Korneev Reverse RSIRethinking the Legendary Relative Strength Index by John Welles Wilder
The essence of the new approach lies in the reverse use of the so-called "overbought" and "oversold" zones. In his 1978 book, "New Concepts in Technical Trading Systems," where the RSI mechanism was thoroughly described, Wilder writes that one way to use the oscillator is to open a long position when the RSI drops into oversold territory (below 30) and to open a short position when the RSI rises to overbought levels (above 70). However, backtesting this strategy with such inputs yields rather mediocre results.
Based on the calculation formula, the RSI calculates the rate of price change over a certain period. Therefore, overbought and oversold zones will have relative significance (relative to the set calculation period). It is no coincidence that the word "relative" was added to the name of the oscillator. It is worth accepting as an axiom the assertion that the price of an asset is fair at every moment in time.
Essentially, the RSI calculates the strength of a trend. If the oscillator value is above 70, it is highly likely that an upward movement is occurring in the market. Therefore, in the current strategy, a long position is opened precisely at the moment of greatest buyer strength (when RSI > 80), i.e., in the direction of the trend, since counter-trend trading with the RSI has proven to be ineffective. The position is closed after the buyers lose their advantage and the RSI drops to 40.
The strategy is recommended to be used only with long positions, as short positions show negative results. The strategy uses a moving average for the RSI with a period of 14 to smooth the oscillator data.
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Переосмысление легендарного осциллятора Relative strength index Джона Уэллса Уайлдера
Суть нового подхода заключается в реверсивном использовании так называемых зон "перекупленности" и "перепроданности". В своей книге от 1978 года "New concepts in tecnical trading systems", в которой был подробно описан механизм работы RSI, Уайлдер пишет, что один из способов использования осциллятора - открытие длинной позиции при снижении RSI в перепроданность (ниже 30) и открытие короткой позиции при повышении RSI до перекупленности (выше 70). Однако бэктест стратегии с такими вводными дает весьма посредственные результаты.
Исходя из формулы расчета, RSI рассчитывает скорость изменения цены за определенный период. Поэтому зоны перекупленности и перепроданности будут иметь относительное значение (относительно установленного периода расчета). Не зря ведь в названии осциллятора было добавлено слово "относительной". Стоит принять за аксиому утверждение, что цена актива справедлива в каждый момент времени.
По сути, RSI рассчитывает силу тренда. Если значение осциллятора выше 70, то на рынке с высокой долей вероятности происходит восходящее движение. Поэтому в текущей стратегии открытие лонга происходит именно в момент наибольшей силы покупателей (когда RSI > 80), то есть в сторону тренда, поскольку контртрендовая торговля по RSI показала свою несостоятельность. Закрытие позиции происходит после того, как покупатели теряют преимущество и RSI снижается до 40.
Стратегию рекомендуется использовать только с длинными позициями, поскольку короткие позиции показывают отрицательный результат. В стратегии используется скользящая средняя для RSI с периодом 14 для сглаживания данных осциллятора.
Cari dalam skrip untuk "backtesting"
Volume Breaker Blocks [UAlgo]The "Volume Breaker Blocks " indicator is designed to identify breaker blocks in the market based on volume and price action. It is a concept that emerges when an order block fails, leading to a change in market structure. It signifies a pivotal point where the market shifts direction, offering traders opportunities to enter trades based on anticipated trend continuation.
🔶 Key Features
Identifying Breaker Blocks: The indicator identifies breaker blocks by detecting pivot points in price action and corresponding volume spikes.
Breaker Block Sensitivity: Traders can adjust breaker block detection sensitivity, length to be used to find pivot points.
Mitigation Method (Close or Wick): Traders can choose between "Close" and "Wick" as the mitigation method. This choice determines whether the indicator considers closing prices or wicks in identifying breaker blocks. Selecting "Close" implies that breaker blocks will be considered broken when the closing price violates the block, while selecting "Wick" implies that the wick of the candle must violate the block for it to be considered broken.
Show Last X Breaker Blocks: Users can specify how many of the most recent breaker blocks to display on the chart.
Visualization: Volume breaker blocks are visually represented on the chart with customizable colors and text labels, allowing for easy interpretation of market conditions. Each breaker block is accompanied by informational text, including whether it's bullish or bearish and the corresponding volume, aiding traders in understanding the significance of each block.
🔶 Disclaimer
Educational Purpose: The "Volume Breaker Blocks " indicator is provided for educational and informational purposes only. It does not constitute financial advice or a recommendation to engage in trading activities.
Risk of Loss: Trading in financial markets involves inherent risks, including the risk of loss of capital. Users should carefully consider their financial situation, risk tolerance, and investment objectives before engaging in trading activities.
Accuracy Not Guaranteed: While the indicator aims to identify potential reversal points in the market, its accuracy and effectiveness may vary. Users should conduct thorough testing and analysis before relying solely on the indicator for trading decisions.
Past Performance: Past performance is not indicative of future results. Historical data and backtesting results may not accurately reflect actual market conditions or future performance.
Sticky Notes, Checklist, To-do, Journal [algoat]I forgot to bring my notes again...
Ever feel like your trading notes are all over the place, much like your portfolio after a market dip? Worry not! With this script, you'll have all your trading notes, tasks, and brilliant (or not so brilliant) ideas neatly organized right on your chart. It's like having a sticky note board, but way cooler and without the risk of paper cuts.
⭐ Features :
To-Do Lists
Keep track of tasks with satisfying checkmarks for those dopamine hits.
Journal Entries
Document your market insights, trade plans, or just random thoughts. "I forgot something" – we've all been there.
Due Dates
Never miss an important deadline again. Red alert for overdue tasks because procrastination is a trader's worst enemy.
Customization
Choose the size and position of your notes because one size doesn't fit all.
Perfect for the organized trader who loves a bit of fun or the chaotic one who needs a bit of structure. Embrace the power of notes and stay on top of your trading game!
