The Exact IndicatorStruggling to get in on a trade? Don't know where to take profits? This indicator might help - it only displays the Buy, Stop Loss and Take profit points when certain conditions are met.
The indicator combines a moving average crossover strategy with trend analysis to identify potential buy opportunities in the market. It utilises a short-term and long-term Simple Moving Average (SMA) to generate buy signals when the short-term SMA crosses above the long-term SMA. Additionally, it displays take profit and stop loss levels, along with a background colour indicating the overall trend strength.
Pros :
Clear Signals : Provides straightforward buy signals based on a well-known crossover strategy, making it easy for traders to identify entry points.
Visual Aids : The inclusion of take profit and stop loss levels, along with background trend colors, enhances decision-making and risk management.
Trend Awareness : The background colour changes based on trend strength, allowing traders to quickly assess market conditions.
Cons :
Lagging Indicator : Moving averages are inherently lagging, which can result in delayed signals, especially in volatile markets.
False Signals : Crossover strategies can produce false signals during sideways or choppy market conditions, leading to potential losses.
Limited Scope : The indicator focuses primarily on buy signals, potentially missing out on other trading opportunities (like short-selling) in a bearish market.
Overall, while this indicator can be a useful tool for identifying bullish trends and potential entry points, traders should use it in conjunction with other analysis methods and risk management strategies to mitigate its limitations.
Скользящие средние
MA rate of changeThis indicator uses moving averages to determine trends. For those who trade using a trend-following strategy, it's not possible to use the slope of the moving average line as an indicator of trend judgment if it's expressed as an angle. This is because the angle changes depending on the adjustments made to the vertical price scale and horizontal time scale of the chart.
Therefore, instead of using the angle, I decided to use the rate of change in price as an alternative indicator.
The relationship between the rate of change of the moving average and the angle of the moving average line is as follows:
- When the value is positive, the moving average line slopes upward.
- When the value is negative, the moving average line slopes downward.
- The larger the absolute value of the rate of change, the steeper the angle; the smaller the value, the gentler the slope.
The trend is determined using the rate of change instead of the angle, as follows:
- Uptrend: Rate of change > 0.5 (this value can be adjusted) ⇒ Display with a red background
- Downtrend: Rate of change < -0.5 (this value can be adjusted) ⇒ Display with a blue background
An example of a trade using this indicator is as follows:
- Enter the trade the day after the trend appears.
- Exit the trade the day after the trend ends.
このインジケーターは移動平均線を使ってトレンドを判断します。トレンドフォロー戦略でトレードする方はこのインジケーターの示す移動平均線の傾きを角度で表してトレンドの判定の指標とすることはできません。なぜなら、角度はチャートの縦軸の価格スケールや横軸の時間のスケールを調整することで変わってしまうからです。
そこで角度に代わる別の指標として価格の変化率を使うことにしました。
移動平均の変化率と、移動平均線の角度の関係は次の通りです。
- プラスの値の場合は移動平均線は右肩上がり
- マイナスの値の場合は移動平均線は右肩下がり
- 変化率の絶対値が大きいほど角度は急になり、小さいほど角度は緩やかになる
トレンドの判定は次のようにします。角度の代わりに変化率で判定します。
- 上昇トレンド : 変化率 > 0.5 (この値は調整可能) ⇒赤色の背景で表示
- 下降トレンド : 変化率 < -0.5 (この値は調整可能)⇒青色の背景で表示
このインジケーターを使ったトレードの例は次の通りです。
- トレンドが発生した翌日エントリー
- トレンドが終了した翌日エグジット
EMA Distance & Sector InfoThis indicator provides insights into price trends relative to Exponential Moving Averages (EMAs) and displays sector/industry information about the asset. Below is a detailed explanation of its purpose and what it is designed to achieve:
Purpose of the Code
The indicator offers two key functionalities:
1. Analyzing Price Distance from Multiple EMAs:
• Helps traders understand how far the current price is from key EMAs, expressed as a percentage.
• Calculates average percentage distances over a specified period (default: 63 days) to spot consistent trends or mean reversion opportunities.
• Useful for trend-following strategies, allowing the trader to see when the price is above or below important EMAs (e.g., 9, 21, 50, 100, and 150-period EMAs).
2. Displaying Asset Sector and Industry Information:
• Displays the sector and industry of the asset being analyzed (e.g., Technology, Consumer Goods).
• Provides additional context when evaluating performance across a specific sector or comparing an asset to its peers.
Who Would Use This Indicator?
This indicator is particularly helpful for:
1. Swing Traders and Positional Traders:
• They can use it to track whether the price is trading significantly above or below critical EMAs, which often signals overbought/oversold conditions or trend strength.
• The average percentage distances help to identify momentum shifts or pullback opportunities.
2. Sector/Industry-Focused Investors:
• Understanding an asset’s sector and industry helps investors gauge how the asset fits into the broader market context.
• This is valuable for sector rotation strategies, where investors shift funds between sectors based on performance trends.
How It Helps in Trading Decisions
1. Entry and Exit Points:
• If the price is far above an EMA (e.g., 21 EMA), it might indicate an overbought condition or a strong trend, while a negative percentage could signal a pullback or reversal opportunity.
• The average percentage distances smooth the fluctuations and reveal longer-term trends.
2. Contextual Information:
• Knowing the sector and industry is useful when analyzing trends. For example, if Technology stocks are doing well, and this asset belongs to that sector, it could indicate sector-wide momentum.
Summary of the Indicator’s Purpose
This code provides:
• EMA trend monitoring: Visualizes the price position relative to multiple EMAs and averages those distances for smoother insights.
• Sector and industry information: Adds valuable context for asset performance analysis.
• Decision-making support: Helps traders identify overbought/oversold levels and assess the asset within the broader market landscape.
In essence, this indicator is a multi-purpose tool that combines technical analysis (through EMA distances) with fundamental context (via sector/industry info), making it valuable for traders and investors aiming to time entries/exits or understand market behavior better.
RSI/MFI Divergence Finder [idahodev]Monitoring RSI (Relative Strength Index) and MFI (Money Flow Index) divergences on a stock or index chart offers several benefits to traders and analysts. Let's break down the advantages:
Comprehensive Market View: Combining both indicators provides a more complete picture of market conditions, as they measure different aspects of price movement. RSI focuses on recent gains/losses relative to price change, while MFI incorporates volume data to assess money flow in and out of a security.
Enhanced Signal Accuracy: When divergences occur simultaneously in both RSI and MFI, it may be considered a stronger signal than if only one indicator showed divergence. This can potentially lead to more reliable trading decisions.
Identification of False Breakouts: Divergences between these indicators and price action can help identify false breakouts or misleading price movements that are not supported by underlying market strength or volume.
