Coinbase Premium ($) Absolute Dollar Amount # Coinbase Dollar Premium Indicator
## Description
The Coinbase Dollar Premium Indicator is a powerful tool for cryptocurrency traders and analysts, providing real-time insight into the price differences between major exchanges. This indicator calculates and visualizes the dollar amount premium or discount of Bitcoin on Coinbase compared to the average price on Binance and Kraken.
## Key Features
1. **Dollar Value**: Unlike percentage-based indicators, this tool shows the actual dollar amount difference, giving traders a clear understanding of the magnitude of price disparities.
2. **Multi-Exchange Comparison**: By averaging the prices from Binance and Kraken, the indicator provides a more robust baseline for comparison, reducing the impact of single-exchange anomalies.
3. **Clear Visual Representation**: The indicator uses a color-coded histogram for easy interpretation:
- Green bars indicate a premium on Coinbase (Coinbase price is higher)
- Red bars indicate a discount on Coinbase (Coinbase price is lower)
- The height of each bar represents the dollar amount of the premium or discount
4. **Zero Line Reference**: A horizontal line at zero helps quickly distinguish between premium and discount states.
## Use Cases
- **Arbitrage Opportunities**: Identify potential arbitrage opportunities between exchanges.
- **Market Sentiment**: Gauge institutional and retail investor sentiment, as Coinbase is often associated with US institutional activity.
- **Price Prediction**: Use divergences between exchanges as a potential indicator of short-term price movements.
- **Risk Management**: Understand the pricing landscape across major exchanges to make more informed trading decisions.
This indicator is valuable for both short-term traders looking for quick opportunities and long-term investors wanting to understand market dynamics. By providing a clear, dollar-based view of inter-exchange price differences, the Coinbase Dollar Premium Indicator offers unique insights into the cryptocurrency market's microstructure.
*Note: This indicator is for informational purposes only and should not be considered financial advice. Always conduct your own research and consider your risk tolerance before trading.*
價格震盪指標(PPO)
Non-Sinusoidal Multi-Layered Moving Average OscillatorThis indicator utilizes multiple moving averages (MAs) of different lengths their difference and its rate of change to provide a comprehensive view of both short-term and long-term market trends. The output signal is characterized by its non-sinusoidal nature, offering distinct advantages in trend analysis and market forecasting.
Combining the difference between two moving averages with the ROC allows to assess not only the direction and strength of the trend but also the momentum behind it. Transforming these signal in to non-sinusoidal output enhances its utility.
The indicator allows traders to select any one or more of seven moving average options. Larger timeframes (e.g., MA89/MA144) provide a broader identification of the overall trend, helping to understand the general market direction. Smaller timeframes (e.g., MA5/MA8) are more sensitive to price changes and can indicate better entry and exit points, aiding in the identification of retracements and pullbacks. By combining multiple timeframes, traders can get a comprehensive view of the market, enabling more precise and informed trading decisions.
Key Features:
Multiple Moving Averages:
The indicator calculates several exponential moving averages (EMAs) based on different lengths: MA5, MA8, MA13, MA21, MA34, MA55, MA89, and MA144.
These MAs are further smoothed using a secondary exponential moving average, with the smoothing length customizable by the user.
Percentage Differences:
The indicator computes the percentage differences between successive MAs (e.g., (MA5 - MA8) / MA8 * 100). These differences highlight the relative movement of prices over different periods, providing insights into market momentum and trend strength.
Short-term MA differences (e.g., MA5/MA8) are more sensitive to recent price changes, making them useful for detecting quick market movements.
Long-term MA differences (e.g., MA89/MA144) smooth out short-term fluctuations, helping to identify major trends.
Rate of Change (ROC):
The indicator applies the Rate of Change (ROC) to the percentage differences of the MAs. ROC measures the speed at which the percentage differences are changing over time, providing an additional layer of trend analysis.
ROC helps in understanding the acceleration or deceleration of market trends, indicating the strength and potential reversals.
