Instant MACD (IMACD)The "Instant MACD" is a tailored version of the traditional Moving Average Convergence Divergence indicator, specifically designed to begin plotting with minimal data, such as in cases of high timeframe charts or newly listed trading instruments. Unlike the standard MACD that requires a substantial amount of data to provide accurate readings, the Instant MACD can deliver insights with as few as two candlesticks.
This iteration of the MACD utilizes the Chebyshev filter for the computation of both the fast and slow moving averages as well as for the signal line. The Chebyshev filter is known for its effectiveness in smoothing data series and reducing ripple effects, which is particularly advantageous when working with limited datasets.
The Instant MACD comprises several components. The histogram, which illustrates the difference between the MACD line and the signal line, adjusts its color based on the directional momentum; it transitions between shades of green and red as the histogram moves above or below the zero line and increases or decreases in value. The MACD line, depicted in blue, represents the disparity between the fast and slow Chebyshev moving averages. Complementing it is the signal line in orange, which is a Chebyshev-filtered mean of the MACD line and serves as an indicator of potential momentum shifts.
Additionally, the indicator includes a zero line for reference, aiding in the visualization of the convergence or divergence of the MACD and signal lines. To enhance its utility, the script encompasses alert conditions to notify users when there is a change in the trend of the histogram—specifically, when it transitions from a rising to a falling state and vice versa, potentially indicating shifts in market momentum.
Overall, the Instant MACD is an innovative tool for traders who require early trend signals in scenarios where traditional MACD analysis might be hampered by the lack of extensive historical data.
tl;dr this is identical to the regular macd but it starts working almost instantly.
Cerca negli script per "histogram"
BTC - Hotness Index### Script Description
#### BTC - Hotness Index
This Pine Script, version 4, aims to generate a "Hotness Index" for Bitcoin (BTC) trading by utilizing a Pi Cycle Top Indicator. The script operates in a daily (`1D`) time frame and involves calculating two Simple Moving Averages (SMA) based on `close` prices:
- 111-day SMA (`D_111SMA`)
- 350-day SMA (`D_350SMA`) multiplied by 2
The primary indicator (`pi_indicator`) is derived by dividing `D_111SMA` by `D_350SMA`.
##### Sell Signal
A sell signal is plotted as a histogram if `pi_indicator` crosses above 1 (`pi_plot` variable).
##### Buy Signal
A buy signal is plotted as a histogram if `pi_indicator` crosses below 0.35 (`pi_plot_buy` variable).
##### Horizontal Lines
Two horizontal lines are included to denote the "Buy Zone" and "Sell Zone":
- "Sell Zone" at `pi_indicator` level of 1
- "Buy Zone" at `pi_indicator` level of 0.35
##### Plotting
Histogram plots are used for visualizing the signals:
- Sell signals are colored red (`RGB: 255, 59, 59`)
- Buy signals are colored green (`RGB: 82, 255, 59`)
This script provides traders a visual guide for potential buy/sell opportunities based on the Pi Cycle Top Indicator and the Hotness Index for Bitcoin. It operates under the terms of the Mozilla Public License 2.0.
MACD HIstgramMA signl CrossingThis indicator highlights points where the MACD's Signal and Simple Moving Average of Histogram cross as entry points.
By incorporating the Simple Moving Average of the Histogram, it aims to avoid false entries during MACD and Signal crosses when volatility is low.
However, since it employs the Simple Moving Average of the Histogram, the appearance of entry points is less frequent and lagging compared to the cross of MACD and Signal.
Filtered Volume Profile [ChartPrime]The "Filtered Volume Profile" is a powerful tool that offers insights into market activity. It's a technical analysis tool used to understand the behavior of financial markets. It uses a fixed range volume profile to provide a histogram representing how much volume occurred at distinct price levels.
Profile in action with various significant levels displayed
How to Use
The script is designed to analyze cumulative trading volumes in different price bins over a certain period, also known as `'lookback'`. This lookback period can be defined by the user and it represents the number of bars to look back for calculating levels of support and resistance.
The `'Smoothing'` input determines the degree to which the output is smoothed. Higher values lead to smoother results but may impede the responsiveness of the indicator to rapid changes in volatility.
The `'Peak Sensitivity'` input is used to adjust the sensitivity of the script's peak detection algorithm. Setting this to a lower value makes the algorithm more sensitive to local changes in trading volume and may result in "noisier" outputs.
The `'Peak Threshold'` input specifies the number of bins that the peak detection mechanism should account for. Larger numbers imply that more volume bins are taken into account, and the resultant peaks are based on wider intervals.
The `'Mean Score Length'` input is used for scaling the mean score range. This is particularly important in defining the length of lookback bars that will be used to calculate the average close price.
Sinc Filter
The application of the sinc-filter to the Filtered Volume Profile reduces the risk of viewing artefacts that may misrepresent the underlying market behavior. Sinc filtering is a high-quality and sharp filter that doesn't manifest any ringing effects, making it an optimal choice for such volume profiling.
Histogram
On the histogram, the volume profile is colored based on the balance of bullish to bearish volume. If a particular bar is more intense in color, it represents a larger than usual volume during a single price bar. This is a clear signal of a strong buying or selling pressure at a particular price level.
Threshold for Peaks
The `peak_thresh` input determines the number of bins the algorithm takes in account for the peak detection feature. The 'peak' represents the level where a significant amount of volume trading has occurred, and usually is of interest as an indicative of support or resistance level.
By increasing the `peak_thresh`, you're raising the bar for what the algorithm perceives as a peak. This could result in fewer, but more significant peaks being identified.
History of Volume Profiles and Evolution into Sinc Filtering
Volume profiling has a rich history in market analysis, dating back to the 1950s when Richard D. Wyckoff, a legendary trader, introduced the concept of volume studies. He understood the critical significance of volume and its relationship with market price movement. The core of Wyckoff's technical analysis suite was the relationship between prices and volume, often termed as "Effort vs Results".
