MVRV Z-ScoreThe MVRV ratio was created by Murad Mahmudov & David Puell. It simply compares Market Cap to Realised Cap, presenting a ratio (MVRV = Market Cap / Realised Cap). The MVRV Z-Score is a later version, refining the metric by normalising the peaks and troughs of the data.
Cycle
Extended Parallel ChannelsThis indicator provides an enhanced version of the popular Parallel Channel tool by allowing channel boundaries to be extended above and below the primary channel. It can also serve as a general tool for drawing parallel lines and grid lines to aid technical analysis.
🟠 Application
There are two primary ways extended channels can provide valuable insights:
🔵 Support and Resistance Levels
When prices break out of a channel, they often encounter strong resistance at approximately the 100% extension point. Breakout traders can utilize the extended channel boundary to place take-profit orders. Meanwhile, reversal traders can look for entry opportunities at this level.
🔵 Grid / Martingale Trading
Grid Trading and Martingale Trading strategies rely heavily on grid lines. This indicator streamlines that process by enabling traders to effortlessly plot grid lines across the chart.
🟠 Instructions
Upon adding the indicator, the user will be prompted to set the channel boundaries by placing three anchor points on the chart. The first two anchors determine one boundary line, while the third anchor determine the other boundary line.
Once the three anchors are positioned, the indicator automatically plots the resulting channel as well as the extended lines. The anchor points are highlighted as movable blue circles, allowing the user to dynamically adjust the channel formation by dragging the anchors to new locations as needed.
Market Time Cycle (Expo)█ Time Cycles Overview
Time cycles are a fascinating and powerful concept in the world of trading and investing. They are all about understanding and predicting the timing of market moves based on the premise that market events and price movements are not random, but instead occur in repeatable, cyclical patterns.
The Concept of Time Cycles: The foundation of time cycles lies in the belief that historical market patterns tend to repeat themselves over specific periods. These periods or cycles could be influenced by a myriad of factors like economic data releases, earnings reports, geopolitical events, or even natural human behavior. For example, some traders observe increased market activity around the start and end of a trading day, which is a form of intraday time cycle.
Understanding time cycles can provide traders with a roadmap, helping them anticipate potential trend shifts and make more informed decisions about when to buy or sell.
█ Indicator Overview
The Market Time Cycle (Expo) is designed to help traders track and analyze market cycles and generate signals for potential trading opportunities. It uses mathematical techniques to analyze market cycles and detect possible turning points. It does this by projecting the estimated cycle timeline and providing visual indications of cyclical phases through the use of color-coded lines and sine wave cycles.
Time cycles offer a compelling way to forecast market trends and time your trades better. By adding time cycles to your trading toolbox, you could potentially gain a new perspective on market movements and refine your trading strategy further. The indicator generates trading signals based on the sine wave's behavior. When the sine wave crosses certain thresholds, the indicator generates a signal suggesting a potential trading opportunity based on cycle behavior.
█ How to use
This indicator can be a valuable tool to help traders understand and predict market trends and time their trades more accurately. By visualizing the cyclic nature of markets, traders can better anticipate potential turning points and adjust their trading strategies accordingly. It helps traders to spot ideal entry and exit points based on the cyclical nature of financial markets.
█ Settings
You can customize the number of bars (NumbOfBars) that are taken into consideration for the cycle. Including a higher number of bars will provide more data, which can be helpful for analyzing long-term trends.
-----------------
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!
Fierytrading: Volatility DepthDear Tradingview community,
I'd like to share one of my staple indicators with you. The volatility depth indicator calculates the volatility over a 7-day period and plots it on your chart.
This indicator only works for the DAILY chart on BTC/USD.
Colors
I've color coded the indicator as follows:
- Red: Extreme Volatility
- Orange: High Volatility
- Yellow: Normal Volatility
- Green: Low Volatility
Red: extreme changes in price. Often during local tops and bottoms.
Orange: higher than average moves in price. Often before or after a "red" period. Often seen in the middle of bear or bull markets.
Yellow: normal price action. Often seen during early stage bull-markets and late stage bear-markets.
Green: very low price movement. Often during times of indecision. Once this indicator becomes green, you can expect a big move in either direction. Low volatility is always followed by high volatility.
In a long-term uptrend, a green period often signals a bullish break out. In a long-term downtrend it often signals a bearish break out.
How to use
Save the indicator and apply it to your chart. You can change the length in the settings, but it's optimized for 7 days, so no need to change it.