More Nuanced Market Understanding: By examining divergent behavior between money flow (MFI) and momentum (RSI), traders gain a more detailed comprehension of the interplay between these factors in shaping market trends.
Early Warning Signs: These divergences can act as early warning signs for potential trend reversals or changes in market sentiment, allowing traders to adjust their strategies proactively.
It's important to note that RSI/MFI divergences should be used as part of a broader trading strategy rather than solely relying on them for buy/sell signals. They can serve as valuable tools for confirming trends, identifying potential turning points, or warning against overbought/oversold conditions.
When using these indicators together, traders must be cautious of false signals, especially in choppy markets or during periods of high volatility. It's crucial to combine this analysis with other technical and fundamental factors before making trading decisions.
In summary, monitoring RSI/MFI divergences may offer a way to gain insights into the underlying strengths and weaknesses of market movements.
This utility differs from other in that it allows for a choke/threshold/sensitivity setting to help weed out noisy signals. This needs to be carefully adjusted per chart.
It also allows for tuning of the MFI smoothing length (number of bars on the current chart) as well as how many previous bars it will take into consideration when calculating RSI and MFI divergences. It will signal when it sees alignment forming between RSI and MFI divergences in a direction. You will likely need to tune this script's settings every few days or at least anytime there is a change in overall market behavior or sustained volatility.
Ultimately, the goal with this script is to provide an additional level of confirmation of weakness or strength. It should be combined with other indicators such as exhaustion, pivots, supply/demand, trendline breaks or tests, and structure changes, to name a few complementary tools or strategies. It's not meant to be a standalone buy/sell signal indicator!
Here are some settings for futures that may help you get started:
ES (4m chart)
RSI Length: 26
MFI Length: 8
MFI Smoothing Length: 32
Divergence Sensitivity: 124
Left Bars for Pivot: 10
Right Bars for Pivot: 1
NQ (4m chart)
RSI Length: 14
MFI Length: 14
MFI Smoothing Length: 21
Divergence Sensitivity: 400
Left Bars for Pivot: 21
Right Bars for Pivot: 1
YM (4m chart)
RSI Length: 14
MFI Length: 14
MFI Smoothing Length: 21
Divergence Sensitivity: 810
Left Bars for Pivot: 33
Right Bars for Pivot: 1
Signals Pro [traderslog]The "Signals Pro" indicator is an advanced and versatile trading tool designed to help traders accurately identify key buy and sell signals using a combination of technical analysis factors such as candle patterns , RSI (Relative Strength Index) , and candle stability . It is highly customizable and offers a range of options that make it suitable for both short-term and long-term traders. By filtering market noise and providing actionable insights, this indicator enhances decision-making and helps traders capitalize on market movements.
At the core of the "Signals Pro" indicator is the concept of Candle Stability . The Candle Stability Index measures the ratio between a candle's body and its wicks, providing insight into the strength of the price movement during that period. A higher value indicates that the candle is more stable, meaning that the price has moved significantly without much retracement. This stability filter is crucial because it prevents the generation of signals during volatile or choppy market conditions where price direction is uncertain. Traders can adjust the Candle Stability Index from 0 to 1, allowing for precise control over how stable a candle must be for the indicator to generate a signal.
Another key feature is the use of RSI (Relative Strength Index) , a momentum oscillator that measures the speed and change of price movements. The RSI index parameter in the indicator can be customized to detect overbought or oversold conditions. When the RSI falls below the defined threshold, it signals that the market may be oversold , which can indicate a potential buying opportunity . Conversely, when the RSI exceeds a certain value, it suggests that the market is overbought , signaling a potential selling opportunity . This allows traders to time their trades more effectively by entering when market conditions are favorable and exiting before a potential reversal occurs.
The Candle Delta Length is another critical element of the "Signals Pro" indicator. This parameter measures how much the price has increased or decreased over a specific number of candles. By adjusting the Candle Delta Length , traders can define how many periods the indicator should analyze before generating a signal. A longer Candle Delta Length means the price has been trending in one direction for a longer period, providing more reliable signals. For instance, if the price has been steadily decreasing for five candles, this could signal a bullish reversal , triggering a buy signal .
To further enhance its accuracy, the "Signals Pro" indicator includes a unique feature that allows traders to disable repeating signals . This is particularly useful in situations where the market is moving sideways or during low volatility periods, where multiple signals may cluster close together, creating confusion. By enabling the disable repeating signals option, traders can prevent these repeated signals and focus on the most important and confirmed signals, ensuring cleaner charts and reducing the risk of overtrading.
A key technical aspect of the indicator is its ability to detect bullish and bearish engulfing patterns . The indicator looks for bullish engulfing patterns, which occur when a bullish candle fully engulfs the body of the previous bearish candle, signaling a potential bullish reversal . Conversely, bearish engulfing patterns occur when a bearish candle fully engulfs the previous bullish candle, indicating a bearish reversal . By incorporating these candle patterns with the Candle Stability Index and RSI levels , the indicator provides highly reliable signals based on price action and market sentiment.
Visual customization is another major advantage of the "Signals Pro" indicator. Traders can choose from several different label styles , such as text bubbles , triangles , or arrows to mark the buy and sell signals on the chart. This makes the signals stand out and easy to interpret at a glance. Furthermore, the color of these signals can be customized: green for buy signals and red for sell signals , along with options to adjust the text size and label styles for even more personalization. Traders can make the signals more or less prominent based on their preference, enhancing readability and workflow efficiency.
The indicator also includes a comprehensive alert system , ensuring traders never miss an opportunity. Alerts can be set for both buy and sell signals , and the system triggers in real-time when a valid signal is generated. This is especially useful for active traders who want to stay on top of the markets without constantly monitoring their screens. The alert system helps ensure that traders are notified of potential trading opportunities as soon as they arise, allowing them to act quickly in volatile markets.
From a practical standpoint, the "Signals Pro" indicator is designed to work seamlessly across multiple timeframes, making it suitable for scalpers, day traders, swing traders, and even long-term investors. Its flexibility allows it to adapt to different trading styles and time horizons, providing value for a wide range of market participants.
In summary, the Signals Pro indicator offers a robust and customizable solution for identifying buy and sell signals . By combining candle stability , RSI analysis , and engulfing patterns , the indicator provides traders with reliable signals to enter or exit trades. The ability to customize signal appearance, coupled with a real-time alert system , makes the "Signals Pro" indicator an invaluable tool for traders looking to improve their timing and decision-making. Whether you are looking to capture short-term price movements or want to time entries and exits in longer-term trends, this indicator offers the insights needed to navigate the markets with confidence.
TrendWave EMA/VWAP IndicatorThe TrendWave EMA/VWAP Indicator is a powerful technical analysis tool designed for traders seeking to enhance their market strategies. By combining the dynamic Exponential Moving Average (EMA) and the Volume Weighted Average Price (VWAP), this indicator provides valuable insights into price trends and potential trading signals, allowing for informed decision-making in various market conditions.
