Sine-Weighted MA ATR [InvestorUnknown]The Sine-Weighted MA ATR is a technical analysis tool designed to emphasize recent price data using sine-weighted calculations , making it particularly well-suited for analyzing cyclical markets with repetitive patterns . The indicator combines the Sine-Weighted Moving Average (SWMA) and a Sine-Weighted Average True Range (SWATR) to enhance price trend detection and volatility analysis.
Sine-Weighted Moving Average (SWMA):
Unlike traditional moving averages that apply uniform or exponentially decaying weights, the SWMA applies Sine weights to the price data.
Emphasis on central data points: The Sine function assigns more weight to the middle of the lookback period, giving less importance to the beginning and end points. This helps capture the main trend more effectively while reducing noise from recent volatility or older data.
// Function to calculate the Sine-Weighted Moving Average
f_Sine_Weighted_MA(series float src, simple int length) =>
var float sine_weights = array.new_float(0)
array.clear(sine_weights) // Clear the array before recalculating weights
for i = 0 to length - 1
weight = math.sin((math.pi * (i + 1)) / length)
array.push(sine_weights, weight)
// Normalize the weights
sum_weights = array.sum(sine_weights)
for i = 0 to length - 1
norm_weight = array.get(sine_weights, i) / sum_weights
array.set(sine_weights, i, norm_weight)
// Calculate Sine-Weighted Moving Average
swma = 0.0
if bar_index >= length
for i = 0 to length - 1
swma := swma + array.get(sine_weights, i) * close
swma
Sine-Weighted ATR:
This is a variation of the Average True Range (ATR), which measures market volatility. Like the SWMA, the ATR is smoothed using Sine-based weighting, where central values are more heavily considered compared to the extremities. This improves sensitivity to changes in volatility while maintaining stability in highly volatile markets.
// Function to calculate the Sine-Weighted ATR
f_Sine_Weighted_ATR(simple int length) =>
var float sine_weights_atr = array.new_float(0)
array.clear(sine_weights_atr)
for i = 0 to length - 1
weight = math.sin((math.pi * (i + 1)) / length)
array.push(sine_weights_atr, weight)
// Normalize the weights
sum_weights_atr = array.sum(sine_weights_atr)
for i = 0 to length - 1
norm_weight_atr = array.get(sine_weights_atr, i) / sum_weights_atr
array.set(sine_weights_atr, i, norm_weight_atr)
// Calculate Sine-Weighted ATR using true ranges
swatr = 0.0
tr = ta.tr(true) // True Range
if bar_index >= length
for i = 0 to length - 1
swatr := swatr + array.get(sine_weights_atr, i) * tr
swatr
ATR Bands:
Upper and lower bands are created by adding/subtracting the Sine-Weighted ATR from the SWMA. These bands help identify overbought or oversold conditions, and when the price crosses these levels, it may generate long or short trade signals.
// - - - - - CALCULATIONS - - - - - //{
bar b = bar.new()
float src = b.calc_src(swma_src)
float swma = f_Sine_Weighted_MA(src, ma_length)
// Use normal ATR or Sine-Weighted ATR based on input
float atr = atr_type == "Normal ATR" ? ta.atr(atr_len) : f_Sine_Weighted_ATR(atr_len)
// Calculate upper and lower bands using ATR
float swma_up = swma + (atr * atr_mult)
float swma_dn = swma - (atr * atr_mult)
float src_l = b.calc_src(src_long)
float src_s = b.calc_src(src_short)
// Signal logic for crossovers and crossunders
var int signal = 0
if ta.crossover(src_l, swma_up)
signal := 1
if ta.crossunder(src_s, swma_dn)
signal := -1
//}
Signal Logic:
Long/Short Signals are triggered when the price crosses above or below the Sine-Weighted ATR bands
Backtest Mode and Equity Calculation
To evaluate its effectiveness, the indicator includes a backtest mode, allowing users to test its performance on historical data:
Backtest Equity: A detailed equity curve is calculated based on the generated signals over a user-defined period (startDate to endDate).
Buy and Hold Comparison: Alongside the strategy’s equity, a Buy-and-Hold equity curve is plotted for performance comparison.
Alerts
The indicator includes built-in alerts for both long and short signals, ensuring users are promptly notified when market conditions meet the criteria for an entry or exit.
Циклический анализ
Parent Session Sweeps + Alert Killzone Ranges with Parent Session Sweep
Key Features:
1. Multiple Session Support: The script tracks three major trading sessions - Asia, London, and New York. Users can customize the timing of these sessions.
2. Killzone Visualization: The strategy visually represents each session's range, either as filled boxes or lines, allowing traders to easily identify key price levels.
3. Parent Session Logic: The core of the strategy revolves around identifying a "parent" session - a session that encompasses the range of the following session. This parent session becomes the basis for potential trade setups.
4. Sweep and Reclaim Setups: The strategy looks for price movements that sweep (break above or below) the parent session's high or low, followed by a reclaim of that level. This price action often indicates a potential reversal.
5. Risk-Reward Filtering: Each potential setup is evaluated based on a user-defined minimum risk-reward ratio, ensuring that only high-quality trade opportunities are considered.
6. Candle Close Filter: An optional filter that checks the characteristics of the candle that reclaims the parent session level, adding an extra layer of confirmation to the setup.
7. Performance Tracking: The strategy keeps track of bullish and bearish setup success rates, providing valuable feedback on its performance over time.
8. Visual Aids: The script draws lines to mark the parent session's high and low, making it easy for traders to identify key levels.
How It Works:
1. The script continuously monitors price action across the defined sessions.
2. When a session fully contains the range of the next session, it's identified as a potential parent session.
3. The strategy then waits for price to sweep either the high or low of this parent session.
4. If a sweep occurs, it looks for a reclaim of the swept level within the parameters set by the user.
5. If a valid setup is identified, the script generates an alert and places a trade (if backtesting or running live).
6. The strategy continues to monitor the trade for either reaching the target (opposite level of the parent session) or hitting the stop loss.
Considerations for Signals:
- Sweep: A break of the parent session's high or low.
- Reclaim: A close back inside the parent session range after a sweep.
- Candle Characteristics: Optional filter for the reclaim candle (e.g., bullish candle for long setups).
- Risk-Reward: Each setup must meet or exceed the user-defined minimum risk-reward ratio.
- Session Timing: The strategy is sensitive to the defined session times, which should be set according to the trader's preferred time zone.
This strategy aims to capitalize on institutional order flow and liquidity patterns in the forex market, providing traders with a systematic approach to identifying potential reversal points with favorable risk-reward profiles.
Trade Entry Detector, Wick to Body Ratio Trade Entry Detector: Wick-to-Body Ratio Strategy with Bollinger Bands
Overview
The Trade Entry Detector is a custom strategy for TradingView that leverages the Bollinger Bands and a unique wick-to-body ratio approach to capture precise entry opportunities. This indicator is designed for traders who want to pinpoint high-probability reversal points when price interacts with Bollinger Bands, all while offering flexible entry fill options.
The strategy performs primary analysis on the daily time frame, regardless of your current chart setting, allowing you to view daily Bollinger Band levels and entry signals even on lower time frames. This approach is suitable for swing traders and short-term traders looking to align intraday moves with higher time frame signals.
How the Strategy Works
1. Bollinger Band Analysis on the Daily Time Frame
Bollinger Bands are calculated using a 20-period simple moving average (SMA) and a standard deviation multiplier (default is 2). These bands dynamically expand and contract based on market volatility, making them ideal for identifying overbought and oversold conditions:
* Upper Band: Indicates potential overbought levels.
* Lower Band: Indicates potential oversold levels.
2. Wick-to-Body Ratio Condition
This strategy places significant emphasis on candle wicks relative to the candle body. Here’s why:
* A large upper wick relative to the body signals potential selling pressure after testing the upper Bollinger Band.
* A large lower wick relative to the body indicates buying support after testing the lower Bollinger Band.
* Ratio Threshold: You can set a minimum wick-to-body ratio (default is 1.0), meaning that the wick must be at least equal in size to the body. This ensures only candles with significant reversals are considered for entry.
3. Flexible Entry Timing
To adapt to various trading styles, the indicator allows you to choose the entry fill timing:
* Daily Close: Enter at the close of the daily candle.
* Daily Open: Enter at the open of the following daily candle.
* HOD (High of Day): Set entry at the daily high, for those who want confirmation of upward momentum.