I've build in alerts for all 4 different volatility periods. In most cases, the low volatility alert is enough.
Good luck!
Market Cycle IndicatorThe Market Cycle Indicator is a tool that integrates the elements of RSI, Stochastic RSI, and Donchian Channels. It is designed to detect market cycles, enabling traders to enter and exit the market at the most opportune times.
This indicator provides a unique perspective on the market, combining multiple strategies into one unified and weighted approach. By factoring in the inputs from each of these popular technical analysis methods, it offers a more holistic view of the market trends and cycles.
Parameter Details:
Donchian Channels (DCO):
- donchianPeriod: Sets the period for the Donchian Channel calculation. Default is set to 14.
- donchianSmoothing: Sets the smoothing factor for the Donchian Channel calculation. Default is set to 3.
- donchianPrice: Selects the price type to be used in the Donchian Channel calculation. Default is set to the closing price.
Relative Strength Index (RSI):
- rsiPeriod: Sets the period for the RSI calculation. Default is set to 14.
- rsiSmoothing: Sets the smoothing factor for the RSI calculation. Default is set to 3.
- rsiPrice: Selects the price type to be used in the RSI calculation. Default is set to the closing price.
Stochastic RSI (StochRSI):
- srsiPeriod: Sets the period for the Stochastic RSI calculation. Default is set to 20.
- srsiSmoothing: Sets the smoothing factor for the Stochastic RSI calculation. Default is set to 3.
- srsiK: Sets the period for the %K line in the Stochastic RSI calculation. Default is set to 5.
- srsiD: Sets the period for the %D line in the Stochastic RSI calculation. Default is set to 5.
- srsiPrice: Selects the price type to be used in the Stochastic RSI calculation. Default is set to the closing price.
Weights:
- rsiWeight: Sets the weight for the RSI in the final aggregate calculation. Default is set to 1.
- srsiWeight: Sets the weight for the Stochastic RSI in the final aggregate calculation. Default is set to 1.
- dcoWeight: Sets the weight for the Donchian Channel in the final aggregate calculation. Default is set to 1.
Limits:
- limitHigh: Sets the upper limit for the indicator. Default is set to 80.
- limitLow: Sets the lower limit for the indicator. Default is set to 20.
By customizing these parameters, users can tweak the indicator to align with their own trading strategies and risk tolerance levels. Whether you're a novice or an experienced trader, the Comprehensive Market Cycle Indicator provides valuable insights into the market's behavior.
Uses library HelperTA
Benner-Fibonacci Reversal Points [CC]This is an original script based on a very old idea called the Benner Theory from the Civil War times. Benner discovered a pattern in pig iron prices (no clue what those are), and this turned out to be a parallel idea to indicators based on Fibonacci numbers. Because a year is 365 days (nearly 377, which is a Fibonacci number), made up of 52 weeks (nearly 55, which is another Fibonacci number), or 12 months (nearly 13, which is another Fibonacci number), Benner theorized that he could find both past and future turning points in the market by using a pattern he found. He discovered that peaks in prices seemed to follow a pattern of 8-9-10, meaning that after a recent peak, it would be 8 bars until the next peak, 9 bars until after that peak for the next, and 10 bars until the following peak. For past peaks, he would just need to reverse this pattern, and so the previous peak would be 10 bars before the most current peak, 9 bars before that peak, and 8 bars before the previous one, and these patterns seemed to repeat. For troughs, he found a pattern of 16,18,20 which follows the same logic, and this idea also seemed to work on long-term peaks and troughs as well.
This is my version of the Benner theory and the major difference between my version and his is that he would manually select a year or date and either work backwards or forwards from that point. I chose to go with an adaptive version that will automatically detect those points and plot those past and future points. I have included several options such as allowing the algorithm to be calculated in reverse which seems to work well for Crypto for some reason. I also have both short and long term options to only show one or both if you choose and of course the option to enable repainting or leave it disabled.
Big thanks to @HeWhoMustNotBeNamed and @RicardoSantos for helping me fix some bugs in my code and for @kerpiciwuasile for suggesting this idea in the first place.
Simple Moving Average Slope [AstrideUnicorn]The Simple Moving Average Slope indicator (SMAS) is a technical analysis tool designed to help traders detect the direction and strength of the current trend in the price of an asset. It is also a great tool for identifying sideways markets. The indicator plots the slope of a simple moving average (SMA) of the closing prices over a specified time period. The slope is normalized by dividing it by the standard deviation of the slope over a longer time period.