Moving forward, in the early 1800s, the esteemed mathematician J. R. Carson made key improvements to the sinc function, which formed the basis for sinc filtering application in time series data. Following these contributions, trading studies continued to create and integrate more advanced statistical measures into market analysis.
This culminated in the 1980s with J. Peter Steidlmayer’s introduction of Market Profile. He suggested that markets were a function of continuous two-way auction processes thus introducing the concept of viewing markets in price/time continuum and price distribution forms. Steidlmayer's Market Profile was the first wide-scale operation of organized volume and price data.
However, despite the introduction of such features, challenges in the analysis persisted, especially due to noise that could misinform trading decisions. This gap has given rise to the need for smoothing functions to help eliminate the noise and better interpret the data. Among such techniques, the sinc filter has become widely recognized within the trading community.
The sinc filter, because of its properties of constructing a smooth passing through all data points precisely and its ability to eliminate high-frequency noise, has been considered a natural transition in the evolution of volume profile strategies. The superior ability of the sinc filter to reduce noise and shield against over-fitting makes it an ideal choice for smoothing purposes in trading scripts, particularly where volume profiling forms the crux of the market analysis strategy, such as in Filtered Volume Profile.
Moving ahead, the use of volume-based studies seems likely to remain a core part of technical analysis. As long as markets operate based on supply and demand principles, understanding volume will remain key to discerning the intent behind price movements. And with the incorporation of advanced methods like sinc filtering, the accuracy and insight provided by these methodologies will only improve.
Mean Score
The mean score in the Filtered Volume Profile script plays an important role in probabilistic inferences regarding future price direction. This score essentially characterizes the statistical likelihood of price trends based on historical data.
The mean score is calculated over a configurable `'Mean Score Length'`. This variable sets the window or the timeframe for calculation of the mean score of the closing prices.
Statistically, this score takes advantage of the concept of z-scores and probabilities associated with the t-distribution (a type of probability distribution that is symmetric and bell-shaped, just like the standard normal distribution, but has heavier tails).
The z-score represents how many standard deviations an element is from the mean. In this case, the "element" is the price level (Point of Control).
The mean score section of the script calculates standard errors for the root mean squared error (RMSE) and addresses the uncertainty in the prediction of the future value of a random variable.
The RMSE of a model prediction concerning observed values is used to measure the differences between values predicted by a model and the values observed.
The lower the RMSE, the better the model is able to predict. A zero RMSE means a perfect fit to the data. In essence, it's a measure of how concentrated the data is around the line of best fit.
Through the mean score, the script effectively predicts the likelihood of the future close price being above or below our identified price level.
Summary
Filtered Volume Profile is a comprehensive trading view indicator which utilizes volume profiling, peak detection, mean score computations, and sinc-filter smoothing, altogether providing the finer details of market behavior.
It offers a customizable look back period, smoothing options, and peak sensitivity setting along with a uniquely set peak threshold. The application of the Sinc Filter ensures a high level of accuracy and noise reduction in volume profiling, making this script a reliable tool for gaining market insights.
Furthermore, the use of mean score calculations provides probabilistic insights into price movements, thus providing traders with a statistically sound foundation for their trading decisions. As trading markets advance, the use of such methodologies plays a pivotal role in formulating effective trading strategies and the Filtered Volume Profile is a successful embodiment of such advancements in the field of market analysis.
P/VF BollThis code draws a custom indicator named "P/VF Boll" on the price chart with the following visual elements:
1. **Basis Line (Blue)**: This line represents the moving average value (ma_value) calculated based on the user-selected moving average type (SMA, EMA, or WMA) and length.
2. **Upper Bands (Green)**: The upper bands are calculated by adding a certain multiple of the standard deviation (dev1 to dev12) to the basis line. These bands represent a certain level of price volatility above the moving average.
3. **Lower Bands (Red)**: The lower bands are calculated by subtracting a certain multiple of the standard deviation (dev1 to dev12) from the basis line. These bands represent a certain level of price volatility below the moving average.
4. **Histogram (White and Gray)**: A histogram is drawn only when the average_price_change values are outside the 3rd standard deviation (dev3) and beyond. The histogram color alternates between white and gray, indicating higher price volatility.
The user can customize the following parameters:
- Average Length: The length of the moving average.
- Moving Average Type: The type of moving average to be used (SMA, EMA, or WMA).
- Timeframe: The timeframe used to calculate volume data.
- Deviation 1 to Deviation 12: Multipliers for calculating the upper and lower bands.
The purpose of this indicator is to visually represent the relationship between price volatility, volume, and the moving average, allowing traders to assess potential price breakouts or reversals when the price moves beyond certain levels of standard deviations from the moving average.
ARSIXARSIX
I have written this indicator after two years of continuous experience in writing and backtesting for several different indicators, and I believe that this indicator with its high capabilities can show you the best point of entry into the market as well as exit from it. arsix should work with any time frame and any instrument used.
This indicator has many points to understand so that you can make the best possible use of it, in the following I will try to bring you some of the most important points:
First, we will have an introduction of the different parts of the indicator:
The above line is a relatively simple but very useful formula to determine the momentum of chart. To understand the exact formula, you can refer to the source of the program itself, and its two colors are used to determine the direction of movement.
At the bottom, we have three opposing elements.
The first is the RSI14 line with dark blue color, the second is the RMA or Relative Momentum Index(RMI20) line with the number 20 for Momentum , which will significantly help us understand the overall momentum of the chart, this part is also made in two colors to increase or It will show the decline of the overall momentum of the chart.
And finally, we have a bar chart that is again created in two colors, and this histogram also calculates the momentum chart with a different formula.
And now let's talk about how to interpret these tools and how to use them for Trading:
At first, you may have the question that all these different indicators are not excessive to determine the momentum chart and are all of them necessary? In response, I must say that yes, each of these parts has been selected and made with great care and with my previous experience, the full explanation of each of these parts is beyond the scope of this article, and I will try to explain it in short words. I will give you a general understanding of each one of them and the rest is up to you to find out their capabilities by working more with these tools.
