Daily % Change MatrixThe "Daily % Change Matrix" is a powerful tool designed to visualize daily percentage changes in stock prices. This indicator helps traders analyze trends and volatility over time, enabling data-driven decisions.
Features
Change Calculation Options:
Choose between two methods:
Previous Close to Current Close: Calculates the percent change from the previous day's close to the current day's close.
Open to Close: Calculates the percent change from the current day's open to its close.
Customizable Table Display:
Size Options: Choose between Small, Normal, and Large.
Positioning: Place the table in any corner of the chart (Top Left, Top Right, Bottom Left, or Bottom Right).
Color Coding:
Green: Positive changes.
Red: Negative changes.
Grey: No data or negligible changes.
Table Details
Rows: Days of the month (1-31).
Columns: The last 13 months of data.
Dynamic Header: Automatically updates based on the selected calculation method.
Usage
Change your chart timeframe to Daily (D).
Configure the table's size and position via inputs.
Select the preferred calculation method.
Ideal For
Swing Traders: Identify monthly performance trends.
Analysts: Study long-term patterns across months.
Portfolio Managers: Gain insights into market behavior during specific periods.
Notes
Ensure the timeframe is set to Daily.
Use the table options to adjust for personal preference and chart space.
Contact
For any issues or suggestions, reach out to me.
Statistics
Up Gap Strategy with DelayThis strategy, titled “Up Gap Strategy with Delay,” is based on identifying up gaps in the price action of an asset. A gap is defined as the percentage difference between the current bar’s open price and the previous bar’s close price. The strategy triggers a long position if the gap exceeds a user-defined threshold and includes a delay period before entering the position. After entering, the position is held for a set number of periods before being closed.
Key Features:
1. Gap Threshold: The strategy defines an up gap when the gap size exceeds a specified threshold (in percentage terms). The gap threshold is an input parameter that allows customization based on the user’s preference.
2. Delay Period: After the gap occurs, the strategy waits for a delay period before initiating a long position. This delay can help mitigate any short-term volatility that might occur immediately after the gap.
3. Holding Period: Once the position is entered, it is held for a user-defined number of periods (holdingPeriods). This is to capture the potential post-gap trend continuation, as gaps often indicate strong directional momentum.
4. Gap Plotting: The strategy visually plots up gaps on the chart by placing a green label beneath the bar where the gap condition is met. Additionally, the background color turns green to highlight up-gap occurrences.
5. Exit Condition: The position is exited after the defined holding period. The strategy ensures that the position is closed after this time, regardless of whether the price is in profit or loss.
Scientific Background:
The gap theory has been widely studied in financial literature and is based on the premise that gaps in price often represent areas of significant support or resistance. According to research by Kaufman (2002), gaps in price action can be indicators of future price direction, particularly when they occur after a period of consolidation or a trend reversal. Moreover, Gaps and their Implications in Technical Analysis (Murphy, 1999) highlights that gaps can reflect imbalances between supply and demand, leading to high momentum and potential price continuation or reversal.
In trading strategies, utilizing gaps with specific conditions, such as delay and holding periods, can enhance the ability to capture significant price moves. The strategy’s delay period helps avoid potential market noise immediately after the gap, while the holding period seeks to capitalize on the price continuation that often follows gap formation.
This methodology aligns with momentum-based strategies, which rely on the persistence of trends in financial markets. Several studies, including Jegadeesh & Titman (1993), have documented the existence of momentum effects in stock prices, where past price movements can be predictive of future returns.
Conclusion:
This strategy incorporates gap detection and momentum principles, supported by empirical research in technical analysis, to attempt to capitalize on price movements following significant gaps. By waiting for a delay period and holding the position for a specified time, it aims to mitigate the risk associated with early volatility while maximizing the potential for sustained price moves.
Statistical Trend Analysis (Scatterplot) [BigBeluga]Statistical Trend Analysis (Scatterplot) provides a unique perspective on market dynamics by combining the statistical concept of z-scores with scatterplot visualization to assess price momentum and potential trend shifts.
🧿 What is Z-Score?
Definition: A z-score is a statistical measure that quantifies how far a data point is from the mean, expressed in terms of standard deviations.
In this Indicator:
A high positive z-score indicates the price is significantly above the average.
A low negative z-score indicates the price is significantly below the average.
The indicator also calculates the rate of change of the z-score, helping identify momentum shifts in the market.
🧿 Key Features:
Scatterplot Visualization:
Displays data points of z-score and its change across four quadrants.
Quadrants help interpret market conditions:
Upper Right (Strong Bullish Momentum): Most data points here signal an ongoing uptrend.
Upper Left (Weakening Momentum): Data points here may indicate a potential market shift or ranging market.
Lower Left (Strong Bearish Momentum): Indicates a dominant downtrend.
Lower Right (Trend Shift to Bullish/Ranging): Suggests weakening bearish momentum or an emerging uptrend.
Color-Coded Candles:
Candles are dynamically colored based on the z-score, providing a visual cue about the price's deviation from the mean.
Z-Score Time Series:
A line plot of z-scores over time shows price deviation trends.
A gray histogram displays the rate of change of the z-score, highlighting momentum shifts.
🧿 Usage:
Use the scatterplot and quadrant gauges to understand the current market momentum and potential shifts.
Monitor the z-score line plot to identify overbought/oversold conditions.
Utilize the gray histogram to detect momentum reversals and trend strength.
This tool is ideal for traders who rely on statistical insights to confirm trends, detect potential reversals, and assess market momentum visually and quantitatively.