Transformations:
The percentage differences undergo a series of mathematical transformations (either inverse hyperbolic sine transformation or inverse fisher transformation) to refine the signal and enhance its interpretability. These transformations include adjustments to stabilize the values and highlight significant movements.
checkbox allows users to select which mathematical transformations to use.
Non-Sinusoidal Nature:
The output signal of this indicator is non-sinusoidal, characterized by abrupt changes and distinct patterns rather than smooth, wave-like oscillations.
The non-sinusoidal signal provides clearer demarcations of trend changes and is more responsive to sudden market shifts.
This nature reduces the lag typically associated with sinusoidal indicators, allowing for more timely and accurate trading decisions.
Customizable Options:
Users can select which MA pairs to include in the analysis using checkboxes. This flexibility allows the indicator to adapt to different trading strategies, whether focused on short-term movements or long-term trends.
Visual Representation:
The indicator plots the transformed values on a separate panel, making it easy for traders to visualize the trends and potential entry or exit points.
Usage Scenarios:
Short-Term Trading: By focusing on shorter MAs (e.g., MA5/MA8), traders can capture quick market movements and identify short-term trends.
Long-Term Analysis: Utilizing longer MAs (e.g., MA89/MA144) helps in identifying major market trends.
Combination of MAs: The ability to mix different MA lengths provides a balanced view, helping traders make decisions based on both immediate price actions and overall market direction.
Practical Benefits:
Early Signal Detection: The sensitivity of short-term MAs provides early signals for potential trend changes, assisting traders in timely decision-making.
Trend Confirmation: Long-term MAs offer stable trend confirmation, reducing the likelihood of false signals in volatile markets.
Noise Reduction: The mathematical transformations and ROC applied to the percentage differences help in filtering out market noise, focusing on meaningful price movements.
Improved Responsiveness: The non-sinusoidal nature of the signal allows the indicator to react more quickly to market changes, providing more accurate and timely trading signals.
Clearer Trend Demarcations: Non-sinusoidal signals make it easier to identify distinct phases of market trends, aiding in better interpretation and decision-making.
Exhaustion Table [SpiritualHealer117]A simple indicator in a table format, is effective for determining when an individual stock or cryptocurrency is oversold or overbought.
Using the indicator
In the column "2σ" , up arrows indicate that the asset is very overbought , down arrows indicate that an asset is very oversold , and an equals sign indicates that the indicator is neutral.
In the column "σ" , up arrows indicate that the asset is overbought , down arrows indicate that an asset is oversold , and an equals sign indicates that the indicator is neutral.
What indicator is
The indicator shows the exhaustion (percentage gap between the closing price and a moving average) at 5 given lengths, 15, 30, 50, 100, and 300. It compares that to two thresholds for exhaustion: one standard deviation out and one two standard deviations out.
BTC Pair Change %This script makes it easier to quickly check how the BTC pair of the current symbol is performing on any pair.
It adds a " change percentage widge t" (of the BTC pair ) to the top right of the chart.
(Refer to the image for an example.)
The change percentage calculation is performed as described here:
www.tradingview.com
To match the "Chg%" that appears on TradingView watchlists, a 24H (1440min) timeframe is used, as described here:
money.stackexchange.com
In short, this script:
Searches for the BTC pair of the current symbol
Calculates the change % using the above described logic (links)
Adds a " change percentage widget " (of the BTC pair) to the top right of the chart
Allows for using 24H timeframe or the current timeframe (enable " Use current timeframe " under the script options)
BTC Indicator By Megalodon TradingThis indicator is designed help you see the potential reversal zones and it helps you accumulate for the long run.
This combines price data on any chart. The chart isolates between 0 and -100. Below -80 is a buy, above -20 is a sell location.
In these locations, try to Slowly Buy and Slowly Sell (accumulate...)
Story Of This Indicator
~I was always obsessed with Fibonacci and used Fibonacci all the time. Thus, i wanted to make a tool to see buying locations and selling locations.