The main thing is to know that none of these tools alone will bring you success and it is their teamwork together that will help you achieve success.
For the sake of simplicity, I will tell you when to open a buy position with this indicator And you can then use this definition of the main thread to interpret the rest of the capabilities of this indicator.
To open a buy position, first the upper indicator should turn light blue, at the same time, the RMI indicator should also turn light blue, and you should also see that this RMI indicator shows the momentum of the overall chart in order to increase. in this case you will be almost sure that the general trend of the chart is towards the rise of the price. In the next step, to determine the exact point of the Entry, you have to wait until the RSI indicator passes the number 50 in this state and at the same time, make sure that the histogram also turns green and shows the increasing direction of momentum in the market, when the RSI is in This state crossed the number 50, you can enter the buy position, it should be noted that due to a series of restrictions, I have moved the RSI indicator down by 50 numbers, so as a result, the number 50 for RSI here is equivalent to The same number zero.
This was an example of how to work with this indicator, I hope that it helped you to understand how to use this indicator. In the end, I would like to point out again that the main topic is understanding the group and mutual behavior of each of the indicators' tools together. For example, if the RSI indicator crosses the number 50 here, but the histogram does not grow or shows a small growth, this indicates that the movement will be low, or for another example, if the RSI indicator cross over From the RMI indicator, This means that the market is very high, and as a result, it is a great opportunity to hold a buy position. In the same way, other parts of this indicator can also be interpreted in opposition to each other.
I hope this indicator will help you in better trades. I look forward to your constructive comments. Thanks Hamid Moradi.
Price & Volume Profile (Expo)█ Overview
The Price & Volume Profile provides a holistic perspective on market dynamics by simultaneously tracking price action and trading volume across a range of price levels. So it is not only a volume-based indicator but also a price-based one. In addition to illustrating volume distribution, it quantifies how frequently the price has fallen within a particular range, thus offering a holistic perspective on market dynamics.
This unique and comprehensive approach to market analysis by considering both price action and trading volume, two crucial dimensions of market activity. Its distinctive methodology offers several advantages:
Holistic Market View: By simultaneously tracking the frequency of specific price ranges (Price Profile) and the volume traded at those ranges (Volume Profile), this indicator provides a more complete picture of market behavior. It shows not only where the market is trading but also how much it's trading, reflecting both price acceptance levels and market participation intensity.
Point of Control (POC): The POC, as highlighted by this indicator, serves as a significant reference point for traders. It identifies the price level with the highest trading activity, thus indicating a strong consensus among market participants about the asset's fair value. Observing how price interacts with the POC can offer valuable insights into market sentiment and potential trend reversals.
Support and Resistance Levels: Price levels with high trading activity often act as support or resistance in future price movements. The indicator visually represents these levels, enabling traders to anticipate potential price reactions.
Price Profile
Price and Volume Profile
█ Calculations
The algorithm analyzes both trade frequency and volume across different price levels. It identifies these levels within the visible chart range, then examines each bar to determine if the selected price falls within these levels. If so, it increases a counter and adds the trading volume. This process repeats across the visible range and is visualized as a horizontal histogram, each bar representing a price level and the bar length reflecting trade frequency and volume. Additionally, it calculates the Point of Control (POC), signifying the price level with the highest activity.
In summary: The histogram presents a dual perspective - not only the traded volume at each price level but also the frequency of the price hitting each range. The longer the bar, the more times the price has frequented that specific range, revealing key insights into price behavior and acceptance levels. These frequently visited areas often emerge as strong support or resistance zones, helping traders navigate market movements.
Please note that the indicator adjusts to the visible price range, making it adaptable to changing market conditions. This dynamic analysis can provide more relevant and timely information than static indicators.
█ How to use
This indicator is beneficial for traders as it offers insights into the distribution of trading activity across different price levels. It helps identify key areas of support and resistance and gives a visual representation of market sentiment and liquidity.
The point of control (POC) , which is the price level with the highest traded volume or frequency count, becomes even more crucial in this context. It marks the price at which the most trading activity occurred, signaling a strong consensus among market participants about the asset's fair value. If the market price deviates significantly from the POC, it could suggest an overbought or oversold condition, potentially leading to a price reversion.
Fair Price Areas/gaps are specific price levels or zones where an asset has spent limited time in the past. These areas are considered interesting or significant because they may have an impact on future price action.
Similar to the concept of fair value gaps, which refers to discrepancies between an asset's market price and its estimated intrinsic value, Fair Price Areas/gaps focus on price levels that have been relatively underutilized in terms of trading activity. When an asset's price reaches a Fair Price Area/gap, traders and investors pay attention because they expect the price to react in some way. The rationale behind this concept is that price tends to gravitate towards areas where it has spent less time in the past, as the market perceives them as significant levels.
█ Settings
The indicator is customizable, allowing users to define the number of price levels (rows), the offset, the data source, and whether to display volume or frequency count. It also adjusts dynamically to the visible price range on the chart, ensuring that the analysis remains relevant and timely with changing market conditions.
Source: The price to use for the calculation. Typically, this is the closing price. By considering the user-selected Source (typically the closing price), the indicator determines the frequency with which the price lands within each designated price level (row) over the selected period. In essence, the indicator provides a count of bars where the Source price falls within each range, essentially creating a "Price Profile."
Row Size: The number of price levels (rows) to divide the visible price range into.
Display: Choose whether to display the number of bars ("Counter") or the total volume ("Volume") for each price level.
Offset: The distance of the histogram from the price chart.
Point of Control (POC): If enabled, the indicator will highlight the price level with the most activity.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Pearson's R Convergence DivergenceThis script calculates the convergence divergence and breakouts from the deviations for a fast and slow linear regression slope.
This can be used to predict major market moves before they happen.
For users familiar with MacD, the blue line is similar to the MacD line and the orange line the signal.