Key Features:
Exponential Moving Average (EMA):
The EMA component helps traders identify the direction of the prevailing trend by giving more weight to recent price action. This responsiveness makes the EMA an essential tool for trend-following strategies.
Customizable Length: Users can adjust the EMA length (default set to 50 periods) to align with their specific trading style and preferences.
Volume Weighted Average Price (VWAP):
The VWAP is crucial for evaluating the average price of a security throughout the trading day, factoring in volume. It serves as a benchmark for price action and can help traders identify significant support and resistance levels.
Real-time Benchmarking: The VWAP enables traders to assess current prices against historical averages, improving their entry and exit strategies.
Signal Generation:
The TrendWave EMA/VWAP Indicator generates clear buy and sell signals based on the interaction between the price and the VWAP:
Bullish Signal: Triggered when the price crosses above the VWAP, indicating a potential upward movement.
Bearish Signal: Triggered when the price crosses below the VWAP, suggesting a potential downward movement.
These signals are visually represented with intuitive arrows on the chart, facilitating quick recognition of trading opportunities.
User-Friendly Interface:
The indicator allows traders to enable or disable components (EMA and VWAP) based on their preferences, ensuring a personalized trading experience.
Clear color coding enhances visual clarity: the EMA is displayed in blue, while the VWAP is shown in orange.
Use Cases:
Trend Following: Use the EMA to confirm the direction of the trend and make trades that align with that trend.
Price Action Analysis: Employ the VWAP to determine the average trading price and identify key support/resistance levels.
Signal Confirmation: Combine signals from both the EMA and VWAP to enhance trading strategies and decision-making.
The TrendWave EMA/VWAP Indicator is an essential addition to any trader's toolkit. By leveraging the strengths of both the EMA and VWAP, this indicator empowers traders to make informed, data-driven decisions and capitalize on market movements with confidence.
Multi-Timeframe SMA Plot**Introducing the Multi-Timeframe SMA Plot**
This script is designed to help traders easily visualize multiple Simple Moving Averages (SMAs) across different timeframes, all on a single chart. The Multi-Timeframe SMA Plot allows you to configure up to three different SMAs with customizable lengths, timeframes, colors, line styles, and line thicknesses, providing a versatile tool to analyze market trends in various granularities.
**Key Features**:
1. **Multiple SMA Timeframes**: You can plot SMAs from different timeframes like 15 minutes, 1 hour, daily, weekly, and more, enabling a comprehensive perspective of market movements.
2. **Fully Customizable**: Each SMA comes with options to adjust the length, timeframe, color, line style (solid, dashed, or dotted), and thickness, giving you control over how you visualize trend data.
3. **User-Friendly Inputs**: The script provides intuitive input fields that make it easy to adjust the settings without diving into the code, making it suitable for both beginner and advanced traders.
**How to Use**:
- Select the desired length and timeframe for each SMA (e.g., 50-period SMA on a 1-hour chart).
- Customize the line style and color to match your chart's theme or make distinctions between each SMA.
- Analyze how different SMAs align or cross over time to identify potential support, resistance, or trend changes.
The Multi-Timeframe SMA Plot is ideal for traders who rely on moving averages to gauge trend strength, direction, and potential entry or exit points. By having multiple SMAs from different timeframes on one chart, you can better understand the overall market sentiment and make more informed decisions.
Give this script a try and streamline your technical analysis with clear, customizable SMA lines!
**Code**: Check out the full script and start customizing it to fit your trading style. Your feedback is always welcome!
E9 Bollinger RangeThe E9 Bollinger Range is a technical trading tool that leverages Bollinger Bands to track volatility and price deviations, along with additional trend filtering via EMAs.
The script visually enhances price action with a combination of trend-filtering EMAs, bar colouring for trend direction, signals to indicate potential buy and sell points based on price extension and engulfing patterns.
Here’s a breakdown of its key components:
Bollinger Bands: The strategy plots multiple Bollinger Band deviations to create different price levels. The furthest deviation bands act as warning signs for traders when price extends significantly, signaling potential overbought or oversold conditions.
Bar Colouring: Visual bar colouring is applied to clearly indicate trend direction: green bars for an uptrend and red bars for a downtrend.
EMA Filtering: Two EMAs (50 and 200) are used to help filter out false signals, giving traders a better sense of the underlying trend.
This combination of signals, visual elements, and trend filtering provides traders with a systematic approach to identifying price deviations and taking advantage of market corrections.
Brief History of Bollinger Bands
Bollinger Bands were developed by John Bollinger in the early 1980s as a tool to measure price volatility in financial markets. The bands consist of a moving average (typically 20 periods) with upper and lower bands placed two standard deviations away. These bands expand and contract based on market volatility, offering traders a visual representation of price extremes and potential reversal zones.
John Bollinger’s work revolutionized technical analysis by incorporating volatility into trend detection. His bands remain widely used across markets, including stocks, commodities, and cryptocurrencies. With the ability to highlight overbought and oversold conditions, Bollinger Bands have become a staple in many trading strategies.
VIDYA ProTrend Multi-Tier ProfitHello! This time is about a trend-following system.
VIDYA is quite an interesting indicator that adjusts dynamically to market volatility, making it more responsive to price changes compared to traditional moving averages. Balancing adaptability and precision, especially with the more aggressive short trade settings, challenged me to fine-tune the strategy for a variety of market conditions.
█ Introduction and How it is Different
The "VIDYA ProTrend Multi-Tier Profit" strategy is a trend-following system that combines the VIDYA (Variable Index Dynamic Average) indicator with Bollinger Bands and a multi-step take-profit mechanism.
Unlike traditional trend strategies, this system allows for more adaptive profit-taking, adjusting for long and short positions through distinct ATR-based and percentage-based targets. The innovation lies in its dynamic multi-tier approach to profit-taking, especially for short trades, where more aggressive percentages are applied using a multiplier. This flexibility helps adapt to various market conditions by optimizing trade management and profit allocation based on market volatility and trend strength.
BTCUSD 6hr performance
█ Strategy, How it Works: Detailed Explanation
The core of the "VIDYA ProTrend Multi-Tier Profit" strategy lies in the dual VIDYA indicators (fast and slow) that analyze price trends while accounting for market volatility. These indicators work alongside Bollinger Bands to filter trade entries and exits.