* LOD (Low of Day): Set entry at the daily low, ideal for confirming downward movement.
4. Position Sizing and Risk Management
The strategy calculates position size based on a fixed risk percentage of your account balance (default is 1%). This approach dynamically adjusts position sizes based on stop-loss distance:
* Stop Loss: Placed at the nearest swing high (for shorts) or swing low (for longs).
* Take Profit: Exits are triggered when the price reaches the opposite Bollinger Band.
5. Order Expiration
Each pending order (long or short) expires after two days if unfilled, allowing for new setups on subsequent candles if conditions are met again.
Using the Trade Entry Detector
Step-by-Step Guide
1. Set the Primary Time Frame
The core calculations run on the daily time frame, but the strategy can be applied to intraday charts (e.g., 65-minute or 15-minute) for deeper insights.
2. Adjust Bollinger Band Settings
* Length: Default is 20, which determines the period for calculating the moving average.
* Standard Deviation Multiplier: Default is 2.0, which sets the width of the bands. Adjusting this can help you capture broader or tighter volatility ranges.
3. Define the Wick-to-Body Ratio
Set the minimum ratio between wick and body (default 1.0). Higher values filter out candles with less wick-to-body contrast, focusing on stronger rejection moves.
4. Choose Entry Fill Timing
Select your preferred fill condition:
* Daily Close: Confirms the trade at the end of the daily session.
* Daily Open: Executes the entry at the open of the next day.
* HOD/LOD: Uses the daily high or low as an additional confirmation for upward or downward moves.
5. Position Sizing and Risk Management
* Set your account balance and risk percentage. The strategy automatically calculates position sizes based on the stop distance to manage risk efficiently.
* Stop Loss and Take Profit points are automatically set based on swing highs/lows and opposing Bollinger Bands, respectively.
Practical Example
Let’s say SPY (S&P 500 ETF) tests the lower Bollinger Band on the daily time frame, with a lower wick that is twice the size of the body (meeting the 1.0 ratio threshold). Here’s how the strategy might proceed:
1. Signal: The lower wick on SPY suggests buying interest at the lower Bollinger Band.
2. Entry Fill Timing: If you’ve selected "Daily Open," the entry order will be placed at the next day's open price.
3. Stop Loss: Positioned at the nearest daily swing low to minimize risk.
4. Take Profit: If SPY price moves up and reaches the upper Bollinger Band, the position is automatically closed.
Indicator Features and Benefits
* Multi-Time Frame Compatibility: Perform daily analysis while tracking signals on any intraday chart.
* Automatic Position Sizing: Tailor risk per trade based on account balance and desired risk percentage.
* Flexible Entry Options: Choose from close, open, HOD, or LOD for optimal timing.
* Effective Trend Reversal Identification: Uses wick-to-body ratio and Bollinger Band interaction to pinpoint potential reversals.
* Dynamic Visualization: Bollinger Bands are displayed on your chosen time frame, allowing seamless intraday tracking.
Summary
The Trade Entry Detector provides a unique, data-driven way to spot reversal points with customizable entry options. By combining Bollinger Bands with wick-to-body ratio conditions, it identifies potential trade setups where price has tested extremes and shown reversal signals. With its flexible entry timing, risk management features, and multi-time frame compatibility, this indicator is ideal for traders looking to blend daily market context with shorter-term execution.
Tips for Usage:
* For swing trading, consider the Daily Open or Close entry options.
* For momentum entries, HOD or LOD may offer better alignment with the direction of the wick.
* Backtest on different assets to find optimal Bollinger Band and wick-to-body settings for your market.
Use this indicator to enhance your understanding of price behavior at key levels and improve the precision of your entry points. Happy trading!
RSI Fakeout Filter with SMA Confirmation [CHE] Introducing: RSI Fakeout Detection
Are you tired of being caught in fakeouts that can lead to frustrating losses? The RSI Fakeout Detection is here to enhance your trading strategy by filtering out false signals and providing you with more reliable entries. This innovative indicator is designed to help traders identify when market momentum, as indicated by the RSI, does not align with price movement – a key indicator of potential fakeouts!
What Does It Do?
The RSI Fakeout Detection focuses on one key goal: avoiding false signals. By monitoring when the RSI exceeds a customizable threshold (indicating strength) but the price remains below a moving average like the SMA, this indicator highlights situations where the market may seem strong, but the price action doesn't support that momentum. In other words, it saves you from those tricky fake breakouts.
Key Benefits:
1. Reduce Risk, Increase Confidence: Get an extra layer of protection against fakeouts by receiving signals only when both RSI and price confirm the market's true direction. Avoid entering false breakouts and trade with more confidence.
2. Dynamic Analysis of SMA Lengths: It doesn’t just rely on one SMA. The indicator automatically analyzes and sorts through different SMA lengths to find the most reliable one for your specific market condition, ensuring that you get the best possible signal.
3. Tailored for You: With customizable RSI thresholds, a choice of multiple moving average types (SMA, EMA, Bollinger Bands, and more), and vibrant color-coded visuals, this tool is built to fit your unique trading style and preferences.
4. Spot Fakeouts with Ease: Visual cues make it easy to see when the market might be tricking you. Labels, plotted lines, and a toggleable disclaimer keep everything transparent and easy to understand.
5. Friendly and Intuitive: Whether you’re new to trading or a seasoned pro, the RSI Fakeout Detection is designed to be simple and effective. The labels and plots are clear, the alerts are timely, and it seamlessly integrates into your chart without cluttering it.
Why Choose RSI Fakeout Detection?
- Accuracy and Precision: By combining RSI and SMA analysis, this indicator minimizes the risk of following false trends and entering trades too early.
- Save Time and Reduce Guesswork: No more spending hours trying to figure out which SMA length works best – the RSI Fakeout Detection does it for you!
- Peace of Mind: Avoiding fakeouts means fewer bad trades, which can lead to more consistent performance and less stress.
Transform the way you trade, and step into a more confident trading future with RSI Fakeout Detection . Whether you’re day trading or swing trading, this tool will give you an edge by helping you filter out the noise and make more informed decisions.
Best regards,
Chervolino
Disclaimer:
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Realized Price Profit/Loss Margin [VWAP Optimized]Shaded Profit/Loss Margin Oscillator
The Shaded Profit/Loss Margin Oscillator is a powerful tool designed to measure Bitcoin’s Net Unrealized Profit/Loss (NUPL). This metric reflects the difference between Bitcoin’s current market price and its realized price, which approximates the price at which coins were last moved. By smoothing the NUPL using a moving average, the indicator provides a clean purple oscillator line that helps users easily gauge market sentiment. When the oscillator is above the zero line, the market is in profit, and when it is below zero, participants are generally in a state of unrealized loss. The shaded area between the oscillator and the zero line enhances visual clarity, making it easier to identify potential shifts in market behavior such as profit-taking or capitulation.
Unique Features and Added Value
What sets this indicator apart from traditional NUPL indicators is the use of a volume-weighted average price (VWAP) as a proxy for the realized price. Unlike the original on-chain NUPL metric, which relies on complex on-chain data, this indicator leverages VWAP to provide an approximation of realized price based solely on price and volume data available directly on TradingView. This method makes it highly accessible to traders who don’t have access to on-chain data platforms.
The use of VWAP not only simplifies the calculation but also provides additional value, as it incorporates volume into the realized price estimation. This volume-sensitive approach may offer a more responsive and dynamic reflection of realized prices compared to on-chain models, which can sometimes lag. In essence, this VWAP-based NUPL oscillator offers a unique edge in tracking profit/loss margins, particularly for traders who want a straightforward and efficient way to gauge sentiment without relying on external on-chain data sources. It brings the essence of NUPL into the world of technical analysis in an accessible and actionable way.
Business Cycle Indicators (Normalized)This script aggregates and normalizes several key economic indicators to provide a comprehensive view of the business cycle and overall market conditions. By combining these indicators into a single, normalized average line, the script helps identify overarching trends and shifts in the economy, aiding in more informed trading and investment decisions.
Included Indicators:
Inverted National Financial Conditions Index (NFCI):
Symbol: FRED:NFCI
Measures financial stress in the markets. An inverted NFCI aligns higher values with positive financial conditions.
Inverted Net Percentage of Banks Tightening Lending Standards (DRTSCIS):
Symbol: FRED:DRTSCIS
Reflects changes in bank lending practices. Inverting this indicator means higher values indicate easing lending standards, which is generally positive for economic growth.