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🧠 General advice
Trading effectively requires a range of techniques, experience, and expertise. From technical analysis to market fundamentals, traders must navigate multiple factors, including market sentiment and economic conditions. However, traders often find themselves overwhelmed by market noise, making it challenging to filter out distractions and make informed decisions. By integrating multiple analytical approaches, traders can tailor their strategies to fit their unique trading styles and objectives.
Confirming Signals with other indicators
As with all technical indicators, it is important to confirm potential signals with other analytical tools, such as support and resistance levels, as well as indicators like RSI, MACD, and volume. This helps increase the probability of a successful trade.
Use proper risk management
When using this or any other indicator, it is crucial to have proper risk management in place. Consider implementing stop-loss levels and thoughtful position sizing.
Combining with other technical indicators
The indicator can be effectively used alongside other technical indicators to create a comprehensive trading strategy and provide additional confirmation.
Keep in mind
Thorough research and backtesting are essential before making any trading decisions. Furthermore, it's crucial to have a solid understanding of the indicator and its behavior. Additionally, incorporating fundamental analysis and considering market sentiment can be vital factors to take into account in your trading approach.
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⭐ Conclusion
We hold the view that the true path to success is the synergy between the trader and the tool, contrary to the common belief that the tool itself is the sole determinant of profitability. The actual scenario is more nuanced than such an oversimplification. A word to the wise is enough: developed by traders, for traders — pioneering innovations for the modern era.
Risk Notice
Everything provided by algoat — from scripts, tools, and articles to educational materials — is intended solely for educational and informational purposes. Past performance does not assure future returns.
Trend Following Parabolic Buy Sell Strategy [TradeDots]The Trend Following Parabolic Buy-Sell Strategy leverages the Parabolic SAR in combination with moving average crossovers to deliver buy and sell signals within a trend-following framework.
This strategy synthesizes proven methodologies sourced from various trading tutorials available on platforms such as YouTube and blogs, enabling traders to conduct robust backtesting on their selected trading pairs to assess the strategy's effectiveness.
HOW IT WORKS
This strategy employs four key indicators to orchestrate its trading signals:
1. Trend Alignment: It first assesses the relationship between the price and the predominant trendline to determine the directional stance—taking long positions only when the price trends above the moving average, signaling an upward market trajectory.
2. Momentum Confirmation: Subsequent to trend alignment, the strategy looks for moving average crossovers as a confirmation that the price is gaining momentum in the direction of the intended trades.
3. Signal Finalization: Finally, buy or sell signals are validated using the Parabolic SAR indicator. A long order is validated when the closing price is above the Parabolic SAR dots, and similarly, conditions are reversed for short orders.
4. Risk Management: The strategy institutes a fixed stop-loss at the moving average trendline and a take-profit level determinable by a prefixed risk-reward ratio calculated from the moving average trendline. These parameters are customizable by the users within the strategy settings.
APPLICATION
Designed for assets exhibiting pronounced directional momentum, this strategy aims to capitalize on clear trend movements conducive to achieving set take-profit targets.
As a lagging strategy that waits for multiple confirmatory signals, entry into trades might occasionally lag beyond optimal timing.
Furthermore, in periods of consolidation or sideways movement, the strategy may generate several false signals, suggesting the potential need for additional market condition filters to enhance signal accuracy during volatile phases.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 70%
Users are advised to adjust and personalize this trading strategy to better match their individual trading preferences and style.
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
LumleyTrading GapsName: LumleyTrading Gaps
Description:
The Gap Tracker Indicator is a powerful tool designed for traders to identify, monitor, and capitalize on price gaps in financial markets. It serves two primary functions:
Identifying Gaps: The indicator scans price action to detect instances where the current trading session's opening price significantly differs from the previous session's closing price. These disparities indicate the presence of price gaps.
Tracking Gap Fills: Once a gap is identified, the indicator continues to monitor the price movement. It dynamically adjusts its parameters to track whether and when the price retraces back to fill the gap. As soon as the gap is filled, the indicator generates a signal to notify traders of this occurrence.
Key Features:
Customizable Parameters: Traders can adjust the sensitivity and criteria for what constitutes a significant gap based on their trading preferences and the market conditions.
Visual Alerts: The indicator provides clear visual signals on price charts, highlighting the presence of gaps and indicating when they are filled. This helps traders to easily spot trading opportunities and make informed decisions.
Alert Notifications: In addition to visual cues, traders can opt to receive real-time alerts via email, SMS, or within their trading platform, ensuring they never miss an opportunity or a filled gap.
Historical Analysis: The indicator may also offer historical gap data, allowing traders to conduct backtesting and analyze the performance of trading strategies based on gap patterns.
Benefits:
Gap Trading Opportunities: Traders can use the indicator to identify potential areas of price continuation or reversal, leveraging the phenomenon of gap trading for profit.
Risk Management: By tracking gap fills, traders can manage their risk more effectively, knowing when a gap is likely to act as support or resistance and adjusting their positions accordingly.
Enhanced Decision Making: With real-time gap detection and fill tracking, traders gain valuable insights into market sentiment and price dynamics, empowering them to make timely and informed trading decisions.
Compatibility:
The Gap Tracker Indicator is compatible with popular trading platforms and can be seamlessly integrated into various technical analysis tools and strategies.
Conclusion:
In the fast-paced world of financial markets, identifying and understanding price gaps is crucial for successful trading. The Gap Tracker Indicator provides traders with a reliable tool to spot, track, and capitalize on gap opportunities, enhancing their trading efficiency and profitability.
Normalised T3 Oscillator [BackQuant]Normalised T3 Oscillator
The Normalised T3 Oscillator is an technical indicator designed to provide traders with a refined measure of market momentum by normalizing the T3 Moving Average. This tool was developed to enhance trading decisions by smoothing price data and reducing market noise, allowing for clearer trend recognition and potential signal generation. Below is a detailed breakdown of the Normalised T3 Oscillator, its methodology, and its application in trading scenarios.
1. Conceptual Foundation and Definition of T3
The T3 Moving Average, originally proposed by Tim Tillson, is renowned for its smoothness and responsiveness, achieved through a combination of multiple Exponential Moving Averages and a volume factor. The Normalised T3 Oscillator extends this concept by normalizing these values to oscillate around a central zero line, which aids in highlighting overbought and oversold conditions.
