Seasonality and Presidential cycleAn incredibly useful indicator that shows seasonality and presidential cycles by indices, stocks and industries. Just type in a ticker and trade according to seasonal patterns
Blue line - seasonality excluding presidential cycles
Green line - seasonality taking into account presidential cycles
*Seasonal patterns over the last 10 years
This indicator uses the request.seed() function.
Requests data from a GitHub repository maintained by our team and returns it as a series.
Pine Seeds is a service to import custom data and access it via TradingView.
Use TradingView as frontend and use a GitHub repository as backend.
github.com
...
Rus: Невероятно полезный индикатор, который показывает сезонность и президентские циклы по индексам, акциям и отраслям. Просто вбейте тикер и торгуйте согласно сезонным паттернам
Синяя линия - сезонность без учета президентских циклов
Зеленая линия - сезонность с учетом президентских циклов
*Сезонные паттерны за последние 10 лет
Cerca negli script per "Cycle"
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}
Cycle Composite 3.6 WeightedThe Cycle Composite is a multi-factor market cycle model designed to classify long-term market behavior into distinct phases using normalized and weighted data inputs.
It combines ten key on-chain, dominance, volatility, sentiment, and trend-following metrics into a single composite output. The goal is to provide a clearer understanding of where the market may stand in the broader cycle (e.g., accumulation, early bull, late bull, or euphoria).
This version (3.4) introduces flexible weighting, trend strength markers, and additional context-aware signals such as risk-on confirmations and altseason flags.
Phases Identified:
The model categorizes the market into one of five zones:
Euphoria (> 85)
Late Bull (70 – 85)
Mid Bull (50 – 70)
Early Bull (30 – 50)
Fear (< 30)
Each phase is determined by a smoothed EMA of the weighted composite score.
Data Sources and Metrics Used (10 total):
BTC Dominance (CRYPTOCAP:BTC.D)
Stablecoin Dominance (USDT + USDC average) (inverted for risk-on)
ETH Dominance (CRYPTOCAP:ETH.D)
BBWP (normalized Bollinger Band Width % over 1-year window)
WVF (Williams VIX Fix for volatility spike detection)
NUPL (Net Unrealized Profit/Loss, external source)
CMF (Chaikin Money Flow, smoothed volume accumulation)
CEX Open Interest (custom input from DAO / external source)
Whale Inflows (custom input from whale exchange transfer data)
Google Trends Average (BTC, Crypto, Altcoin terms)
All inputs are normalized over a 200-bar window and combined via weighted averaging, where each weight is user-configurable.
Additional Features:
Phase Labels: Labels are printed only when a new phase is entered.
Bull Continuation Marker: Triangle up when composite makes higher highs and NUPL increases.
Weakening Marker: Triangle down when composite rolls over in Late Bull and NUPL falls.
Risk-On Signal: Green circle appears when CMF and Google Trends are both rising.
Altseason Flag: Orange diamond appears when dominance of "others.d" exceeds BTC.D and ETH.D and composite is above 50.
Background Shading: Each phase is shaded with a semi-transparent background color.
Timeframe-Aware Display: All markers and signals are shown only on weekly timeframe for clarity.
Intended Use:
This script is intended for educational and macro-trend analysis purposes.
It can be used to:
Identify macro cycle position (accumulation, bull phases, euphoria, etc.)
Spot long-term trend continuation or weakening signals
Add context to price action with external on-chain and sentiment data
Time rotation events such as altseason risk
Disclaimer:
This script does not constitute financial advice.
It is intended for informational and research purposes only.
Users should conduct their own due diligence and analysis before making investment decisions.
Benner Cycle + Auto Weekly FibonacciBenner Cycle Wave
A sinusoidal wave modeled after the historic Benner Cycle theory, which suggests regular economic and market turning points.
- Auto-adjusts based on chart time
- Displays BUY/SELL signal markers at cycle peaks and troughs
Fibonacci Retracement Levels
Automatically draws key Fibonacci levels (0% to 100%) using the daily high and low, helping you spot potential reversal or continuation zones.
- Fully dynamic: updates at the start of each week
- Great for intraday and swing traders looking to time pullbacks or breakouts
Why use both?
The Benner wave highlights when markets may shift. The Fibonacci levels show where price could react. Together, they give you time + price confluence — a powerful edge in trade planning.
PCTR - Pi Cycle Top Risk [Logue]Pi-cycle Top Risk (PCTR) - The PCTR indicator uses divergence of the Pi-cycle top indicator display the risk that a macro top in Bitcoin (BTC) is near. The Pi-cycle top indicator is simply the cross of the 111-day moving average above a 2x multiple of the 350-day moving average of the BTC price. While there is no fundamental reasoning behind why this works, it has worked to indicate previous bitcoin tops by taking advantage of the cyclicality of the BTC price and measurement overextension of BTC price. This indicator triggers a top signal when the fast moving average (111-day) crosses above the 2x multiple of the slow moving average (350-day).
What's interesting is the indicator can also signal a bottom when the divergence of the fast moving average is at an extreme versus the slow moving average. The indicator signals a bottom when the fast MA is 66% away from the slow MA value.