HOW TO USE
Traders can use the Simple Moving Average Slope indicator in various ways. One common way is to look for bullish or bearish signals. A bullish signal occurs when the normalized slope rises above a predetermined threshold, resulting in the indicator turning green, indicating an upward trend in the market. Conversely, a bearish signal is generated when the normalized slope falls below the negative value of the threshold, causing the indicator to turn red, signaling a downtrend in the market. When the normalized slope falls between the positive and negative threshold values, a neutral signal is generated, indicating that the market is moving sideways. This can help traders avoid false trend signals from other indicators and strategies that may occur when the market is in a sideways regime. Additionally, traders can use the Simple Moving Average Slope indicator in conjunction with other technical indicators to confirm the trend direction.
SETTINGS
Window - specifies the number of bars used to calculate the SMA slope. The default value is 20.
Threshold - specifies the threshold value used to generate the bullish and bearish signals. The default value is 0.6. Traders can adjust these settings based on their trading strategy and the asset being analyzed.
Fed Projected Interest RatesThis script shows you the current interest rates by the FED (see ZQ symbol nearest expiration)
and the next expirations (see ZQ further expiration dates).
It is important to keep your expiration and descriptions up to date, to do that to the indicator inputs and change as you please.
AstroLibLibrary "AstroLib", or Astro Library, is a collection of public Pinescript functions & calculations for use in astrology & astronomy indicators. Unless noted otherwise, this library was written jointly by @badsector666 and @BarefootJoey.
Library "AstroLib"
t_(txt)
Parameters:
txt (string)
JDNv2(t, withFraction)
Parameters:
t (float)
withFraction (bool)
J2K(t)
Parameters:
t (float)
J2KtoUnix(TimeInJDN)
Parameters:
TimeInJDN (float)
atan2(y, x)
Parameters:
y (float)
x (float)
DegSin(x)
Parameters:
x (float)
DegCos(x)
Parameters:
x (float)
DegTan(x)
Parameters:
x (float)
DegArcsin(x)
Parameters:
x (float)
DegArccos(x)
Parameters:
x (float)
DegArctan(x)
Parameters:
x (float)
DegAtan2(y, x)
Parameters:
y (float)
x (float)
range2pi(x)
Parameters:
x (float)
range360(x)
Parameters:
x (float)
gst(days)
Parameters:
days (float)
DegDecimal(Degrees, Minutes, Seconds)
Parameters:
Degrees (float)
Minutes (float)
Seconds (float)
Rectangular(R, theta, phi, Index)
Parameters:
R (float)
theta (float)
phi (float)
Index (float)
rLength(x, y, z)
Parameters:
x (float)
y (float)
z (float)
spherical(x, y, z, Index)
Parameters:
x (float)
y (float)
z (float)
Index (float)
obliquity(d)
Parameters:
d (float)
requatorial(x, y, z, d, Index)
Parameters:
x (float)
y (float)
z (float)
d (float)
Index (float)
recliptic(x, y, z, d, Index)
Parameters:
x (float)
y (float)
z (float)
d (float)
Index (float)
sequatorial(R, theta, phi, d, Index)
Parameters:
R (float)
theta (float)
phi (float)
d (float)
Index (float)
secliptic(R, theta, phi, d, Index)
Parameters:
R (float)
theta (float)
phi (float)
d (float)
Index (float)
precess(d1, d2, DEC, RA, Index, ddec, dra)
Parameters:
d1 (float)
d2 (float)
DEC (float)
RA (float)
Index (float)
ddec (float)
dra (float)
riset(J2000, DEC, RA, GLat, GLong, Index)
Parameters:
J2000 (float)
DEC (float)
RA (float)
GLat (float)
GLong (float)
Index (float)
ssun(d, Index)
Parameters:
d (float)
Index (float)
rsun(d, Index)
Parameters:
d (float)
Index (float)
sun(d, Index)
Parameters:
d (float)
Index (float)
SunLongitude(d, Index)
Parameters:
d (float)
Index (float)
Sunrise(J2000, GLat, GLong, Index, altitudex)
Parameters:
J2000 (float)
GLat (float)
GLong (float)
Index (float)
altitudex (float)