2. Normalization Process
Normalization in this context refers to the adjustment of the T3 values to ensure that the oscillator provides a standard range of output. This is accomplished by calculating the lowest and highest values of the T3 over a user-defined period and scaling the output between -0.5 to +0.5. This process not only aids in standardizing the indicator across different securities and time frames but also enhances comparative analysis.
3. Integration of the Oscillator and Moving Average
A unique feature of the Normalised T3 Oscillator is the inclusion of a secondary smoothing mechanism via a moving average of the oscillator itself, selectable from various types such as SMA, EMA, and more. This moving average acts as a signal line, providing potential buy or sell triggers when the oscillator crosses this line, thus offering dual layers of analysis—momentum and trend confirmation.
4. Visualization and User Interaction
The indicator is designed with user interaction in mind, featuring customizable parameters such as the length of the T3, normalization period, and type of moving average used for signals. Additionally, the oscillator is plotted with a color-coded scheme that visually represents different strength levels of the market conditions, enhancing readability and quick decision-making.
5. Practical Applications and Strategy Integration
Traders can leverage the Normalised T3 Oscillator in various trading strategies, including trend following, counter-trend plays, and as a component of a broader trading system. It is particularly useful in identifying turning points in the market or confirming ongoing trends. The clear visualization and customizable nature of the oscillator facilitate its adaptation to different trading styles and market environments.
6. Advanced Features and Customization
Further enhancing its utility, the indicator includes options such as painting candles according to the trend, showing static levels for quick reference, and alerts for crossover and crossunder events, which can be integrated into automated trading systems. These features allow for a high degree of personalization, enabling traders to mold the tool according to their specific trading preferences and risk management requirements.
7. Theoretical Justification and Empirical Usage
The use of the T3 smoothing mechanism combined with normalization is theoretically sound, aiming to reduce lag and false signals often associated with traditional moving averages. The practical effectiveness of the Normalised T3 Oscillator should be validated through rigorous backtesting and adjustment of parameters to match historical market conditions and volatility.
8. Conclusion and Utility in Market Analysis
Overall, the Normalised T3 Oscillator by BackQuant stands as a sophisticated tool for market analysis, providing traders with a dynamic and adaptable approach to gauging market momentum. Its development is rooted in the understanding of technical nuances and the demand for a more stable, responsive, and customizable trading indicator.
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
Consecutive count backtester / quantifytools- Overview
Consecutive counting is a simple method to mechanically define trending states to the upside and downside. Consecutive counts are calculated by taking reference price level (e.g. close 4 candles ago) and count closes above/below it up to a maximum count that resets the consecutive count back to 1. This tool provides the means to backtest each count by measuring % change in price after each count (e.g. % gain 2 candles after a given count).
Users can define reference source that starts the consecutive count (e.g. close 4 candles ago), maximum count where counter resets (e.g. after 9th count) and backtesting period (e.g. price change 2 candles after count).
Filters add extra conditions that must be met on the consecutive count to qualify as valid, which are also reflected on the backtest metrics. The counts can be refined using the following filters:
- RSI above/below X
- Price above/below/at moving average of choice
- Relative volume above/below X
Average gain corresponding to each count as they occur can be toggled off for less clutter. Average price change can also be visualized using candle color. Colors, gradient and table/label sizes are fully customizable.
- Practical guide
Example #1: Identify reversal potential
Consecutive counting is a simple yet effective method to for detecting reversals, for which 7-9 counts are traditionally used. Whether that holds true or not can now be put through a test with different variations of the method as well as using additional filters to improve the probability of a turn.
Example #2: Identify trend following potential
Consecutive counts can also have utility value for trend following. When historical short term change is to the downside, expect downside, when to the upside, expect upside.
Khaled Tamim's Avellaneda-Stoikov StrategyDescription:
This strategy applies the Avellaneda-Stoikov (A-S) model to generate buy and sell signals for underlying assets based on option pricing theory. The A-S model estimates bid and ask quotes for options contracts considering factors like volatility (sigma), time to expiration (T), and risk aversion (gamma).
Key Concepts:
Avellaneda-Stoikov Model: A mathematical framework for option pricing that incorporates volatility, time decay, and risk tolerance.
Bid-Ask Quotes: The theoretical buy and sell prices for an option contract.
Inventory Management: The strategy tracks its long or short position based on signals.
How it Works:
A-S Model Calculation: The avellanedaStoikov function calculates bid and ask quotes using the underlying asset's closing price, user-defined parameters (gamma, sigma, T, k, and M), and a small fee (adjustable).
Signal Generation: The strategy generates long signals when the closing price falls below the adjusted bid quote and short signals when it exceeds the adjusted ask quote.
Trade Execution: Buy and sell orders are triggered based on the generated signals (long for buy, short for sell).
Inventory Tracking: The strategy's net profit reflects the current inventory level (long or short position).
Customization:
Gamma (γ): Controls risk aversion in the A-S model (higher values imply lower risk tolerance).
Sigma (σ): Represents the underlying asset's expected volatility.
T: Time to expiration for the hypothetical option (defaults to a short-term option).
k: A constant factor in the A-S model calculations.
M: Minimum price buffer for buy/sell signals (prevents excessive churn).
Important Note:
This strategy simulates option pricing behavior for a theoretical option and does not directly trade options contracts. Backtesting results may not reflect actual market conditions.
Further Considerations:
The 0.1% fee is a placeholder and may need adjustment based on real-world trading costs.
Consider using realistic timeframes for T (e.g., expiry for a real option)
Disclaimer: This strategy is for educational purposes only and does not constitute financial advice.
Volume-Supported Linear Regression Trend Modified StrategyHi everyone, this will be my first published script on Tradingview, maybe more to come.
For quite some time I have been looking for a script that performs no matter if price goes up or down or sideways. I believe this strategy comes pretty close to that. Although nowhere near the so called "buy&hold equity" of BTC, it has produced consistent profits even when price goes down.