Both the top and bottom signals are clearly shown on the chart on a scale from 100 to 0.
Cosmic Pi CycleAn adaptation of the Pi Cycle type indicator that
uses more accurate "pi" moving average periods
allows to adjust the numerator mult
shows cycle bottoms
shows a basis line
can be layered like in the example to create a Pi Cycle Channel
Market Cycle & Scalping entry / exitCycle indicator is an oscillator commonly used to identify market trends and provide buy and sell signals to traders. The Cyle indicator is based on the assumption that currency trends accelerate and decelerate in cyclical patterns that may reflect the dominant price cycle of any stock, during any time frame. It works best on a 1 min chart for quick scalp plays.
Blockchain Fundamentals: Liquidity Cycle MomentumLiquidity Cycle Momentum Indicator
Overview:
This indicator analyzes global liquidity trends by calculating a unique Liquidity Index and measuring its year-over-year (YoY) percentage change. It then applies a momentum oscillator to the YoY change, providing insights into the cyclical momentum of liquidity. The indicator incorporates a limited historical data workaround to ensure accurate calculations even when the chart’s history is short.
Features Breakdown:
1. Limited Historical Data Workaround
Function: The limit(length) function adjusts the lookback period when there isn’t enough historical data (i.e., near the beginning of the chart), ensuring that calculations do not break due to insufficient data.
2. Global Liquidity Calculation
Data Sources:
TVC:CN10Y (10-year yield from China)
TVC:DXY (US Dollar Index)
ECONOMICS:USCBBS (US Central Bank Balance Sheet)
FRED:JPNASSETS (Japanese assets)
ECONOMICS:CNCBBS (Chinese Central Bank Balance Sheet)
FRED:ECBASSETSW (ECB assets)
Calculation Methodology:
A ratio is computed (cn10y / dxy) to adjust for currency influences.
The Liquidity Index is then derived by multiplying this ratio with the sum of the other liquidity components.
3. Year-over-Year (YoY) Percent Change
Computation:
The indicator determines the number of bars that approximately represent one year.
It then compares the current Liquidity Index to its value one year ago, calculating the YoY percentage change.
4. Momentum Oscillator on YoY Change
Oscillator Components:
1. Calculated using the Chande Momentum Oscillator (CMO) applied to the YoY percent change with a user-defined momentum length.
2. A weighted moving average (WMA) that smooths the momentum signal.
3. Overbought and Oversold zones
Signal Generation:
Buy Signal: Triggered when the momentum crosses upward from an oversold condition, suggesting a potential upward shift in liquidity momentum.
Sell Signal: Triggered when crosses below an overbought condition, indicating potential downward momentum.
State Management:
The indicator maintains a state variable to avoid repeated signals, ensuring that a new buy or sell signal is only generated when there’s a clear change in momentum.
5. Visual Presentation and Alerts
Plots:
The oscillator value and signalline are plotted for visual analysis.
Overbought and oversold levels are marked with dashed horizontal lines.
Signal Markers:
Buy and sell signals are marked with green and maroon circles, respectively.
Background Coloration:
Optionally, the chart’s background bars are colored (yellow for buy signals and fuchsia for sell signals) to enhance visual cues when signals are triggered.
Conclusion
In summary, the Liquidity Cycle Momentum Indicator provides a robust framework to analyze liquidity trends by combining global liquidity data, YoY changes, and momentum oscillation. This makes it an effective tool for traders and analysts looking to identify cyclical shifts in liquidity conditions and potential turning points in the market.
Weierstrass Function (Fractal Cycles)THE WEIERSTRASS FUNCTION
f(x) = ∑(n=0)^∞ a^n * cos(b^n * π * x)
The Weierstrass Function is the sum of an infinite series of cosine functions, each with increasing frequency and decreasing amplitude. This creates powerful multi-scale oscillations within the range ⬍(-2;+2), resembling a system of self-repetitive patterns. You can zoom into any part of the output and observe similar proportions, mimicking the hidden order behind the irregularity and unpredictability of financial markets.
IT DOESN’T RELY ON ANY MARKET DATA, AS THE OUTPUT IS BASED PURELY ON A MATHEMATICAL FORMULA!
This script does not provide direct buy or sell signals and should be used as a tool for analyzing the market behavior through fractal geometry. The function is often used to model complex, chaotic systems, including natural phenomena and financial markets.
APPLICATIONS:
Timing Aspect: Identifies the phases of market cycles, helping to keep awareness of frequency of turning points
Price-Modeling features: The Amplitude, frequency, and scaling settings allow the indicator to simulate the trends and oscillations. Its nowhere-differentiable nature aligns with the market's inherent uncertainty. The fractured oscillations resemble sharp jumps, noise, and dips found in volatile markets.
SETTINGS
Amplitude Factor (a): Controls the size of each wave. A higher value makes the waves larger.
Frequency Factor (b): Determines how fast the waves oscillate. A higher value creates more frequent waves.