smoon(dx, Index)
Parameters:
dx (float)
Index (float)
rmoon(d, Index)
Parameters:
d (float)
Index (float)
tmoon(d, GLat, GLong, Index)
Parameters:
d (float)
GLat (float)
GLong (float)
Index (float)
moon(d, Index)
Parameters:
d (float)
Index (float)
Element(d, pnum)
Parameters:
d (float)
pnum (int)
kepler(m, ecc, eps)
Parameters:
m (float)
ecc (float)
eps (float)
rplanet(d, pnumber, Index)
Parameters:
d (float)
pnumber (int)
Index (float)
planet(d, pnumber, Index)
Parameters:
d (float)
pnumber (int)
Index (float)
altaz(d, DEC, RA, GLat, GLong, Index)
Parameters:
d (float)
DEC (float)
RA (float)
GLat (float)
GLong (float)
Index (float)
prise(d, P, GLat, GLong, Index)
Parameters:
d (float)
P (int)
GLat (float)
GLong (float)
Index (float)
MoonSize(d)
Parameters:
d (float)
Refraction(Temperature_C, Atmospheric_Pressure_mBar, Altitude_Deg)
Parameters:
Temperature_C (float)
Atmospheric_Pressure_mBar (float)
Altitude_Deg (float)
MoonRise(d, Longitude, Latitude, Index)
Parameters:
d (float)
Longitude (float)
Latitude (float)
Index (float)
f_to_sec(dec)
Parameters:
dec (float)
f_to_time(sec)
Parameters:
sec (float)
deg_to_time(deg)
Parameters:
deg (float)
toDMS(coordinate)
Parameters:
coordinate (float)
convertDMS(lat, lng)
Parameters:
lat (float)
lng (float)
convlatdec(deg)
Parameters:
deg (float)
PlanetName(pnum)
Parameters:
pnum (int)
PlanetNameV(pnum)
Parameters:
pnum (int)
PlanetSign(pnum)
Parameters:
pnum (int)
PlanetColor(pnum)
Parameters:
pnum (int)
zodiaccolor(deg)
Parameters:
deg (float)
degsign(deg)
Parameters:
deg (float)
degsignf(deg)
Parameters:
deg (float)
degnash(deg)
Parameters:
deg (float)
degname(deg)
Parameters:
deg (float)
retrogradesym(deg)
Parameters:
deg (float)
degaspsign(deg)
Parameters:
deg (float)
degaspname(deg)
Parameters:
deg (float)
degaspfull(deg)
Parameters:
deg (float)
degaspfullV2(deg)
Parameters:
deg (float)
degaspnameV2(deg)
Parameters:
deg (float)
degtolowest180(deg)
Parameters:
deg (float)
degaspfullapproach(deg)
Parameters:
deg (float)
virinchiaspectcol(deg, bull_col, bear_col)
Parameters:
deg (float)
bull_col (color)
bear_col (color)
virinchiaspectemo(deg, bull_emo, bear_emo)
Parameters:
deg (float)
bull_emo (string)
bear_emo (string)
aspectfastsigndeg(deg)
Parameters:
deg (float)
aspectfastfull(deg)
Parameters:
deg (float)
aspectslowfull(deg)
Parameters:
deg (float)
aspectslowsigndeg(deg)
Parameters:
deg (float)
aspectslowsign(deg)
Parameters:
deg (float)
aspectsignprecision(deg, precision)
Parameters:
deg (float)
precision (int)
aspectsignprecisionV2(deg, precision)
Parameters:
deg (float)
precision (float)
aspectsignprecisionV2ext(deg, precision)
Parameters:
deg (float)
precision (float)
IPaspectsignprecision(planet1, planet2, precision)
Parameters:
planet1 (float)
planet2 (float)
precision (float)
IPaspectsignprecisionFull(planet1, planet2, precision)
Parameters:
planet1 (float)
planet2 (float)
precision (float)
IPaspectlineprecision(planet1, planet2, precision, style, width)
Parameters:
planet1 (float)
planet2 (float)
precision (float)
style (string)
width (int)
rDeg(deg)
Parameters:
deg (float)
AngToCirc(angle)
Parameters:
angle (float)
AngToCirc180(angle)
Parameters:
angle (float)
sidereal(deg, sidereal)
Parameters:
deg (float)
sidereal (bool)
J2000(JDN)
Parameters:
JDN (float)
JDN(t, d, tz)
Parameters:
t (float)
d (float)
tz (float)
getsun(index, day, dayr, latitude, longitude, tz)
Parameters:
index (int)
day (float)
dayr (float)
latitude (float)
longitude (float)
tz (float)
getmoon(index, day, dayr, latitude, longitude)
Parameters:
index (int)
day (float)
dayr (float)
latitude (float)
longitude (float)
getplanet(planet, index, day, dayr, latitude, longitude, tz)
Parameters:
planet (int)
index (int)
day (float)
dayr (float)
latitude (float)
longitude (float)
tz (float)
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.