It is a strategy which seems to work best on the 1H timeframe for cryptocurrencies.
Just by testing different settings for SL and TP you can customize it for each pair.
THE STRATEGY:
Basically, I used the Volume Supported Linear Regression Trend Model that LonesomeTheBlue has created and modified a few things such as entry and exit conditions. So all credits go to him!
LONG ENTRY: When there is a bullish cross of the short term trend (the histogram/columns), while the long term trend is above 0 and rising.
SHORT ENTRY: When there is a bearish cross (green to red) of the short-term trend (the histogram/columns), while the long term trend is beneath 0 and decreasing.
LONG EXIT: Bearish crossover of short-term trend while long term trend is below 0
SHORT EXIT: Bullish crossover of short-term trend while long term trend is above 0
Combining this with e.g. a SL of 2% and a TP of 20% (as used in my backtesting), combined with pyramiding and correct risk management, it gives pretty consistent results.
Be aware, this is only for educational purpose and in no means financial advise. Past results do not guarantee future results. This strategy can lose money!
Enjoy :)
PS: It works not only on BTC of course, works even better on some other major crypto pairs. I'll leave it to you to find out which ones ;)
FVG Breakaway/3rd Candle (Arjo) [MK]Simple script to identify FVGs (Fair Value Gaps) on the current chart timeframe. The script differs from other FVG indicators on the Tradingview platform by using Arjos 3rd candle rule to identify which gaps are 'Breakway Gaps' and which Gaps are likely to be returned to.
NOTE: As with all 'trading rules' this theory is not 100% accurate.
default settings:
Breakaway Gaps = YELLOW
Gaps that price may return to = GREEN
Mitigated Gaps = 100% TRANSPARENT
What is a FVG:
A FVG is a price area defined by a 3 candle pattern. For a bullish FVG, the low of the 3rd candle must be higher than the high of the 1st candle. This then leaves an area that is drawn as in the example below:
A bearish FVG is defined by the high of the 3rd candle being lower than the low of the 1st candle, as shown in the example below:
FVGs can act like magnets where price will either retrace to or reach for, therefore they can be used as entry points and also for take profit target levels.
If for example, a trader would like to use an FVG for an entry, it would be useful to know which FVGs are more likely for price to re-enter and which FVG will be left un-touched. FVGs that are likely to be left un-touched by price are called 'Breakaway Gaps'.
How do we define a 'Breakaway Gap':
First we identify FVGs using the rules stated above, then we look to see where the 3rd candle closed in relation to the 2nd candle. For a bullish 'Breakaway Gap' we want to see the 3rd candle close above the high of the 2nd candle. An example of a bullish Breakaway Gap is shown in the example below:
A bearish 'Breakaway Gap' is defined by the close of the 3rd candle being lower than the low of the 2nd candle. An example is shown below:
How do we define an FVG that price may return to:
Any gap that does not meet the above rules for a 'Breakway Gap' is therefore considered an FVG that price may return to. So for a bullish FVG that price may return to we would look to see if the close of the 3rd candle is above the high of the 2nd candle. If it is not above the high of the 2nd candle then it more likely that price will retrace into the FVG before continuing higher. An example is shown below:
A bearish gap that price may return to is defined by the close of the 3rd candle not being lower than the low of the 2nd candle. An example is shown below:
The indicator is based on the teachings of 'Arjo'. Note: breakaway gaps will only remain 'breakaway' until a liquidity level is reached. Breakaways therefore do not remain 'breakaway' forever. Users of the indicators must fully comprehend this theory before using the indicator with live markets.
Users of the script should be fully aware of this concept and also have conducted thorough backtesting using a large data set before using this indicator with live accounts.
Price Based Z-Trend - Strategy [presentTrading]█ Introduction and How it is Different
Z-score: a statistical measurement of a score's relationship to the mean in a group of scores.
Simple but effective approach.
The "Price Based Z-Trend - Strategy " leverages the Z-score, a statistical measure that gauges the deviation of a price from its moving average, normalized against its standard deviation. This strategy stands out due to its simplicity and effectiveness, particularly in markets where price movements often revert to a mean. Unlike more complex systems that might rely on a multitude of indicators, the Z-Trend strategy focuses on clear, statistically significant price movements, making it ideal for traders who prefer a streamlined, data-driven approach.
BTCUSD 6h LS Performance
█ Strategy, How It Works: Detailed Explanation
🔶 Calculation of the Z-score
"Z-score is a statistical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score. A Z-score of 1.0 would indicate a value that is one standard deviation from the mean. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean."
The Z-score is central to this strategy. It is calculated by taking the difference between the current price and the Exponential Moving Average (EMA) of the price over a user-defined length, then dividing this by the standard deviation of the price over the same length:
z = (x - μ) /σ
Local
🔶 Trading Signals
Trading signals are generated based on the Z-score crossing predefined thresholds:
- Long Entry: When the Z-score crosses above the positive threshold.
- Long Exit: When the Z-score falls below the negative threshold.
- Short Entry: When the Z-score falls below the negative threshold.
- Short Exit: When the Z-score rises above the positive threshold.
█ Trade Direction
The strategy allows users to select their preferred trading direction through an input option.
█ Usage
To use this strategy effectively, traders should first configure the Z-score thresholds according to their risk tolerance and market volatility. It's also crucial to adjust the length for the EMA and standard deviation calculations based on historical performance and the expected "noise" in price data.
The strategy is designed to be flexible, allowing traders to refine settings to better capture profitable opportunities in specific market conditions.
█ Default Settings
- Trade Direction: Both
- Standard Deviation Length: 100
- Average Length: 100
- Threshold for Z-score: 1.0
- Bar Color Indicator: Enabled
These settings offer a balanced starting point but can be customized to suit various trading styles and market environments. The strategy's parameters are designed to be adjusted as traders gain experience and refine their approach based on ongoing market analysis.
Z-score is a must-learn approach for every algorithmic trader.