Ability to Invert the output: Just like any cosine function it starts its journey with a decline, which is not distinctive to the behavior of most assets. The default setting is in "inverted mode".
Scale Factor: Adjusts the speed at which the oscillations grow over time.
Number of Terms (n_terms): Increases the number of waves. More terms add complexity to the pattern.
Pi Cycle Indicator Low and High
The Pi Cycle Indicator is a technical analysis tool used in finance, particularly within cryptocurrency markets, to identify potential market tops or bottoms. It is based on two moving averages: the 111-day moving average and the 350-day moving average of Bitcoin's price. The indicator suggests that when these two moving averages converge or cross each other, it may signal significant market turning points. The name "Pi Cycle" comes from the mathematical relationship between these two moving averages, roughly equivalent to the mathematical constant Pi (3.14). Traders and analysts use this indicator to gauge potential trend reversals and make informed decisions regarding their trading strategies. However, like any technical analysis tool, it should be used in conjunction with other indicators and fundamental analysis for a comprehensive understanding of market conditions.
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.
Pi CycleImplementation of Pi Cycle Top and Pi Cycle Bottom with clear visualization
Pi Circle Top is slightly modified to be closer to Pi sma 113 & sma (355) * 2)
Pi Circle Bottom is ISO sma 571 & ema 150
Script will adapt to timeframe but under hourly it might not work due to the high amount of candles to take into account.
Sentimental Cycles with CrossingsThis indicator provides the following options, where you can choose to display:
DEMA TEMA cycles, filtered by default with sentiment.
Sentiment cloud, based on the 200ema area between the 1 minute and 1 hour lines.
One or both ema crossings with their respective timeframes (independent from current chart timeframe) and optional line display.
One or two tickers and their respective crossings based on selected timeframes.
Additional EMA lines supplied with their very own timeframe.
This indicator is intended to be used any way suitable to the user, nearly every aspect is customizable, and the defaults are just enough to get you started on deciding whether it's time to enter calls or puts.
TIPS for optimal results:
- Try using 2 charts: the 1 minute and the 1 hour per symbol. Under the 1 minute chart, use the 3 minute and 5 minute timeframe for crossings.
- Try to start a position when a sentimental DEMA TEMA cloud is beginning to form. The first bar usually pays thicc.
- Tickers SPY and VXX can be of good reference for market direction. If all crossings coincide, it's because there's a strong momentum in a certain direction for the market.
[SM] Bitcoin cycles bull market
An indicator to determine the seasonality / cyclicality of bitcoin for long trades.
Application
- For traders: Identification of zones with lower risk of entering long positions
- For swing traders and investors: customizable calendar of entries into long position
Indicator structure
1. Vertical zones (green and red) of time ranges. Only for historical bars. The range width is adjustable in the indicator settings.
2. Table (in the form of a calendar) for determining the time of entering a trade in the future. The table is not editable. It displays the result of the configured zones on the historical bars.
General settings
- choose the color of the Tradingview theme (light or dark)
Table settings
- Turn table display on / off
- Set the number of months to be displayed in the table
Settings of vertical zones (green and red)
Each cycle (1 month summer, 1 month autumn, ...) has four dates
- start date of the green zone (day and month)
- date of the end of the green zone
- start date of the red zone
- date of the end of the red zone
Lunar Cycles Projected Forward; Moon phases into futureProjecting Lunar Cycles/ half-cycles forward in time
User sets the recent Full moon in history to anchor from; Indicator projects 1/2 cycles forward in time
//inputs//
-input number of full lunar cycles to project forward from input full moon time
-choose color/opacity/border color/text display
Quick scan for cycles🙏🏻
The followup for
As I told before, ML based algorading is all about detecting any kind of non-randomness & exploiting it (cuz allegedly u cant trade randomness), and cycles are legit patterns that can be leveraged
But bro would u really apply Fourier / Wavelets / 'whatever else heavy' on every update of thousands of datasets, esp in real time on HFT / nearly HFT data? That's why this metric. It works much faster & eats hell of a less electicity, will do initial rough filtering of time series that might contain any kind of cyclic behaviour. And then, only on these filtered datasets u gonna put Periodograms / Autocorrelograms and see what's going there for real. Better to do it 10x times less a day on 10x less datasets, right?
I ended up with 2 methods / formulas, I called em 'type 0' and 'type 1':
- type 0: takes sum of abs deviations from drift line, scales it by max abs deviation from the same drift line;
- type 1: takes sum of abs deviations from drift line, scales it by range of non-abs deviations from the same drift line.
Finnaly I've chosen type 0 , both logically (sum of abs dev divided by max abs dev makes more sense) and experimentally. About that actually, here are both formulas put on sine waves with uniform noise:
^^ generated sine wave with uniform noise
^^ both formulas on that wave
^^ both formulas on real data
As you can see type 0 is less affected by noise and shows higher values on synthetic data, but I decided to put type 1 inside as well, in case my analysis was not complete and on real data type 1 can actually be better since it has a lil higher info gain / info content (still not sure). But I can assure u that out of all other ways I've designed & tested for quite a time I tell you, these 2 are really the only ones who got there.