ROE BandROE Band shows the return on net profit from shareholders' equity and the formula for decomposition
ROE = ROA x CSL x CEL
ROE Band consists of 5 parts:
1. ROE (TTM) is the 12-month ROE calculation in "green"
2. Return on Equity (ROE) is the current quarterly net profit / the average of the beginning and ending periods of shareholders' equity in "yellow"
3. Return on Assets (ROA) is the current quarterly NOPAT (net profit before tax) / the average of the beginning and ending periods of total assets in "blue"
4. Capital structure leverage (CSL) is a financial measure that compares a company's debt to its total capital. It is calculated by taking the average of the beginning and ending periods of total assets / the average of the beginning and ending periods of shareholders' equity. The higher the CSL, the more deb, in. "red"
5. Common earnings leverage (CEL) is the proportion of net profit and NOPAT (net profit before tax), where a lower CEL means more tax, in "orange"
The "😱" emoji represents the value if it increases by more than or decreases by less than 20%, e.g.
- ROE(TTM), ROE, ROA, CEL is decreasing
- CSL is increasing
The "🔥" emoji represents the value if it increases by more than or decreases, e.g.
- ROE(TTM), ROE, ROA, CEL is increasing
- CSL is decreasing
NSE & BSE Option Chain - Auto Option Data InputDefinition
An options chain is a list of all available option contracts for a specific security, organized by expiration date and strike price.
What Is an Options Chain ?
Understanding how to read and analyze options chains is crucial for investors venturing into options trading. These display all available option contracts for a particular security, typically in a table format that organizes contracts by expiration date and strike price. The tool provides a wealth of information at a glance, including present prices, trading volume, and implied volatility (IV) for both call and put options.
While the long list of prices and other information can look at first to be overly complicated, learning to navigate an options chain will significantly improve your ability to trade in these derivatives and identify prospects in the market. As options continue to gain popularity among retail investors, mastering the intricacies of the options chain has become an essential skill for those looking to expand their trading strategies beyond traditional stock investments.
Key Takeaways
An options chain displays all available option contracts for a security, organized by expiration date and strike price.
Options chains typically show each contract's bid price, ask price, volume, open interest, and implied volatility (IV).
Options chains can be used to identify trading prospects, such as mispriced options or favorable risk-reward scenarios.
Understanding Options Chains
Option chains list all available option contracts for a particular underlying security. For traders, they provide a snapshot of crucial information about each contract, including strike prices, expiration dates, and market prices.
Typically organized in a table, options chains have separate sections for call and put options. The rows represent different strike prices, while the columns show various data points for each contract. This lets traders quickly compare options with different characteristics to make informed decisions.
Decoding Options Chains
The columns of an option chain, as seen in the example chart above, include the following:
Strike price: The price the option holder can buy (for calls) or sell (for puts) the underlying asset.
Expiration date: The last day the option contract is valid.
1
Bid price: The highest price a buyer is willing to pay for the option.
Ask price: The lowest price a seller is willing to accept for the option.
Last price: The most recent trading price for the option.
Percentage change: The net change column reflects the direction (up, down, or flat) for the underlying asset, as well as the amount of the price shift.
Volume: The number of contracts traded during the current session.
2
Open interest: The total of outstanding contracts.
Mastering the art of reading options chains is essential for any serious options trader. It's where market sentiment, price inefficiencies, and trading prospects all come together.
In options trading, information is power. A well-analyzed option chain can reveal market inefficiencies that savvy traders can exploit. For example, comparing the bid-ask spread across different strike prices can help identify more liquid options, while analyzing open interest can help you understand market sentiment.
A skilled user can quickly decipher an options chain for what it says about price moves and where there are high and low levels of liquidity. For the best trades, this is critical information. For those not quite there yet, let's break down other parts of the options chain tables into manageable parts:
Calls vs. puts: Option chains typically separate call options (the right to buy) from put options (the right to sell). This division allows traders to focus straightaway on bullish or bearish strategies.
Filters and customization: Most trading platforms enable you to customize your options chain view. You can quickly filter by expiration date, strike price range, or specific Greek values to focus on the most relevant contracts.
The Bottom Line
The options chain is indispensable for options traders, providing a comprehensive view of all available contracts for a given security. By learning to read and analyze options chains, you can gain greater clarity about market sentiment, identify trading prospects, and make more informed decisions for your options strategies.
While it takes a bit of time to become proficient in interpreting all the data presented, mastering the options chain is crucial for those looking to leverage the full potential of options trading in their investment approaches.
Fully Auto Option Data Input for All Currently Available NSE Indices and Stock & BSE Sensex Indices
ATH DrawdownThis Pine Script indicator, titled "ATH Drawdown," is designed to help traders and analysts visualize various drawdown levels from the all-time high (ATH) of a security over the past 365 days. This indicator plots several key drawdown levels on the chart and dynamically updates their color and labels to reflect market conditions.
Key Features:
Daily High Calculation:
Fetches the daily high prices for the security using the request.security function.
Highest High Calculation:
Calculates the highest high over the last 365 days using daily data. This represents the all-time high (ATH) for the specified period.
Drawdown Levels:
Computes various drawdown levels from the ATH:
2% Drawdown
5% Drawdown
10% Drawdown
15% Drawdown
25% Drawdown
45% Drawdown
50% Drawdown
Dynamic Line Coloring:
The color of the 2% drawdown line changes dynamically based on the current closing price:
Red if the close is below the 2% drawdown level.
