also susceptible to periods of drawdown due to sudden reversals. By incorporating volatility as a dynamic component, DTOM adapts to changing market conditions, addressing one of the primary challenges of traditional momentum models (Barroso & Santa-Clara, 2015).
Sentiment and Volatility as Core Drivers
The NYSE Down Ticks serve as a proxy for short-term negative sentiment. Sudden increases in Down Ticks often signal panic-driven selling, creating potential opportunities for mean reversion. Behavioral finance studies suggest that investor overreaction to negative news can lead to temporary mispricings, which systematic strategies can exploit (De Bondt & Thaler, 1985). By incorporating a rate-of-change (ROC) oscillator into the model, DTOM tracks the momentum of Down Ticks over a specified lookback period, identifying periods of extreme sentiment.
In addition, the strategy dynamically adjusts entry and exit thresholds based on recent volatility. Research indicates that incorporating volatility into momentum strategies can enhance risk-adjusted returns by improving adaptability to market conditions (Moskowitz, Ooi, & Pedersen, 2012). DTOM uses standard deviations of the ROC as a measure of volatility, allowing thresholds to contract during calm markets and expand during turbulent ones. This approach helps mitigate false signals and aligns with findings that volatility scaling can improve strategy robustness (Barroso & Santa-Clara, 2015).
Practical Implications
The DTOM framework is particularly well-suited for systematic traders seeking to exploit behavioral inefficiencies while maintaining adaptability to varying market environments. By leveraging sentiment metrics such as the NYSE Down Ticks and combining them with a volatility-adjusted momentum oscillator, the strategy addresses key limitations of traditional trend-following models, such as their lagging nature and susceptibility to reversals in volatile conditions.
References
• Barroso, P., & Santa-Clara, P. (2015). Momentum Has Its Moments. Journal of Financial Economics, 116(1), 111–120.
• Carhart, M. M. (1997). On Persistence in Mutual Fund Performance. The Journal of Finance, 52(1), 57–82.
• De Bondt, W. F., & Thaler, R. (1985). Does the Stock Market Overreact? The Journal of Finance, 40(3), 793–805.
• Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65–91.
• Moskowitz, T. J., Ooi, Y. H., & Pedersen, L. H. (2012). Time Series Momentum. Journal of Financial Economics, 104(2), 228–250.
Global Relevant Events MarkerThe Global Relevant Events Marker script is designed to mark significant global events on a chart, such as economic crises or major geopolitical events. It uses vertical lines to indicate the exact dates of these events and places labels (optional) near the lines to provide a description of the event.
Trend with ADX/EMA - Buy & Sell SignalsThis script is designed to help traders make buy and sell decisions based on trend analysis using two key methods: ADX (Average Directional Index) and EMA (Exponential Moving Averages). Here's a breakdown in simple terms:
What Does It Do?
Identifies the Trend's Strength and Direction:
Uses the ADX indicator to determine how strong the trend is.
Compares two lines (DI+ and DI−) to identify whether the trend is moving up or down.
Generates Buy and Sell Signals:
Uses two EMAs (a fast one and a slow one) to check when the price crosses key levels, signaling a possible buy or sell opportunity.
Plots visual indicators (arrows and labels) for easy interpretation.
Color-Codes the Chart:
Highlights the background in green when the trend is bullish (uptrend).
Highlights the background in red when the trend is bearish (downtrend).
Alerts the User:
Creates alerts when specific conditions for buying or selling are met.
Key Components:
1. ADX (Trend Strength & Direction)
What is ADX?
ADX measures how strong the trend is (not the direction). Higher ADX means a stronger trend.
It also calculates two lines:
DI+: Measures upward movement strength.
DI−: Measures downward movement strength.
How It Works in the Script:
If DI+ is greater than DI−, it’s a bullish trend (upward).
If DI− is greater than DI+, it’s a bearish trend (downward).
The background turns green for an uptrend and red for a downtrend.
2. EMA (Buy and Sell Decisions)
What is EMA?
EMA is a moving average that gives more weight to recent prices. It’s used to smooth out price fluctuations.
How It Works in the Script:
The script calculates two EMAs:
Fast EMA (short-term average): Reacts quickly to price changes.
Slow EMA (long-term average): Reacts slower and shows overall trends.
When the Fast EMA crosses above the Slow EMA, it’s a signal to Buy.
When the Fast EMA crosses below the Slow EMA, it’s a signal to Sell.
These signals are marked on the chart as "Buy" and "Sell" labels.
3. Buy and Sell Alerts
The script sets up alerts for the user:
Buy Alert: When a crossover indicates a bullish signal.
Sell Alert: When a crossunder indicates a bearish signal.
Visual Elements on the Chart:
Background Colors:
Green: When the DI+ line indicates an uptrend.
Red: When the DI− line indicates a downtrend.
EMA Lines:
Green Line: Fast EMA.
Red Line: Slow EMA.
Buy/Sell Labels:
"Buy" label: Shown when the Fast EMA crosses above the Slow EMA.
"Sell" label: Shown when the Fast EMA crosses below the Slow EMA.
Why Use This Script?
Trend Analysis: Helps you quickly identify the strength and direction of the market trend.