HYG Close Price (iShares High Yield Corporate Bond ETF):
Symbol: AMEX:HYG
Represents the performance of high-yield corporate bonds, providing insight into credit market conditions.
Inverted High-Yield Credit Spread (BAMLH0A0HYM2):
Symbol: FRED:BAMLH0A0HYM2
Measures the spread between high-yield bonds and risk-free securities. A narrower (inverted) spread indicates better market conditions.
Manufacturing/Non-Manufacturing New Orders Ratio:
Symbols: ECONOMICS:USMNO (Manufacturing), ECONOMICS:USNMNO (Non-Manufacturing)
Compares manufacturing to non-manufacturing new orders to gauge shifts in economic activity.
US PMI (Purchasing Managers' Index):
Symbol: ECONOMICS:USBCOI
An indicator of the economic health of the manufacturing sector.
10-Year Inflation Breakeven (T10YIE):
Symbol: FRED:T10YIE
Represents market expectations of inflation over the next ten years.
Inverted 10-Year Real Yield (DFII10):
Symbol: FRED:DFII10
Reflects the real yield on 10-year Treasury Inflation-Protected Securities (TIPS). Inverted to align higher values with positive economic sentiment.
Copper/Gold Ratio:
Symbols: CAPITALCOM:COPPER (Copper), TVC:GOLD (Gold)
Compares the prices of copper and gold, often used as a barometer for global economic activity.
Features:
Normalized Indicators: Each indicator is normalized to a 0-100 scale to facilitate direct comparison, regardless of their original units or scales.
Normalized Average Line: Calculates and plots the average of all available normalized indicators, providing a single line that represents the combined economic signals.
Customizable Display:
Show Individual Indicators: Option to display individual normalized indicators for detailed analysis.
Show Normalized Average Line: Option to display the normalized average line for a consolidated view.
Dynamic Labeling: Displays the latest value of the normalized average directly on the chart for quick reference.
How to Use:
Adding the Script:
Apply the script to a chart in TradingView using a timeframe that aligns with the frequency of the economic data (daily or weekly recommended).
Customization:
Show Normalized Average Line: Enabled by default to display the combined indicator.
Show Individual Indicators: Enable this option in the script settings to display all individual normalized indicators.
Interpretation:
Normalized Scale (0-100): Higher values generally indicate stronger economic conditions, while lower values may suggest weakening conditions.
Trend Analysis: Use the normalized average line to identify trends and potential turning points in the business cycle.
Notes:
Data Availability: Ensure you have access to all the data sources used in the script. Some data feeds may require specific TradingView subscriptions.
Indicator Limitations: Economic indicators are subject to revisions and may not reflect real-time market conditions.
No Investment Advice: This script is a tool for analysis and should not be considered as financial advice. Always conduct your own research before making investment decisions.
Unlock the Power of Seasonality: Monthly Performance StrategyThe Monthly Performance Strategy leverages the power of seasonality—those cyclical patterns that emerge in financial markets at specific times of the year. From tax deadlines to industry-specific events and global holidays, historical data shows that certain months can offer strong opportunities for trading. This strategy was designed to help traders capture those opportunities and take advantage of recurring market patterns through an automated and highly customizable approach.
The Inspiration Behind the Strategy:
This strategy began with the idea that market performance is often influenced by seasonal factors. Historically, certain months outperform others due to a variety of reasons, like earnings reports, holiday shopping, or fiscal year-end events. By identifying these periods, traders can better time their market entries and exits, giving them an advantage over those who solely rely on technical indicators or news events.
The Monthly Performance Strategy was built to take this concept and automate it. Instead of manually analyzing market data for each month, this strategy enables you to select which months you want to focus on and then executes trades based on predefined rules, saving you time and optimizing the performance of your trades.
Key Features:
Customizable Month Selection: The strategy allows traders to choose specific months to test or trade on. You can select any combination of months—for example, January, July, and December—to focus on based on historical trends. Whether you’re targeting the historically strong months like December (often driven by the 'Santa Rally') or analyzing quieter months for low volatility trades, this strategy gives you full control.
Automated Monthly Entries and Exits: The strategy automatically enters a long position on the first day of your selected month(s) and exits the trade at the beginning of the next month. This makes it perfect for traders who want to benefit from seasonal patterns without manually monitoring the market. It ensures precision in entering and exiting trades based on pre-set timeframes.
Re-entry on Stop Loss or Take Profit: One of the standout features of this strategy is its ability to re-enter a trade if a position hits the stop loss (SL) or take profit (TP) level during the selected month. If your trade reaches either a SL or TP before the month ends, the strategy will automatically re-enter a new trade the next trading day. This feature ensures that you capture multiple trading opportunities within the same month, instead of exiting entirely after a successful or unsuccessful trade. Essentially, it keeps your capital working for you throughout the entire month, not just when conditions align perfectly at the beginning.
Built-in Risk Management: Risk management is a vital part of this strategy. It incorporates an Average True Range (ATR)-based stop loss and take profit system. The ATR helps set dynamic levels based on the market’s volatility, ensuring that your stops and targets adjust to changing market conditions. This not only helps limit potential losses but also maximizes profit potential by adapting to market behavior.
Historical Performance Testing: You can backtest this strategy on any period by setting the start year. This allows traders to analyze past market data and optimize their strategy based on historical performance. You can fine-tune which months to trade based on years of data, helping you identify trends and patterns that provide the best trading results.
Versatility Across Asset Classes: While this strategy can be particularly effective for stock market indices and sector rotation, it’s versatile enough to apply to other asset classes like forex, commodities, and even cryptocurrencies. Each asset class may exhibit different seasonal behaviors, allowing you to explore opportunities across various markets with this strategy.
How It Works:
The trader selects which months to test or trade, for example, January, April, and October.
The strategy will automatically open a long position on the first trading day of each selected month.
If the trade hits either the take profit or stop loss within the month, the strategy will close the current position and re-enter a new trade on the next trading day, provided the month has not yet ended. This ensures that the strategy continues to capture any potential gains throughout the month, rather than stopping after one successful trade.
At the start of the next month, the position is closed, and if the next month is also selected, a new trade is initiated following the same process.
Risk Management and Dynamic Adjustments:
Incorporating risk management with this strategy is as easy as turning on the ATR-based system. The strategy will automatically calculate stop loss and take profit levels based on the market’s current volatility, adjusting dynamically to the conditions. This ensures that the risk is controlled while allowing for flexibility in capturing profits during both high and low volatility periods.
Maximizing the Seasonal Edge:
By automating entries and exits based on specific months and combining that with dynamic risk management, the Ultimate Monthly Performance Strategy takes advantage of seasonal patterns without requiring constant monitoring. The added re-entry feature after hitting a stop loss or take profit ensures that you are always in the game, maximizing your chances to capture profitable trades during favorable seasonal periods.
Who Can Benefit from This Strategy?
This strategy is perfect for traders who:
Want to exploit the predictable, recurring patterns that occur during specific months of the year.
Prefer a hands-off, automated trading approach that allows them to focus on other aspects of their portfolio or life.
Seek to manage risk effectively with ATR-based stop losses and take profits that adjust to market conditions.
Appreciate the ability to re-enter trades when a take profit or stop loss is hit within the month, ensuring that they don't miss out on multiple opportunities during a favorable period.
In summary, the Ultimate Monthly Performance Strategy provides traders with a comprehensive tool to capitalize on seasonal trends, optimize their trading opportunities throughout the year, and manage risk effectively. The built-in re-entry system ensures you continue to benefit from the market even after hitting targets within the same month, making it a robust strategy for traders looking to maximize their edge in any market.
Risk Disclaimer:
Trading financial markets involves significant risk and may not be suitable for all investors. The Monthly Performance Strategy is designed to help traders identify seasonal trends, but past performance does not guarantee future results. It is important to carefully consider your risk tolerance, financial situation, and trading goals before using any strategy. Always use appropriate risk management and consult with a professional financial advisor if necessary. The use of this strategy does not eliminate the risk of losses, and traders should be prepared for the possibility of losing their entire investment. Be sure to test the strategy on a demo account before applying it in live markets.
Gann Square of 9Understanding the Gann Square of 9
Delve into the fascinating realm of W.D. Gann’s Square of 9, a tool that has intrigued traders for generations. As we explore the insights behind this unique structure, we’ll show you how our Gann Square of 9 Indicator can become a valuable asset in your trading toolkit.