Green if the close is above the 2% drawdown level.
Plotting Drawdown Levels:
Plots each drawdown level on the chart with specific colors and line widths for easy visual distinction:
2% Drawdown: Green or Red, depending on the closing price.
5% Drawdown: Orange.
10% Drawdown: Blue.
15% Drawdown: Maroon.
25% Drawdown: Purple.
45% Drawdown: Yellow.
50% Drawdown: Black.
Labels for Drawdown Levels:
Adds labels at the end of each drawdown line to indicate the percentage drawdown:
Labels display "2%", "5%", "10%", "15%", "25%", "45%", and "50%" respectively.
The labels are positioned dynamically at the latest bar index to ensure they are always visible.
Example Use Cases:
Risk Management: Quickly identify significant drawdown levels to assess the risk of current positions.
Support Levels: Use drawdown levels as potential support levels where price might find buying interest.
Performance Tracking: Monitor how far the price has retraced from its all-time high to understand market sentiment and performance.
This script offers traders and analysts an efficient way to visualize and track important drawdown levels from the ATH, helping in better risk management and decision-making. The dynamic color and label features enhance the readability and usability of the indicator.
Multiple Values TableThis Pine Script indicator, named "Multiple Values Table," provides a comprehensive view of various technical indicators in a tabular format directly on your trading chart. It allows traders to quickly assess multiple metrics without switching between different charts or panels.
Key Features:
Table Position and Size:
Users can choose the position of the table on the chart (e.g., top left, top right).
The size of the table can be adjusted (e.g., tiny, small, normal, large).
Moving Averages:
Calculates the 5-day Exponential Moving Average (5DEMA) using daily data.
Calculates the 5-week and 20-week EMAs (5WEMA and 20WEMA) using weekly data.
Indicates whether the current price is above or below these moving averages in percentage terms.
Drawdown and Williams VIX Fix:
Computes the drawdown from the 365-day high to the current close.
Calculates the Williams VIX Fix (WVF), which measures the volatility of the asset.
Shows both the current WVF and a 2% drawdown level.
Relative Strength Index (RSI):
Displays the current RSI and compares it to the RSI from 14 days ago.
Indicates whether the RSI is increasing, decreasing, or flat.
Stochastic RSI:
Computes the Stochastic RSI and compares it to the value from 14 days ago.
Indicates whether the Stochastic RSI is increasing, decreasing, or flat.
Normalized MACD (NMACD):
Calculates the Normalized MACD values.
Indicates whether the MACD is increasing, decreasing, or flat.
Awesome Oscillator (AO):
Calculates the AO on a daily timeframe.
Indicates whether the AO is increasing, decreasing, or flat.
Volume Analysis:
Displays the average volume over the last 22 days.
Shows the current day's volume as a percentage of the average volume.
Percentile Calculations:
Calculates the current percentile rank of the WVF and ATH over specified periods.
Indicates the percentile rank of the current volume percentage over the past period.
Table Display:
All these values are presented in a neatly formatted table.
The table updates dynamically with the latest data.
Example Use Cases:
Comprehensive Market Analysis: Quickly assess multiple indicators at a glance.
Trend and Momentum Analysis: Identify trends and momentum changes based on various moving averages and oscillators.
Volatility and Drawdown Monitoring: Track volatility and drawdown levels to manage risk effectively.
This script offers a powerful tool for traders who want to have a holistic view of various technical indicators in one place. It provides flexibility in customization and a user-friendly interface to enhance your trading experience.
RSI Trend [MacroGlide]The RSI Trend indicator is a versatile and intuitive tool designed for traders who want to enhance their market analysis with visual clarity. By combining Stochastic RSI with moving averages, this indicator offers a dynamic view of market momentum and trends. Whether you're a beginner or an experienced trader, this tool simplifies identifying key market conditions and trading opportunities.
Key Features:
• Stochastic RSI-Based Calculations: Incorporates Stochastic RSI to provide a nuanced view of overbought and oversold conditions, enhancing standard RSI analysis.
• Dynamic Moving Averages: Includes two customizable moving averages (MA1 and MA2) based on smoothed Stochastic RSI, offering flexibility to align with your trading strategy.
• Candle Color Coding: Automatically colors candles on the chart:
• Blue: When the faster moving average (MA2) is above the slower one (MA1), signaling bullish momentum.
• Orange: When the faster moving average is below the slower one, indicating bearish momentum.
• Integrated Scaling: The indicator dynamically adjusts with the chart's scale, ensuring seamless visualization regardless of zoom level.
How to Use:
• Add the Indicator: Apply the indicator to your chart from the TradingView library.
• Interpret Candle Colors: Use the color-coded candles to quickly identify bullish (blue) and bearish (orange) phases.
• Customize to Suit Your Needs: Adjust the lengths of the moving averages and the Stochastic RSI parameters to better fit your trading style and timeframe.
• Combine with Other Tools: Pair this indicator with trendlines, volume analysis, or support and resistance levels for a comprehensive trading approach.
Methodology:
The indicator utilizes Stochastic RSI, a derivative of the standard RSI, to measure momentum more precisely. By applying smoothing and calculating moving averages, the tool identifies shifts in market trends. These trends are visually represented through candle color changes, making it easy to spot transitions between bullish and bearish phases at a glance.
Originality and Usefulness:
What sets this indicator apart is its seamless integration of Stochastic RSI and moving averages with real-time candle coloring. The result is a visually intuitive tool that adapts dynamically to chart scaling, offering clarity without clutter.