🔶 VIDYA Calculation
The VIDYA indicator is calculated using the following formula:
Smoothing factor (𝛼):
alpha = 2 / (Length + 1)
VIDYA formula:
VIDYA(t) = alpha * k * Price(t) + (1 - alpha * k) * VIDYA(t-1)
Where:
k = |Chande Momentum Oscillator (MO)| / 100
🔶 Bollinger Bands as a Volatility Filter
Bollinger Bands are calculated using a rolling mean and standard deviation of price over a specified period:
Upper Band:
BB_upper = MA + (K * stddev)
Lower Band:
BB_lower = MA - (K * stddev)
Where:
MA is the moving average,
K is the multiplier (typically 2), and
stddev is the standard deviation of price over the Bollinger Bands length.
These bands serve as volatility filters to identify potential overbought or oversold conditions, aiding in the entry and exit logic.
🔶 Slope Calculation for VIDYA
The slopes of both fast and slow VIDYAs are computed to assess the momentum and direction of the trend. The slope for a given VIDYA over its length is:
Slope = (VIDYA(t) - VIDYA(t-n)) / n
Where:
n is the length of the lookback period. Positive slope indicates bullish momentum, while negative slope signals bearish momentum.
LOCAL picture
🔶 Entry and Exit Conditions
- Long Entry: Occurs when the price moves above the slow VIDYA and the fast VIDYA is trending upward. Bollinger Bands confirm the signal when the price crosses the upper band, indicating bullish strength.
- Short Entry: Happens when the price drops below the slow VIDYA and the fast VIDYA trends downward. The signal is confirmed when the price crosses the lower Bollinger Band, showing bearish momentum.
- Exit: Based on VIDYA slopes flattening or reversing, or when the price hits specific ATR or percentage-based profit targets.
🔶 Multi-Step Take Profit Mechanism
The strategy incorporates three levels of take profit for both long and short trades:
- ATR-based Take Profit: Each step applies a multiple of the ATR (Average True Range) to the entry price to define the exit point.
The first level of take profit (long):
TP_ATR1_long = Entry Price + (2.618 * ATR)
etc.
█ Trade Direction
The strategy offers flexibility in defining the trading direction:
- Long: Only long trades are considered based on the criteria for upward trends.
- Short: Only short trades are initiated in bearish trends.
- Both: The strategy can take both long and short trades depending on the market conditions.
█ Usage
To use the strategy effectively:
- Adjust the VIDYA lengths (fast and slow) based on your preference for trend sensitivity.
- Use Bollinger Bands as a filter for identifying potential breakout or reversal scenarios.
- Enable the multi-step take profit feature to manage positions dynamically, allowing for partial exits as the price reaches specified ATR or percentage levels.
- Leverage the short trade multiplier for more aggressive take profit levels in bearish markets.
This strategy can be applied to different asset classes, including equities, forex, and cryptocurrencies. Adjust the input parameters to suit the volatility and characteristics of the asset being traded.
█ Default Settings
The default settings for this strategy have been designed for moderate to trending markets:
- Fast VIDYA Length (10): A shorter length for quick responsiveness to price changes. Increasing this length will reduce noise but may delay signals.
- Slow VIDYA Length (30): The slow VIDYA is set longer to capture broader market trends. Shortening this value will make the system more reactive to smaller price swings.
- Minimum Slope Threshold (0.05): This threshold helps filter out weak trends. Lowering the threshold will result in more trades, while raising it will restrict trades to stronger trends.
Multi-Step Take Profit Settings
- ATR Multipliers (2.618, 5.0, 10.0): These values define how far the price should move before taking profit. Larger multipliers widen the profit-taking levels, aiming for larger trend moves. In higher volatility markets, these values might be adjusted downwards.
- Percentage Levels (3%, 8%, 17%): These percentage levels define how much the price must move before taking profit. Increasing the percentages will capture larger moves, while smaller percentages offer quicker exits.
- Short TP Multiplier (1.5): This multiplier applies more aggressive take profit levels for short trades. Adjust this value based on the aggressiveness of your short trade management.
Each of these settings directly impacts the performance and risk profile of the strategy. Shorter VIDYA lengths and lower slope thresholds will generate more trades but may result in more whipsaws. Higher ATR multipliers or percentage levels can delay profit-taking, aiming for larger trends but risking partial gains if the trend reverses too early.
Crypto Divergence from BTCThis script is used to indicate when price action of a crypto coin is diverging significantly from that of BTC.
Explanation of the Script:
Inputs:
roc_length: The period used for calculating the Rate of Change.
ma_length: The period used for the moving average of the ROC.
threshold: The percentage difference that indicates a divergence.
Price Data:
The script retrieves the current asset's price and Bitcoin's price.
ROC Calculation:
The ROC for both the current asset and BTC is calculated based on the defined roc_length.
Moving Averages:
Simple moving averages (SMA) of the ROC values are calculated to smooth out the data.
Divergence Detection:
The indicator checks if the current asset's ROC MA is significantly higher or lower than Bitcoin's ROC MA based on the specified threshold.
Plotting:
The script plots the ROC values and their moving averages.
It also highlights the background in green when a bullish divergence is detected (when the asset is moving up while BTC is lagging) and in red for a bearish divergence.
Fourier Transformed & Kalman Filtered EMA Crossover [Mattes]The Fourier Transformed & Kalman Filtered EMA Crossover (FTKF EMAC) is a trend-following indicator that leverages Fourier Transform approximation, Kalman Filtration, and two Exponential Moving Averages (EMAs) of different lengths to provide accurate and smooth market trend signals. By combining these three components, it captures the underlying market cycles, reduces noise, and produces actionable insights, making it suitable for detecting both emerging trends and confirming existing ones.
TECHNICALITIES:
>>> The Fourier Transform approximation is designed to identify dominant cyclical patterns in price action by focusing on key frequencies, while filtering out noise and less significant movements. It emphasizes the most meaningful price cycles, enabling the indicator to isolate important trends while ignoring minor fluctuations. This cyclical awareness adds an extra layer of depth to trend detection, allowing the EMAs to work with a cleaner and more reliable data set.
>>> The Kalman Filter adds dynamic noise reduction, adjusting its predictions of future price trends based on past and current data. As new price data comes in, the filter recalibrates itself to ensure that the price action remains smooth and devoid of erratic movements. This real-time adjustment is key to minimizing lag while avoiding false signals, which ensures that the EMAs react to more accurate and stable market data. The Kalman Filter’s ability to smooth price data without losing sensitivity to trend changes complements the Fourier approximation, ensuring a high level of precision in volatile and stable market environments.