The History of the Gann Square of 9
The story behind the Gann Square of 9 is as fascinating as the man who created it. W.D. Gann, a pioneering trader from the early 20th century, introduced a method that highlighted the connection between time and price. Rooted in ancient mathematics and geometry, Gann’s theory suggests that financial markets follow cyclical patterns, which are captured in the design of the Square of 9.
Core Principles of the Gann Square of 9
At its heart, the Gann Square of 9 is based on a numerical system that spirals outward from a central point. This unique arrangement allows traders to identify potential support and resistance levels in the market. Each number represents a possible pivot point, indicating shifts in market direction, aligned with Gann’s time-price equilibrium theory.
Applying the Gann Square in Market Analysis
The strength of the Gann Square of 9 lies in its ability to predict key moments in the market where significant price movements may occur. By utilizing our Gann Square of 9 Indicator, traders can easily pinpoint these crucial points, applying Gann’s principles to anticipate both market highs and lows. This section will guide you through practical applications of the Gann Square for making both short-term and long-term trading decisions.
Market Timing with the Gann Square of 9 Indicator
Unlock the potential of market timing and price prediction using our Gann Square of 9 Indicator. This versatile tool brings Gann’s trading insights into the modern world of finance. Here, you’ll find a detailed walkthrough on how to use the indicator to enhance your trading strategies.
Step-by-Step Guide
Input the Source Price: Open, High, Low, Close on specific Timeframe.
Set the Pip Value: Adjust the pip value according to the scale of your trades. The pip value helps define the precision of the price levels the calculator will generate.
Analyze Results: The generated grid displays a central value (your input price) surrounded by numbers representing possible support and resistance levels.
Use the Support and Resistance Levels: Below the grid, you’ll find specific support and resistance points. These are key price levels that can help you plan your trading strategy, such as entry or exit points.
Apply Gann's Trading Entries: At the bottom, suggested long and short trade entries, with targets and stop-loss levels, giving you essential tools for managing risk effectively.
By following these steps, you can effectively incorporate Gann’s time-tested techniques into modern market analysis. Our Gann Square of 9 Indicator simplifies complex calculations while offering powerful insights, helping you make informed trading decisions rooted in one of market analysis’s most influential theories.
Whether you’re new to Gann’s approach or a seasoned trader, this indicator is designed to provide valuable insights aligned with Gann’s original concepts while delivering a seamless user experience for today’s traders. With just a few clicks, you can transform market data into a geometric pattern of time and price, setting the stage for strategic trading based on the cyclical nature of financial markets.
90 Minute Cycles Full90-Minute Cycles Indicator for London and NY Sessions
This is a more streamlined version of the 90-minute cycle indicator by sunwoo101.
The 90-Minute Cycles Indicator is built to help traders easily follow and trade around key market cycles during the London and New York sessions. Marking important 90-minute intervals and highlighting the True Cycle Open Price provides clear visual cues to help you make more informed trading decisions.
Key Features:
90-Minute Cycles for London and NY: The indicator automatically draws vertical lines marking every 90-minute cycle for the London and NY sessions. These lines are great for timing your trades and spotting potential shifts in market momentum.
True Cycle Open Price: A horizontal line is drawn at the True Cycle Open Price, which stays visible throughout the session. This gives you a key reference point for price levels that tend to act as support or resistance.
Customizable Visuals: You can fully personalize the indicator’s appearance - adjusting the colors and line styles and even controlling when the lines appear - so it blends perfectly with your existing charts.
All Cycles Drawn from the Start: Unlike other indicators, this one draws all the 90-minute cycles right when the session begins, so you can see the full day’s potential market moves as soon as the first cycle starts.
What’s Different About This Indicator:
London Session Support: In addition to the NY session, you now have 90-minute cycles for the London session, complete with its own True Cycle Open Price.
Better Customization: You have more control over the visual aspects of the indicator, so it can be tailored to fit your specific charting preferences.
Complete Cycle Visibility: All cycles are drawn immediately when the session starts, providing a full view of the day’s key moments right from the opening.
How to Use:
This indicator is perfect for scalping and short-term trading. Whether trading Forex or Indices and following SMT concepts, the cycle timing can help you pinpoint the best times for entering and exiting trades. The True Cycle Open Price is a crucial level of support or resistance throughout the session, making it a key marker to watch.
Scalpers: Use the 90-minute cycle lines to time your trades with the market's rhythm.
Day Traders: This indicator tracks the London and NY sessions, making it an excellent tool for day trading strategies where timing is critical.
Multi-Session Support:
Whether you're trading the London or New York session, the indicator will automatically adjust to your time zone and align the cycles to the relevant session. This helps you stay on top of key market activity across major trading hubs without changing anything manually.
Ichimoku Wave Oscillator with Custom MAIchimoku Wave Oscillator with Custom MA - Pine Script Description
This script uses various types of moving averages (MA) to implement the concept of Ichimoku wave theory for wave analysis. The user can select from SMA, EMA, WMA, TEMA, SMMA to visualize the difference between short-term, medium-term, and long-term waves, while identifying potential buy and sell signals at crossover points.
Key Features:
MA Type Selection:
The user can select from SMA (Simple Moving Average), EMA (Exponential Moving Average), WMA (Weighted Moving Average), TEMA (Triple Exponential Moving Average), and SMMA (Smoothed Moving Average) to calculate the waves. This script is unique in that it combines TEMA and SMMA, distinguishing it from other simple moving average-based indicators.
TEMA (Triple Exponential Moving Average): Best suited for capturing short-term trends with quick responsiveness.
SMMA (Smoothed Moving Average): Useful for identifying long-term trends with minimal noise, providing more stable signals.
Wave Calculations:
The script calculates three waves: Wave 9-17, Wave 17-26, and Wave 9-26, each of which analyzes different time horizons.
Wave 9-17 (blue): Primarily used for analyzing short-term trends, ideal for detecting quick changes.
Wave 17-26 (red): Used to analyze medium-term trends, providing a more stable market direction.
Wave 9-26 (green): Represents long-term trends, suitable for understanding broader trend shifts.
Baseline (0 Line):
Each wave is visualized around the 0 line, where waves above the line indicate an uptrend and waves below the line indicate a downtrend. This allows for easy identification of trend reversals.
Crossover Signals:
CrossUp: When Wave 9-17 (short-term wave) crosses Wave 17-26 (medium-term wave) upward, it is considered a buy signal, indicating a potential upward trend shift.
CrossDown: When Wave 9-17 (short-term wave) crosses Wave 17-26 downward, it is considered a sell signal, indicating a potential downward trend shift.
Background Color for Signal:
The script visually highlights the signals with background colors. When a buy signal occurs, the background turns green, and when a sell signal occurs, the background turns red. This makes it easier to spot reversal points.
Calculation Method:
The script calculates the difference between moving averages to display the wave oscillation. Wave 9-17, Wave 17-26, and Wave 9-26 represent the difference between the moving averages for different time periods, allowing for analysis of short-term, medium-term, and long-term trends.
Wave 9-17 = MA(9) - MA(17): Represents the difference between the short-term moving averages.
Wave 17-26 = MA(17) - MA(26): Represents the difference between medium-term moving averages.
Wave 9-26 = MA(9) - MA(26): Provides insight into the long-term trend.
This calculation method effectively visualizes the oscillation of waves and helps identify trend reversals at crossover points.
Uniqueness of the Script:
Unlike other moving average-based indicators, this script combines TEMA (Triple Exponential Moving Average) and SMMA (Smoothed Moving Average) to capture both short-term sensitivity and long-term stability in trends. This duality makes the script more versatile for different market conditions.
TEMA is ideal for short-term traders who need quick signals, while SMMA is useful for long-term investors seeking stability and noise reduction. By combining these two, this script provides a more refined analysis of trend changes across various timeframes.
How to Use:
This script is effective for trend analysis and reversal detection. By visualizing the crossover points between the waves, users can spot potential buy and sell signals to make more informed trading decisions.
Scalping strategies can rely on Wave 9-17 to detect quick trend changes, while those looking for medium-term trends can analyze signals from Wave 17-26.
For a broader market overview, Wave 9-26 helps users understand the long-term market trend.
This script is built on the concept of wave theory to anticipate trend changes, making it suitable for various timeframes and strategies. The user can tailor the characteristics of the waves by selecting different MA types, allowing for flexible application across different trading strategies.