Charts:
When applied, the indicator plots two moving averages alongside color-coded candles. The combination of visual cues and trend logic helps traders easily interpret market momentum and make informed decisions.
Enjoy the game!
Z-Score Indicator by RafIf the z-score goes above 2, this may indicate overbought and If the z-score goes below -2, this may indicate oversold
Smooth RSI [MarktQuant]This indicator combines elements of the Relative Strength Index (RSI) and Rate of Change (RoC) to provide a smoother and potentially more insightful view of market momentum and price movement. The Smooth RSI calculates RSI values across four price points (high, open, low, close) to average them, offering a less volatile RSI signal. Additionally, it incorporates a Rate of Change for trend confirmation, enhancing the decision-making process for trade entries and exits.
Features:
Multi-RSI Calculation: RSI is computed for high, open, low, and close prices, then averaged to reduce noise.
Trend Confirmation with RoC: Uses the Rate of Change to validate the RSI signals, coloring bars based on the trend direction.
Visual Signals:
Bar colors change based on combined RSI and RoC signals.
Green for bullish signals (RSI above 50 and positive RoC).
Red for bearish signals (RSI below 50 and negative RoC).
Horizontal lines at 30, 50, and 70 to denote overbought, neutral, and oversold conditions.
Customizable Display:
Option to show/hide RSI plot or RoC plot for cleaner charts.
Candle plot overlay option to visualize current price action alongside the indicator.
Inputs:
RSI Length: Default 28. Adjusts the lookback period for RSI calculation.
RoC Length: Default 28. Sets the period for the Rate of Change calculation.
Plot Settings:
Show RSI - Toggle RSI plot visibility.
Show RoC - Toggle RoC plot visibility.
Usage:
Long signals are indicated when the average RSI is above 50 and the RoC is positive.
Short signals are suggested when the average RSI falls below 50 with a negative RoC.
The color coding helps visually confirm trends at a glance.
Notes:
This indicator is best used in conjunction with other analysis methods to confirm signals.
Adjust the length parameters based on your trading timeframe for optimal results.
Disclaimer:
This indicator does not guarantee trading success; use it as part of a comprehensive trading strategy. Always conduct your own analysis before making trading decisions.
TradeShields Strategy Builder🛡 WHAT IS TRADESHIELDS?
This no-code strategy builder is designed for traders on TradingView, offering an intuitive platform to create, backtest, and automate trading strategies. While identifying signals is often straightforward, the real challenge in trading lies in managing risk and knowing when not to trade. It equips users with advanced tools to address this challenge, promoting disciplined decision-making and structured trading practices.
This is not just a collection of indicators but a comprehensive toolkit that helps identify high-quality opportunities while placing risk management at the core of every strategy. By integrating customizable filters, robust controls, and automation capabilities, it empowers traders to align their strategies with their unique objectives and risk tolerance.
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🛡 THE GOAL: SHIELD YOUR STRATEGY
The mission is simple: to shield your strategy from bad trades . Whether you're a seasoned trader or just starting, the hardest part of trading isn’t finding signals—it’s avoiding trades that can harm your account. This framework prioritizes quality over quantity , helping filter out suboptimal setups and encouraging disciplined execution.
With tools to manage risk, avoid overtrading, and adapt to changing market conditions, it protects your strategy against impulsive decisions and market volatility.
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🛡 HOW TO USE IT
1. Apply Higher Timeframe Filters
Begin by analyzing broader market trends using tools like the 200 EMA, Ichimoku Cloud, or Supertrend on higher timeframes (e.g., daily or 4-hour charts).
- Example: Ensure the price is above the 200 EMA on the daily chart for long trades or below it for short trades.
2. Identify the Appropriate Entry Signal
Choose an entry signal that aligns with your model and the asset you're trading. Options include:
Supertrend changes for trend reversals.
Bollinger Band touches for mean-reversion trades.
RSI strength/weakness for overbought or oversold conditions.
Breakouts of key levels (e.g., daily or weekly highs/lows) for momentum trades.
MACD and TSI flips.
3. Determine Take-Profit and Stop-Loss Levels
Set clear exit strategies to protect your capital and lock in profits:
Use single, dual, or triple take-profit levels based on percentages or price levels.
Choose a stop-loss type, such as fixed percentage, ATR-based, or trailing stops.
Optionally, set breakeven adjustments after hitting your first take-profit target.
4. Apply Risk Management Filters
Incorporate risk controls to ensure disciplined execution:
Limit the number of trades per day, week, or month to avoid overtrading.
Use time-based filters to trade during specific sessions or custom windows.
Avoid trading around high-impact news events with region-specific filters.
5. Automate and Execute
Leverage the advanced automation features to streamline execution. Alerts are tailored specifically for each supported platform, ensuring seamless integration with tools like PineConnector, 3Commas, Zapier, and more.
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🛡 CORE FOCUS: RISK MANAGEMENT, AUTOMATION, AND DISCIPLINED TRADING
This builder emphasizes quality over quantity, encouraging traders to approach markets with structure and control. Its innovative tools for risk management and automation help optimize performance while reducing effort, fostering consistency and long-term success.
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🛡 KEY FEATURES
General Settings
Theme Customization : Light and dark themes for a tailored interface.
Timezone Adjustment : Align session times and news schedules with your local timezone.
Position Sizing : Define lot sizes to manage risk effectively.
Directional Control : Choose between long-only, short-only, or both directions for trading.
Time Filters
Day-of-Week Selection : Enable or disable trading on specific days.