>>> The EMA Crossover involves using two EMAs: a shorter EMA that reacts quickly to price movements and a longer EMA that responds more slowly. The shorter EMA is responsible for capturing immediate market shifts, detecting potential bullish or bearish trends. The longer EMA smooths out price fluctuations and provides trend confirmation, working with the shorter EMA to ensure the signals are reliable. When the shorter EMA crosses above the longer EMA, it indicates a bullish trend, likewise when it goes below the longer EMA, it signals a bearish trend. This setup provides a clear way to track market direction, with color-coded signals (green for bullish, red for bearish) for visual clarity. The flexibility of adjusting the EMA periods allows traders to fine-tune the indicator to their preferred timeframe and strategy, making it adaptable to different market conditions.
|-> A key technical aspect is that the first EMA should always be shorter than the second one. If the first EMA is longer than the second, the tool’s effectiveness is compromised because the faster EMA is designed to signal long conditions, while the longer one is made for signaling a bearish trend. Reversing their roles would lead to delayed or confused signals, reducing the indicator’s ability to detect trend shifts early and making it less efficient in volatile markets. This is the only key weakness of the indicator, failure to submit to this rule will result in confusion.
>>> These components work together like a clock to create a comprehensive and effective trend-following system. The Fourier approximation highlights key cyclical movements, the Kalman Filter refines these movements by removing noise, and the EMAs interpret the filtered data to generate actionable trend signals. Each component enhances the next, ensuring that the final output is both responsive and reliable, with minimal false signals or lag. creating an indicator using widespread concepts which haven't been combined before.
Summary
This indicator combines Fourier Transform approximation, Kalman Filtration, and two EMAs of different lengths to deliver accurate and timely trend-following signals. The Fourier approximation identifies dominant market cycles, while the Kalman Filter dynamically removes noise and refines the price data in real time. The two EMAs then use this filtered data to generate buy and sell signals based on their crossovers. The shorter EMA reacts quickly to price changes, while the longer EMA provides smoother trend confirmation. The components work in synergy to capture trends with minimal false signals or lag, ensuring traders can act promptly on market shifts. Customizable EMA periods make the tool adaptable to different market conditions, enhancing its versatility for various trading strategies.
To use the indicator, traders should adjust the EMA lengths based on their timeframe and strategy, ensuring that the shorter EMA remains shorter than the longer EMA to preserve the tool’s responsiveness. The color-coded signals offer visual clarity, making it easy to identify potential entry and exit points. This confluence of Fourier, Kalman, and EMA methodologies provides a smooth, highly effective trend-following tool that excels in both trending and ranging markets.
Dont make me crossStrategy Overview
This trading strategy utilizes Exponential Moving Averages (EMAs) to generate buy and sell signals based on the crossover of two EMAs, which are shifted downwards by 50 points. The strategy aims to identify potential market reversals and trends based on these crossovers.
Components of the Strategy
Exponential Moving Averages (EMAs):
Short EMA: This is calculated over a shorter period (default is 9 periods) and is more responsive to recent price changes.
Long EMA: This is calculated over a longer period (default is 21 periods) and provides a smoother view of the price trend.
Both EMAs are adjusted by a fixed shift amount of -50 points.
Input Parameters:
Short EMA Length: The period used to calculate the short-term EMA. This can be adjusted based on the trader's preference or market conditions.
Long EMA Length: The period used for the long-term EMA, also adjustable.
Shift Amount: A fixed value (default -50) that is subtracted from both EMAs to shift their values downwards. This is useful for visual adjustments or specific strategy requirements.
Plotting:
The adjusted EMAs are plotted on the price chart. The short EMA is displayed in blue, and the long EMA is displayed in red. This visual representation helps traders identify the crossover points easily.
Signal Generation:
Buy Signal: A buy signal is generated when the short EMA crosses above the long EMA. This is interpreted as a bullish signal, indicating potential upward price movement.
Sell Signal: A sell signal occurs when the short EMA crosses below the long EMA, indicating potential downward price movement.
Trade Execution:
When a buy signal is triggered, the strategy enters a long position.
Conversely, when a sell signal is triggered, the strategy enters a short position.
Trading Logic
Market Conditions: The strategy is most effective in trending markets. During sideways or choppy market conditions, it may generate false signals.
Risk Management: While this script does not include explicit risk management features (like stop-loss or take-profit), traders should consider implementing these to manage their risk effectively.
Customization
Traders can customize the EMA lengths and the shift amount based on their analysis and preferences.
The strategy can also be enhanced with additional indicators, such as volume or volatility measures, to filter signals further.
Use Cases
This strategy can be applied to various timeframes, such as intraday, daily, or weekly charts, depending on the trader's style.
It is suitable for both novice and experienced traders, offering a straightforward approach to trading based on technical analysis.
Summary
The EMA Crossover Strategy with a -50 shift is a straightforward technical analysis approach that capitalizes on the momentum generated by the crossover of short and long-term EMAs. By shifting the EMAs downwards, the strategy can help traders visualize potential entry and exit points more clearly, although it's important to consider additional risk management and market context for effective trading.
Exponantial Spread StrategyIt is strongly recommended to evaluate the strategy's performance on long time frames such as 1D or 4H.
This strategy calculates a custom moving average by the formula EMA+(TEMA-DEMA)*G,
G being the gain parameter. The main idea behind that is since TEMA is much more adaptive than DEMA their spread give us momentum, and incorporating this with a gain allows us to calculate a very responsive but yet not noisy moving average.
We calculate 4 MAs like described with gains 0,1,2,3 from less adaptive (normal EMA) to most adaptive. When they align in terms of position and the price is above the original MA we enter a long position, and do partial exits at each crossunder weighted by how adaptive ma is, the more adaptive the less weight, we do a full stop when the price crossed below under the original MA or the position aligment changed.
Chartonaut: GlimpseDisplays an overview of some key metrics as a table.
Market Cap : value of the company.
Float Shares : number of shares available for trading.
AR# : average range over the last # sessions.
ATR# : average true range over the last # sessions.
ATR#/MA# : distance of the current price from the given moving average (MA) in terms of ATR multiples.
Rel Volatility : current session's range, including gaps from previous close, relative to the ATR.
Additionally, it highlights some metrics if they are crossing a given threshold, as to warn that some criteria might not be met.
Manoj Personal EMA 5-203 EMA Trading Strategy Script Overview:
EMAs Used:
5 EMA: Short-term moving average.
20 EMA: Medium-term moving average.
564 EMA: Long-term moving average to identify overall trend direction.
Entry Signals:
Strong Buy: Triggered when:
Price is above the 564 EMA (uptrend).
The 5 EMA crosses above the 20 EMA (bullish crossover).
The current candle is green (close > open).
Strong Sell: Triggered when:
Price is below the 564 EMA (downtrend).
The 5 EMA crosses below the 20 EMA (bearish crossover).
The current candle is red (close < open).
Exit Signal:
Position is closed when the price touches back to the 564 EMA (either side, up or down):
A "Close Position" label is shown in green for long trades.
A "Close Position" label is shown in red for short trades.
Risk Management:
Stop-Loss: Placed at the last swing low (for longs) or last swing high (for shorts), calculated over the last 10 bars.
Take-Profit: A 1:3 risk/reward ratio is used, where the potential reward is three times the risk.
