Ehlers DecyclerJohn F. Ehlers introuced Decycler in his book "Cycle Analytics for Traders", chapter 4.
The decycler is designed to remove the influence of shorter cycle fluctuations, resulting in an output that closely resembles a one-pole low-pass filter.
A standout feature of the decycler is its notably minimal lag. The most extended cycle elements experience a delay of less than five bars. When considering a frequency of 0.05 cycles per bar (equivalent to a 20-bar cycle period), the lag approximates 1.5 bars. Components with a higher frequency face even lesser delays. Consequently, any higher-frequency variations that pass the filter's attenuation align closely with the price fluctuations. This makes the decycler an optimal "immediate trend detector," giving a true depiction of the data's trend.
While the SuperSmoother filter can yield a comparably smoothed output, the decycler typically exhibits less lag when the two are juxtaposed. It's worth noting that the decycler operates as a one-pole filter, implying it doesn't have the best filtering capabilities. It's not advisable to use the decycler as a smoothing filter to eliminate aliasing disturbances. Instead, its application should focus on generating an immediate trend representation, especially when choosing a larger cutoff period. The broad cutoff period equips the decycler with the ability to reduce aliasing disturbances, given that it's significantly distant from the Nyquist frequency.
There are already several decycler indicators on Tradingview, but I like to structure the code and highlight the main components as functions rather than hiding them in the code. I hope this is useful for those who are starting to learn Pine Script.
Trendlineanalysis
Tetra Trendline Indicator 2.0This script is designed to help traders visualize and identify potential overbought and oversold conditions in a financial instrument's price chart using four customizable trendlines. It also provides the option to set alerts for these conditions. Users can adjust the input parameters to tailor the indicator's behavior to their trading preferences.
Input Parameters: The script allows users to configure various input parameters to customize the behavior of the indicator. These parameters include:
showTrendlineX: Boolean inputs to control whether to show each of the four trendlines (Trendline 1, Trendline 2, Trendline 3, and Trendline 4).
trendlineColorX: Color inputs to specify the color of each trendline.
trendlineWidthX: Numeric inputs to set the width of each trendline.
trendlineLengthX: Numeric inputs to determine the length of each trendline.
alertOnTrendlineXBreak: Boolean inputs to enable or disable alerts for each trendline when they are breached.
Trendline Calculations: The script calculates the coordinates for each of the four trendlines. It does this by identifying the starting and ending points of each trendline based on user-defined parameters and the highest or lowest price levels within a specified length.
Plotting Trendlines: The script uses the plot function to display the calculated trendlines on the price chart. It also fills the area between the trendlines to visually emphasize the region.
Alert Conditions: The script defines alert conditions for each trendline. Alerts are triggered when certain price conditions are met:
Trendline 1: An alert is triggered when the price crosses above the Trendline 1 (indicating overbought conditions).
Trendline 2: An alert is triggered when the price crosses below the Trendline 2 (indicating oversold conditions).
Trendline 3: Similar to Trendline 1, an alert is triggered when the price crosses above Trendline 3 (overbought).
Trendline 4: Similar to Trendline 2, an alert is triggered when the price crosses below Trendline 4 (oversold).
Traders Trend DashboardThe Traders Trend Dashboard (TTD) is a comprehensive trend analysis tool designed to assist traders in making informed trading decisions across various markets and timeframes. Unlike conventional trend-following scripts, TTD goes beyond simple trend detection by incorporating a unique combination of moving averages and a visual dashboard, providing traders with a clear and actionable overview of market trends. Here's how TTD stands out from the crowd:
Originality and Uniqueness:
TTD doesn't rely on just one moving average crossover to detect trends. Instead, it employs a dynamic approach by comparing two moving averages of distinct periods across multiple timeframes. This innovative methodology enhances trend detection accuracy and reduces false signals commonly associated with single moving average systems.
Market Applicability:
TTD is versatile and adaptable to various financial markets, including forex, stocks, cryptocurrencies, and commodities. Its flexibility ensures that traders can utilize it across different asset classes and capitalize on market opportunities.
Optimal Timeframe Utilization:
Unlike many trend indicators that work best on specific timeframes, TTD caters to traders with diverse trading preferences. It offers support for intraday trading (1m, 3m, 5m), short-term trading (15m, 30m, 1h), and swing trading (4h, D, W, M), making it suitable for a wide range of trading styles.