Instead of drawing fibonacci's and manually interpreting buy/sell locations, i wanted algorithms to do the job for me. So, i created this algorithm and many more like it.
If you think i did a good job and want to do further work with me, feel free to contact.
I have a ton of other tools that can change everything for your trading/investing.
Best wishes
~Megalodon
T3 PPO [Loxx]T3 PPO is a percentage price oscillator indicator using T3 moving average. This indicator is used to spot reversals. Dark red is upward price exhaustion, dark green is downward price exhaustion.
What is Percentage Price Oscillator (PPO)?
The percentage price oscillator (PPO) is a technical momentum indicator that shows the relationship between two moving averages in percentage terms. The moving averages are a 26-period and 12-period exponential moving average (EMA).
The PPO is used to compare asset performance and volatility, spot divergence that could lead to price reversals, generate trade signals, and help confirm trend direction.
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.
PPO w/ Discontinued Signal Lines [Loxx]PPO w/ Discontinued Signal Lines is a Percentage Price Oscillator with some upgrades. This indicator has 33 source types and 35+ moving average types as well as Discontinued Signal Lines and divergences. These additions reduce noise and increase hit rate.
What is the Price Percentage Oscillator?
The percentage price oscillator (PPO) is a technical momentum indicator that shows the relationship between two moving averages in percentage terms. The moving averages are a 26-period and 12-period exponential moving average (EMA).
The PPO is used to compare asset performance and volatility, spot divergence that could lead to price reversals, generate trade signals, and help confirm trend direction.
Included:
Bar coloring
3 signal variations w/ alerts
Divergences w/ alerts
Loxx's Expanded Source Types
Loxx's Moving Averages
MACD-VWhat is it?
The MACD-V indicator is the normal version of the MACD (Moving Average Convergence Divergence) indicator but normalized for volatility. It is normalized for volatility in order to compare momentum values across time and across tickers which the normal MACD indicator fails to do.
Formula
The formula for the MACD-V is as follows
MACD Line = [ / ATR(26)] * 100
Signal Line = EMA(9,MACD)
Histogram = MACD Line - Signal Line
How to Use
The MACD-V indicator is used to analyze normalized trends. If the MACD line is above 150, it is considered overbought. If the MACD line is below -150, it is considered oversold. Crossovers of the MACD line and the signal line are considered to be points of trend changes as well.
Features
Customizable Overbought/Oversold boundaries
Customizable colors
Credits
All credit for the idea behind this indicator goes to Alex Spiroglou CMT. His academic paper on the indicator can be found here .
In addition to Alex's idea for the paper, one TradingView user, Mik3Christ3ns3n has created a partial version of it which can be found here .
Infiten's Price Percentage Oscillator Channel (PPOC Indicator)What is the script used for?
Infiten's Price Percentage Oscillator (PPOC Indicator) can be used as a contrarian indicator for volatile stocks and futures to indicate reversals, areas of support and resistance. For longer term trading, if the Short SMA or prices go above the High PPO Threshold line, it is a sign that the asset is overbought, whereas prices or the Short SMA going below the Low PPO Threshold line indicates that the asset is oversold.
What lines can be plotted?
Low PPO Thresh - Calculated as -PPO Threshold * Short MA + Long MA : Gives the price below which the PPO hits your lower threshold
High PPO Thresh - Calculated as PPO Threshold * Short MA + Long MA : Gives the price above which the PPO hits your upper threshold
MA PPO : Plots candles with the Low PPO Thresh as the low, High PPO Thresh as the high, Short MA as the open, and Long MA as the close.
Short SMA : plots the short simple moving average
Long SMA : plots the long simple moving average
Customizable Values :
Short MA Length : the number of bars back used to calculate the short moving average for a PPO
Long MA Length : the number of bars back used to calculate the long moving average for a PPO
PPO Threshold : the percent difference from the moving average expressed as a decimal (0.5 = 50%)
Recommendations:
Longer timeframes like 300 days are best with larger PPO Thresholds, I recommend using a PPO Threshold of 0.5 or higher. For shorter timeframes like 14 days I recommend setting smaller PPO Thresholds, like 0.3 or lower. I find that these values typically capture the most extremes in price action.