Alerts:
Alerts are triggered for buy and sell signals.
Alerts are also triggered when the exit condition (price touching the 564 EMA) is met.
This script is designed to work on timeframes of 15 minutes or higher but can also be used for 5-minute scalping. It plots the EMAs on the chart, highlights buy/sell opportunities, shows stop-loss and take-profit levels, and generates alerts for key signals.
DEB SuperTrend [Mattes]The Dynamic Envelope Based Supertrend integrates two key concepts: dynamic envelopes and the Supertrend, creating a powerful trend-following tool. Understanding its functionality requires a closer look at how the envelopes are constructed and how they interact with price action.
Dynamic Envelopes
>>> Dynamic envelopes are bands that surround a central moving average (MA) which is set by the user. These are then calculated based on the standard deviation of price movements over a specified period. The formula for the upper and lower envelopes is as follows:
Upper Envelope=MA+(Multiplier×STD)
Lower Envelope=MA−(Multiplier×STD)
This dynamic approach ensures that the envelopes expand and contract based on market volatility. In periods of high volatility, the envelopes widen, allowing for more price movement without triggering false signals. Conversely, in low-volatility periods, the envelopes tighten, enhancing sensitivity to price changes.
Interaction with the Supertrend
The Supertrend component is a trend-following indicator that utilizes the concept of Average True Range (ATR) to define its trailing stop levels.
In this indicator however (like I've mentioned before), the ATR bands have been replaced with the STD envelopes, as they offer a better performance compared to ATR bands.
Trend Direction
The Supertrend indicator generates buy and sell signals based on price crossing the calculated upper and lower envelopes:
>>> Buy Signal: Triggered when the price closes above the upper envelope, indicating a potential upward trend.
>>> Sell Signal: Triggered when the price closes below the lower envelope, suggesting a downward trend.
Adaptive Nature:
The dynamic envelopes effectively serve as dynamic support and resistance levels, which adapt to price movements and volatility, while the Supertrend tracks these levels to confirm the trend direction and adjust accordingly to changes, making it an enhanced version of ATR Based Supertrends.
Unique Aspects and Advantages
->>>> The Dynamic Envelope Based Supertrend is unique for several reasons:
>>> Volatility Responsiveness: The indicator adjusts its sensitivity based on market conditions, reducing the likelihood of false signals during quiet market phases and improving reliability during volatile periods. This is reasoned by the STD envelope bands contracting and expanding relative to the tickers performance.
>>> Trend Confirmation: By integrating the Supertrend logic, the indicator not only provides entry signals but also guides traders on when to exit, maintaining a focus on trend-following rather than mean reversion.
>>> Stability: Due to its use of Standard deviation envelopes, it is very ressistant in periods of uncertainty, Rather than buy bottom and selling tops, it stays long/short for the complete period of mean reverting environments, which is based on the bigger and fuller trend direction on the larger timescales.
>>> Clear Signals: The indicator simplifies decision-making by offering visual cues through its envelopes and trend signals, making it accessible to traders of all experience levels.
Summary:
The Dynamic Envelope Based Supertrend is a sophisticated trend-following indicator that intelligently combines dynamically adjusted STD envelopes with Supertrend logic. By incorporating volatility metrics, it offers a clear and actionable framework for traders, enhancing their ability to identify and follow trends effectively.
DSL Trend Analysis [ChartPrime]The DSL Trend Analysis indicator utilizes Discontinued Signal Lines (DSL) deployed directly on price, combined with dynamic bands, to analyze the trend strength and momentum of price movements. By tracking the high and low price values and comparing them to the DSL bands, it provides a visual representation of trend momentum, highlighting both strong and weakening phases of market direction.
⯁ KEY FEATURES AND HOW TO USE
⯌ DSL-Based Trend Detection :
This indicator uses Discontinued Signal Lines (DSL) to evaluate price action. When the high stays above the upper DSL band, the line turns lime, indicating strong upward momentum. Similarly, when the low stays below the lower DSL band, the line turns orange, indicating strong downward momentum. Traders can use these visual signals to identify strong trends in either direction.
⯌ Bands for Trend Momentum :
The indicator plots dynamic bands around the DSL lines based on ATR (Average True Range). These bands provide a range within which price can fluctuate, helping to distinguish between strong and weakening trends. If the high remains within the upper band, the lime-colored line becomes transparent, showing weakening upward momentum. The same concept applies for the lower band, where the line turns orange with transparency, indicating weakening downward momentum.
If high and low stays between bands line has no color
to make sure indicator catches only strong momentum of price
⯌ Real-Time Band Price Labels :
The indicator places two labels on the chart, one at the upper DSL band and one at the lower DSL band, displaying the real-time price values of these bands. These labels help traders track the current price relative to the key bands, which are essential in determining potential breakout or reversal zones.
⯌ Visual Confirmation of Momentum Shifts :
By monitoring the relationship between the high and low values of the price relative to the DSL bands, this indicator provides a reliable way to confirm whether the trend is gaining or losing strength. This allows traders to act accordingly, whether it's to enter or exit positions based on trend strength or weakness.
⯁ USER INPUTS
Length : Defines the period used to calculate the DSL lines, influencing the sensitivity of the trend detection.
Offset : Adjusts the offset applied to the upper and lower DSL bands, affecting how the thresholds for strong or weak momentum are set.
Width (ATR Multiplier) : Determines the width of the DSL bands based on an ATR multiplier, providing a dynamic range around the price for momentum analysis.
⯁ CONCLUSION
The DSL Trend Analysis indicator is a powerful tool for assessing price momentum and trend strength. By combining Discontinued Signal Lines with dynamically calculated bands, traders can easily spot key moments when momentum shifts from strong to weak or vice versa. The color-coded lines and real-time price labels provide valuable insights for trading decisions in both trending and ranging markets.
MomentumSignal Kit RSI-MACD-ADX-CCI-CMF-TSI-EStoch// ----------------------------------------
// Description:
// ----------------------------------------
// MomentumKit RSI/MACD-ADX-CCI-CMF-TSI-EStoch Suite is a comprehensive momentum indicator suite designed to provide robust buy and sell signals through the consensus of multiple normalized momentum indicators. This suite integrates the following indicators:
// - **Relative Strength Index (RSI)**
// - **Stochastic RSI**
// - **Moving Average Convergence Divergence (MACD)** with enhanced logic
// - **True Strength Index (TSI)**
// - **Commodity Channel Index (CCI)**
// - **Chaikin Money Flow (CMF)**
// - **Average Directional Index (ADX)**
// - **Ehlers' Stochastic**
//
// **Key Features:**
// 1. **Normalization:** Each indicator is normalized to a consistent scale, facilitating easier comparison and interpretation across different momentum metrics. This uniform scaling allows traders to seamlessly analyze multiple indicators simultaneously without the confusion of differing value ranges.