Ichimoku Wave Oscillator with Custom MA - Pine Script 설명
이 스크립트는 다양한 이동 평균(MA) 유형을 활용하여 일목 파동론의 개념을 기반으로 파동 분석을 시도하는 지표입니다. 사용자는 SMA, EMA, WMA, TEMA, SMMA 중 원하는 이동 평균을 선택할 수 있으며, 이를 통해 단기, 중기, 장기 파동 간의 차이를 시각화하고, 교차점에서 상승 및 하락 신호를 포착할 수 있습니다.
주요 기능:
이동 평균(MA) 유형 선택:
사용자는 SMA(단순 이동 평균), EMA(지수 이동 평균), WMA(가중 이동 평균), TEMA(삼중 지수 이동 평균), SMMA(평활 이동 평균) 중 하나를 선택하여 파동을 계산할 수 있습니다. 이 스크립트는 TEMA와 SMMA의 독창적인 조합을 통해 기존의 단순한 이동 평균 지표와 차별화됩니다.
TEMA(삼중 지수 이동 평균): 빠른 반응으로 단기 트렌드를 포착하는 데 적합합니다.
SMMA(평활 이동 평균): 장기적인 추세를 파악하는 데 유용하며, 노이즈를 최소화하여 안정적인 신호를 제공합니다.
파동(Wave) 계산:
이 스크립트는 Wave 9-17, Wave 17-26, Wave 9-26의 세 가지 파동을 계산하여 각각 단기, 중기, 장기 추세를 분석합니다.
Wave 9-17 (파란색): 주로 단기 추세를 분석하는 데 사용되며, 빠른 추세 변화를 포착하는 데 유용합니다.
Wave 17-26 (빨간색): 중기 추세를 분석하는 데 사용되며, 좀 더 안정적인 시장 흐름을 보여줍니다.
Wave 9-26 (녹색): 장기 추세를 나타내며, 큰 흐름의 방향성을 파악하는 데 적합합니다.
기준선(0 라인):
각 파동은 0 라인을 기준으로 변동성을 시각화합니다. 0 위에 있는 파동은 상승세, 0 아래에 있는 파동은 하락세를 나타내며, 이를 통해 추세의 전환을 쉽게 확인할 수 있습니다.
파동 교차 신호:
CrossUp: Wave 9-17(단기 파동)이 Wave 17-26(중기 파동)을 상향 교차할 때, 상승 신호로 간주됩니다. 이는 단기적인 추세 변화가 발생할 수 있음을 의미합니다.
CrossDown: Wave 9-17(단기 파동)이 Wave 17-26(중기 파동)을 하향 교차할 때, 하락 신호로 해석됩니다. 이는 시장이 약세로 돌아설 가능성을 나타냅니다.
배경 색상 표시:
교차 신호가 발생할 때, 상승 신호는 녹색 배경, 하락 신호는 빨간색 배경으로 시각적으로 강조되어 사용자가 신호를 쉽게 인식할 수 있습니다.
계산 방식:
이 스크립트는 이동 평균 간의 차이를 계산하여 각 파동의 변동성을 나타냅니다. Wave 9-17, Wave 17-26, Wave 9-26은 각각 설정된 주기의 이동 평균(MA)의 차이를 통해, 시장의 단기, 중기, 장기 추세 변화를 시각적으로 표현합니다.
Wave 9-17 = MA(9) - MA(17): 단기 추세의 차이를 나타냅니다.
Wave 17-26 = MA(17) - MA(26): 중기 추세의 차이를 나타냅니다.
Wave 9-26 = MA(9) - MA(26): 장기적인 추세 방향을 파악할 수 있습니다.
이러한 계산 방식은 파동의 변동성을 파악하는 데 유용하며, 추세의 교차점을 통해 상승/하락 신호를 잡아냅니다.
스크립트의 독창성:
이 스크립트는 기존의 이동 평균 기반 지표들과 달리, TEMA(삼중 지수 이동 평균)와 SMMA(평활 이동 평균)을 함께 사용하여 짧은 주기와 긴 주기의 트렌드를 동시에 파악할 수 있도록 설계되었습니다. 이를 통해 단기 트렌드의 민감한 변화와 장기 트렌드의 안정성을 모두 반영합니다.
TEMA는 단기 트레이더에게 빠르고 민첩한 신호를 제공하며, SMMA는 장기 투자자에게 보다 안정적이고 긴 호흡의 트렌드를 파악하는 데 유리합니다. 두 지표의 결합으로, 다양한 시장 환경에서 추세의 변화를 더 정교하게 분석할 수 있습니다.
사용 방법:
이 스크립트는 추세 분석과 변곡점 포착에 효과적입니다. 각 파동 간의 교차점을 시각적으로 확인하고, 상승 또는 하락 신호를 포착하여 매매 시점 결정을 도울 수 있습니다.
스캘핑 전략에서는 Wave 9-17을 주로 참고하여 빠르게 추세 변화를 잡아내고, 중기 추세를 참고하고 싶은 경우 Wave 17-26을 사용해 신호를 분석할 수 있습니다.
장기적인 시장 흐름을 파악하고자 할 때는 Wave 9-26을 통해 큰 트렌드를 확인할 수 있습니다.
이 스크립트는 파동 이론의 개념을 기반으로 시장의 추세 변화를 예측하는 데 유용하며, 다양한 시간대와 전략에 맞추어 사용할 수 있습니다. 특히, 사용자가 선택한 MA 유형에 따라 파동의 특성을 변화시킬 수 있어, 여러 매매 전략에 유연하게 대응할 수 있습니다.
RoC Momentum CycleRoC Momentum Cycles (RMC) is derived from RoC (Rate of Change) indicator.
Motivation behind RMC: Addressing RoC’s Shortcomings
While the Rate of Change (RoC) indicator is a valuable tool for assessing momentum, it has notable limitations that traders must be aware of. One of the primary challenges with the traditional RoC is its sensitivity to price fluctuations, which can lead to false signals in volatile markets. This often results in premature entries or exits, impacting trading performance.
By smoothing out the RoC calculations and focusing on more consistent signal generation (using SMA on smoothed RoC), RMC offers a more consistent representation of price trends.
Momentum Cycles
RMC helps visualize momentum cycles in a much better way compared to RoC.
Long Momentum Cycle : A cross-over of smoothed RoC (blue line) above averaged signal (orange line) below zero marks start of a new potential upside cycle which ends when the blue line comes back to zero line from above.
Short Momentum Cycle : A cross-under of blue line below orange line above zero marks beginning of a potential downside cycle which ends when the blue line comes back to zero from below.
Dynamic Price Oscillator [CHE]Dynamic Price Oscillator
Overview:
Welcome to the Dynamic Price Oscillator ! This indicator is designed to help traders identify potential trend reversals and divergences by comparing short-term and long-term price movements in percentage terms. It’s a powerful tool to enhance your trading strategies by spotting bullish and bearish divergences effectively.
Key Features:
Dynamic Oscillator Calculation: The DPO calculates the percentage difference between two EMAs (Exponential Moving Averages), offering insight into the relative strength of price movements.
Bullish & Bearish Divergence Detection:
The indicator highlights divergences between price and the oscillator, allowing you to identify potential reversal points with ease.
Long-Term Divergence Option: Enable or disable long-term divergences to focus on either short-term trends or broader market movements.
High/Low Markers:
Visual markers for significant peaks and troughs in the DPO, helping you quickly spot potential trade setups.
Custom Alerts: Set up alerts for both bullish and bearish divergence signals, ensuring you never miss an important opportunity.
How to Use:
Bullish Divergence: A bullish divergence occurs when price is making lower lows, but the DPO shows higher lows. This can indicate a potential reversal to the upside.
Bearish Divergence: A bearish divergence happens when price is making higher highs, but the DPO shows lower highs. This can signal a potential downside reversal.
Customizable Settings: Adjust the fast and slow EMA periods, smoothing factor, and divergence lookback to fit your personal trading style.
Ideal For:
Swing traders and day traders looking for early signs of market reversals.
Those who want a clear, visual representation of divergence between price and momentum.
Traders who appreciate flexibility with customizable parameters and built-in alerts.
Why Use Dynamic Price Oscillator ?
This indicator gives you the edge by providing a reliable way to measure price momentum and detect divergences that are often missed by other indicators. With the option to enable long-term divergences, you can tailor the indicator to fit both short-term and long-term strategies.
Give it a try and see how the Dynamic Price Oscillator can enhance your trading performance!