The difference is this is not a moving average comparison but a comparison between Pearson's R values.
-0.1 (positive direction)
0.1 (negative direction)
This is why the colors look inverse for a typical MacD.
How to use this:
The idea is that when both trends converge in the 0.8 or -0.8 range and you see a breakout cross occur on either line then the price has a high likelihood of reversing its current trend.
If you see a green cross it means the top of the linear regression for the 'fast' or 'slow' linear regression deviation was broken by the current price. This can signify that upward movement is coming soon.
On the flip side a red cross means the bottom of the linear regression for the 'fast' or 'slow' linear regression deviation was broken by the current price. This can signify that downward movement is coming soon.
These crosses mean a lot more if the pearson's R value is already maxed out near 0.8 or -0.8.
This indicator works because the more sure a trend becomes the more likely it is to break as more traders see the pattern.
The histogram colors do not mean much being 'red' or 'green', what you want to look for is when the histogram starts to approach the 0 mark. This signifies that both linear regression trends are about to reach their peak before reversing trend. So don't confuse this with how you might read the MacD even though it looks very similar. The histogram sloping towards the 0 line will give you a clue how long it might take before the reversal occurs .
Please PM me if you have any questions, and enjoy!
High Liquidity Zones and Threshold VolumeThe High Liquidity Zones indicator is designed to identify areas of significant liquidity in the market. It helps traders recognize regions where trading volume is notably higher, indicating potential areas of increased market activity and interest.
The indicator calculates the average volume over a specified lookback period, which can be customized according to individual preferences. This average volume acts as a reference point to determine the threshold volume level. The threshold percentage input allows users to set the sensitivity of the indicator, defining the minimum volume required for an area to be considered a high liquidity zone.
When the current volume surpasses the threshold volume level, the indicator highlights these areas as high liquidity zones. This visual representation allows traders to quickly identify and focus on periods of heightened trading activity. The high liquidity zones are marked with square shapes below the histogram, providing a clear visual indication on the chart.
The first plot line represents the threshold volume level as a histogram, showing the volume levels in relation to the threshold. This histogram helps traders assess the magnitude of the volume in the identified high liquidity zones.
The second plot line represents the threshold volume's simple moving average (SMA) over the lookback period. The SMA acts as a reference line, smoothing out fluctuations in the threshold volume and providing a more stable measure of high liquidity zones. Traders can use this line to better understand the overall trend and dynamics of liquidity.
The High Liquidity Zones indicator offers flexibility, allowing traders to adapt it to their preferred trading style and timeframe. By adjusting the lookback period and threshold percentage, users can fine-tune the sensitivity of the indicator based on their trading strategies and market conditions.
Furthermore, traders can combine the High Liquidity Zones indicator with other technical analysis tools to confirm trading signals or identify areas of potential support and resistance. It can help them locate price levels where market participants have a substantial presence and where significant buying or selling pressure may occur.
Overall, the High Liquidity Zones indicator is a valuable tool for traders seeking to gain insights into market liquidity dynamics. By highlighting areas of intense trading activity, it assists in making informed trading decisions and identifying opportunities within the market.
Price Action - Support & Resistance + MACD LONG StrategyUsing "Price Action - Support & Resistance by DGT" and the MACD (Moving Average Convergence Divergence) indicator in TradingView can help develop a trade strategy. Here's a step-by-step approach you can follow:
1. Identifying Support and Resistance Levels: Apply the "Price Action - Support & Resistance by DGT" indicator to your chart. This indicator helps you identify key support and resistance levels based on price action. These levels act as potential areas where the price may reverse or consolidate.
2. Confirming Support and Resistance Levels: Once the indicator has plotted support and resistance levels on your chart, analyze the historical price action around these levels. Look for multiple touches or bounces from the same level, which adds strength to the support or resistance zone.
3. Analyzing the MACD Indicator: Add the MACD indicator to your chart. The MACD consists of two lines: the MACD line and the signal line, along with a histogram representing the difference between the two lines. The MACD helps identify momentum and potential trend reversals.
When the MACD line crosses above the signal line and the histogram turns positive, it suggests bullish momentum.
4. Identifying Trade Opportunities:
Bullish Trade: Look for a bullish setup when the price approaches a strong support level identified by the "Price Action - Support & Resistance by DGT" indicator. Wait for the MACD lines to cross above the signal line and the histogram to turn positive, indicating bullish momentum. Enter a long position with a stop loss below the
support level.
Managing the Trade: Once you enter a trade, consider setting a target based on the distance between your entry point and the nearest significant support or resistance level. You can also use trailing stop losses or other risk management techniques to protect your profits and limit potential losses.
Remember that no trading strategy is guaranteed to be successful, and it's important to practice proper risk management and conduct thorough analysis before making any trading decisions. Additionally, it's recommended to backtest and demo trade this strategy before using it with real money.
ETH Volume*Close Top Exchanges in millions $The script is designed to create a custom indicator that calculates the total volume of Ethereum traded on various exchanges, calculated in millions of dollars, and then plots a histogram of that volume along with a Simple Moving Average (SMA) of the volume.
The script starts by setting some input parameters such as the length of the SMA and the range period. It then requests data on the volume of Ethereum traded on several exchanges such as Binance, Coinbase, Kraken, and others. It calculates the combined total volume across all these exchanges and multiplies it by the close price of Ethereum to get a value in millions of dollars.
The script then checks if the volume is rising while the price is lower than the previous 5 bars high and higher than the previous 5 bars low, and if so, it sets the color of the histogram bars to white. It then plots the histogram bars and the SMA on the chart.
BTC Volume*Close from Top ExchangesThe script is designed to create a custom indicator that calculates the total volume of Bitcoin traded on various exchanges, calculated in millions of dollars, and then plots a histogram of that volume along with a Simple Moving Average (SMA) of the volume.