//
// 2. **Consensus-Based Signals:** By combining multiple indicators, MomentumKit generates buy and sell signals based on the agreement among various momentum measurements. This multi-indicator consensus approach enhances signal reliability and reduces the likelihood of false positives.
//
// 3. **Overlap Analysis:** The normalization process aids in identifying overlapping signals, where multiple indicators point towards a potential change in price or momentum. Such overlaps are strong indicators of significant market movements, providing traders with timely and actionable insights.
//
// 4. **Enhanced Logic for MACD:** The MACD component within MomentumKit utilizes enhanced logic to improve its responsiveness and accuracy in detecting trend changes.
//
// 5. **Debugging Features:** MomentumKit includes advanced debugging tools that display individual buy and sell signals generated by each indicator. These features are intended for users with technical and programming skills, allowing them to:
// - **Visualize Signal Generation:** See real-time buy and sell signals for each integrated indicator directly on the chart.
// - **Adjust Signal Thresholds:** Modify the criteria for what constitutes a buy or sell signal for each indicator, enabling tailored analysis based on specific trading strategies.
// - **Filter and Manipulate Signals:** Enable or disable specific indicators' contributions to the overall buy and sell signals, providing flexibility in signal generation.
// - **Monitor Indicator Behavior:** Utilize debug plots and labels to understand how each indicator reacts to market movements, aiding in strategy optimization.
//
// **Work in Progress:**
// MomentumKit is continuously evolving, with ongoing enhancements to its algorithms and user interface. Current debugging features are designed to offer deep insights for technically adept users, allowing for extensive customization and fine-tuning. Future updates aim to introduce more user-friendly interfaces and automated optimization tools to cater to a broader audience.
//
// **Usage Instructions:**
// - **Visibility Controls:** Users can toggle the visibility of individual indicators to focus on specific momentum metrics as needed.
// - **Parameter Adjustments:** Each indicator comes with customizable parameters, allowing traders to fine-tune the suite according to their trading strategies and market conditions.
// - **Debugging Features:** Enable the debugging mode to visualize individual indicator signals and adjust their contribution to the overall buy/sell signals. This requires a basic understanding of the underlying indicators and their operational thresholds.
//
// **Benefits:**
// - **Simplified Analysis:** Normalization simplifies the process of analyzing multiple indicators, making it easier to identify consistent signals across different momentum measurements.
// - **Improved Decision-Making:** Consensus-based signals backed by multiple normalized indicators provide a higher level of confidence in trading decisions.
// - **Versatility:** Suitable for various trading styles and market conditions, MomentumKit offers a versatile toolset for both novice and experienced traders.
//
// **Technical Requirements:**
// - **Programming Knowledge:** To fully leverage the debugging and signal manipulation features, users should possess a foundational understanding of Pine Script and the mechanics of momentum indicators.
// - **Customization Skills:** Ability to adjust indicator parameters and debug filters to align with specific trading strategies.
//
// **Disclaimer:**
// This indicator suite is intended for educational and analytical purposes only and does not constitute financial advice. Trading involves significant risk, and past performance is not indicative of future results. Always conduct your own analysis or consult a qualified financial advisor before making trading decisions.
Stochastics Confluences 4 in 1Description of the Pine Script:
This script plots the Full Stochastic indicator for four different time periods, and highlights conditions where potential buy or sell signals can be identified. The Stochastic indicator measures the position of the current closing price relative to the range of high and low prices over a defined period, helping traders identify overbought and oversold conditions.
Key Features:
Stochastic Calculation for 4 Different Periods:
The script calculates the Stochastic for four separate lookback periods: 9, 14, 40, and 60 bars.
Each Stochastic value is smoothed by a Simple Moving Average (SMA) to reduce noise and provide a clearer signal.
Visual Representation:
It plots each Stochastic value on the chart using different colors, allowing the user to see how the different periods of the indicator behave relative to each other.
Horizontal lines are drawn at 80 (Upper Bound) and 20 (Lower Bound), commonly used to identify overbought and oversold regions.
Highlighting Buy and Sell Conditions:
Green Highlight (Potential Buy Signal):
When all four Stochastic values (for the four different periods) are below 20, this suggests that the asset is in an oversold condition across multiple timeframes. The green background highlight appears when the Stochastic lines converge below 20, indicating a potential buy signal, as the price may be preparing to move upward from an oversold state.
Red Highlight (Potential Sell Signal):
When all four Stochastic values are above 80, the asset is in an overbought condition across multiple timeframes. The red background highlight appears when the Stochastic lines converge above 80, indicating a potential sell signal, as the price may soon reverse downward from an overbought state.
How to Interpret the Signals:
Buy Signals (Green Highlight):
When the chart is highlighted in green, it means the Stochastic indicators for all four periods are below 20, signaling that the asset is oversold and may be nearing a potential upward reversal. This condition suggests a possible buying opportunity, especially when other indicators confirm the potential for an upward trend.
Sell Signals (Red Highlight):
When the chart is highlighted in red, it indicates that the Stochastic indicators for all four periods are above 80, meaning the asset is overbought. This condition signals a possible downward reversal, suggesting a potential selling opportunity if the price begins to show signs of weakness.
By using this script, traders can visually identify periods of strong confluence across different timeframes when the Stochastic indicators are in extreme oversold or overbought conditions, which are traditionally seen as strong buy or sell signals.
This approach helps filter out weaker signals and focuses on moments when all timeframes align, increasing the probability of a successful trade.
Cosine-Weighted MA ATR [InvestorUnknown]The Cosine-Weighted Moving Average (CWMA) ATR (Average True Range) indicator is designed to enhance the analysis of price movements in financial markets. By incorporating a cosine-based weighting mechanism , this indicator provides a unique approach to smoothing price data and measuring volatility, making it a valuable tool for traders and investors.
Cosine-Weighted Moving Average (CWMA)
The CWMA is calculated using weights derived from the cosine function, which emphasizes different data points in a distinctive manner. Unlike traditional moving averages that assign equal weight to all data points, the cosine weighting allocates more significance to values at the edges of the data window. This can help capture significant price movements while mitigating the impact of outlier values.
The weights are shifted to ensure they remain non-negative, which helps in maintaining a stable calculation throughout the data series. The normalization of these weights ensures they sum to one, providing a proportional contribution to the average.