Best regards Chervolino
Elliott Wave Oscillator with Peak DetectionThe Elliott Wave Oscillator with Derivative Peak Detection and Breakout Bands is a technical indicator that blends traditional Elliott Wave theory with modern derivative-based peak detection and breakout bands for a clearer view of market trends.
Key Components:
Elliott Wave Oscillator (EWO):
The core of the indicator is based on the difference between two simple moving averages (SMA): a short-term SMA (default length: 5) and a long-term SMA (default length: 35).
This difference is expressed either as an absolute value or a percentage of the current price, depending on the user’s input.
Smoothing:
The EWO is smoothed using an Exponential Moving Average (EMA) to filter out noise and provide a clearer trend direction.
The smoothing length is adaptive based on the current chart's timeframe (e.g., longer smoothing for daily charts).
Derivative Peak Detection:
The smoothed EWO is analyzed for peaks (positive) and troughs (negative) by calculating the derivative (rate of change) between consecutive values.
Peaks are detected when the derivative transitions from positive to negative, while troughs are identified when the derivative switches from negative to positive.
Tolerance levels are adjustable and vary by timeframe to avoid false signals.
Breakout Bands:
Upper and lower breakout bands are dynamically generated based on the smoothed EWO.
The bands help to filter significant peaks and troughs, only highlighting those that occur beyond the breakout levels.
Users can choose to display these bands and use them to filter out less significant peaks and troughs.
Visualization:
The original, unsmoothed EWO is plotted as a histogram, with positive values in green and negative values in red.
The smoothed EWO is plotted as a blue line, providing a clearer view of the underlying trend.
The breakout bands, if enabled, are plotted as white lines to visualize the upper and lower bounds of the oscillator's movement.
Positive peaks and negative troughs that meet the filtering criteria are marked with purple triangles (for peaks) and red triangles (for troughs) on the chart.
Customization Options:
Timeframe-based Smoothing and Tolerance: Different smoothing lengths and tolerance levels can be set for daily, hourly, and 5-minute charts.
Breakout Bands: Users can toggle the display of breakout bands and adjust their visual properties.
Peak Filtering: Peaks and troughs can be filtered based on whether they break out beyond the bands, or all peaks can be shown.
This indicator provides a unique blend of trend detection through the Elliott Wave Oscillator and derivative analysis to highlight significant market reversals while offering breakout bands as a filtering mechanism for false signals.
Short-Only Cycle IndicatorThis script is a follow-up to my previous 60-day Cycle, Long-Only Indicator.
The "Short-Only Cycle Indicator" is designed to help traders navigate optimal shorting opportunities by analyzing cyclical price behavior over a defined period. It focuses on recognizing distribution phases (ideal for shorting) and accumulation phases (where shorting should be avoided). It should be used with assets that the trader has an existing thesis for downward price movement.
Key Features:
1. Cycle Length: The indicator uses a 60-day cycle to identify high and low points in price, which are then used to determine the current market phase.
2. Distribution Phase: When the price is near the cycle high, the indicator signals a distribution phase, indicating potential shorting opportunities.
3. Accumulation Phase: When the price is near the cycle low, the indicator signals an accumulation phase, advising traders to avoid shorting.
4. Short Signal: A short signal is triggered when the price crosses below the cycle high, which is visually marked on the chart for easy identification.
This indicator is particularly useful for traders who prefer a short-only strategy, as it helps them time their entries and avoid shorting during unfavorable market conditions.
Seasonality normalizedThis custom indicator provides an in-depth analysis of historical price performance to identify potential seasonal patterns and correlations. By examining data from the past 10 years, the indicator filters out outlier performances and focuses on the most consistent seasonal trends.
Key Features:
Intelligent Clustering Algorithm: The indicator employs a custom clustering algorithm to group similar yearly performances together. This approach effectively filters out anomalous years, such as those affected by black swan events like the COVID-19 pandemic, providing a more accurate representation of typical seasonal behavior.
Seasonal Correlation Measurement: The indicator calculates the percentage of years exhibiting similar performance patterns for each week. This measurement helps traders assess the strength of seasonal correlations and make informed decisions based on the consistency of historical data.
High and Low Seasonality Bands: The indicator plots two distinct bands on the chart, representing the expected range of price movement based on historical highs and lows. These bands offer valuable insight into potential support and resistance levels during specific weeks.
Enhanced Visualization: Weeks with high seasonal correlations are prominently highlighted, making it easy for traders to identify periods with the strongest historical patterns. The seasonality bands extend to cover the last and future 3 months, divided into weekly segments, providing a comprehensive view of the current market context.
Dynamic Adaptation: The seasonality bands are dynamically tied to the current high and low prices, ensuring that the indicator remains relevant and responsive to the latest market conditions.
Under the Hood:
The indicator begins by calculating the performance of the asset for each week, going back 10 years.
The custom clustering algorithm groups similar performances together, effectively filtering out outlier years.
The percentage of years falling into the largest performance cluster is calculated, representing the seasonal correlation for each week.
The average performance of the largest cluster is used to plot the high and low seasonality bands, anchored to the current high and low prices.
The bands are color-coded based on the strength of the seasonal correlation, with darker colors indicating higher consistency.
This indicator is designed to help professional traders identify and capitalize on seasonal patterns in the market. By providing a robust and adaptable framework for analyzing historical performance, the Seasonality Indicator offers valuable insights for making informed trading decisions.
We believe this tool will be a valuable addition to your trading arsenal, complementing your existing strategies and enhancing your market analysis capabilities. As a professional trader, your feedback and ideas are invaluable to us. Please share your thoughts, experiences, and suggestions for improvement as you incorporate the Seasonality Indicator into your trading workflow. Together, we can refine this powerful tool to better serve the needs of the trading community.
Inflation-Adjusted Price IndicatorThis indicator allows traders to adjust historical prices for inflation using customizable CPI data. The script computes the adjusted price by selecting a reference date, the original price, and the CPI source (US CPI or custom input) and plots it as a line on the chart. Additionally, a table summarizes the adjusted price values and average and total inflation rates.
While the indicator serves as a standalone tool to understand inflation's impact on prices, it is a supportive element in more advanced trading strategies requiring accurate analysis of inflation-adjusted data.
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
Statistical Volatility° [Pro+] (Joshuuu)Introduction:
Statistical Volatility is a custom-built indicator designed to help traders track the historical range volatility of each individual candle of a given Timeframe. Compared to traditional volatility metrics, or lookback-based volatility calculations, this indicator is focused on the idea of Time-based volatility.
Description:
Whether you are looking at intraday price movements or weekly trends, this tool provides a clear, visual representation of the average range each candle typically covers. By understanding these volatility patterns, traders can observe when markets are likely to expand or consolidate, based on Time.
To obtain this insightful metrics, all available candle range data is normalized; values are therefore represented as a percentage of the maximum historical Time volatility, indicating how each candle range compares relative to the highest value. This allows for an easy comparison of volatility across different Time periods.
Key Features:
Detailed Volatility Tracking: The Statistical Volatility indicator enables traders to track the volatility of each candle throughout the day, week, or month, depending on the selected Timeframe. It helps to identify statistical Times of expansion or consolidation, beyond what current price data may showcase.
Timeframe Adaptability: On lower timeframes such as the 5 Minute Timeframe, the indicator calculates and plots the statistical range for each 5 Minute candle of the day, respectively. On higher timeframes, such as 1 Hour Timeframe or above, the ranges are plotted for each candle of the week, respectively. This adaptability ensures the indicator is versatile enough for day traders, scalpers, and swing traders alike; maintaining a highly granular yet versatile statistical edge.
Flexible Display Options: Traders can choose between different visualization methods, in form of a Heatmap or a Barchart, to display the volatility calculations. The heatmap offers a simple visualization of the data, relying entirely on the color gradient to display volatility. On the other hand, the Barchart gives more flexibility to the analyst by providing a more detailed visual analysis, with the ability of overlaying and comparing the current Time-based volatility.
How Traders Can Use Statistical Volatility (Joshuuu) Effectively:
Data-Based Optimization: By understanding when the market typically experiences its largest or smallest moves, traders can better frame the current narrative. Especially when backtesting, this information can help optimize analysts' entry mechanisms thanks to the introduction of a Time-based statistical component.