Now about dem thresholds and how to use it.
Both type 0 and type 1 can be modelled with Beta distribution, and based on it and on some obvious & tho non mainstream statistical modelling techniques, I got these thresholds, so these are not optimized overfitted values, but natural ones. Each type has 3 thresholds (from lowest to highest):
- typical value (turned off by default). aka basis ;
- typical deviation from typical value, aka deviation ;
- maximum modelled deviation from typical value (idk whow to call it properly for now, this is my own R&D), aka extension .
So when the metric is above one of these thresholds (which one is up to you, you'll read about it in a sec), it means that there might be a strong enough periodic signal inside the data, and the data got to be put through proper spectral analysis tools to confirm / deny it.
If you look at the pictures above again, you'll see gray signal, that's uniform noise. Take a look at it and see where does it sit comparing to the thresholds. Now you just undertand that picking up a threshold is all about the amount of false positives you care to withstand.
If you take basis as threshold, you'll get tons of false positives (that's why it's even turned off by default), but you'll almost never miss a true positive. If you take deviation as threshold, it's gonna be kinda balanced approach. If you take extension as threshold, you gonna miss some cycles, and gonna get only the strongest ones.
More true positives -> more false positives, less false positives -> less true positives, can't go around that mane
Just to be clear again, I am not completely sure yet, but I def lean towards type 0 as metric, and deviation as threshold.
Live Long and Prosper
P.S.: That was actually the main R&D of the last month, that script I've released earlier came out as derivative.
P.S.: These 2 are the first R&Ds made completely in " art-space", St. Petersburg. Come and see me, say wassup🤘🏻
Sacred: Cycles"Cycles offer freedom to those who see them, and fate to those who don't."
Following liquidity cycles is one of the most useful tools of making in financial markets. Over the longer term, it helps you get in at the beginning of plenty and out before the droughts. This script aims to simplify that for the average trader by displaying tree types of information:
Currents
More often than you might imagine, prices are interacting with moving averages across various timeframes. Zoom in or out enough and you'll probably find a moving average that intersects any given price turn/pause. But how to find them? It turns out if you take a fractal approach and scale up or down common time periods, you can generate surprisingly useful support and resistance levels you wouldn't otherwise plot. I call these moving averages "currents". By changing time intervals, you'll be able to find which current is affecting your charts price. (Note: Only works with tickers that have volume data.)
Financial Conditions
Proper technical analysis will give you an idea of which price levels are important and when a pattern is likely to resolve. But how to decide which direction you should bet on? That's where liquidity comes into play. For those tickers that are sensitive to broader liquidity conditions, these markers will tell you if you're in a bearish or bullish regime. After a bearish marker, it's time to sell rips. In a bearish one, buy the dip.
Recessions
Waiting for recessions to be announced by the NBER is a waste of time. You need to know today if recessionary conditions exist. That's where following coincident growth indicators instead of lagging ones helps. This script adds a red background to indicate weakening US growth.
Quarterly Cycle Theory with DST time AdjustedThe Quarterly Theory removes ambiguity, as it gives specific time-based reference points to look for when entering trades. Before being able to apply this theory to trading, one must first understand that time is fractal:
Yearly Quarters = 4 quarters of three months each.
Monthly Quarters = 4 quarters of one week each.
Weekly Quarters = 4 quarters of one day each (Monday - Thursday). Friday has its own specific function.
Daily Quarters = 4 quarters of 6 hours each = 4 trading sessions of a trading day.
Sessions Quarters = 4 quarters of 90 minutes each.
90 Minute Quarters = 4 quarters of 22.5 minutes each.
Yearly Cycle: Analogously to financial quarters, the year is divided in four sections of three months each:
Q1 - January, February, March.
Q2 - April, May, June (True Open, April Open).
Q3 - July, August, September.
Q4 - October, November, December.
S&P 500 E-mini Futures (daily candles) — Monthly Cycle.
Monthly Cycle: Considering that we have four weeks in a month, we start the cycle on the first month’s Monday (regardless of the calendar Day):
Q1 - Week 1: first Monday of the month.
Q2 - Week 2: second Monday of the month (True Open, Daily Candle Open Price).
Q3 - Week 3: third Monday of the month.
Q4 - Week 4: fourth Monday of the month.
S&P 500 E-mini Futures (4 hour candles) — Weekly Cycle.
Weekly Cycle: Daye determined that although the trading week is composed by 5 trading days, we should ignore Friday, and the small portion of Sunday’s price action:
Q1 - Monday.
Q2 - Tuesday (True Open, Daily Candle Open Price).
Q3 - Wednesday.
Q4 - Thursday.
S&P 500 E-mini Futures (1 hour candles) — Daily Cycle.
Daily Cycle: The Day can be broken down into 6 hour quarters. These times roughly define the sessions of the trading day, reinforcing the theory’s validity:
Q1 - 18:00 - 00:00 Asia.
Q2 - 00:00 - 06:00 London (True Open).
Q3 - 06:00 - 12:00 NY AM.
Q4 - 12:00 - 18:00 NY PM.