// Function to calculate the Cosine-Weighted Moving Average with shifted weights
f_Cosine_Weighted_MA(series float src, simple int length) =>
var float cosine_weights = array.new_float(0)
array.clear(cosine_weights) // Clear the array before recalculating weights
for i = 0 to length - 1
weight = math.cos((math.pi * (i + 1)) / length) + 1 // Shift by adding 1
array.push(cosine_weights, weight)
// Normalize the weights
sum_weights = array.sum(cosine_weights)
for i = 0 to length - 1
norm_weight = array.get(cosine_weights, i) / sum_weights
array.set(cosine_weights, i, norm_weight)
// Calculate Cosine-Weighted Moving Average
cwma = 0.0
if bar_index >= length
for i = 0 to length - 1
cwma := cwma + array.get(cosine_weights, i) * close
cwma
Cosine-Weighted ATR Calculation
The ATR is an essential measure of volatility, reflecting the average range of price movement over a specified period. The Cosine-Weighted ATR uses a similar weighting scheme to that of the CWMA, allowing for a more nuanced understanding of volatility. By emphasizing more recent price movements while retaining sensitivity to broader trends, this ATR variant offers traders enhanced insight into potential price fluctuations.
// Function to calculate the Cosine-Weighted ATR with shifted weights
f_Cosine_Weighted_ATR(simple int length) =>
var float cosine_weights_atr = array.new_float(0)
array.clear(cosine_weights_atr)
for i = 0 to length - 1
weight = math.cos((math.pi * (i + 1)) / length) + 1 // Shift by adding 1
array.push(cosine_weights_atr, weight)
// Normalize the weights
sum_weights_atr = array.sum(cosine_weights_atr)
for i = 0 to length - 1
norm_weight_atr = array.get(cosine_weights_atr, i) / sum_weights_atr
array.set(cosine_weights_atr, i, norm_weight_atr)
// Calculate Cosine-Weighted ATR using true ranges
cwatr = 0.0
tr = ta.tr(true) // True Range
if bar_index >= length
for i = 0 to length - 1
cwatr := cwatr + array.get(cosine_weights_atr, i) * tr
cwatr
Signal Generation
The indicator generates long and short signals based on the relationship between the price (user input) and the calculated upper and lower bands, derived from the CWMA and the Cosine-Weighted ATR. Crossover conditions are used to identify potential entry points, providing a systematic approach to trading decisions.
// - - - - - CALCULATIONS - - - - - //{
bar b = bar.new()
float src = b.calc_src(cwma_src)
float cwma = f_Cosine_Weighted_MA(src, ma_length)
// Use normal ATR or Cosine-Weighted ATR based on input
float atr = atr_type == "Normal ATR" ? ta.atr(atr_len) : f_Cosine_Weighted_ATR(atr_len)
// Calculate upper and lower bands using ATR
float cwma_up = cwma + (atr * atr_mult)
float cwma_dn = cwma - (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, cwma_up)
signal := 1
if ta.crossunder(src_s, cwma_dn)
signal := -1
//}
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.
Visualization and Alerts
The indicator features customizable plots, allowing users to visualize the CWMA, ATR bands, and signals effectively. The colors change dynamically based on market conditions, with clear distinctions between long and short signals.
Alerts can be configured to notify users of crossover events, providing timely information for potential trading opportunities.
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.
TEMA For Loop [Mattes]The TEMA For Loop indicator is a powerful tool designed for technical analysis, combining the Triple Exponential Moving Average (TEMA) with a custom scoring mechanism based on a for loop. It evaluates price trends over a specified period, allowing traders to identify potential entry and exit points in the market. This indicator enhances decision-making by providing visual cues through dynamic candle coloring, reflecting market sentiment and trends effectively.
Technical Details:
Triple Exponential Moving Average (TEMA):
- TEMA is known for its responsiveness to price changes, as it reduces lag compared to traditional moving averages. The TEMA calculation employs three nested Exponential Moving Averages (EMAs) to produce a smoother trend line, which helps traders identify the direction and momentum of the market.
Scoring Mechanism:
- The scoring mechanism is based on a custom for loop that compares the current TEMA value to previous values over a specified range. The loop counts how many previous values are less than the current value, generating a score that reflects the strength of the trend:
- A higher score indicates a stronger upward trend.
- A lower (negative) score suggests a downward trend.
Threshold Levels:
- Upper Threshold: A score above this level signals a potential long entry, indicating strong bullish momentum.
- Lower Threshold: A score below this level indicates a potential short entry, suggesting bearish sentiment.
>>>These thresholds are adjustable, allowing traders to fine-tune their strategy according to their risk tolerance and market conditions.
Signal Logic:
- The indicator provides clear signals for entering long or short positions based on the score crossing the defined thresholds.
>>Long Entry Signal: When the smoothed score crosses above the upper threshold.
>>Short Entry Signal: When the smoothed score crosses below the lower threshold.
Why This Indicator Is Useful:
>>> Enhanced Decision-Making: The TEMA For Loop indicator offers traders a clear and objective view of market trends, reducing the emotional aspect of trading. By visualizing bullish and bearish conditions, it assists traders in making timely decisions.
>>> Customizable Parameters: The ability to adjust TEMA period, thresholds, and other settings allows traders to tailor the indicator to their specific trading strategies and market conditions.
Visual Clarity: The integration of dynamic candle coloring provides immediate visual cues about the prevailing trend, making it easier for traders to spot potential trade opportunities at a glance.
The TEMA For Loop - Smoothed with Candle Colors indicator is a sophisticated trading tool that utilizes TEMA and a custom scoring mechanism to identify and visualize market trends effectively. By employing dynamic candle coloring, traders gain immediate insights into market sentiment, enabling informed decision-making for entry and exit strategies. This indicator is designed for traders seeking a systematic approach to trend analysis, enhancing their trading performance through clear, actionable signals.
Breakout & Distribution DetectorHow the Script Works:
1. Bollinger Bands:
• The upper and lower Bollinger Bands are used to detect volatility and potential breakouts. When the price closes above the upper band, it’s considered a bullish breakout. When the price closes below the lower band, it’s a bearish breakout.
2. RSI (Relative Strength Index):
• The RSI is used for momentum confirmation. A bullish breakout is confirmed if the RSI is above 50, and a bearish breakout is confirmed if the RSI is below 50.
• If the RSI enters overbought (above 70) or oversold (below 30) levels, it signals a distribution phase, indicating the market may be ready to reverse or consolidate.
3. Moving Average:
• A simple moving average (SMA) of 20 periods is used to ensure we’re trading in the direction of the trend. Breakouts above the upper Bollinger Band are valid if the price is above the SMA, while breakouts below the lower Bollinger Band are valid if the price is below the SMA.
4. Signals and Alerts:
• BUY Signal: A green “BUY” label appears below the candle if a bullish breakout is detected.
• SELL Signal: A red “SELL” label appears above the candle if a bearish breakout is detected.
• Distribution Phase: The background turns purple if the market enters a distribution phase (RSI in overbought or oversold territory).
• Alerts: You can set alerts based on these conditions to get notifications for breakouts or when the market enters a distribution phase.