Ehlers Stochastic Center Of Gravity [CC]The Stochastic Center Of Gravity Indicator was created by John Ehlers (Cybernetic Analysis For Stocks And Futures pgs 79-80), and this is one of the many cycle scripts that I have created but not published yet because, to be honest, I don't use cycle indicators in my everyday trading. Many of you probably do, so I will start publishing my big backlog of cycle-based indicators. These indicators work best with a trend confirmation or some other confirmation indicator to pair with it. The current cycle is the length of the trend, and since most stocks generally change their underlying trend quite often, especially during the day, it makes sense to adjust the length of this indicator to match the stock you are using it on. As you can see, the indicator gives constant buy and sell signals during a trend which is why I recommend using a confirmation indicator.
I have color-coded it to use lighter colors for normal signals and darker colors for strong signals. Buy when the line turns green and sell when it turns red.
Let me know if there are any other scripts you would like to see me publish!
Ehlers Reflex Indicator [CC]The Reflex Indicator was created by John Ehlers (Stocks and Commodities Feb 2020) and this is a zero lag indicator that works similar to an overbought/oversold indicator but with the current stock cycle data. I find that this indicator works well as a leading indicator as well as a divergence indicator. Generally speaking, this indicator indicates a medium to long term downtrend when the indicator is below the line and a medium to long term uptrend when the indicator is above the line. Ehlers has created a few complementary indicators that I will release in the next few days but just keep in mind that this indicator focuses on the underlying cycle component while removing as much noise with no lag. I have color coded the lines to show strong signals with the darker colors and normal signals with the lighter colors. Buy when the line turns green and sell when it turns red.
Let me know if there are any other scripts you would like to see me publish!
Stan Weinstein Trend IndicatorThis indicator is a trend indicator for trading charts based on the method of Stan Weinstein. It uses various technical methods to identify four trend phases on an asset: consolidation, advancement, plateauing, and decline. Users can customize the indicator by modifying parameters such as the periods for various calculations, such as the exponential moving average (EMA), the relative strength index (RSI), and support and resistance levels. The results of these calculations are then used to determine if an asset is in a phase of consolidation, advancement, plateauing, or decline.
The results are displayed as markers on the chart, with the following colors:
White: Consolidation
Green: Advancement
Blue: Plateauing
Red: Decline
According to the method of Stan Weinstein, it is recommended to buy an asset during an advancement phase and sell it during a plateauing phase. Similarly, it is recommended to sell an asset during a decline phase and cut this sale when the consolidation phase starts. It is important to note that this indicator is for informational purposes only and should not be used as investment advice. It is important to conduct fundamental and technical analysis before making an investment decision. It is also recommended to combine this analysis with other methods for optimal results and to consider the risks associated with any investment.
All default parameters of this indicator have been carefully chosen to provide the best possible results, however, it is possible to modify them according to personal preferences. It is important to note that modifying certain parameters may make the indicator less relevant and it is therefore recommended not to deviate too much from default values, unless you have a good understanding of the Stan Weinstein method and the technical indicators used.
It is important to note that this indicator is optimized for 1-week charts. It can be used to look at charts at other timeframes but calculations will always be based on weekly data.
Also, it is noteworthy that this indicator is optimized for cryptocurrencies, except Bitcoin, as it is used to calculate the relative strength of a token. However, you can choose the asset or index you want in the menu to calculate the relative strength. Furthermore, all the default settings are carefully chosen, but users are free to modify them, but doing so may result in less relevant results.
30MIN CYCLE█ HOW DOES IT WORK?
The known 90 min cycle is used as one killzone. But actually all 18 min are relevant to search for a trade. All 18 min when a new box starts only then is the placement of an order valid. If the entry candle isn't in a box then it will probably fail. The boxes should only be used in the M1 or M5 timeframe. The best hitrate is in the M1 timeframe. Included are the last 48 "Mini-Killzones" für intraday trading and backtesting. These "Mini-Killzones" can be used with the "Liquidity Inducement Strategy".
█ WHAT MAKES IT UNIQUE?