Session-Based Trading : Restrict trades to major market sessions (Asia, London, New York) or custom windows.
Custom Time Windows : Precisely control the timeframes for trade execution.
Risk Management Tools
Trade Limits : Maximum trades per day, week, or month to avoid overtrading.
Automatic Trade Closures : End-of-session, end-of-day, or end-of-week options.
Duration-Based Filters : Close trades if take-profit isn’t reached within a set timeframe or if they remain unprofitable beyond a specific duration.
Stop-Loss and Take-Profit Options : Fixed percentage or ATR-based stop-losses, single/dual/triple take-profit levels, and breakeven stop adjustments.
Economic News Filters
Region-Specific Filters : Exclude trades around major news events in regions like the USA, UK, Europe, Asia, or Oceania.
News Avoidance Windows : Pause trades before and after high-impact events or automatically close trades ahead of scheduled news releases.
Higher Timeframe Filters
Multi-Timeframe Tools : Leverage EMAs, Supertrend, or Ichimoku Cloud on higher timeframes (Daily, 4-hour, etc.) for trend alignment.
Chart Timeframe Filters
Precision Filtering : Apply EMA or ADX-based conditions to refine trade setups on current chart timeframes.
Entry Signals
Customizable Options : Choose from signals like Supertrend, Bollinger Bands, RSI, MACD, Ichimoku Cloud, or EMA pullbacks.
Indicator Parameter Overrides : Fine-tune default settings for specific signals.
Exit Settings
Flexible Take-Profit Targets : Single, dual, or triple targets. Exit at significant levels like daily/weekly highs or lows.
Stop-Loss Variability : Fixed, ATR-based, or trailing stop-loss options.
Alerts and Automation
Third-Party Integrations : Seamlessly connect with platforms like PineConnector, 3Commas, Zapier, and Capitalise.ai.
Precision-Formatted Alerts : Alerts are tailored specifically for each platform, ensuring seamless execution. For example:
- PineConnector alerts include risk-per-trade parameters.
- 3Commas alerts contain bot-specific configurations.
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🛡 PUBLISHED CHART SETTINGS: 15m COMEX:GC1!
Time Filters : Trades are enabled from Tuesday to Friday, as Mondays often lack sufficient data coming off the weekend, and weekends are excluded due to market closures. Custom time sessions are turned off by default, allowing trades throughout the day.
Risk Filters : Risk is tightly controlled by limiting trades to a maximum of 2 per day and enabling a mechanism to close trades if they remain open too long and are unprofitable. Weekly trade closures ensure that no positions are carried over unnecessarily.
Economic News Filters : By default, trades are allowed during economic news periods, giving traders flexibility to decide how to handle volatility manually. It is recommended to enable these filters if you are creating strategies on lower timeframes.
Higher Timeframe Filters : The setup incorporates confluence from higher timeframe indicators. For example, the 200 EMA on the daily timeframe is used to establish trend direction, while the Ichimoku cloud on the 30-minute timeframe adds additional confirmation.
Entry Signals : The strategy triggers trades based on changes in the Supertrend indicator.
Exit Settings : Trades are configured to take partial profits at three levels (1%, 2%, and 3%) and use a fixed stop loss of 2%. Stops are moved to breakeven after reaching the first take profit level.
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🛡 WHY CHOOSE THIS STRATEGY BUILDER?
This tool transforms trading from reactive to proactive, focusing on risk management and automation as the foundation of every strategy. By helping users avoid unnecessary trades, implement robust controls, and automate execution, it fosters disciplined trading.
NexTrade
Overview of NexTrade: The Future of Crypto Trading
Introduction
NexTrade is a cutting-edge algorithmic trading platform designed to optimize cryptocurrency trading strategies. Developed by myself, a software engineer with a passion for quantitative development. Over the past year, I have focused on learning and applying quantitative techniques to the crypto space, ultimately crafting a platform that leverages advanced market analysis, automation, and robust risk management to help investors maximize returns while minimizing risk. NexTrade is engineered to help you capitalize on market movements in a fast-paced and highly competitive space, that is Cryptocurrency.
Key Features and Advantages
Sophisticated Market Analysis: NexTrade uses a comprehensive market analysis framework that examines historical trends, price movements, and market conditions across multiple cryptocurrency exchanges. The algorithm identifies trading opportunities by chart analysis on higher timeframes in order to follow trends, allowing it to execute trades at optimal moments.
Multi-Exchange Integration: NexTrade connects to multiple leading cryptocurrency exchanges, such as Binance, Kraken, and Coinbase Pro, to ensure access to diverse liquidity pools. This multi-exchange connectivity allows the platform to execute trades at the most favorable prices, optimizing profitability and minimizing slippage across various platforms. However, we suggest using the exchange with lowest fees possible.
Risk Management: NexTrade’s risk management features such as Stop Losses, ATR Trailing SL, and ADX chop indicator allows us to ensure we are effectively managing our risk.
Backtesting and Optimization: Before going live, NexTrade’s trading strategies undergo rigorous backtesting using historical market data. This enables users to see how strategies would have performed under various conditions, providing transparency and confidence in the platform’s potential for generating consistent returns. Ongoing optimization ensures that strategies evolve in response to market changes.
Real-Time Performance Monitoring: Users have access to detailed, real-time performance reports, tracking key metrics such as trades executed, profits, losses, and overall portfolio performance. This transparency allows investors to make informed decisions and monitor their investments closely at any time.