The script starts by setting some input parameters such as the length of the SMA and the range period. It then requests data on the volume of Bitcoin traded on several exchanges such as Binance, Coinbase, Kraken, and others. It calculates the combined total volume across all these exchanges and multiplies it by the close price of Bitcoin to get a value in millions of dollars.
The script then checks if the volume is rising while the price is lower than the previous 5 bars high and higher than the previous 5 bars low, and if so, it sets the color of the histogram bars to white. It then plots the histogram bars and the SMA on the chart.
OBV-MACDThe OBV-MACD indicator is a momentum-based technical analysis tool that helps traders identify trend reversals and trend strength. This Pine script is an implementation of the OBV-MACD indicator that uses the On-Balance Volume (OBV) and Moving Average Convergence Divergence (MACD) indicators to provide a momentum data of OBV.
The OBV-MACD indicator uses the OBV to calculate the cumulative volume, which is then smoothed using two moving averages - fast and slow. The difference between these moving averages is plotted as a histogram, with a signal line plotted over it. A buy signal is generated when the histogram crosses above the signal line, indicating a bullish trend, while a sell signal is generated when the histogram crosses below the signal line, indicating a bearish trend.
This Pine script also includes an OBV-MACD-Donchian version that incorporates Donchian channels for the OBV-MACD. The Donchian channel is a technical analysis indicator that helps traders identify the highs and lows of an asset's price over a certain period. The OBV-MACD-Donchian version uses the OBV-MACD indicator along with the Donchian channels to provide signals that the momentum of OBV is making new high/low during that period of time.
Traders can customize the input parameters of the OBV-MACD indicator, such as the timeframe, method of calculation for the moving averages, and the lengths of the moving averages and breakout lengths. The colors of the plot can also be customized to suit the trader's preferences.
Strategy Myth-Busting #11 - TrendMagic+SqzMom+CDV - [MYN]This is part of a new series we are calling "Strategy Myth-Busting" where we take open public manual trading strategies and automate them. The goal is to not only validate the authenticity of the claims but to provide an automated version for traders who wish to trade autonomously.
Our 11th one is an automated version of the "Magic Trading Strategy : Most Profitable Indicator : 1 Minute Scalping Strategy Crypto" strategy from "Fx MENTOR US" who doesn't make any official claims but given the indicators he was using, it looked like on the surface that this might actually work. The strategy author uses this on the 1 minute and 3 minute timeframes on mostly FOREX and Heiken Ashi candles but as the title of his strategy indicates is designed for Crypto. So who knows..
To backtest this accurately and get a better picture we resolved the Heiken Ashi bars to standard candlesticks . Even so, I was unable to sustain any consistency in my results on either the 1 or 3 min time frames and both FOREX and Crypto. 10000% Busted.
This strategy uses a combination of 3 open-source public indicators:
Trend Magic by KivancOzbilgic
Squeeze Momentum by LazyBear
Cumulative Delta Volume by LonesomeTheBlue
Trend Magic consists of two main indicators to validate momentum and volatility. It uses an ATR like a trailing Stop to determine the overarching momentum and CCI as a means to validate volatility. Together these are used as the primary indicator in this strategy. When the CCI is above 0 this is confirmation of a volatility event is occurring with affirmation based upon current momentum (ATR).
The CCI volatility indicator gets confirmation by the the Cumulative Delta Volume indicator which calculates the difference between buying and selling pressure. Volume Delta is calculated by taking the difference of the volume that traded at the offer price and the volume that traded at the bid price. The more volume that is traded at the bid price, the more likely there is momentum in the market.
And lastly the Squeeze Momentum indicator which uses a combination of Bollinger Bands, Keltner Channels and Momentum are used to again confirm momentum and volatility. During periods of low volatility, Bollinger bands narrow and trade inside Keltner channels. They can only contract so much before it can’t contain the energy it’s been building. When the Bollinger bands come back out, it explodes higher. When we see the histogram bar exploding into green above 0 that is a clear confirmation of increased momentum and volatile. The opposite (red) below 0 is true when there are low periods. This indicator is used as a means to really determine when there is premium selling plays going on leading to big directional movements again confirming the positive or negative momentum and volatility direction.
If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
Trading Rules
1 - 3 min candles
FOREX or Crypto
Stop loss at swing high/low | 1.5 risk/ratio
Long Condition
Trend Magic line is Blue ( CCI is above 0) and above the current close on the bar
Squeeze Momentum's histogram bar is green/lime
Cumulative Delta Volume line is green
Short Condition
Trend Magic line is Red ( CCI is below 0) and below the current close on the bar
Squeeze Momentum's histogram bar is red/maroon
Cumulative Delta Volume line is peach
Stochastic Moving Average Convergence Divergence (SMACD)This is my attempt at making a Stochastic MACD indicator. To get this to work I have introduced a DC offset to the MACD histogram output. I figured that if theirs a Stochastic RSI their might as well be a Stochastic everything else! lmao enjoy. Honestly, from what I can tell it's even faster than Stochastic Smooth RSI.
The Stochastic Oscillator (STOCH) is a range bound momentum oscillator. The Stochastic indicator is designed to display the location of the close compared to the high/low range over a user defined number of periods. Typically, the Stochastic Oscillator is used for three things; Identifying overbought and oversold levels, spotting divergences and also identifying bull and bear set ups or signals
MACD is an extremely popular indicator used in technical analysis. MACD can be used to identify aspects of a security's overall trend. Most notably these aspects are momentum, as well as trend direction and duration. What makes MACD so informative is that it is actually the combination of two different types of indicators. First, MACD employs two Moving Averages of varying lengths (which are lagging indicators) to identify trend direction and duration. Then, MACD takes the difference in values between those two Moving Averages (MACD Line) and an EMA of those Moving Averages (Signal Line) and plots that difference between the two lines as a histogram which oscillates above and below a center Zero Line. The histogram is used as a good indication of a security's momentum
[blackcat] L3 Banker Fund AttackLevel 3
Background
This indicator is used to capture the movement of the banker fund. The buying and selling point is determined according to whether the momentum of the banker fund and the price momentum resonate.