This is the first indicator on tradingview that shows all mini-killzones for trading and backtesting a whole tradingday. The well-known killzones of ICT are from 08:00-11:00 and 14:00 - 17:00 (UTC+1) but with this indicator there is finally a refinement of the ICT Smart Money Concept killzones.
█ HOW TO USE IT?
For a proper use of this indicator we suggest to know already at least SMC or better Liquidity Indcuement Trading. This indicator is a further confluence before placing an order. After you made your setup you will have these mini-killzones as a confluence. We don't suggest to open a trade only according to this indicator.
█ ADDITIONAL INFO
This indicator is free to use for all tradingview users.
█ DISCLAIMER
This is not financial advice.
AlexD Market annual seasonalityThe indicator displays the percentage of bullish days with a given date over several years.
This allows you to determine the days of the year when the price usually goes up or down.
Indicator has a built-in "simple moving average" shifted back by half a period, due to which the delay of this smoothing is removed.
timing marketIntraday time cycle . it is valid for nifty and banknifty .just add this on daily basis . ignore previous day data
Cycle-Period Adaptive, Linear Regression Slope Oscillator [Loxx]Cycle-Period Adaptive, Linear Regression Slope Oscillator is an osciallator that solves for the Linear Regression slope and turns it into an oscillator. This is a very simple calculation and uses one of Ehler's first implementations of his cycle period calculations. The output slope value is smoothed after calculation and before being drawn. This is a sort of momentum indicator and has a rich history with Forex traders around the world.
What is the Cycle Period?
The spectral content of the data are measured in a bank of contiguous filters as described in "Measuring Cycle Periods" in the March 2008 issue of Stocks & Commodities Magazine. The filter having the strongest output is selected as the current dominant cycle period. The cycle period is measured as the number of bars contained in one full cycle period.
What is Linear Regression?
In statistics, linear regression is a linear approach for modeling the relationship between a scalar response and one or more explanatory variables. The case of one explanatory variable is called simple linear regression; for more than one, the process is called multiple linear regression.
Included:
Bar coloring
2 signal types
Alerts
Loxx's Expanded Source Types
Loxx's Moving Averages
Pi Cycle Indicators Comparison IndicatorThere are now 3 Pi Cycle Indicators that I am aware of; the original, improved**, and bottom.
This indicator attempts to provide all three indicators in a dingle, easy to view script.
I coded this script to displace the moving averages above and below the price bars for easy viewing. This was accomplished by placing a scaling factor (/# or *#) at the end of the ta.sma or ta.ema functions.
A vertical arrow, purposely posing as a short vertical line, marks the crossing of the long and short MAs for each indicator. These are color coded to match their respective indicators and the long and short MAs are similarly color coded for easy differentiation.
The red colored MAs and arrows above the price line are the Improved Pi-Cycle Top Indicator.
The green colored MAs and arrows below the price line are the Original Pi-Cycle Top Indicator.
The blue colored MAs and arrows below the green lines and price line are the Pi-Cycle Bottom Indicator.
One last feature of the chart is the use of the location function to enable easy comparison of the crossings of each indicator to the indicator itself and to the price. This can be accomplished simply by moving the chart up and down.
**{I should note that while researching this I found that BitcoinMamo turns out to have beat me to the punch on the Improved Indicator Long.Short and Multiplier numbers. He should therefor get the credit for that}
Bitcoin Golden Pi CyclesTops are signaled by the fast top MA crossing above the slow top MA, and bottoms are signaled by the slow bottom MA crossing above the fast bottom MA. Alerts can be set on top and bottom prints. Does not repaint.
Similar to the work of Philip Swift regarding the Bitcoin Pi Cycle Top, I’ve recently come across a similar mathematically curious ratio that corresponds to Bitcoin cycle bottoms. This ratio was extracted from skirmantas’ Bitcoin Super Cycle indicator . Cycle bottoms are signaled when the 700D SMA crosses above the 137D SMA (because this indicator is closed source, these moving averages were reverse-engineered). Such crossings have historically coincided with the January 2015 and December 2018 bottoms. Also, although yet to be confirmed as a bottom, a cross occurred June 19, 2022 (two days prior to this article)
The original pi cycle uses the doubled 350D SMA and the 111D SMA . As pointed out this gives the original pi cycle top ratio:
350/111 = 3.1532 ≈ π
Also, as noted by Swift, 111 is the best integer for dividing 350 to approximate π. What is mathematically interesting about skirmanta’s ratio?