Market Opportunity
The cryptocurrency market continues to experience rapid growth, with trillions of dollars in trading volume annually. However, it is also notoriously volatile, creating both risk and reward opportunities for traders. To successfully navigate this market, investors need sophisticated tools that can automate the trading process and optimize decisions based on accurate market analysis.
NexTrade was developed to address this need. With its combination of data-driven market analysis, automated execution, and risk management, NexTrade is positioned to help investors gain an edge in a market that is often unpredictable and challenging. The platform offers a reliable, scalable solution to crypto trading, designed for both beginners and seasoned professionals.
Why Invest in NexTrade?
Scalable and Flexible: Whether you’re trading small amounts or large volumes, NexTrade can scale to accommodate your needs. The platform supports multiple exchanges, giving users the flexibility to diversify and grow their investments. Users can start with as low as $100!
Risk-Adjusted Returns: By focusing on risk management, NexTrade aims to deliver returns that are balanced with the level of risk the investor is willing to accept. The algorithm continuously adjusts trading strategies to align with market conditions, maximizing the potential for profits while minimizing the likelihood of significant losses.
24/7 Trading: The cryptocurrency market operates around the clock, and NexTrade is designed to take advantage of this. Its automated nature means that it can execute trades at any time, without the need for human intervention.
Conclusion
NexTrade offers a sophisticated yet accessible solution for investors looking to capitalize on the growth of the cryptocurrency market. With its focus on data-driven analysis, automated trade execution, and advanced risk management, NexTrade empowers investors to achieve optimal returns while managing risk effectively. Whether you are new to crypto or an experienced trader, NexTrade provides the tools needed to stay competitive and succeed in a fast-moving market.
By investing in NexTrade, you are gaining access to a proven algorithmic trading platform that has the potential to enhance your crypto trading strategy and deliver consistent results. The future of cryptocurrency trading is automated, risk-managed, and optimized—and NexTrade is leading the way.
If users wish the enable the chop detector on the bot, which uses ADX, they can turn it on in the settings after the strategu is added to the chart. By default, it is set to false.
Market Correlation AnalysisMarket Correlation Analysis is an indicator that measures the correlation of any two instruments.
To express price changes in a way that is comparable, this indicator uses a percentage of the ATR as a unit.
User Inputs:
Other Symbol - the symbol which we want to compare with the symbol of the main chart.
ATR for Price Movement Normalisation - I recommend high values to get the ATR more stable across time - if the ATR drastically changes, the indicator will register that as a price movement, because the unit in which price movements are measured itself changed by a lot. However, with higher values the ATR is stable and, in my opinion, more reliable than simply a percentage change of the current price.
Correlation Length - this is the number of bars for which the correlation coefficient will be calculated.
About The Indicator:
Market Correlation Analysis expresses the price changes of both instruments in question on the same histogram.
By default, the price changes that represent the instrument of the main chart are expressed with thinner bars of stronger colour, while the price changes that represent the other instrument are expressed with much thicker bars, which are of more pale colour.
The correlation coefficient is not expressed on the histogram, as it has a different scale. Therefore, it is only showed as a number.
I hope this indicator can make it easier to understand just how much two instruments have been similar to one another over a certain period of time. The possibility to see the correlation for any given time frame can give information that very specific to any trading style.
Enhanced Price Z-Score OscillatorThe Enhanced Price Z-Score Oscillator by tkarolak is a powerful tool that transforms raw price data into an easy-to-understand statistical visualization using Z-Score-derived candlesticks. Simply put, it shows how far prices stray from their average in terms of standard deviations (Z-Scores), helping traders identify when prices are unusually high (overbought) or unusually low (oversold).
The indicator’s default feature displays Z-Score Candlesticks, where each candle reflects the statistical “distance” of the open, high, low, and close prices from their average. This creates a visual map of market extremes and potential reversal points. For added flexibility, you can also switch to Z-Score line plots based on either Close prices or OHLC4 averages.
With clear threshold lines (±2σ and ±3σ) marking moderate and extreme price deviations, and color-coded zones to highlight overbought and oversold areas, the oscillator simplifies complex statistical concepts into actionable trading insights.
Temporary Help Services Jobs - Trend Allocation StrategyThis strategy is designed to capitalize on the economic trends represented by the Temporary Help Services (TEMPHELPS) index, which is published by the Federal Reserve Economic Data (FRED). Temporary Help Services Jobs are often regarded as a leading indicator of labor market conditions, as changes in temporary employment levels frequently precede broader employment trends.
Methodology:
Data Source: The strategy uses the FRED dataset TEMPHELPS for monthly data on temporary help services.
Trend Definition:
Uptrend: When the current month's value is greater than the previous month's value.
Downtrend: When the current month's value is less than the previous month's value.
Entry Condition: A long position is opened when an uptrend is detected, provided no position is currently held.
Exit Condition: The long position is closed when a downtrend is detected.
Scientific Basis:
The TEMPHELPS index serves as a leading economic indicator, as noted in studies analyzing labor market cyclicality (e.g., Katz & Krueger, 1999). Temporary employment is often considered a proxy for broader economic conditions, particularly in predicting recessions or recoveries. Incorporating this index into trading strategies allows for aligning trades with potential macroeconomic shifts, as suggested by research on employment trends and market performance (Autor, 2001; Valetta & Bengali, 2013).
Usage:
This strategy is best suited for long-term investors or macroeconomic trend followers who wish to leverage labor market signals for equity or futures trading. It operates exclusively on end-of-month data, ensuring minimal transaction costs and noise.