Rise Sense Capital - RSI MACD Spot Buying IndicatorToday, I'll share a spot buying strategy shared by a member @KR陳 within the DATA Trader Alliance Alpha group. First, you need to prepare two indicators:
今天分享一個DATA交易者聯盟Alpha群組裏面的群友@KR陳分享的現貨買入策略。
首先需要準備兩個指標
RSI Indicator (Relative Strength Index) - RSI is a technical analysis tool based on price movements over a period of time to evaluate the speed and magnitude of price changes. RSI calculates the changes in price over a period to determine whether the recent trend is relatively strong (bullish) or weak (bearish).
RSI指標，(英文全名:Relative Strength Index)，中文稱為「相對強弱指標」，是一種以股價漲跌為基礎，在一段時間內的收盤價，用於評估價格變動的速度 (快慢) 與變化 (幅度) 的技術分析工具，RSI藉由計算一段期間內股價的漲跌變化，判斷最近的趨勢屬於偏強 (偏多) 還是偏弱 (偏空)。
MACD Indicator (Moving Average Convergence & Divergence) - MACD is a technical analysis tool proposed by Gerald Appel in the 1970s. It is commonly used in trading to determine trend reversals by analyzing the convergence and divergence of fast and slow lines.
MACD 指標 (Moving Average Convergence & Divergence) 中文名為平滑異同移動平均線指標，MACD 是在 1970 年代由美國人 Gerald Appel 所提出，是一項歷史悠久且經常在交易中被使用的技術分析工具，原理是利用快慢線的交錯，藉以判斷股價走勢的轉折。
In MACD analysis, the most commonly used values are 12, 26, and 9, known as MACD (12,26,9). The market often uses the MACD indicator to determine the future direction of assets and to identify entry and exit points.
在 MACD 的技術分析中，最常用的值為 12 天、26 天、9 天，也稱為 MACD (12,26,9)，市場常用 MACD 指標來判斷操作標的的後市走向，確定波段漲幅並找到進、出場點。
Strategy analysis by member KR陳:
策略解析 by群友 KR陳 ：
Condition 1: RSI value in the previous candle is below oversold zone(30).
條件1：RSI 在前一根的數值低於超賣區（30）
buycondition1 = RSI <30
Condition 2: MACD histogram changes from decreasing to increasing.
條件2：MACD柱由遞減轉遞增
buycondition2 = hist >hist and hist <hist
Strategy Effect Display:
策略效果展示：
Slight modification:
稍微修改：
I've added the ATR-MACD, developed earlier, as a filter signal alongside the classic MACD. The appearance of an upward-facing triangle indicates that the ATR MACD histogram also triggers the condition, aiming to serve as a filtering mechanism.
我在經典的macd作爲條件的同時 也加入了之前開發的ATR-MACD作爲過濾信號 出現朝上的三角圖示代表ATR MACD的柱狀圖一樣觸發條件 希望可以以此起到過濾的作用
Asset/Usage Instructions:
使用標的/使用説明
Through backtesting, it's found that it's not suitable for smaller time frames as there's a lot of noise. It's recommended to use it in assets with a long-term bullish view, focusing on time frames of 12 hours or longer such as 12H, 16H, 1D, 1W to find spot buying opportunities.
經過回測發現 并不適用與一些小級別時區 噪音會非常多，建議在一些長期看漲的標的中切入12小時以上的時區如12H，16H, 1D, 1W 中間尋找現貨買入的機會。
A few thoughts:
Overall, it's a very good indicator strategy for spot buying in the physical market. Thanks to member @KR陳 for sharing!
一些小感言 綜合來看是一個針對現貨買入非常好的指標策略，感謝群友@KR陳的分享！
Previous Candle + Inside/OutsideThe script uses the previous candle of the current timeframe to assess the state of the current candle.
1. Previous candle high/low and midpoint are displayed
2. Highlights current bar if INSIDE previous candle
3. Highlights current bar if POTENTIAL OUTSIDE bar. This condition uses the logic that if the previous high/low has been swept and price then reaches previous bar 50%, then an OUTSIDE bar is possible.
4. If current candle breaks previous high/low, a label is added to identify.
5. If above condition is true and current candle color is opposite of previous, then label is highlighted to show possible bull/bear condition.
6. If current candle live price is below previous midpoint, a BEAR label is shown
7. If current candle live price is above previous midpoint, a BULL label is shown
I personally use the indicator on Daily/Weekly/Monthly charts to help with my overall market assessment. However users may find their own use for the indicator...or modify it to their own preferences.
As ever, the indicator should only be used with live trading accounts after thorough backtesting using a large data range.
London Killzone + Deviations[MK]For traders that use the London Killzone session high/low to project possible take profit targets.
The indicator will determine the current day London killzone high and low range and draw a range box to the right of the last candle on the chart. Drawing to the right of the chart keeps the workspace cleaner.
The high/low range is then used to project Standard Deviation levels above and below the London range.
Levels projected are +/- 1, 2, 2.5, 3, 4.
Users of the script should conduct proper backtesting using a large data range before applying to live accounts.
EMA Scalping StrategyEMA Slope Indicator Overview:
The indicator plots two exponential moving averages (EMAs) on the chart: a 9-period EMA and a 15-period EMA.
It visually represents the EMAs on the chart and highlights instances where the slope of each EMA exceeds a certain threshold (approximately 30 degrees).
Scalping Strategy:
Using the EMA Slope Indicator on a 5-minute timeframe for scalping can be effective, but it requires adjustments to account for the shorter time horizon.
Trend Identification: Look for instances where the 9-period EMA is above the 15-period EMA. This indicates an uptrend. Conversely, if the 9-period EMA is below the 15-period EMA, it suggests a downtrend.
Slope Analysis: Pay attention to the slope of each EMA. When the slope of both EMAs is steep (exceeds 30 degrees), it signals a strong trend. This can be a favorable condition for scalping as it suggests potential momentum.
Entry Points:
For Long (Buy) Positions: Consider entering a long position when both EMAs are sloping upwards strongly (exceeding 30 degrees) and the 9-period EMA is above the 15-period EMA. Look for entry points when price retraces to the EMAs or when there's a bullish candlestick pattern.