How to use the indicator:
The red column line indicates that the banker fund accumulation signal appears, and the following 2 conditions are all satisfied to buy; (both above the green line of the banker fund attack threshold)
1. The yellow line and the purple line all cross the red accumulation histogram signal;
2. The yellow and purple trend lines are up
Key point: If the yellow line crosses the green line of the banker fund attack threshold, it will be pulled up or the big market will open! The main thing is to see the red accumulation histogram signal, or the green line that crosses the banker fund attack threshold. If there is a red accumulation histogram signal, it means that there are main low-acquisition chips, and start trading on the left to open a position. The area above the green line of the banker fund attack threshold belongs to the main force pulling stage. When the green line of the banker fund attack threshold is not broken upwards, there is still a lot of profit space, but if it can be effectively broken through, it is highly profitable!
Remarks
This indicator only effective for instruments that contains banker fund. If there is no obvious large fund inside, the indicator is not as meaningful as it is called.
I verified it worked well for > 4H or 1D timeframe. For the other time frames, you may need to check and verify by yourself.
Feedbacks are appreciated.
HMA Slope Variation [Loxx]HMA Slope Variation is an indicator that uses HMA moving average to calculate a slope that is then weighted to derive a signal.
The center line
The center line changes color depending on the value of the:
Slope
Signal line
Threshold
If the value is above a signal line (it is not visible on the chart) and the threshold is greater than the required, then the main trend becomes up. And reversed for the trend down.
Colors and style of the histogram
The colors and style of the histogram will be drawn if the value is at the right side, if the above described trend "agrees" with the value (above is green or below zero is red) and if the High is higher than the previous High or Low is lower than the previous low, then the according type of histogram is drawn.
What is the Hull Moving Average?
The Hull Moving Average ( HMA ) attempts to minimize the lag of a traditional moving average while retaining the smoothness of the moving average line. Developed by Alan Hull in 2005, this indicator makes use of weighted moving averages to prioritize more recent values and greatly reduce lag.
Included
Alets
Signals
Bar coloring
Loxx's Expanded Source Types
T3 Slope Variation [Loxx]T3 Slope Variation is an indicator that uses T3 moving average to calculate a slope that is then weighted to derive a signal.
The center line
The center line changes color depending on the value of the:
Slope
Signal line
Threshold
If the value is above a signal line (it is not visible on the chart) and the threshold is greater than the required, then the main trend becomes up. And reversed for the trend down.
Colors and style of the histogram
The colors and style of the histogram will be drawn if the value is at the right side, if the above described trend "agrees" with the value (above is green or below zero is red) and if the High is higher than the previous High or Low is lower than the previous low, then the according type of histogram is drawn.
What is the T3 moving average?
Better Moving Averages Tim Tillson
November 1, 1998
Tim Tillson is a software project manager at Hewlett-Packard, with degrees in Mathematics and Computer Science. He has privately traded options and equities for 15 years.
Introduction
"Digital filtering includes the process of smoothing, predicting, differentiating, integrating, separation of signals, and removal of noise from a signal. Thus many people who do such things are actually using digital filters without realizing that they are; being unacquainted with the theory, they neither understand what they have done nor the possibilities of what they might have done."
This quote from R. W. Hamming applies to the vast majority of indicators in technical analysis . Moving averages, be they simple, weighted, or exponential, are lowpass filters; low frequency components in the signal pass through with little attenuation, while high frequencies are severely reduced.
"Oscillator" type indicators (such as MACD , Momentum, Relative Strength Index ) are another type of digital filter called a differentiator.
Tushar Chande has observed that many popular oscillators are highly correlated, which is sensible because they are trying to measure the rate of change of the underlying time series, i.e., are trying to be the first and second derivatives we all learned about in Calculus.
We use moving averages (lowpass filters) in technical analysis to remove the random noise from a time series, to discern the underlying trend or to determine prices at which we will take action. A perfect moving average would have two attributes:
It would be smooth, not sensitive to random noise in the underlying time series. Another way of saying this is that its derivative would not spuriously alternate between positive and negative values.
It would not lag behind the time series it is computed from. Lag, of course, produces late buy or sell signals that kill profits.
The only way one can compute a perfect moving average is to have knowledge of the future, and if we had that, we would buy one lottery ticket a week rather than trade!
Having said this, we can still improve on the conventional simple, weighted, or exponential moving averages. Here's how:
Two Interesting Moving Averages
We will examine two benchmark moving averages based on Linear Regression analysis.
In both cases, a Linear Regression line of length n is fitted to price data.
I call the first moving average ILRS, which stands for Integral of Linear Regression Slope. One simply integrates the slope of a linear regression line as it is successively fitted in a moving window of length n across the data, with the constant of integration being a simple moving average of the first n points. Put another way, the derivative of ILRS is the linear regression slope. Note that ILRS is not the same as a SMA ( simple moving average ) of length n, which is actually the midpoint of the linear regression line as it moves across the data.
We can measure the lag of moving averages with respect to a linear trend by computing how they behave when the input is a line with unit slope. Both SMA (n) and ILRS(n) have lag of n/2, but ILRS is much smoother than SMA .
Our second benchmark moving average is well known, called EPMA or End Point Moving Average. It is the endpoint of the linear regression line of length n as it is fitted across the data. EPMA hugs the data more closely than a simple or exponential moving average of the same length. The price we pay for this is that it is much noisier (less smooth) than ILRS, and it also has the annoying property that it overshoots the data when linear trends are present.
However, EPMA has a lag of 0 with respect to linear input! This makes sense because a linear regression line will fit linear input perfectly, and the endpoint of the LR line will be on the input line.
These two moving averages frame the tradeoffs that we are facing. On one extreme we have ILRS, which is very smooth and has considerable phase lag. EPMA has 0 phase lag, but is too noisy and overshoots. We would like to construct a better moving average which is as smooth as ILRS, but runs closer to where EPMA lies, without the overshoot.