Infiten Slope StrategyThis model is an index fund trading model, which uses moving averages and price percentage oscillators to minimize downside exposure.
MicroStrategy MetricsA script showing all the key MSTR metrics. I will update the script every time degen Saylor sells some more office furniture to buy BTC.
All based around valuing MSTR, aside from its BTC holdings. I.e. the true market cap = enterprise value - BTC holdings. Hence, you're left with the value of the software business + any premium/discount decided by investors.
From this we can derive:
- BTC Holdings % of enterprise value
- Correlation to BTC (in this case we use CME futures...may change this)
- Equivalent Share Price (true market cap divided by shares outstanding)
- P/E Ratio (equivalent share price divided by quarterly EPS estimates x 4)
- Price to FCF Ratio (true market cap divided by FCF (ttm))
- Price to Revenue (^ but with total revenue (ttm))
Bitcoin Movement vs. Coin's Movement MTFThis script tracks the percent change of Bitcoin vs. the percent change of the coin on the chart. Crypto markets are usually affected greatly by Bitcoin swings so being able to see if the given coin is trending above or below Bitcoin is useful market data. All choices made with this script are your own! Thanks.
Improved Percent Price Oscillator w/ Colored Candles[C2Trends]The Percent Price Oscillator(PPO) is a momentum oscillator that measures the difference between two moving averages as a percentage of the larger moving average. Similar to the Moving Average Convergence/Divergence(MACD), the PPO is comprised of a signal line, a histogram and a centerline. Signals are generated with signal line crossovers, centerline crossovers, and divergences. Because these signals are no different than those associated with MACD, this indicator can be read exactly as the MACD is read. The main differences between the PPO and MACD are: 1) PPO readings are not subject to the price level of the security. 2) PPO readings for different securities can be compared, even when there are large differences in the price. MACD readings for different securities cannot be compared when there are large differences in price.
PPO Calculations:
Percentage Price Oscillator(PPO): {(12-day EMA - 26-day EMA )/26-day EMA} x 100
Signal Line: 9-day EMA of PPO
PPO Histogram: PPO - Signal Line
iPPO includes everything from standard PPO plus:
1)Plots for PPO/Signal line crosses.
2)Plots for PPO/0 level crosses.
3)PPO/Signal line gap color fill.
4)PPO/0 level gap color fill.
4)Background fill for PPO/Signal line crosses.
5)Background fill for PPO/0 level crosses.
6)Price candles colored based on PPO indicator readings.
7)All plots, lines and fill colors can be turned on/off individually from the 'Input' tab of the iPPO indicator settings menu.
Indicator Notes:
1) When the green PPO line is above the 0 level, intermediate to long-term price momentum can be considered bullish(begins w/yellow cross, green background).
2) When the green PPO line is below the 0 level, intermeidate to long-term price momentum can be considered bearish(begins w/red cross, purple background).
3) Green PPO line above purple Signal line + both lines rising + both lines above 0 level = bullish short-term price momentum(begins w/green dot above 0 level, green highlight).
4) Green PPO line below purple Signal line + both lines falling + both lines above 0 level = loss of short-term bullish price momentum(begins w/purple dot above 0 level, purple highlight).
5) Green PPO line below purple Signal line + both lines falling + both lines below 0 level = bearish short-term price momentum(begins w/purple dot below 0 level, purple highlight).
6) Green PPO line above purple Signal line + both lines rising + both lines below 0 level = loss of short-term bearish price momentum(begins w/green dot below 0 level, green highlight).
7) Price candles are colored lime when the PPO line is above the Signal line and both lines are above the 0 level.
8) Price candles are colored green when the PPO line is below the Signal line and both lines are above the 0 level.
9) Price candles are colored fuschia when the PPO line is below the Signal line and both lines are below the 0 level.