Option Time ValueThis TradingView script calculates and visualizes the time value of an option (Call or Put) based on its market price and intrinsic value. The time value represents the premium paid for the option above its intrinsic value, and it is a key metric for analyzing the cost of holding an option.
This script is suitable for traders analyzing options on indices or stocks, such as the NIFTY 50, and supports both Call and Put options. By dynamically extracting the strike price and option type from the input symbol, it adapts seamlessly to the selected instrument.
Key Features:
Dynamic Instrument Selection:
Users can input the underlying asset (e.g., NSE:NIFTY) and the specific option instrument (e.g., NSE:NIFTY250327C24000 for a Call or NSE:NIFTY250327P24000 for a Put).
Automatic Option Type Detection:
The script detects whether the option is a Call or a Put by parsing the input symbol for the characters "C" (Call) or "P" (Put).
Dynamic Strike Price Extraction:
The strike price is dynamically extracted from the input option symbol, eliminating the need for hardcoding and reducing user errors.
Key Metrics Plotted:
Time Value: The premium paid above the intrinsic value, plotted in blue.
Intrinsic Value: The calculated intrinsic value of the option, plotted in green.
Seamless Integration:
Designed for ease of use and integration into existing TradingView setups.
Automatically adjusts to the timeframe and pricing data of the selected instruments.
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.
Z-Strike RecoveryThis strategy utilizes the Z-Score of daily changes in the VIX (Volatility Index) to identify moments of extreme market panic and initiate long entries. Scientific research highlights that extreme volatility levels often signal oversold markets, providing opportunities for mean-reversion strategies.
How the Strategy Works
Calculation of Daily VIX Changes:
The difference between today’s and yesterday’s VIX closing prices is calculated.
Z-Score Calculation:
The Z-Score quantifies how far the current change deviates from the mean (average), expressed in standard deviations:
Z-Score=(Daily VIX Change)−MeanStandard Deviation
Z-Score=Standard Deviation(Daily VIX Change)−Mean
The mean and standard deviation are computed over a rolling period of 16 days (default).
Entry Condition:
A long entry is triggered when the Z-Score exceeds a threshold of 1.3 (adjustable).
A high positive Z-Score indicates a strong overreaction in the market (panic).
Exit Condition:
The position is closed after 10 periods (days), regardless of market behavior.
Visualizations:
The Z-Score is plotted to make extreme values visible.
Horizontal threshold lines mark entry signals.
Bars with entry signals are highlighted with a blue background.
This strategy is particularly suitable for mean-reverting markets, such as the S&P 500.
Scientific Background
Volatility and Market Behavior:
Studies like Whaley (2000) demonstrate that the VIX, known as the "fear gauge," is highly correlated with market panic phases. A spike in the VIX is often interpreted as an oversold signal due to excessive hedging by investors.
Source: Whaley, R. E. (2000). The investor fear gauge. Journal of Portfolio Management, 26(3), 12-17.
Z-Score in Financial Strategies:
The Z-Score is a proven method for detecting statistical outliers and is widely used in mean-reversion strategies.
Source: Chan, E. (2009). Quantitative Trading. Wiley Finance.
Mean-Reversion Approach:
The strategy builds on the mean-reversion principle, which assumes that extreme market movements tend to revert to the mean over time.
Source: Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
MA Deviation Suite [InvestorUnknown]This indicator combines advanced moving average techniques with multiple deviation metrics to offer traders a versatile tool for analyzing market trends and volatility.
Moving Average Types :
SMA, EMA, HMA, DEMA, FRAMA, VWMA: Standard moving averages with different characteristics for smoothing price data.
Corrective MA: This method corrects the MA by considering the variance, providing a more responsive average to price changes.
f_cma(float src, simple int length) =>
ma = ta.sma(src, length)
v1 = ta.variance(src, length)
v2 = math.pow(nz(ma , ma) - ma, 2)
v3 = v1 == 0 or v2 == 0 ? 1 : v2 / (v1 + v2)
var tolerance = math.pow(10, -5)
float err = 1
// Gain Factor
float kPrev = 1
float k = 1
for i = 0 to 5000 by 1
if err > tolerance
k := v3 * kPrev * (2 - kPrev)
err := kPrev - k
kPrev := k
kPrev
ma := nz(ma , src) + k * (ma - nz(ma , src))
Fisher Least Squares MA: Aims to reduce lag by using a Fisher Transform on residuals.
f_flsma(float src, simple int len) =>
ma = src
e = ta.sma(math.abs(src - nz(ma )), len)
z = ta.sma(src - nz(ma , src), len) / e
r = (math.exp(2 * z) - 1) / (math.exp(2 * z) + 1)
a = (bar_index - ta.sma(bar_index, len)) / ta.stdev(bar_index, len) * r
ma := ta.sma(src, len) + a * ta.stdev(src, len)
Sine-Weighted MA & Cosine-Weighted MA: These give more weight to middle bars, creating a smoother curve; Cosine weights are shifted for a different focus.
Deviation Metrics :
Average Absolute Deviation (AAD) and Median Absolute Deviation (MAD): AAD calculates the average of absolute deviations from the MA, offering a measure of volatility. MAD uses the median, which can be less sensitive to outliers.
Standard Deviation (StDev): Measures the dispersion of prices from the mean.
Average True Range (ATR): Reflects market volatility by considering the day's range.
Average Deviation (adev): The average of previous deviations.