A easy way to attempt this is to split the difference, i.e. use (ILRS(n)+EPMA(n))/2. This will give us a moving average (call it IE /2) which runs in between the two, has phase lag of n/4 but still inherits considerable noise from EPMA. IE /2 is inspirational, however. Can we build something that is comparable, but smoother? Figure 1 shows ILRS, EPMA, and IE /2.
Filter Techniques
Any thoughtful student of filter theory (or resolute experimenter) will have noticed that you can improve the smoothness of a filter by running it through itself multiple times, at the cost of increasing phase lag.
There is a complementary technique (called twicing by J.W. Tukey) which can be used to improve phase lag. If L stands for the operation of running data through a low pass filter, then twicing can be described by:
L' = L(time series) + L(time series - L(time series))
That is, we add a moving average of the difference between the input and the moving average to the moving average. This is algebraically equivalent to:
2L-L(L)
This is the Double Exponential Moving Average or DEMA , popularized by Patrick Mulloy in TASAC (January/February 1994).
In our taxonomy, DEMA has some phase lag (although it exponentially approaches 0) and is somewhat noisy, comparable to IE /2 indicator.
We will use these two techniques to construct our better moving average, after we explore the first one a little more closely.
Fixing Overshoot
An n-day EMA has smoothing constant alpha=2/(n+1) and a lag of (n-1)/2.
Thus EMA (3) has lag 1, and EMA (11) has lag 5. Figure 2 shows that, if I am willing to incur 5 days of lag, I get a smoother moving average if I run EMA (3) through itself 5 times than if I just take EMA (11) once.
This suggests that if EPMA and DEMA have 0 or low lag, why not run fast versions (eg DEMA (3)) through themselves many times to achieve a smooth result? The problem is that multiple runs though these filters increase their tendency to overshoot the data, giving an unusable result. This is because the amplitude response of DEMA and EPMA is greater than 1 at certain frequencies, giving a gain of much greater than 1 at these frequencies when run though themselves multiple times. Figure 3 shows DEMA (7) and EPMA(7) run through themselves 3 times. DEMA^3 has serious overshoot, and EPMA^3 is terrible.
The solution to the overshoot problem is to recall what we are doing with twicing:
DEMA (n) = EMA (n) + EMA (time series - EMA (n))
The second term is adding, in effect, a smooth version of the derivative to the EMA to achieve DEMA . The derivative term determines how hot the moving average's response to linear trends will be. We need to simply turn down the volume to achieve our basic building block:
EMA (n) + EMA (time series - EMA (n))*.7;
This is algebraically the same as:
EMA (n)*1.7-EMA( EMA (n))*.7;
I have chosen .7 as my volume factor, but the general formula (which I call "Generalized Dema") is:
GD (n,v) = EMA (n)*(1+v)-EMA( EMA (n))*v,
Where v ranges between 0 and 1. When v=0, GD is just an EMA , and when v=1, GD is DEMA . In between, GD is a cooler DEMA . By using a value for v less than 1 (I like .7), we cure the multiple DEMA overshoot problem, at the cost of accepting some additional phase delay. Now we can run GD through itself multiple times to define a new, smoother moving average T3 that does not overshoot the data:
T3(n) = GD ( GD ( GD (n)))
In filter theory parlance, T3 is a six-pole non-linear Kalman filter. Kalman filters are ones which use the error (in this case (time series - EMA (n)) to correct themselves. In Technical Analysis , these are called Adaptive Moving Averages; they track the time series more aggressively when it is making large moves.
Included
Alets
Signals
Bar coloring
Loxx's Expanded Source Types
A_HMS_RSI_COMPOSITMy majic Macd Indicator with Ema base macd is My great Indicator that combine four ema base macd lines with its signal lines that show price gravity by best way , and one spatial chart that is the best part of this magic indicator that help you to trading without any problem
for better use note that:
green fill line is ema 66 and ema 199 macd and signal its name is macd very slow signal line
blue fill line is ema 19 and ema 66 macd and signal its name is macd normal signal line
red fill line is ema 9 and ema 19 macd and signal its name is macd very fast signal line
black line is ema 4 and ema 14 macd its name is macd main signal line
in all of this lines we can define divergence
when this lines crossing over and under from together each of this crossings give me some signals and because this signals very much we cant describe thats in some lines
but note that we in fact trade just by black line but short and long position determine by position of black line instead of other lines and positions of other lines from each ones
purple line is rsi line
red line is composite line
blue line is rmi line
red and Blue below line is Slow Stochastic lines
blue and orange line is Stochastic ema with ema12 - ema21
and third chart is a secret indicator that help more to determine best place to start trading
A_HMS_RSI is My great Indicator that RSI , RMI and , momentum of price movement by a histogram , that help you to trading without any problem
for better use note that:
blue line is rsi line with hl2 source and 14 length
low color line is rmi line with momentum 33
rmi of price with momentum 33 is a very good signal for long positions.
momentum histogram help us to define strong of price motion in each time
some futures is hidden by default:
composite red and green signal line
rmi of price with momentum 4
ema 13, 33 of rmi as signal line and rsi and composit
finaly u can change any colors from setting
in background we determine some filled zones for better use of Indicator
when composite line run away from histogram momentum increase rapidly
when composite and rsi line is in same way its time to get position .
rmi of price with momentum 20 is a very good signal for long positions.
some futures is hidden by default:
composite red and green signal line
rmi of price with momentum 20
ema 13, 33 of rmi as signal line
finaly u can change any colors from setting
and you can get stoch signals too
in background we determine some filled zones for better use of Indicator
Distance from Vwap// How it Works \\
Measuring the distance of the close price from a higher timeframe VWAP - Volume Weighted Average Price
There is a threshold which is calculated by looking back at the previous x amount of bars and storing the highest/lowest values
If the distance from the vwap stretches above that threshold, the histogram will go green if price is above VWAP and red if its below the vwap
If the distance from the vwap reaches below the low threshold you will see the histogram flashes orange
// Settings \\
In the settings you have the ability to change what timeframe the indicator is calculated on, as well as this you can change the timeframe the VWAP is calculated on.