S&P 500 E-mini Futures (15 minute candles) — 6 Hour Cycle.
6 Hour Quarters or 90 Minute Cycle / Sessions divided into four sections of 90 minutes each (EST/EDT):
Asian Session
Q1 - 18:00 - 19:30
Q2 - 19:30 - 21:00 (True Open)
Q3 - 21:00 - 22:30
Q4 - 22:30 - 00:00
London Session
Q1 - 00:00 - 01:30
Q2 - 01:30 - 03:00 (True Open)
Q3 - 03:00 - 04:30
Q4 - 04:30 - 06:00
NY AM Session
Q1 - 06:00 - 07:30
Q2 - 07:30 - 09:00 (True Open)
Q3 - 09:00 - 10:30
Q4 - 10:30 - 12:00
NY PM Session
Q1 - 12:00 - 13:30
Q2 - 13:30 - 15:00 (True Open)
Q3 - 15:00 - 16:30
Q4 - 16:30 - 18:00
S&P 500 E-mini Futures (5 minute candles) — 90 Minute Cycle.
Micro Cycles: Dividing the 90 Minute Cycle yields 22.5 Minute Quarters, also known as Micro Sessions or Micro Quarters:
Asian Session
Q1/1 18:00:00 - 18:22:30
Q2 18:22:30 - 18:45:00
Q3 18:45:00 - 19:07:30
Q4 19:07:30 - 19:30:00
Q2/1 19:30:00 - 19:52:30 (True Session Open)
Q2/2 19:52:30 - 20:15:00
Q2/3 20:15:00 - 20:37:30
Q2/4 20:37:30 - 21:00:00
Q3/1 21:00:00 - 21:23:30
etc. 21:23:30 - 21:45:00
London Session
00:00:00 - 00:22:30 (True Daily Open)
00:22:30 - 00:45:00
00:45:00 - 01:07:30
01:07:30 - 01:30:00
01:30:00 - 01:52:30 (True Session Open)
01:52:30 - 02:15:00
02:15:00 - 02:37:30
02:37:30 - 03:00:00
03:00:00 - 03:22:30
03:22:30 - 03:45:00
03:45:00 - 04:07:30
04:07:30 - 04:30:00
04:30:00 - 04:52:30
04:52:30 - 05:15:00
05:15:00 - 05:37:30
05:37:30 - 06:00:00
New York AM Session
06:00:00 - 06:22:30
06:22:30 - 06:45:00
06:45:00 - 07:07:30
07:07:30 - 07:30:00
07:30:00 - 07:52:30 (True Session Open)
07:52:30 - 08:15:00
08:15:00 - 08:37:30
08:37:30 - 09:00:00
09:00:00 - 09:22:30
09:22:30 - 09:45:00
09:45:00 - 10:07:30
10:07:30 - 10:30:00
10:30:00 - 10:52:30
10:52:30 - 11:15:00
11:15:00 - 11:37:30
11:37:30 - 12:00:00
New York PM Session
12:00:00 - 12:22:30
12:22:30 - 12:45:00
12:45:00 - 13:07:30
13:07:30 - 13:30:00
13:30:00 - 13:52:30 (True Session Open)
13:52:30 - 14:15:00
14:15:00 - 14:37:30
14:37:30 - 15:00:00
15:00:00 - 15:22:30
15:22:30 - 15:45:00
15:45:00 - 15:37:30
15:37:30 - 16:00:00
16:00:00 - 16:22:30
16:22:30 - 16:45:00
16:45:00 - 17:07:30
17:07:30 - 18:00:00
S&P 500 E-mini Futures (30 second candles) — 22.5 Minute Cycle.
MÈGAS ALGO : ZIG-ZAG CYCLE INSIGTH [INDICATOR]Overview
The Zig-Zag Cycle Insigth is a revisited version of the classic Zig Zag indicator, designed to provide traders with a more comprehensive and actionable view of price movements.
This advanced tool not only highlights significant price swings but also incorporates additional features such as cycle analysis, real-time data tracking, and Fibonacci retracement levels. These enhancements make it an invaluable resource for identifying trends, potential reversal points, and market structure.
This indicator adheres to TradingView's guidelines and is optimized for both technical analysts and active traders who seek deeper insights into market dynamics.
Key Features:
1. Customizable Thresholds for Price Movements:
- Users can set personalized thresholds for price movement percentages and time periods.
This ensures that only significant price swings are plotted, reducing noise and increasing
clarity.
- Straight lines connect swing highs and lows, providing a cleaner visual representation of
the trend.
2. Cycle Analysis Table:
- A dynamic table is included to analyze price cycles based on three key factors:
- Price Change: Measures the magnitude of each swing (high-to-low or low-to-high).
- Time Duration (Bar Count): Tracks the number of bars elapsed between consecutive swings,
offering precise timing insights.
- Volume: Analyzes trading volume during each segment of the cycle.
- The indicator calculates the **maximum**, **minimum**, and **mean** values for each
parameter across all completed cycles, providing deeper statistical insights into market
behavior.