700/138 = 5.1095
After playing around with this for a while I realized that 5.11 is very close to the product of the two most numerologically significant geometrical constants, π and the golden ratio, ϕ:
πϕ = 5.0832
However, 138 turns out to be the best integer denominator to approximate πϕ:
700/138 = 5.0725 ≈ πϕ
This is what I’ve dubbed the Bitcoin Golden Pi Bottom Ratio.
In the spirit of numerology I must mention that 137 does have some things going for it: it’s a prime number and is very famously almost exactly the reciprocal of the fine structure constant (α is within 0.03% of 1/137).
Now why 350 and 700 and not say 360 and 720? After all, 360 is obviously much more numerologically significant than 350, which is proven by the fact that 360 has its own wikipedia page, and 350 does not! Using 360/115 and 720/142, which are also approximations of π and πϕ respectively, this also calls cycle tops and bottoms.
There are infinitely many such ratios that could work to approximate π and πϕ (although there are a finite number whose daily moving averages are defined). Further analysis is needed to find the range(s) of numerators (the numerator determines the denominator when maintaining the ratio) that correctly produce bottom and top signals.
Hybrid, Zero lag, Adaptive cycle MACD [Loxx]TASC's March 2008 edition Traders' Tips includes an article by John Ehlers titled "Measuring Cycle Periods," and describes the use of bandpass filters to estimate the length, in bars, of the currently dominant price cycle.
What are Dominant Cycles and Why should we use them?
Even the most casual chart reader will be able to spot times when the market is cycling and other times when longer-term trends are in play. Cycling markets are ideal for swing trading however attempting to “trade the swing” in a trending market can be a recipe for disaster. Similarly, applying trend trading techniques during a cycling market can equally wreak havoc in your account. Cycle or trend modes can readily be identified in hindsight. But it would be useful to have an objective scientific approach to guide you as to the current market mode.
There are a number of tools already available to differentiate between cycle and trend modes. For example, measuring the trend slope over the cycle period to the amplitude of the cyclic swing is one possibility.
We begin by thinking of cycle mode in terms of frequency or its inverse, periodicity. Since the markets are fractal; daily, weekly, and intraday charts are pretty much indistinguishable when time scales are removed. Thus it is useful to think of the cycle period in terms of its bar count. For example, a 20 bar cycle using daily data corresponds to a cycle period of approximately one month.
When viewed as a waveform, slow-varying price trends constitute the waveform's low frequency components and day-to-day fluctuations (noise) constitute the high frequency components. The objective in cycle mode is to filter out the unwanted components--both low frequency trends and the high frequency noise--and retain only the range of frequencies over the desired swing period. A filter for doing this is called a bandpass filter and the range of frequencies passed is the filter's bandwidth .
Indicator Features
-Zero lag or Regular MACD/signal calculation
- Fixed or Band-pass Dominant Cycle for MACD and Signal MA period inputs
-10 different moving average options for both MACD and Signal MA calculations
-Separate Band-pass Dominant Cycle calculations for both MACD and Signal MA calculations
- Slow-to-Fast Band-pass Dominant Cycle input to tweak the ratio of MACD MA input periods as they relate to each other
DominantCycleCollection of Dominant Cycle estimators. Length adaptation used in the Adaptive Moving Averages and the Adaptive Oscillators try to follow price movements and accelerate/decelerate accordingly (usually quite rapidly with a huge range). Cycle estimators, on the other hand, try to measure the cycle period of the current market, which does not reflect price movement or the rate of change (the rate of change may also differ depending on the cycle phase, but the cycle period itself usually changes slowly). This collection may become encyclopaedic, so if you have any working cycle estimator, drop me a line in the comments below. Suggestions are welcome. Currently included estimators are based on the work of John F. Ehlers
mamaPeriod(src, dynLow, dynHigh) MESA Adaptation - MAMA Cycle
Parameters:
src : Series to use
dynLow : Lower bound for the dynamic length
dynHigh : Upper bound for the dynamic length
Returns: Calculated period
Based on MESA Adaptive Moving Average by John F. Ehlers
Performs Hilbert Transform Homodyne Discriminator cycle measurement
Unlike MAMA Alpha function (in LengthAdaptation library), this does not compute phase rate of change