Asset-Specific Insights: Currencies like Forex pairs (i.e. FOREXCOM:EURUSD , FOREXCOM:AUDUSD ) or other Asset Classes tied to a particular geographical location (i.e. CME_MINI:NQ1! in the United States, XETR:DAX in Germany), experience volatility spikes during the operational hours of major banks. Each asset has its own “active” Time when liquidity and volatility are higher, tied to when their corresponding markets are open. This makes Statistical Volatility particularly useful for traders who focus on multiple assets across different time zones.
Usage Guidance:
Add Statistical Volatility (Joshuuu) to your TradingView chart.
Customize your preferred volatility calculation type, gradient colors, and plot styles.
Use the volatility graphic to monitor current and upcoming shifts in volatility.
Incorporate Statistical Volatility (Joshuuu) into your existing statistical strategies to fine-tune your interpretation of market behaviour.
These tools are available ONLY on the TradingView platform.
Terms and Conditions
Our charting tools are products provided for informational and educational purposes only and do not constitute financial, investment, or trading advice. Our charting tools are not designed to predict market movements or provide specific recommendations. Users should be aware that past performance is not indicative of future results and should not be relied upon for making financial decisions. By using our charting tools, the purchaser agrees that the seller and the creator are not responsible for any decisions made based on the information provided by these charting tools. The purchaser assumes full responsibility and liability for any actions taken and the consequences thereof, including any loss of money or investments that may occur as a result of using these products. Hence, by purchasing these charting tools, the customer accepts and acknowledges that the seller and the creator are not liable nor responsible for any unwanted outcome that arises from the development, the sale, or the use of these products. Finally, the purchaser indemnifies the seller from any and all liability. If the purchaser was invited through the Friends and Family Program, they acknowledge that the provided discount code only applies to the first initial purchase of the Toodegrees Premium Suite subscription. The purchaser is therefore responsible for cancelling – or requesting to cancel – their subscription in the event that they do not wish to continue using the product at full retail price. If the purchaser no longer wishes to use the products, they must unsubscribe from the membership service, if applicable. We hold no reimbursement, refund, or chargeback policy. Once these Terms and Conditions are accepted by the Customer, before purchase, no reimbursements, refunds or chargebacks will be provided under any circumstances.
By continuing to use these charting tools, the user acknowledges and agrees to the Terms and Conditions outlined in this legal disclaimer.
Fetch cycles
This script tracks cycles in the market, specifically aiming to identify the cycle low and visually represent the cycle on the chart. It begins by initializing a cycle that spans 55 days (configurable) and incorporates a deviation margin for approximation.
The script increments the day count from a defined start date (December 15, 2018) and looks for potential cycle lows after a specified number of days (50). Once a low is detected, using a comparison of the current price against the low from 4 days prior (configurable), the day count resets, and the script begins a new cycle.
The cycle low is visually marked with a triangle below the bar where the low is confirmed. Dots are plotted on the chart to indicate the days leading up to the cycle low, with one set of dots appearing 5 days before the low and another set plotted closer to the cycle end.
Additionally, the script tracks the days since the last cycle ended, and the start of the first cycle is marked with a blue triangle. This provides a clear visual indicator of the current cycle's progression and approximations of when the next low may occur.
Optimized Future Time CyclesThis script is based on time cycles and visually displays the cyclical fluctuations of the past and future, helping to predict trend reversal points and market turning points. Below, I will explain the main functions of this indicator and how to interpret it.
1. Main Features of the Indicator
Time Cycle Settings:
Users can set different time cycles (e.g., 9 days, 17 days, 26 days), and each cycle is visually distinguished by colors and labels.
A specific date is set as the reference date, from which the cycles are calculated. The cycles appear as vertical lines on the chart, both in the past and future, allowing you to spot trend reversals.
Future and Past Cycles:
Future cycles help predict when trend changes will occur in the future. Based on the set cycles, you can anticipate turning points in market trends.
Past cycles allow you to examine historical cycles, providing insights into past market movements, which can serve as a basis for predicting future patterns. This helps identify similar patterns from the past that might repeat.
2. How to Use and Interpret the Indicator
Reference Date Setting:
The reference date is a crucial factor in this indicator. For example, if you set the reference date as an important market turning point in the past, you can obtain a more accurate analysis.
If the reference date is too recent, multiple cycles may overlap on the chart, but this is a normal phenomenon. In this case, it is recommended to set the reference date further back in time for a clearer chart.
Cycle Analysis:
Each cycle represents cyclical market volatility. Shorter cycles like 9-day, 17-day, and 26-day cycles represent different timeframes' volatility. When multiple cycles overlap, this could indicate a significant trend reversal.
Pay attention to points where cycles overlap, as these could signal stronger trend changes.
Importance of Future Cycles:
It’s especially important to pay attention to future cycles as they provide insights into potential trend reversals. Future cycles can indicate likely points of trend reversal, helping you prepare in advance.
3. Additional Considerations
Vertical Line and Label Spacing:
Since multiple cycles are displayed on the chart simultaneously, you can customize the spacing of the vertical lines and labels. If the chart becomes too crowded, you can adjust the line style (solid, dotted, etc.) to reduce visual clutter.
Short-Term vs. Long-Term Cycles:
Short-term cycles (e.g., 9-day cycles) are useful for predicting short-term volatility, while long-term cycles (e.g., 200-day cycles) help predict larger trend changes. You can combine short and long cycles for deeper analysis.
4. Recommended Combination: With Moving Average Wave Indicator
This time cycle indicator works well in combination with the Moving Average Wave Indicator. While the time cycle indicator identifies timing for trend changes, the Moving Average Wave Indicator visually shows the direction of the trend. When used together, they offer precise entry and exit points for trades.
Time Cycles indicate when a trend change might occur, and Moving Average Waves show the direction of that trend at those specific points. Combining both helps you identify strong buy/sell signals.
5. Conclusion
This indicator uses time cycles to help you predict past and future market volatility. The reference date plays a critical role, and when multiple cycles overlap, you can expect strong trend reversals. Focusing on future cycles and combining this with the Moving Average Wave Indicator allows you to grasp both the timing and direction of trend changes, making this a powerful tool for market analysis.
"It is recommended to combine it with the Ichimoku Wave Oscillator with Custom MA indicator."
이 스크립트는 **시간 주기(Time Cycle)**에 기반한 지표로, 과거 및 미래의 주기적 변동을 시각적으로 보여주어 추세 변화의 시점과 시장 변곡점을 예측하는 데 도움을 줍니다. 이 지표의 주요 기능과 해석 방법을 중심으로 자세히 설명드리겠습니다.
1. 지표의 주요 기능
시간 주기 설정:
각기 다른 시간 주기(9일, 17일, 26일 등)를 사용자가 설정할 수 있으며, 각 주기는 색상과 레이블로 시각적으로 구분됩니다.
특정 날짜를 **기준 날짜(reference date)**로 설정하여 그 날짜부터 주기들이 계산됩니다. 기준 날짜를 기반으로 과거와 미래의 주기가 차트에 수직선과 함께 나타나며, 이를 통해 추세의 변곡점을 확인할 수 있습니다.
미래 주기 및 과거 주기:
미래 주기는 미래의 추세 변화 시점을 예측하는 데 도움이 됩니다. 각 주기가 설정된 기준에 따라 추세 변곡점이 언제 도래할지 미리 알 수 있습니다.
과거 주기는 과거 시장에서의 주기적 변동을 확인하여, 앞으로의 시장 움직임을 예측하는 데 참고할 수 있습니다. 이를 통해 과거와 유사한 패턴을 포착할 수 있습니다.
2. 지표 사용 및 해석 방법
기준 날짜 설정:
이 지표의 기준 날짜는 매우 중요한 요소입니다. 예를 들어, 시장에서 중요한 변동이 있었던 날짜를 기준으로 설정하면 더 정확한 분석이 가능합니다.
기준 날짜가 너무 최근일 경우, 여러 주기들이 차트 상에서 겹칠 수 있는데 이는 정상적인 현상입니다. 이 경우, 기준 날짜를 더 과거로 설정하면 차트가 좀 더 깔끔하게 보일 수 있습니다.
주기 분석:
각 주기는 시장 변동성의 주기적 패턴을 나타냅니다. 9일, 17일, 26일 등의 주기는 각기 다른 시간대의 변동성을 나타내며, 주기가 겹칠 때 추세 전환 시점이 강하게 나타날 수 있습니다.
주기가 겹치는 시점에서 변동이 강해질 가능성이 있으며, 이때는 추세 변화에 주목할 필요가 있습니다.