For Short (Sell) Positions: Look for opportunities to enter short positions when both EMAs are sloping downwards strongly (exceeding -30 degrees) and the 9-period EMA is below the 15-period EMA. Similar to long positions, consider entering on retracements or bearish candlestick patterns.
Exit Strategy: Use tight stop-loss orders to manage risk, and aim for small, quick profits. Since scalping involves short-term trading, consider exiting positions when the momentum starts to weaken or when the price reaches a predetermined profit target.
Risk Management:
Scalping involves high-frequency trading with smaller profit targets, so it's crucial to implement strict risk management practices. This includes setting stop-loss orders to limit potential losses and not risking more than a small percentage of your trading capital on each trade.
Backtesting and Optimization:
Before implementing the strategy in live trading, backtest it on historical data to assess its performance under various market conditions. You may also consider optimizing the strategy parameters (e.g., EMA lengths) to maximize its effectiveness.
Continuous Monitoring:
Keep a close eye on market conditions and adjust your strategy accordingly. Market dynamics can change rapidly, so adaptability is key to successful scalping.
Candlestick Patterns detection and backtester [TrendX_]INTRODUCTION:
The Candlestick Patterns detection and backtester is designed to empower traders by identifying and analyzing candlestick patterns. Leveraging the robust Pine Script's add-in “All Candlestick Patterns”, this indicator meticulously scans the market for candlestick formations, offering insights into potential market movements. With its backtesting capabilities, we evaluate historical data to present traders with performance metrics such as win rates, net profit, and profit factors for each pattern. This allows traders to make informed decisions based on empirical evidence. The customizable settings, including trend filters and exit conditions, provide a tailored experience, adapting to various trading styles and strategies.
CREDIT:
This indicator is powered by the Pinescript add-in, *All Candlestick Patterns*, which provides a comprehensive library of candlestick formations.
TABLE USAGE:
The indicator features a detailed usage table that presents backtested results of all candlestick patterns. This includes:
Win Rates: The percentage of trades that resulted in a profit.
Net Profit: The total profit after subtracting losses from gains.
Profit Factor: A measure of the indicator’s profitability (gross profit / gross loss).
Total Trades: The total number of trades taken for every candlestick pattern's appearance.
CHART CANDLESTICK USAGE:
The indicator integrates candlestick pattern detections directly into the chart, displaying:
Pattern Detections: Each detected pattern is marked on the chart.
Win Rates: The win rate of each pattern is shown in brackets next to the detection.
CHART SETTINGS:
Users can customize the indicator with a variety of trend filters and settings:
Trend Filters: Apply filters based on SMA50, SMA200, Supertrend, and RSI threshold to refine pattern detections.
Exit Condition: Set an exit condition based on the crossing of a simple moving average of customizable length.
Visibility: Choose to show or hide the candlestick patterns’ detections on the chart.
Gaussian Price Filter [BackQuant]Gaussian Price Filter
Overview and History of the Gaussian Transformation
The Gaussian transformation, often associated with the Gaussian (normal) distribution, is a mathematical function characteristically prominent in statistics and probability theory. The bell-shaped curve of the Gaussian function, expressing the normal distribution, is ubiquitously employed in various scientific and engineering disciplines, including financial market analysis. This transformation's core utility in trading and economic forecasting is derived from its efficacy in smoothing data series and highlighting underlying trends, which are pivotal for making strategic trading decisions.
The Gaussian filter, specifically, is a type of data-smoothing algorithm that mitigates the random "noise" of market price data, thus enhancing the visibility of crucial trend changes and patterns. Historically, this concept was adapted from fields such as signal processing and image editing, where precise extraction of useful information from noisy environments is critical.
1. What is a Gaussian Transformation?
A Gaussian transformation involves the application of a Gaussian function to a set of data points. The function is applied as a filter in the context of trading algorithms to smooth time series data, which helps in identifying the intrinsic trends obscured by market volatility. The transformation is characterized by its parameter, sigma (σ), representing the standard deviation, which determines the width of the Gaussian bell curve. The breadth of this curve impacts the degree of smoothing: a wider curve (higher sigma value) results in more smoothing, beneficial for longer-term trend analysis.
2. Filtering Price with Gaussian Transformation and its Benefits
In the provided Script, the Gaussian transformation is utilized to filter price data. The filtering process involves convolving the price data with Gaussian weights, which are calculated based on the chosen length (the number of data points considered) and sigma. This convolution process smooths out short-term fluctuations and highlights longer-term movements, facilitating a clearer analysis of market trends.
Benefits:
Reduces noise: It filters out minor price movements and random fluctuations, which are often misleading.
Enhances trend recognition: By smoothing the data, it becomes easier to identify significant trends and reversals.
Improves decision-making: Traders can make more informed decisions by focusing on substantive, smoothed data rather than reacting to random noise.
3. Potential Limitations and Issues
While Gaussian filters are highly effective in smoothing data, they are not without limitations:
Lag introduction: Like all moving averages, the Gaussian filter introduces a lag between the actual price movements and the output signal, which can delay decision-making.
Feature blurring: Over-smoothing might obscure significant price movements, especially if a large sigma is used.
Parameter sensitivity: The choice of length and sigma significantly affects the output, requiring optimization and backtesting to determine the best settings for specific market conditions.
4. Extending Gaussian Filters to Other Indicators
The methodology used to filter price data with a Gaussian filter can similarly be applied to other technical indicators, such as RSI (Relative Strength Index) or MACD (Moving Average Convergence Divergence). By smoothing these indicators, traders can reduce false signals and enhance the reliability of the indicators' outputs, leading to potentially more accurate signals and better timing for entering or exiting trades.
5. Application in Trading
In trading, the Gaussian Price Filter can be strategically used to:
Spot trend reversals: Smoothed price data can more clearly indicate when a trend is starting to change, which is crucial for catching reversals early.
Define entry and exit points: The filtered data points can help in setting more precise entry and exit thresholds, minimizing the risk and maximizing the potential return.