Underlying Conditions and Interpretation:
TTD is particularly effective during trending markets, where its multi-timeframe approach helps identify consistent trends across various time horizons. In ranging markets, TTD can indicate potential reversals or areas of uncertainty when moving averages converge or cross frequently.
How to Use TTD:
1. Timeframe Selection: Choose the relevant timeframes based on your trading style and preferences. Enable or disable timeframes in the settings to focus on the most relevant ones for your strategy.
2. Dashboard Interpretation: The TTD dashboard displays green (🟢) and red (🔴) symbols to indicate the relationship between two moving averages. A green symbol suggests that the shorter moving average is above the longer one, indicating a potential bullish trend. A red symbol suggests the opposite, indicating a potential bearish trend.
3. Confirmation and Strategy: Consider TTD signals as confirmation for your trading strategy. For instance, in an uptrend, look for long opportunities when the dashboard displays consistent green symbols. Conversely, in a downtrend, focus on short opportunities when red symbols dominate.
4. Risk Management: As with any indicator, use TTD in conjunction with proper risk management techniques. Avoid trading solely based on indicator signals; instead, integrate them into a comprehensive trading plan.
Conclusion:
The Traders Trend Dashboard (TTD) offers traders a powerful edge in trend analysis, combining innovation, versatility, and clarity. By understanding its unique methodology and integrating its signals with your trading strategy, you can make more informed trading decisions across various markets and timeframes. Elevate your trading with TTD and unlock a new level of trend analysis precision.
Linear On MACDUnlocking the Magic of Linear Regression in TradingView
In the ever-evolving world of financial markets, traders and investors seek effective tools to gauge price movements, make informed decisions, and achieve their financial goals. One such tool that has proven its worth over time is linear regression, a mathematical concept that has found its way into technical analysis and trading strategies. In this blog post, we will explore the magic behind linear regression, delve into its history, and understand how it's widely used as a technical indicator.
The Birth of Linear Regression: From Mathematics to Trading
Linear regression is a statistical method that aims to model the relationship between two variables by fitting a linear equation to observed data. The formula for a linear regression line is typically expressed as y = a + bx, where y is the dependent variable, x is the independent variable, a is the intercept, and b is the slope.
While the roots of linear regression trace back to the field of statistics, it didn't take long for traders and investors to recognize its potential in the financial world. By applying linear regression to historical price data, traders can identify trends, assess the relationship between variables, and even predict potential future price levels.
The Linear On MACD Strategy
Let's take a closer look at a powerful example of how linear regression is employed in a trading strategy right within TradingView. The "Linear On MACD" strategy harnesses the potential of linear regression in conjunction with the Moving Average Convergence Divergence (MACD) indicator. The goal of this strategy is to generate buy and sell signals based on the interactions between the predicted stock price and the MACD indicator.
Here's a breakdown of the strategy's components:
Calculation of Linear Regression: The strategy begins by calculating linear regression coefficients for the historical stock price based on volume. This helps predict potential future price levels.
Predicted Stock Price: The linear regression results are then used to plot the predicted stock price on the chart. This provides a visual representation of where the price could trend based on historical data.
Buy and Sell Signals: The strategy generates buy signals when certain conditions are met. These conditions include the predicted stock price being between the open and close prices, a rising MACD, and other factors that suggest a potential bullish trend. On the other hand, sell signals are generated based on MACD trends and predicted price levels.
Risk Management: The strategy also incorporates risk tolerance levels to determine entry and exit points. This ensures that traders take into account their risk appetite when making trading decisions.
Embracing the Magic of Linear Regression
As we explore the "Linear On MACD" strategy, we uncover the power of linear regression in aiding traders and investors. Linear regression, a mathematical marvel, seamlessly merges with technical analysis to provide insights into potential price movements. Its historical significance in statistics blends perfectly with the demands of modern financial markets.
Whether you're a seasoned trader or a curious investor, the Linear On MACD strategy exemplifies how a robust mathematical concept can be harnessed to make informed trading decisions. By embracing the magic of linear regression, you're tapping into a tool that continues to evolve alongside the financial world it empowers.