- This table updates in real-time, offering traders a quantitative understanding of how price
behaves over different cycles.
3. Real-Time Data Integration:
- The indicator displays live updates of current price action relative to the last identified
swing high/low. This includes:
- Current distance from the last pivot point.
- Percentage change since the last pivot.
- Volume traded since the last pivot.
4. Fibonacci Retracement Levels:
- Integrated Fibonacci retracement levels are dynamically calculated based on the most
recent significant swing high and low.
- Key retracement levels (23.6%, 38.2%, 50%, 61.8%, and 78.6%) are plotted alongside the Zig
Zag lines, helping traders identify potential support/resistance zones.
- Extension levels (100%, 161.8%, etc.) are also included to anticipate possible breakout
targets.
5. Customizable Alerts:
- Users can configure alerts for specific real-time conditions, such as:
- Price Change
- Duration
- Volume
- Fibonacci Retracement Levels
How It Works:
1. Zig Zag Identification:
- The indicator scans historical price data to identify significant turning points where the
price moves by at least the user-defined percentage threshold.
- These turning points are connected by straight lines to form the Zig Zag pattern.
2. Cycle Analysis:
For each completed cycle (from one swing high/low to the next), the indicator calculates:
- Price Change: Difference between the start and end prices of the cycle.
- Maximum Price Change: The largest price difference observed across all cycles.
- Minimum Price Change: The smallest price difference observed across all cycles.
- Mean Price Change: The average price difference across all cycles.
- Time Duration (Bar Count): Number of bars elapsed between consecutive swings.
- Maximum Duration: The longest cycle in terms of bar count.
- Minimum Duration: The shortest cycle in terms of bar count.
- Mean Duration: The average cycle length in terms of bar count.
- Volume: Total volume traded during the cycle.
- Maximum Volume: The highest volume traded during any single cycle.
- Minimum Volume: The lowest volume traded during any single cycle.
- Mean Volume: The average volume traded across all cycles.
- These calculations provide traders with a statistical overview of market behavior, enabling
them to identify patterns and anomalies in price, time, and volume.
3. Fibonacci Integration:
- Once a new swing high or low is identified, the indicator automatically calculates Fibonacci
retracement and extension levels.
- These levels serve as reference points for potential entry/exit opportunities.
4. Real-Time Updates:
- As the market evolves, the indicator continuously monitors the relationship between the
current price and the last identified swing point.
- Real-time metrics, such as percentage change and volume, are updated dynamically.
5. Alerts Based on Real-Time Parameters:
- The indicator allows users to set customizable alerts based on real-time conditions:
- Price Change Alert: Triggered when the real-time price change is less or greater than a
predefined percentage threshold (e.g., > or < fixed value).
- Duration Alert: Triggered when the cycle duration (in bars) is less or greater than a
predefined
bar count threshold (e.g., > or < fixed value).
- Volume Alert: Triggered when the trading volume during the current cycle is less or greater
than a predefined volume threshold (e.g., > or < fixed value).
Advantages of Zig-Zag Cycle Insigth
- Comprehensive Insights: Combining cycle analysis, Fibonacci retracements, and real-time data
provides a holistic view of market conditions.
- Statistical Analysis: The inclusion of maximum, minimum, and mean values for price change,
duration, and volume offers deeper insights into market behavior.
- Actionable Signals: Customizable alerts ensure traders never miss critical market events based
on real-time price, duration, and volume parameters.
- User-Friendly Design: Clear visuals and intuitive controls make it accessible for traders of all
skill levels.
Reference:
TradingView/ZigZag
TradingView/AutofibRetracement
Please Note:
This indicator is provided for informational and educational purposes only. It is not financial advice, and it should not be considered a recommendation to buy, sell, or trade any financial instrument. Trading involves significant risks, including the potential loss of your entire investment. Always conduct your own research and consult with a licensed financial advisor before making any trading decisions.
The results and images provided are based on algorithms and historical/paid real-time market data but do not guarantee future results or accuracy. Use this tool at your own risk, and understand that past performance is not indicative of future outcomes.
Adaptive Cycle Oscillator with EMADescription of the Adaptive Cycle Oscillator with EMA Pine Script
This Pine Script, titled "Adaptive Cycle Oscillator with EMA", is a custom technical indicator designed for TradingView to help traders analyze market cycles and identify potential buy or sell opportunities. It combines an Adaptive Cycle Oscillator (ACO) with multiple Exponential Moving Averages (EMAs), displayed as colorful, wavy lines, and includes features like buy/sell signals and divergence detection. Below is a beginner-friendly explanation of how the script works, adhering to TradingView's Script Publishing Rules.
What This Indicator Does
The Adaptive Cycle Oscillator with EMA helps you:
Visualize market cycles using an oscillator that adapts to price movements.
Track trends with seven EMAs of different lengths, plotted as a rainbow of wavy lines.
Identify potential buy or sell signals when the oscillator crosses predefined thresholds.
Spot divergences between the oscillator and price to anticipate reversals.
Use customizable settings to adjust the indicator to your trading style.
Note: This is a technical analysis tool and does not guarantee profits. Always combine it with other analysis methods and practice risk management.