10) Price candles are colored purple when the PPO line is above the Signal line and both lines are below the 0 level.
11) Price candles are colored gray when the green PPO line is within a set % of the 0 level. This value can be set manually in the indicator settings. The default value is 0.25% to ensure
smooth candle color transition between timeframes, charts, sectors and markets. Adjust value up or down if gray candles are absent or too abundant. Gray candles should mostly only appear
during periods of price consolidation(flat/sideways price movement), or just before a significant move up or down in price.
Aggresive Scalper/Swing Crypto StrategyThis is a simple yet very efficient scalper long strategy adapted for low timeframes for crypto. Can also be used with bigger timeframes as a swinger.
Its main components are:
Price oscillator swing
Vortex
Risk management for TP/SL
Rules for entry
We calculate the difference between the oscillator from the lowest low and the highest high. If the difference is positive, its a long potential. If its negative we exit from the long trade.
At the same time we check that the we have a crossover between the VIP vortex with the VIM vortex part.
Lastly we check that the current candle is bigger the second previous high.
Rules for exit
If we reach the take profit or the stop loss.
If we have a negative difference betwee LL and HH and VIP vortex crossunder with VIM vortex .
In this example I aimed for a 1:10 risk reward ratio, meaing that for every dollar lost, we will gain 10 when we win. Thus having a 10% minimum win rate will give us a profit over many trades.
If you have any questions, let me know !
Buy/Sell RatingIdentifies prices above and below input percentile thresholds over the input length of time. Use to identify buy/sell opportunities relative to recent pricing. Also provides percent of price distance from moving average over the same length.
Dynamic Price SwingFinally, a price channel oscillator that works.
I programmed three flavors into this.
The first flavor uses the Fast and Slow EMA to check for the trend to ensure you don't trade in the wrong direction simply because the price crosses the previous highest high or lowest low (based on lookback bars).
The second flavor uses a seven point average of the Fibonacci bands to create an upper and lower central channel for quick trades (like DOGE).
The third flavor uses the golden Fibonacci ratio of 1.618 and trades when the price moves above or below this band.
Difference in price changeCompares price change between current symbol and other one (eg. BTC vs S&P500). It calculates price change on each bar (from high to low or from open to close) and compares with price change of equivalent bar from the other source.
Example
Current symbol
open = 10 USD
close = 7 USD
change = -3 USD
% change = -30%
Second symbol
open = 3 USD
close = 4 USD
change = +1 USD
% change = +33%
Performance of price change = (-30) - (+30) = -63 // It means that current source has weaker performance right now
Detrended Rhythm Oscillator (DRO)How to detect the current "market beat" or market cycle?
A common way to capture the current dominant cycle length is to detrend the price and look for common rhythms in the detrended series. A common approach is to use a Detrended Price Oscillator (DPO). This is done in order to identify and isolate short-term cycles.
A basic DPO description can be found here:
www.tradingview.com
Improvements to the standard DPO
The main purpose of the standard DPO is to analyze historical data in order to observe cycle's in a market's movement. DPO can give the technical analyst a better sense of a cycle's typical high/low range as well as its duration. However, you need to manually try to "see" tops and bottoms on the detrended price and measure manually the distance from low-low or high-high in order to derive a possible cycle length.
Therefore, I added the following improvements:
1) Using a DPO to detrend the price
2) Indicate the turns of the detrended price with a ZigZag lines to better see the tops/bottoms
3) Detrend the ZigZag to remove price amplitude between turns to even better see the cyclic turns ("rhythm")
4) Measure the distance from last detrended zigzag pivot (high-high / low-low) and plot the distance in bars above/below the turn
Now, you can clearly see the rhythm of the dataset indicated by the Detrended Rhythm Oscillator including the exact length between the turns. This makes the procedure to "spot" turns and "measure" distance more simple for the trader.