미래 주기의 중요성:
특히 미래 주기를 확인하는 것이 중요한데, 미래에 어떤 시점에서 변곡점이 나타날지 예측하는 데 사용할 수 있기 때문입니다. 미래 주기는 추세 전환 가능성이 높은 시점을 알려줄 수 있으므로, 미리 준비하고 대응할 수 있게 도와줍니다.
3. 추가적으로 고려할 사항
수직선과 레이블 간격:
여러 주기들이 한꺼번에 차트에 표시되기 때문에, 수직선이나 레이블 간의 간격을 커스터마이징할 수 있습니다. 특히, 차트가 혼잡할 경우 선 스타일(실선, 점선 등)을 조정하여 시각적으로 덜 복잡하게 설정할 수 있습니다.
단기 vs. 장기 주기:
**단기 주기(예: 9일)**는 빠른 변동성을 예측하는 데 유리하며, **장기 주기(예: 200일)**는 더 큰 추세 변화를 예측하는 데 도움이 됩니다. 두 주기 간의 상호작용을 고려하여 분석의 깊이를 더할 수 있습니다.
4. 결합 사용 추천: 이평선 파동 지표와 함께
이 시간 주기 지표는 이평선 파동 지표와 결합하여 사용할 때 추세의 방향성과 변곡점을 동시에 분석하는 데 매우 유용합니다.
시간 주기는 추세 변곡점의 시점을 알려주고, 이평선 파동은 그 시점에서의 추세 방향성을 시각적으로 나타내므로, 두 지표를 함께 사용하면 정확한 매매 타이밍을 잡는 데 큰 도움이 됩니다.
5. 결론
이 지표는 **시간 주기(Time Cycle)**를 활용하여 과거 및 미래의 시장 변동성을 예측할 수 있도록 도와줍니다. 특히, 기준 날짜 설정이 매우 중요하며, 여러 주기가 겹치는 시점에서는 강한 추세 전환을 예상할 수 있습니다. 미래 주기를 중점적으로 분석하고, 이평선 파동 지표와 결합하여 사용하면 추세 변화의 방향성과 시점을 동시에 잡아낼 수 있어 매우 유용합니다. "Ichimoku Wave Oscillator with Custom MA 지표와 결합해서 사용하면 좋습니다."
Fourier For Loop [BackQuant]Fourier For Loop
PLEASE Read the following, as understanding an indicator's functionality is essential before integrating it into a trading strategy. Knowing the core logic behind each tool allows for a sound and strategic approach to trading.
Introducing BackQuant's Fourier For Loop (FFL) — a cutting-edge trading indicator that combines Fourier transforms with a for-loop scoring mechanism. This innovative approach leverages mathematical precision to extract trends and reversals in the market, helping traders make informed decisions. Let's break down the components, rationale, and potential use-cases of this indicator.
Understanding Fourier Transform in Trading
The Fourier Transform decomposes price movements into their frequency components, allowing for a detailed analysis of cyclical behavior in the market. By transforming the price data from the time domain into the frequency domain, this indicator identifies underlying patterns that traditional methods may overlook.
In this script, Fourier transforms are applied to the specified calculation source (defaulted to HLC3). The transformation yields magnitude values that can be used to score market movements over a defined range. This scoring process helps uncover long and short signals based on relative strength and trend direction.
Why Use Fourier Transforms?
Fourier Transforms excel in identifying recurring cycles and smoothing noisy data, making them ideal for fast-paced markets where price movements may be erratic. They also provide a unique perspective on market volatility, offering traders additional insights beyond standard indicators.
Calculation Logic: For-Loop Scoring Mechanism
The For Loop Scoring mechanism compares the magnitude of each transformed point in the series, summing the results to generate a score. This score forms the backbone of the signal generation system.
Long Signals: Generated when the score surpasses the defined long threshold (default set at 40). This indicates a strong bullish trend, signaling potential upward momentum.
Short Signals: Triggered when the score crosses under the short threshold (default set at -10). This suggests a bearish trend or potential downside risk.'
Thresholds & Customization
The indicator offers customizable settings to fit various trading styles:
Calculation Periods: Control how many periods the Fourier transform covers.
Long/Short Thresholds: Adjust the sensitivity of the signals to match different timeframes or risk preferences.
Visualization Options: Traders can visualize the thresholds, change the color of bars based on trend direction, and even color the background for enhanced clarity.
Trading Applications
This Fourier For Loop indicator is designed to be versatile across various market conditions and timeframes. Some of its key use-cases include:
Cycle Detection: Fourier transforms help identify recurring patterns or cycles, giving traders a head-start on market direction.
Trend Following: The for-loop scoring system helps confirm the strength of trends, allowing traders to enter positions with greater confidence.
Risk Management: With clearly defined long and short signals, traders can manage their positions effectively, minimizing exposure to false signals.
Final Note
Incorporating this indicator into your trading strategy adds a layer of mathematical precision to traditional technical analysis. Be sure to adjust the calculation start/end points and thresholds to match your specific trading style, and remember that no indicator guarantees success. Always backtest thoroughly and integrate the Fourier For Loop into a balanced trading system.
Thus following all of the key points here are some sample backtests on the 1D Chart
Disclaimer: Backtests are based off past results, and are not indicative of the future .
INDEX:BTCUSD
INDEX:ETHUSD
BINANCE:SOLUSD
2024 - Seasonality - Open to CloseScript Description:
This Pine Script is designed to visualise **seasonality** in the financial markets by calculating the **open-to-close percentage change** for each month of a selected asset. It creates a **heatmap** table to display the monthly performance over multiple years. The script provides detailed statistical summaries, including:
- **Average monthly percentage changes**
- **Standard deviation** of the changes
- **Percentage of months with positive returns**
The script also allows users to adjust colour intensities for positive and negative values, specify which year to start from, and skip specific months. Key metrics such as averages, standard deviations, and percentages of positive months can be toggled on or off based on user preferences. The result is a clear, visual representation of how an asset typically performs month by month, aiding in seasonality analysis.
Fed Net LiquidityNet Liquidity = Federal Reserve Total Assets - Treasury General Account (TGA) - Reverse Repurchase Agreements (RRP) Balance
1. Federal Reserve Total Assets: This is the sum of everything the Fed owns, like government bonds and mortgage-backed securities. You can snag this data from the Fed’s weekly balance sheet report.
2. Treasury General Account (TGA): Think of this as the U.S. government’s checking account at the Fed. When the TGA balance goes up, it means the government is pulling liquidity out of the market, and vice versa.
3. Reverse Repurchase Agreements (RRP) Balance: This represents the liquidity the Fed absorbs from the market through reverse repo operations. When financial institutions park money in the Fed’s RRP account, there’s less cash available in the market.
Why Use Net Liquidity?
Net liquidity is seen as a key indicator of the actual amount of money available in the market. It helps gauge the overall liquidity conditions that can influence financial markets.
Where to Find the Data:
1. Federal Reserve Total Assets: You can find this in the Fed’s weekly balance sheet (the H.4.1 report). Here’s the link: Federal Reserve Statistical Release - H.4.1.
Steps to Calculate Net Liquidity Yourself:
1. Get the Fed’s Total Assets: Look up the latest H.4.1 report and jot down the total assets figure.
2. Find the TGA Balance: Head over to the U.S. Treasury’s Daily Treasury Statement to locate the “Treasury General Account” balance.
3. Get the RRP Balance: You can find this number in the H.4.1 report or on the New York Fed’s website under “Reverse Repurchase Agreements.”
4. Do the Math: Simply subtract the TGA and RRP balances from the Fed’s total assets—that gives you the net liquidity.
Relative PPP for USDBRLThis indicator calculates the USDBRL exchange rate using the Relative Purchasing Power Parity method, which considers that the variation in the exchange rate is equal to the variation in inflation in Brazil minus the variation in inflation in the US. It is derived from the Law of One Price, which states that an identical good should have the same price in different markets when adjusted for exchange rates, assuming the absence of arbitrage barriers such as transaction costs or trade restrictions.
The indicator is calculated starting from June 1994, at the launch of the Real Plan, which equalized the value of the Brazilian Real and the US Dollar at that time. This indicator is useful for providing an idea of the long-term trend of the Dollar exchange rate (months or years), acting similarly to a moving average, around which the exchange rate gravitates.
It's useful for analysts who have to forecast the USDBRL in the long term.