Filter other data streams: Apply the Gaussian filter on volume or open interest data to identify significant changes in market dynamics.
6. Functionality of the Script
The script is designed to:
Calculate Gaussian weights (f_gaussianWeights function): Generates the weights used for the Gaussian kernel based on the provided length and sigma.
Apply the Gaussian filter (f_applyGaussianFilter function): Uses the weights to compute the smoothed price data.
Conditional Trend Detection and Coloring: Determines the trend direction based on the filtered price and colors the price bars on the chart to visually represent the trend.
7. Specific Actions of This Code
The Pine Script provided by BackQuant executes several specific actions:
Input Handling: It allows users to specify the source data (src), kernel length, and sigma directly in the chart settings.
Weight Calculation and Normalization: Computes the Gaussian weights and normalizes them to ensure their sum equals one, which maintains the original data scale.
Filter Application: Applies the normalized Gaussian kernel to the price data to produce a smoothed output.
Trend Identification and Visualization: Identifies whether the market is trending upwards or downwards based on the smoothed data and colors the bars green (up) or red (down) to indicate the trend direction.
UT Bot Stochastic RSIUT Bot Stochastic RSI is a powerful trading tool designed to help traders identify potential buy and sell signals in the market. This indicator combines the Stochastic and RSI (Relative Strength Index) oscillators, two of the most popular and effective technical analysis tools, to provide a comprehensive view of market conditions.
The Stochastic oscillator is a momentum indicator that compares a security's closing price to its price range over a given time period. The RSI, on the other hand, is a momentum oscillator that measures the speed and change of price movements. By combining these two indicators, the UT Bot Stochastic RSI can help traders identify overbought and oversold conditions, as well as potential trend reversals.
The UT Bot Stochastic RSI also includes an ATR (Average True Range) trailing stop, which can be used to set stop-loss levels and manage risk. This feature is particularly useful in volatile markets, where price movements can be large and unpredictable.
In addition to its powerful technical analysis tools, the UT Bot Stochastic RSI also includes a backtesting feature, allowing traders to test their strategies on historical data. This can help traders identify the most effective settings for the indicator and improve their trading performance.
Overall, the UT Bot Stochastic RSI is a versatile and effective tool for traders of all levels, providing valuable insights into market conditions and helping to improve trading decisions
Hurst Future Lines of Demarcation StrategyJ. M. Hurst introduced a concept in technical analysis known as the Future Line of Demarcation (FLD), which serves as a forward-looking tool by incorporating a simple yet profound line into future projections on a financial chart. Specifically, the FLD is constructed by offsetting the price half a cycle ahead into the future on the time axis, relative to the Hurst Cycle of interest. For instance, in the context of a 40 Day Cycle, the FLD would be represented by shifting the current price data 20 days forward on the chart, offering an idea of future price movement anticipations.
The utility of FLDs extends into three critical areas of insight, which form the backbone of the FLD Trading Strategy:
A price crossing the FLD signifies the confirmation of either a peak or trough formation, indicating pivotal moments in price action.
Such crossings also help determine precise price targets for the upcoming peak or trough, aligned with the cycle of examination.
Additionally, the occurrence of a peak in the FLD itself signals a probable zone where the price might experience a trough, helping to anticipate of future price movements.
These insights by Hurst in his "Cycles Trading Course" during the 1970s, are instrumental for traders aiming to determine entry and exit points, and to forecast potential price movements within the market.
To use the FLD Trading Strategy, for example when focusing on the 40 Day Cycle, a trader should primarily concentrate on the interplay between three Hurst Cycles:
The 20 Day FLD (Signal) - Half the length of the Trade Cycle
The 40 Day FLD (Trade) - The Cycle you want to trade
The 80 Day FLD (Trend) - Twice the length of the Trade Cycle
Traders can gauge trend or consolidation by watching for two critical patterns:
Cascading patterns, characterized by several FLDs running parallel with a consistent separation, typically emerge during pronounced market trends, indicating strong directional momentum.
Consolidation patterns, on the other hand, occur when multiple FLDs intersect and navigate within the same price bandwidth, often reversing direction to traverse this range multiple times. This tangled scenario results in the formation of Pause Zones, areas where price momentum is likely to temporarily stall or where the emergence of a significant trend might be delayed.
This simple FLD indicator provides 3 FLDs with optional source input and smoothing, A-through-H FLD interaction background, adjustable “Close the Trade” triggers, and a simple strategy for backtesting it all.
The A-through-H FLD interactions are a framework designed to classify the different types of price movements as they intersect with or diverge from the Future Line of Demarcation (FLD). Each interaction (designated A through H by color) represents a specific phase or characteristic within the cycle, and understanding these can help traders anticipate future price movements and make informed decisions.
The adjustable “Close the Trade” triggers are for setting the crossover/under that determines the trade exits. The options include: Price, Signal FLD, Trade FLD, or Trend FLD. For example, a trader may want to exit trades only when price finally crosses the Trade FLD line.
Shoutouts & Credits for all the raw code, helpful information, ideas & collaboration, conversations together, introductions, indicator feedback, and genuine/selfless help:
🏆 @TerryPascoe
🏅 @Hpotter
👏 @parisboy
Multi conditions matricesLibrary "multi_conditions_matrices"
: facilitate including multiple AND / OR conditions to a script such as two entry / exit inputs groups.
method addConditions(conditions, conditionPair)
Helper to append conditions to a matrix condition array
Namespace types: matrix
Parameters:
conditions (matrix)
conditionPair (array) : array A condition pair , an input can be passed directly to enable
method check(conditions, operatorAnd)
check several condition within given operator
Namespace types: matrix
Parameters:
conditions (matrix)
operatorAnd (bool) : bool true if the operator between condition is AND (default OR)
Returns: bool Evaluates conditions
isWeekend()
isNightSignal(nightHour, morningHour, timezone)
Parameters:
nightHour (int)
morningHour (int)
timezone (string)
ICT Silver Bullet Vertical Lines by Fahmi EshaqThis indicator is designed for users interested in backtesting the Silver Bullet strategy. It eliminates the need for manual drawing of vertical lines by automatically highlighting specific times known as ICT Silver Bullet times. These times correspond to periods when smart money are active the market. The indicator marks these Silver Bullet times with vertical lines, making them easily identifiable. The specified Silver Bullet times are 3AM-4AM, 10AM-11AM, and 2PM-3PM New York time. Additionally, a vertical line is added at 12:00AM to demarcate the start of each day, as days begin at midnight.