How to use this information
The purpose is to check if there is a common rhythm or beat in the underlying dataset. To check that, look for recurring pattern in the numbers. E.g. if you often see the same measured distance, you can conclude that there is a major dominant cycle in this market. Also watch for harmonic relations between the numbers. So in the example above you see the highlighted cluster of detected length of around 40,80 and 120. There three numbers all have a harmonic relation to 40.
Once you have this cyclic information, you can use this number to optimize or tune technical indicators based on the current dominant cycle length. E.g. set the length parameter of a technical indicator to the detected harmonic length with the DRO indicator.
Example Use-Case
You can use this information to set the input for the following free public open-source script:
Disclaimer
This is not meant to be a technical indicator on its own and the derived cyclic length should not be used to forecast the next turn per se. The indicator should give you an indication of the current market beat or dominant beats which can be use to further optimize other oscillator or trading related settings.
Options & settings
The indicator allows to plot different versions. It allows to plot the original DPO, the DRO with ZigZag lines, the DRO with detrended ZigZag lines and length labels on/off. You can turn on or off these version in the indicator settings. So you can tweak it visually to your own needs.
Momentum Trader + Trinity LinesThis is an updated version of the 'Momentum Trader' by user ProfitProgrammers + the 'Bollinger Bands %b & RSI & Stochastic Smoothed Indicator & Alert' by the user Zamboniman.
Links to those original scripts are below:
script/7S49kLWh-Bollinger-Bands-b-RSI-Stochastic-Smoothed-Indicator-Alert/
script/OMULR9es-Momentum-Trader/
The only real updates are so that it works on Version 4 of pinescript and some color and visual updates that makes these two scripts work well together. This must be used on normal candles and not HA or any other types or you can get misleading entry / exit points.
Here is some info about this indicator and the moving parts within it:
Chande Momentum Oscillator:
-Measures trend strength, with higher absolute values meaning greater strength.
-Also tracks divergence. When price increases, but is not accompanied by an increase in Chande Momentum Oscillator values, it signifies bearish divergence and a reversal is likely to follow.
-Shown as the teal and pink histogram.
Percentage Price Oscillator:
-Similar to the MACD , except that it expresses the difference between the two moving averages in terms of a percentage. This makes it a little easier to visualize.
-PPO values greater than zero indicate an uptrend, as that means the fast EMA is greater than the slow (and vice versa).
Trinity Lines:
-These 3 colored lines at the top are RSI + normalized Bollinger Band &b + normalized smoothed Stochastic.
-A confirmation entry for a long is when the lines are in the order from top to bottom of Green Yellow Red.
Entry and Exit Conditions:
Enter When:
1) Chande Momentum crosses over zero from negative to positive territory. AND
2) Chande Momentum is rising(positive slope). AND
3) Trinity lines are Green, Yellow, Red (Top to bottom)
Exit When:
1) Chande Momentum is greater than the upper line. AND
2) PPO has a negative slope. AND
3) Trinity lines are Red, Yellow, Green (Top to bottom)
Percentage Oscillator Swing highest high and lowest lowThis is a simple but efficient indicator.
Its made from an oscillator, which is calculated from the current close price with the highest high and the lowest low over a period of time.
This way we can see how much prices has changed over a X ammount of candles ( in positive or negative ) .
US Inflation Rate [nb]This is the United States inflation rate, based on the total Consumer Price Index published by the U.S. Bureau of Labor Statistics.
Option to toggle:
A line to display the inflation rate in December. It does not change until the next December.
What the color change to red is indicative of:
According to the Federal Open Market Committee (FOMC) regarding inflation rate, "2% is a bae number to be around". This does not imply a strict 2% inflation for success and allows room for federal rate cuts should they be needed.
Although FOMC declared 2% to be "bae" in 2012, James Bullard, of federal banking fame, claims that started to become the norm in 1995. Therefore the inflation rate line will only turn red 1995 onwards, and serves as a friendly reminder that inflation has been over at or over 2% for more than one month.
Sources:
www.bls.gov
www.federalreserve.gov
www.stlouisfed.org