Disclaimer: The information provided in this blog post is for educational purposes only and does not constitute financial advice. Trading and investing carry risks, and it's important to conduct thorough research and consider seeking professional advice before making any trading decisions.
Trendline Pivots [QuantVue]Trendline Pivots
The Trend Line Pivot Indicator works by automatically drawing and recognizing downward trendlines originating from and connecting pivot highs or upward trendlines originating from and connecting pivot lows.
These trendlines serve as reference points of potential resistance and support within the market.
Once identified, the trend line will continue to be drawn and progress with price until one of two conditions is met: either the price closes(default setting) above or below the trend line, or the line reaches a user-defined maximum length.
If the price closes(default setting) above a down trend line or below an up trend line, an "x" is displayed, indicating the resistance or support has been broken. At the same time, the trend line transforms into a dashed format, enabling clear differentiation from active non-breached trend lines.
This indicator is fully customizable from line colors, pivot length, the number lines you wish to see on your chart and works on any time frame and any market.
Don't hesitate to reach out with any questions or concerns.
We hope you enjoy!
Cheers.
Donchian Channel Oscillator (DonOsc) Preface
DonOsc stands for Donchian Channel Oscillator. This channel envelopes all prices, so if you set the height of the channel to 100 percent, you can plot the prices as percent in between, creating this sub-pane oscillator. For clarity the example chart shows a Donchian channel in the main-pane with the same look-back as the DonOsc, this way you can see how both are related.
Price River
Not only the close is plotted, but also the high and the low of the bar. Thus you get a structure that can be associated with a river, streaming from left to right, in which the price moves between the left bank (i.e. the plotted highs) and the right bank (i.e. the plotted lows), which meanders between the high border (100%) and the low border (0%) of the oscillator. The surface of the price river is gray. The price line is blue when up and dark red when down. The river has also color patches dark red, light red, blue and aqua. Stochastic patches; up: aqua, down: light red
If you look at the price river, you may notice that the price line is closer to the left bank (highs) when moving up and to the right bank (lows) when moving down. Because this phenomenon is used in the stochastic indicator, I named these stochastic patches. These are depicted on the wide side for visibility, so the aqua patches are to the right of the price line and the light-red patches to the left.
Widening patches; up: blue, down: red
If you look at tops or bottoms in bar charts, you may notice that long bars (wide range) tend to be there. You may say that prices turn with a ‘range bang’. This causes a widening of the price river, depicted as a patch on the wide side.
Channel Features
High (76.4 %) and low (23.6 %) Fibonacci levels.
In the oscillator there is no need to calculate Fibonacci levels, we can just plot them. If the price is above 50% the low level is shown with a green color, when below the high level with a pink color. When the price river crosses a level a ‘near border’ highlighter will flash, lime near the high border and orange near the low one.
New high and new low markers.
A flaw in the oscillator is that is doesn’t show actual new lows and new highs in the Donchian Channel, because everything is made relative. This is ‘repaired’ by adding markers, dark red for new low depicted between the high fib and border, blue for new high depicted between low fib and border. Used are the same colors as in the widening patches, because new highs and lows also lead to widening of the actual Channel.
Uptrend and downtrend highlighters.
If in the actual Channel the bars run in the upper half, an uptrend is happening as long as these remain there, a downtrend when the bars remain in the lower half. In the oscillator a yellow highlighter flashes when the price is higher than 50%, a red highlighter below 50%.
Interpretation of the DonOsc
This sub-pane indicator provides a wealth of useful information about what is going on in the market. First of all you immediately see whether there is an up or down trend and whether these lead to new highs or lows. Second of all you can estimate the importance of price movements in the context of the look-back period. Thirdly the width of the price river reveals the emotions in the market. The higher the emotions run, the more risk is involved in a postilion in the charted instrument.
Settings of the DonOsc
Look-back settings.
By default the script sets the look-back, depending on the time frame. This overrules the standard manual setting. If you switch this off, the manual setting will work. A feed-back label can by shown which informs about the current setting.
Smoothing
This concerns the price river. Default is 2, if you increase this setting, the river will loose its touch with the channel borders. O.t.o.h. the river wil be wider and better visible. Maximum setting is 5.
Colors
The momentum colors set both the river widening patches and new high and low markers.
Take care, Eykpunter.
RS Stage AnalysisThis script trying to detect different lifecycle of stock / Stages.