MBAND 200 4H BTC/USDT - By MGS-TradingMBAND 200 4H BTC/USDT with RSI and Volume by MGS-Trading: A Neural Network-Inspired Indicator
Introduction:
The MBAND 200 4H BTC/USDT with RSI and Volume represents a groundbreaking achievement in the integration of artificial intelligence (AI) into cryptocurrency market analysis. Developed by MGS-Trading, this indicator is the culmination of extensive research and development efforts aimed at leveraging AI's power to enhance trading strategies. By synthesizing neural network concepts with traditional technical analysis, the MBAND indicator offers a dynamic, multi-dimensional view of the market, providing traders with unparalleled insights and actionable signals.
Innovative Approach:
Our journey to create the MBAND indicator began with a simple question: How can we mimic the decision-making prowess of a neural network in a trading indicator? The answer lay in the weighted aggregation of Exponential Moving Averages (EMAs) from multiple timeframes, each serving as a unique input akin to a neuron in a neural network. These weights are not arbitrary; they were painstakingly optimized through backtesting across various market conditions to ensure they reflect the significance of each timeframe’s contribution to overall market dynamics.
Core Features:
Neural Network-Inspired Weights: The heart of the MBAND indicator lies in its AI-inspired weighting system, which treats each timeframe’s EMA as an input node in a neural network. This allows the indicator to process complex market data in a nuanced and sophisticated manner, leading to more refined and informed trading signals.
Multi-Timeframe EMA Analysis: By analyzing EMAs from 15 minutes to 3 days, the MBAND indicator captures a comprehensive snapshot of market trends, enabling traders to make informed decisions based on a broad spectrum of data.
RSI and Volume Integration: The inclusion of the Relative Strength Index (RSI) and volume data adds layers of confirmation to the signals generated by the EMA bands. This multi-indicator approach helps in identifying high-probability setups, reinforcing the neural network’s concept of leveraging multiple data points for decision-making.
Usage Guidelines:
Signal Interpretation: The MBAND bands provide a visual representation of the market’s momentum and direction. A price moving above the upper band signals strength and potential continuation of an uptrend, while a move below the lower band suggests weakness and a possible downtrend.
Overbought/Oversold Conditions: The RSI component identifies when the asset is potentially overbought (>70) or oversold (<30). Traders should watch for these conditions near the MBAND levels for potential reversal opportunities.
Volume Confirmation: An increase in volume accompanying a price move towards or beyond an MBAND level serves as confirmation of the strength behind the move. This can indicate whether a breakout is likely to sustain or if a reversal has substantial backing.
Strategic Entry and Exit Points: Combine the MBAND readings with RSI and volume indicators to pinpoint strategic entry and exit points. For example, consider entering a long position when the price is near the lower MBAND, RSI indicates oversold conditions, and there is a notable volume increase.
About MGS-Trading:
At MGS-Trading, we are passionate about harnessing the transformative power of AI to revolutionize cryptocurrency trading. Our indicators and tools are designed to provide traders with advanced analytics and insights, drawing on the latest AI techniques and methodologies. The MBAND 200 4H BTC/USDT with RSI and Volume indicator is a prime example of our commitment to innovation, offering traders a sophisticated, AI-enhanced tool for navigating the complexities of the cryptocurrency markets.
Disclaimer:
The MBAND indicator is provided for informational purposes only and does not constitute investment advice. Trading cryptocurrencies involves significant risk and can result in the loss of your investment. We recommend conducting your own research and consulting with a qualified financial advisor before making any trading decisions.
Cycle Oscillator V2 [OmegaTools]Introducing the "Cycle Oscillator" by OmegaTools, an innovative addition to your TradingView analysis toolkit. This script is designed to offer a unique approach to understanding market cycles without the need for volume data, making it versatile across various market conditions and asset classes.
Key Features:
- Cycle Length Customization: Tailor the cycle length from 10 to 200 bars to fit the specific rhythm of the market you're analyzing, ensuring relevance and precision.
- Smoothness Adjustment: Fine-tune the oscillator's smoothness to capture the essence of market movements with options ranging from 1 to 20.
- Aesthetic Flexibility: Choose your preferred colors for the oscillator's upward and downward movements, personalizing your chart to your liking.
- Historical Mode: Toggle the historical mode to either focus on real-time analysis or review past cycle data for backtesting and study.
- Candle Color Modes: Enhance your visual analysis with optional candle coloring based on trend, signals, or extensions, providing immediate insight into market conditions.
Usage Guide:
1. Setting Up: Easily adjust the cycle length and smoothness to match the market's current volatility and your trading style.
2. Understanding Market Cycles: The oscillator plots the average deviation from three distinct moving averages, offering a clear view of potential market turns or continuations.
3. Identifying Overbought/Oversold Conditions: Utilize the upper and lower bounds to recognize extreme market conditions, guiding your entry and exit decisions.
4. Visual Enhancements: Customize the visual aspects, including colors and candle coloring, to make your analysis both effective and aesthetically pleasing.
5. Anticipating Market Movements: The script provides forward-looking lines to suggest potential future highs or lows, aiding in predictive analysis.
Designed with both novice and experienced traders in mind, the "Cycle Oscillator" is a testament to OmegaTools' commitment to providing high-quality, innovative trading tools. Whether you're looking to refine your trading strategy or seeking new analytical perspectives, this script offers a comprehensive solution to navigating the ebbs and flows of the financial markets.
Join the community of traders enhancing their TradingView experience with the "Cycle Oscillator" by OmegaTools. Start exploring deeper market insights and unlock new trading opportunities today.