Step-by-Step Explanation for New Users
1. Understanding the Indicator
Adaptive Cycle Oscillator (ACO): The ACO analyzes price data (based on high, low, and close prices, or HLC3) to detect market cycles. It smooths price movements to create an oscillator that swings between overbought and oversold levels.
EMAs: Seven EMAs of different lengths are applied to the ACO and scaled based on the market's dominant cycle. These EMAs are plotted as colorful, wavy lines to show trend direction.
Buy/Sell Signals: The script generates signals when the ACO crosses above or below user-defined thresholds, indicating potential entry or exit points.
Divergence Detection: The script identifies bullish or bearish divergences between the ACO and the fastest EMA, which may signal potential reversals.
Visual Style: The indicator uses a rainbow of seven colors (red, orange, yellow, green, blue, indigo, violet) for the EMAs, with wavy lines for a unique visual effect. Static levels (zero, overbought, oversold) are also wavy for consistency.
2. How to Add the Indicator to Your Chart
Open TradingView and load the chart of any asset (e.g., stock, forex, crypto).
Click on the Indicators button at the top of the chart.
Search for "Adaptive Cycle Oscillator with EMA" (or paste the script into TradingView’s Pine Editor if you have access to it).
Click to add the indicator to your chart. It will appear in a separate panel below the price chart.
3. Customizing the Indicator
The script offers several input options to tailor it to your needs:
Base Cycle Length (Default: 20): Sets the initial period for calculating the dominant cycle. Higher values make the indicator slower; lower values make it more sensitive.
Alpha Smoothing (Default: 0.07): Controls how much the ACO smooths price data. Smaller values produce smoother results.
Show Buy/Sell Signals (Default: True): Toggle to display green triangles (buy) and red triangles (sell) on the chart.
Threshold (Default: 0.0): Defines overbought (above threshold) and oversold (below threshold) levels. Adjust to widen or narrow signal zones.
EMA Base Length (Default: 10): Sets the starting length for the fastest EMA. Other EMAs are incrementally longer (12, 14, 16, etc.).
Divergence Lookback (Default: 14): Determines how far back the script looks to detect divergences.
To adjust these:
Right-click the indicator on your chart and select Settings.
Modify the inputs in the pop-up window.
Click OK to apply changes.
4. Reading the Indicator
Oscillator and EMAs: The ACO and seven EMAs are plotted in a separate panel. The EMAs (colored lines) move in a wavy pattern:
Red (fastest) to Violet (slowest) represent different response speeds.
When the faster EMAs (e.g., red, orange) are above slower ones (e.g., blue, violet), it suggests bullish momentum, and vice versa.
Zero Line: A gray wavy line at zero acts as a neutral level. The ACO above zero indicates bullish conditions; below zero indicates bearish conditions.
Overbought/Oversold Lines: Red (overbought) and green (oversold) wavy lines mark threshold levels. Extreme ACO values near these lines may suggest reversals.
Buy/Sell Signals:
Green Triangle (Bottom): Appears when the ACO crosses above the oversold threshold, suggesting a potential buy.
Red Triangle (Top): Appears when the ACO crosses below the overbought threshold, suggesting a potential sell.
Divergences:
Green Triangle (Bottom): Indicates a bullish divergence (price makes a lower low, but the EMA makes a higher low), hinting at a potential upward reversal.
Red Triangle (Top): Indicates a bearish divergence (price makes a higher high, but the EMA makes a lower high), hinting at a potential downward reversal.
5. Using Alerts
You can set alerts for key events:
Right-click the indicator and select Add Alert.
Choose a condition (e.g., "ACO Buy Signal", "Bullish Divergence").
Configure the alert settings (e.g., notify via email, app, or pop-up).
Click Create to activate the alert.
Available alert conditions:
ACO Buy Signal: When the ACO crosses above the oversold threshold.
ACO Sell Signal: When the ACO crosses below the overbought threshold.
Bullish Divergence: When a potential upward reversal is detected.
Bearish Divergence: When a potential downward reversal is detected.
6. Tips for Using the Indicator
Combine with Other Tools: Use the indicator alongside support/resistance levels, candlestick patterns, or other indicators (e.g., RSI, MACD) for confirmation.
Test on Different Timeframes: The indicator works on any timeframe (e.g., 1-minute, daily). Shorter timeframes may produce more signals but with more noise.
Practice Risk Management: Never rely solely on this indicator. Set stop-losses and position sizes to manage risk.
Backtest First: Use TradingView’s Strategy Tester (if you convert the script to a strategy) to evaluate performance on historical data.
Compliance with TradingView’s Script Publishing Rules
This description adheres to TradingView’s Script Publishing Rules (as outlined in the provided link):
No Performance Claims: The description avoids promising profits or specific results, emphasizing that the indicator is a tool for analysis.
Clear Instructions: It provides step-by-step guidance for adding, customizing, and using the indicator.
Risk Disclaimer: It notes that trading involves risks and the indicator should be used with other analysis methods.