Introduced in the September 2001 issue of Stocks and Commodities
Inspired by the @everget implementation:
Inspired by the @anoojpatel implementation:
paPeriod(src, dynLow, dynHigh, preHP, preSS, preHP) Pearson Autocorrelation
Parameters:
src : Series to use
dynLow : Lower bound for the dynamic length
dynHigh : Upper bound for the dynamic length
preHP : Use High Pass prefilter (default)
preSS : Use Super Smoother prefilter (default)
preHP : Use Hann Windowing prefilter
Returns: Calculated period
Based on Pearson Autocorrelation Periodogram by John F. Ehlers
Introduced in the September 2016 issue of Stocks and Commodities
Inspired by the @blackcat1402 implementation:
Inspired by the @rumpypumpydumpy implementation:
Corrected many errors, and made small speed optimizations, so this could be the best implementation to date (still slow, though, so may revisit in future)
High Pass and Super Smoother prefilters are used in the original implementation
dftPeriod(src, dynLow, dynHigh, preHP, preSS, preHP) Discrete Fourier Transform
Parameters:
src : Series to use
dynLow : Lower bound for the dynamic length
dynHigh : Upper bound for the dynamic length
preHP : Use High Pass prefilter (default)
preSS : Use Super Smoother prefilter (default)
preHP : Use Hann Windowing prefilter
Returns: Calculated period
Based on Spectrum from Discrete Fourier Transform by John F. Ehlers
Inspired by the @blackcat1402 implementation:
High Pass, Super Smoother and Hann Windowing prefilters are used in the original implementation
phasePeriod(src, dynLow, dynHigh, preHP, preSS, preHP) Phase Accumulation
Parameters:
src : Series to use
dynLow : Lower bound for the dynamic length
dynHigh : Upper bound for the dynamic length
preHP : Use High Pass prefilter (default)
preSS : Use Super Smoother prefilter (default)
preHP : Use Hamm Windowing prefilter
Returns: Calculated period
Based on Dominant Cycle from Phase Accumulation by John F. Ehlers
High Pass and Super Smoother prefilters are used in the original implementation
doAdapt(type, src, len, dynLow, dynHigh, chandeSDLen, chandeSmooth, chandePower, preHP, preSS, preHP) Execute a particular Length Adaptation or Dominant Cycle Estimator from the list
Parameters:
type : Length Adaptation or Dominant Cycle Estimator type to use
src : Series to use
len : Reference lookback length
dynLow : Lower bound for the dynamic length
dynHigh : Upper bound for the dynamic length
chandeSDLen : Lookback length of Standard deviation for Chande's Dynamic Length
chandeSmooth : Smoothing length of Standard deviation for Chande's Dynamic Length
chandePower : Exponent of the length adaptation for Chande's Dynamic Length (lower is smaller variation)
preHP : Use High Pass prefilter for the Estimators that support it (default)
preSS : Use Super Smoother prefilter for the Estimators that support it (default)
preHP : Use Hann Windowing prefilter for the Estimators that support it
Returns: Calculated period (float, not limited)
doEstimate(type, src, dynLow, dynHigh, preHP, preSS, preHP) Execute a particular Dominant Cycle Estimator from the list
Parameters:
type : Dominant Cycle Estimator type to use
src : Series to use
dynLow : Lower bound for the dynamic length
dynHigh : Upper bound for the dynamic length
preHP : Use High Pass prefilter for the Estimators that support it (default)
preSS : Use Super Smoother prefilter for the Estimators that support it (default)
preHP : Use Hann Windowing prefilter for the Estimators that support it
Returns: Calculated period (float, not limited)
Tesla Coil MLThis is a re-implementation of @veryfid's wonderful Tesla Coil indicator to leverage basic Machine Learning Algorithms to help classify coil crossovers. The original Tesla Coil indicator requires extensive training and practice for the user to develop adequate intuition to interpret coil crossovers. The goal for this version is to help the user understand the underlying logic of the Tesla Coil indicator and provide a more intuitive way to interpret the indicator. The signals should be interpreted as suggestions rather than as a hard-coded set of rules.
NOTE: Please do NOT trade off the signals blindly. Always try to use your own intuition for understanding the coils and check for confluence with other indicators before initiating a trade.
Bitcoin Bull Runs Mid Cycle Aligned This script plots 2 lines which are the 2013 and 2016 bull run. The plots are aligned on their mid cycles to the 2021 mid cycle.
Settings:
You can move the plots on the x and y axis in the settings for the Daily, Weekly and Monthly TFs.
The plot is weird on the Monthly TF, best to use the Daily and Weekly.
If it doesn't load at first you have to zoom out fully and go back to 2013 for it to load. Then it will load.