// Calculate deviations
float aad = f_aad(src, dev_len, ma) * dev_mul
float mad = f_mad(src, dev_len, ma) * dev_mul
float stdev = ta.stdev(src, dev_len) * dev_mul
float atr = ta.atr(dev_len) * dev_mul
float avg_dev = math.avg(aad, mad, stdev, atr)
// Calculated Median with +dev and -dev
float aad_p = ma + aad
float aad_m = ma - aad
float mad_p = ma + mad
float mad_m = ma - mad
float stdev_p = ma + stdev
float stdev_m = ma - stdev
float atr_p = ma + atr
float atr_m = ma - atr
float adev_p = ma + avg_dev
float adev_m = ma - avg_dev
// upper and lower
float upper = f_max4(aad_p, mad_p, stdev_p, atr_p)
float upper2 = f_min4(aad_p, mad_p, stdev_p, atr_p)
float lower = f_min4(aad_m, mad_m, stdev_m, atr_m)
float lower2 = f_max4(aad_m, mad_m, stdev_m, atr_m)
Determining Trend
The indicator generates trend signals by assessing where price stands relative to these deviation-based lines. It assigns a trend score by summing individual signals from each deviation measure. For instance, if price crosses above the MAD-based upper line, it contributes a bullish point; crossing below an ATR-based lower line contributes a bearish point.
When the aggregated trend score crosses above zero, it suggests a shift towards a bullish environment; crossing below zero indicates a bearish bias.
// Define Trend scores
var int aad_t = 0
if ta.crossover(src, aad_p)
aad_t := 1
if ta.crossunder(src, aad_m)
aad_t := -1
var int mad_t = 0
if ta.crossover(src, mad_p)
mad_t := 1
if ta.crossunder(src, mad_m)
mad_t := -1
var int stdev_t = 0
if ta.crossover(src, stdev_p)
stdev_t := 1
if ta.crossunder(src, stdev_m)
stdev_t := -1
var int atr_t = 0
if ta.crossover(src, atr_p)
atr_t := 1
if ta.crossunder(src, atr_m)
atr_t := -1
var int adev_t = 0
if ta.crossover(src, adev_p)
adev_t := 1
if ta.crossunder(src, adev_m)
adev_t := -1
int upper_t = src > upper ? 3 : 0
int lower_t = src < lower ? 0 : -3
int upper2_t = src > upper2 ? 1 : 0
int lower2_t = src < lower2 ? 0 : -1
float trend = aad_t + mad_t + stdev_t + atr_t + adev_t + upper_t + lower_t + upper2_t + lower2_t
var float sig = 0
if ta.crossover(trend, 0)
sig := 1
else if ta.crossunder(trend, 0)
sig := -1
Backtesting and Performance Metrics
The code integrates with a backtesting library that allows traders to:
Evaluate the strategy historically
Compare the indicator’s signals with a simple buy-and-hold approach
Generate performance metrics (e.g., mean returns, Sharpe Ratio, Sortino Ratio) to assess historical effectiveness.
Practical Usage and Calibration
Default settings are not optimized: The given parameters serve as a starting point for demonstration. Users should adjust:
len: Affects how smooth and lagging the moving average is.
dev_len and dev_mul: Influence the sensitivity of the deviation measures. Larger multipliers widen the bands, potentially reducing false signals but introducing more lag. Smaller multipliers tighten the bands, producing quicker signals but potentially more whipsaws.
This flexibility allows the trader to tailor the indicator for various markets (stocks, forex, crypto) and time frames.
Disclaimer
No guaranteed results: Historical performance does not guarantee future outcomes. Market conditions can vary widely.
User responsibility: Traders should combine this indicator with other forms of analysis, appropriate risk management, and careful calibration of parameters.
Ultra Trade JournalThe Ultra Trade Journal is a powerful TradingView indicator designed to help traders meticulously document and analyze their trades. Whether you're a novice or an experienced trader, this tool offers a clear and organized way to visualize your trading strategy, monitor performance, and make informed decisions based on detailed trade metrics.
Detailed Description
The Ultra Trade Journal indicator allows users to input and visualize critical trade information directly on their TradingView charts.
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User Inputs
Traders can specify entry and exit prices , stop loss levels, and up to four take profit targets.
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Dynamic Plotting
Once the input values are set, the indicator automatically plots horizontal lines for entry, exit, stop loss, and each take profit level on the chart. These lines are visually distinct, using different colors and styles (solid, dashed, dotted) to represent each element clearly.
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Live Position Tracking
If enabled, the indicator can adjust the exit price in real-time based on the current market price, allowing traders to monitor live positions effectively.
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Tick Calculations
The script calculates the number of ticks between the entry price and each exit point (stop loss and take profits). This helps in understanding the movement required for each target and assessing the potential risk and reward.
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Risk-Reward Ratios
For each take profit level, the indicator computes the risk-reward (RR) ratio by comparing the ticks at each target against the stop loss ticks. This provides a quick view of the potential profitability versus the risk taken.
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Comprehensive Table Display
A customizable table is displayed on the chart, summarizing all key trade details. This includes the entry and exit prices, stop loss and take profit levels, tick counts, and their respective RR ratios.
Users can adjust the table's Position and text color to suit their preferences.
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Visual Enhancements
The indicator uses adjustable background shading between entry and stop loss/take profit lines to visually represent potential trade outcomes. This shading adjusts based on whether the trade is long or short, providing an intuitive understanding of trade performance.
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Overall, the Ultra Trade Journal combines visual clarity with detailed analytics, enabling traders to keep a well-organized record of their trades and enhance their trading strategies through insightful data.