I always recommend using a higher timeframe vwap as they tend to me more respected
e.g on the hourly timeframe, I use the weekly VWAP, on 1 minute timeframe you may want to use 4 hour timeframe but obviously feel free to experiment
// Use Case \\
When histogram is flashing green, prices is pulling far away from the vwap, obviously you don't want to be buying a falling knife but if you have levels of confluence this can help spot reversals.
I personally wait until the first candle after its been green to get confirmation of the fall weakening. Vica versa for reds and shorts/sells.
When you see orange flashes, this shows that price has been consolidating and the price is very close to the higher time frame VWAP which could be considered a safe entry point as they tend to lead to a big move to follow
// Suggestions \\
Happy for anyone to make any suggestions on changes which could improve the script,
// Terms \\
Feel free to use the script, If you do use the script could you please just tag me as I am interested to see how people are using it. Good Luck!
KINSKI Multi Trend OscillatorThe Multi Trend Oscillator is a tool that combines the ratings of several indicators to facilitate the search for profitable trades. I was inspired by the excellent indicator "Technical Ratings" from Team TradingView to create an alternative with a technically new approach. Therefore, it is not a modified copy of the original, but newly conceived and implemented.
The recommendations of the indicator are based on the calculated ratings from the different indicators included in it. The special thing here is that all settings for the individual indicators can be changed according to your own needs and displayed as a histogram and MA line. This provides an excellent visual control of your own settings. Alarms are also triggered.
Criteria for determining the rating
Relative Strength Index (RSI)
Buy - Crossover oversold level and indicator < oversold level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Relative Strength Index (RSI) Laguerre
Buy - Crossover Oversold Level and Indicator < Oversold Level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Noise free Relative Strength Index (RSX)
Buy - Crossover Oversold Level and Indicator < Oversold Level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Money Flow Index (MFI)
Buy - Crossover Oversold Level and Indicator < Oversold Level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Commodity Channel Index (CCI)
Buy - Crossover Oversold Level and Indicator < Oversold Level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Moving Average Convergence/Divergence (MACD)
Buy - values of the main line > values of the signal line and rising
Sell - values of the main line < values of the signal line and falling
Neutral - neither Buy nor Sell
Klinger
Buy - indicator >= 0 and rising
Sell - indicator < 0 and falling
Neutral - neither Buy nor Sell
Average Directional Index (ADX)
Buy - indicator > 20 and +DI line crosses over the -DI line and rising
Sell - indicator > 20 and +DI line crosses below the -DI line and falling
Neutral - neither Buy nor Sell
Awesome Oscillator
Buy - Crossover 0 and values are greater than 0, or exceed the zero line
Sell - Crossunder 0 and values are lower than 0, or fall below the zero line
Neutral - neither Buy nor Sell
Ultimate Oscillator
Buy - Crossover oversold level and indicator < oversold level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Williams Percent Range
Buy - Crossover Oversold Level and Indicator < Oversold Level and rising
Sell - Crossunder Oversold Level and Indicator >= Oversold Level and falling
Neutral - neither Buy nor Sell
Momentum
Buy - Crossover 0 and indicator levels rising
Sell - Crossunder 0 and indicator values falling
Neutral - neither Buy nor Sell
Total Ratings
The numerical value of the rating "Sell" is 0, "Neutral" is 0 and "Buy" is 1. The total rating is calculated as the average of the ratings of the individual indicators and are determined according to the following criteria:
MaxCount = 12 (depending on whether other oscillators are added).
CompareSellStrong = MaxCount * 0.3
CompareMid = MaxCount * 0.5
CompareBuyStrong = MaxCount * 0.7
value <= CompareSellStrong - Strong Sell
value < CompareMid and value > CompareSellStrong - Sell
value == 6 - Neutral
value > CompareMid and value < CompareBuyStrong - Buy
value >= CompareBuyStrong - Strong Buy
Understanding the results
The Multi Trend Oscillator is designed so that its values fluctuate between 0 and currently 12 (maximum number of integrated indicators). Its values are displayed as a histogram with green, red and gray bars. The bars are gray when the value of the indicator is at half of the number of indicators used, currently 12. Increasingly saturated green bars indicate increasing values above 6, and increasingly saturated red bars indicate increasingly decreasing values below 6.
The table at the end of the histogram shows details (can be activated in the settings) about the overall rating and the individual indicators. Its color is determined by the rating value: gray for neutral, green for buy or strong buy, red for sell or strong sell.
The following alarms are triggered:
Multi Trend Oscillator: Sell
Multi Trend Oscillator: Strong Sell
Multi Trend Oscillator: Buy
Multi Trend Oscillator: Strong Buy
Selected MACD Areas CompareThis is a simple tool to compare two selected MACD histogram area. The MACD histogram area is sometimes used to determine trend reversal or trend strength. One may have difficulty with this when the compared MACD areas are of different shape or similar in size. This indicator/tool allows user to select two time periods on the chart and get a precise compare result.
To use the indicator, place a regular MACD indicator on the chart which shows the histogram, then add this indicator and select the two areas of which you want to compare the size. Please make sure that the regular MACD indicator this one have the same source.
Scalping Trading System ALERT Crypto and StocksThis is the alert version of the strategy with the same name.
Indicators
SImple Moving Average
Exponential Moving Average
Keltner Channels
MACD Histogram
Stochastics
Rules for entry
long= Close of the candle bigger than both moving averages and close of the candle is between the top and bot levels from Keltner . At the same time the macd histogram is negative and stochastic is below 50.
short= Close of the candle smaller than both moving averages and close of the candle is between the top and bot levels from Keltner . At the same time the macd histogram is positive and stochastic is above 50.
Rules for exit
We exit when we meet an opposite reverse order.
This strategy has no risk management inside, so use it with caution !