Buy/Sell Signals: Gives clear signals to enter or exit trades based on trend and EMA crossovers.
Custom Alerts: Ensures you never miss a trading opportunity by notifying you when conditions are met.
Visual Simplicity: Makes it easy to interpret trading signals with color-coded backgrounds and labeled arrows.
Emergent Rays - NovaTheMachineEmergent Rays
An emergent ray is a refracted ray of light that exits a medium or channel. Emergent rays can be created when light passes through a prism, glass slab, or mirror
This visual indicator has been designed to aid in developing psychological understanding of price action. Many traders often struggle with developing strategy that they can act on, repeatedly. The difference between gambling and trading successfully comes down to following a plan, that you have tested and determined to be profitable over the long term.
Some traders experience anxiety when trading trends, trying to time a reversal, or entering a trade based on emotions and are unsure where they should place a stop - if they bother to place one at all.
I developed this indicator to help traders practice responsible trading practices and develop discipline. When applied to a chart an array of light rays will be plotted, similarly to those that are emitted from light passing through a medium such as a prism. These rays are a series of EMAs high & low values, filled with an assigned color.
The indicator does not suggest an entry or exit, it allows for freedom of user interpretation, however - when in a trending market you may notice that the rays are tested multiple times when the market is trending in the same direction. When trading trends it makes sense to enter at the discounted value (pullbacks) and exit on extensions. There are two main reasons for this; first is manage risk, second is to profit from a successful trade.
To practice discipline and remove emotions from trading, one must be willing to accept the outcome of a trade - regardless of whether it was profitable or not, based on their strategy.
The visual gradient of the rays signifies the pullback to stoploss risk. As price expands it is clear to see that the distance from red to blue rays increases, which means entering a trade on a touch of the red ray requires a larger stoploss than entering a pullback to the green or blue rays. When price closes on the opposite side of a ray from where it was trending - we accept the trend may have ended and must wait for the next trend cycle. If the price action is range bound we will notice the rays melting together to create a grey ray that signifies this is not the best place to be trading any type of trend following strategy.
Using this indicator in an uptrend (price expansion upwards), we look to enter long positions of retests (pullbacks) into the rays - with a stoploss set below the lowest rays; as we do not believe the uptrend is over until the trend has been broken.
Using this indicator in a downtrend (price expansion downwards), we look to enter short positions of retests (pullbacks) into the rays - with a stoploss set below the lowest rays; as we do not believe the uptrend is over until the trend has been broken.
When price is range bound or consolidating, we do not enter trades; wait for clear trend to be established.
By practicing discipline, we are able to overcome the emotions involved with trading, remove hesitation, and trade our plans more confidently through appropriate risk management and radical acceptance.
Demand and Supply Zones Intraday Strategy(SAMARESH PANDA)Explanation:
Input Parameters:
length: Determines the number of bars to look back for identifying the highest and lowest prices to mark demand and supply zones.
zoneBuffer: A buffer in pips to place the stop and limit orders near the identified demand and supply zones.
Demand and Supply Zones:
The script identifies demand zones as the lowest low over the past length bars and supply zones as the highest high over the same period.
Buy (Long) Condition:
A buy signal is generated when the price crosses above the demand zone from below and the price closes above the demand zone.
Sell (Short) Condition:
A sell signal is generated when the price crosses below the supply zone from above and the price closes below the supply zone.
Stop and Limit Orders:
For long trades, the stop is placed just below the demand zone (zoneBuffer), and the limit is placed just above the demand zone.
For short trades, the stop is placed just above the supply zone (zoneBuffer), and the limit is placed just below the supply zone.
Exit Conditions:
The long position is closed when the price moves above the supply zone.
The short position is closed when the price moves below the demand zone.
Additional Notes:
Customization: You can modify the length and zoneBuffer values to adjust how sensitive the strategy is to price action and the zone buffers.
Risk Management: You may want to add additional filters for volume, indicators like RSI/MACD, or other market conditions to filter out false signals.
Testing & Optimization: As with any strategy, it's important to backtest and optimize it according to your preferred market conditions and risk tolerance.
Using the Strategy:
Apply the script to a 1-hour or 30-minute chart for identifying the demand and supply zones.
For better precision in entry, you can switch to a lower timeframe (like 5-minute or 15-minute) to execute your trades more accurately when the price reaches a demand or supply zone.
The buy and sell signals will appear on the chart as green (BUY) and red (SELL) labels.
Example of Execution:
Long Entry: The price closes above the demand zone and crosses up. A long position is opened with a stop below the demand zone and a limit near it.
Short Entry: The price closes below the supply zone and crosses down. A short position is opened with a stop above the supply zone and a limit near it.
This strategy works best in trending markets where price tends to respect these zones. Make sure to monitor the strategy closely and adjust it based on market volatility or changes in the broader trend.
You said:
create a pine script pivot point standard for buy sell
ChatGPT said:
ChatGPT
Sure! Below is a Pine Script that implements the Pivot Point Standard for intraday trading, with buy and sell signals based on the pivot point strategy.
Pivot points are calculated based on the previous day’s high, low, and close prices, and they are widely used in intraday trading to determine potential support and resistance levels.