No Misleading Terms: Terms like “buy” and “sell” are used to describe signals, not guaranteed actions.
Transparency: The description explains the indicator’s components (ACO, EMAs, signals, divergences) without exaggerating its capabilities.
No External Links: The description avoids linking to external resources or soliciting users.
Educational Tone: It focuses on educating users about the indicator’s functionality.
Limitations
Not a Standalone System: The indicator is not a complete trading strategy. It provides insights but requires additional analysis.
Lagging Nature: As with most oscillators and EMAs, signals may lag behind price movements, especially in fast markets.
False Signals: Signals and divergences may not always lead to successful trades, particularly in choppy markets.
Market Dependency: Performance varies across assets and market conditions (e.g., trending vs. ranging markets).
Gann Cycle IndicatorVersion "Beta 1.0.0"
The "Gann Cycle Indicator" helps you analyze market cycles, from the smaller ones to the bigger ones. It requires you to know how Gann used market cycles to trade efficently. It helps predict where to expect a minum or a maximum and where to expect the start of a new cycle. It works with any market and can be set up as you prefer. It takes some inputs to work properly:
1) Starting X: this is the offset on the X axis where all the cycles start from. Once you applied this indicator on your graph, you must adjust the starting position to match the start of the cycle you found on the graph.
2) Cycles (1 to 4). These are the period, expressed in candles number, of each cycles. "Cycle 1" (i.e 3,25 days) should be the smaller of the 4 while "Cycle 4" the bigger one (i.e 15 days).
In this example, we trade BTCUSD on the 15 days cycle, so 15 days on the graph is composed of 360 candles. Our bigger cycle (Cycle 4) take 360 as period. For simplicity, "Cycle 3 to 1" take each time half of the period so: Cycle 3 -> 180, Cycle 2-> 90, Cycle 1 (smaller) -> 45.
3) Trend. 0 to a rectangle trend, -1 for bearish trend and 1 for a bullish trend .
4) Trend strength. From 0 to 2, step 0.1
This parameter expresses the strength of the trend. In a bullish market (Trend set to 1) you can set Trend strength from 0 to 2 to allow the indicator to follow the current market trend
Note:
This indicator must be put in a separate Y axis so it can overaly the graph.
G. Santostasi Power Law Cycle Comparison
G. Santostasi Power Law Cycle Comparison Indicator
The "G. Santostasi Power Law Cycle Comparison" indicator is a revolutionary tool designed to provide deep insights into Bitcoin's historical price behavior, based on the renowned G. Santostasi power law model. This indicator goes beyond simple trend analysis, leveraging the power law model to analyze Bitcoin's cyclical patterns by shifting and superimposing past cycles onto the current price action.
Key Features and Insights:
Cycle-Based Comparison:
The indicator divides each Bitcoin cycle into three distinct phases:
Exponential Growth Phase (Year 1): A year of near-exponential price appreciation, often associated with the post-halving effect and the inflow of new market participants.
Exponential Correction Phase (Year 2): A sharp, quasi-exponential price decline as the market corrects from speculative highs.
Power Law Growth Phase (Years 3 and 4): A steady and predictable price increase along the power law support line, representing Bitcoin’s intrinsic long-term value trajectory.
Visual Clarity:
By overlaying past cycles onto the current cycle, the indicator highlights recurring patterns, making it easy for investors to identify similarities and deviations in price behavior. This visual comparison helps pinpoint where we are within the current cycle.
Orientation Tool for Investors:
Provides a "map" of Bitcoin's price action across cycles, enabling investors to orient themselves and make more informed decisions.
Helps distinguish between short-term noise and long-term trends, offering a broader perspective on Bitcoin’s price trajectory.
Consistency and Coherence:
The indicator’s ability to show how Bitcoin cycles adhere to a consistent framework underscores its robustness and reliability. The distinct phases of growth, correction, and stabilization align perfectly with the power law model, offering a coherent narrative of Bitcoin’s market dynamics.
Utility for Risk Management and Strategy:
Investors can use this indicator to anticipate major price movements, identify overbought or oversold conditions within the context of the cycle, and plan entry or exit points based on historical patterns.
Uniqueness of the Indicator:
Unlike traditional indicators that focus solely on momentum or trend, the G. Santostasi Power Law Cycle Comparison is rooted in a scientific approach. By applying the power law model to Bitcoin's cyclical behavior, this tool offers unparalleled insights into the underlying mechanics of price action. The ability to compare current price dynamics with past cycles provides a unique perspective, revealing patterns that are often missed by conventional technical analysis.
Who Should Use This Indicator?
Long-Term Investors: Gain confidence in understanding Bitcoin’s price action over its multi-year cycles.
Active Traders: Identify key phases within the cycle to time market entries and exits.
Analysts and Researchers: Explore the fundamental consistency of Bitcoin’s power law behavior across cycles.
The "G. Santostasi Power Law Cycle Comparison" indicator is not just a tool; it’s a lens through which Bitcoin’s intricate market cycles can be viewed, understood, and navigated. By aligning historical context with current price action, this indicator empowers investors with clarity, foresight, and actionable insights.