There is mainly 4 stages of stocks.
1) stage 1 - Accumulation = color = aqua
2) stage 2 - Advancing = color = green
3) stage 3 - Distribution = color = yellow
4) stage 4 - Declining = color = red
At some point the condition i wrote wont detect any stage.
Another New Adaptive Moving Average [CC]The New Adaptive Moving Average was created by Scott Cong (Stocks and Commodities Mar 2023) and this is a companion indicator to my previous script . This indicator still works off of the same concept as before with effort vs results but this indicator takes a slightly different approach and instead defines results as the absolute difference between the closing price and a closing price x bars ago. As you can see in my chart example, this indicator works great to stay with the current trend and provides either a stop loss or take profit target depending on which direction you are going in. As always, I use darker colors to show stronger signals and lighter colors to show normal signals. Buy when the line turns green and sell when it turns red.
Let me know if there are any other indicator scripts you would like to see me publish!
A New Adaptive Moving Average [CC]The New Adaptive Moving Average was created by Scott Cong (Stocks and Commodities Mar 2023) and his idea was to focus on the Adaptive Moving Average created by Perry Kaufman and to try to improve it by introducing a concept of effort vs results. In this case the effort would be the total range of the underlying price action since each bar is essentially a war of the bulls vs the bears. The result would be the total range of the close so we are looking for the highest close and lowest close in that same time period. This gives us an alpha that we can use to plug into the Kaufman Adaptive Moving Average algorithm which gives us a brand new indicator that can hug the price just enough to allow us to ride the stock up or down. I have color coded it to be darker colors when it is a strong signal and lighter colors when it is a normal signal. Buy when the line turns green and sell when it turns red.
Let me know if there are any other indicators you would like to see me publish!
Market Meanness Index [CC]The Market Meanness Index was created by Johann Christian Lotter and I added some smoothing of my own, so feel free to try it without any smoothing to see the differences. This indicator relies on the mean reversion theory that all prices will eventually revert to the mean over a long period of time. Obviously there is more to the theory but the basic idea is if you plot a sma or other typical moving average, you will see the price moving up or below the long term moving average such as a 200 day sma but usually heads back to the average in the short term. This is a good statistical analysis used for volatility which is where this indicator comes in. Simply put, we calculate volatility based on how often a price is both above the median and above the previous price or vice versa.
A rising Market Meanness Index means that the market is becoming more volatile and that there is a high likelihood of a change in the underlying trend. A falling Market Meanness Index means that the current trend is dying and there is a high likelihood of a trend reversal. Typically I put general buy and sell signals in red or green but in this particular case, this indicator works best as a overall trend filter and you would want to place a trade when this indicator has a peak or valley. Let me know if you find a good overall buy and sell signal system of course.
I know I keep saying that I will get active again and post more indicators but life is very hectic for me. For those who have been following my updates, my twins were finally born a little over a month ago and as you can imagine, they keep me up at all hours of the day so it is hard to create new indicator scripts when I'm getting no sleep lol. I will do my best to start publishing the giant backlog of scripts I have created but in the meantime, please be patient with me. This indicator was a special request so let me know if you have any special requests of your own!
RSI based support resistance levelsThis indicator draws support line and resistance lines in the price chart.
How ?
For drawing the support/resistance line we need to first determine the demand and supply.
We are using too-familiar indicator RSI to determine when the script is oversold and overbought.
Now oversold (in RSI) is not a point, it’s a zone. The RSI indicator comes below 30, stays there and goes up above 30. Similarly for overbought.
Now if you carefully look at the oversold region – the lowest point of the oversold region is the place where the demand came (for surety) and push the indicator (and price) up.
Similarly: the highest point of overbought is the place where (for surety) the supply came and push the indicator (and price) down.
So that’ the supply / demand line (for surety).
In this indicator, based on the RSI we are just drawing support and resistance lines in the chat. That’s all.
What is unique ?
Trendline concept is not new. RSI is not new. RSI overbought/oversold is not new.
There are indicators exist to draw trendlines. Some of them works beautifully.
However, none of these, we are aware of, uses RSI to determine it. And, we believe, the most logical way to determine support/resistance is RSI.
Note: We are not responsible for any trading/investment decision you are taking out of the outcome of this indicator.
