My-Indicator - Global Liquidity & Money Supply M2 + Time OffsetThis script is designed to visualize a global liquidity and money supply index by combining data from various regions and, optionally, central bank activity. Visualizing this data on a chart allows you to see how central banks are intervening in the financial system and how the total amount of money in the economy is changing. Let’s take a look at how it works:
Central Bank Liquidity
Shows the actions of central banks (e.g. FED, ECB) providing short-term cash to commercial banks. If you see spikes or a steady increase in these indicators, it may suggest that liquidity is being increased through intervention, which often stimulates the market.
Money Supply
M2 money supply is a monetary aggregate that includes M1 (cash and current deposits) plus savings deposits, small term deposits, and other financial instruments that, while not as liquid as M1, can be quickly converted into cash. As a result, M2 provides a broader picture of the available money in the economy, which is useful for analyzing market conditions and potential economic trends.
How does it help investors?
It allows you to quickly see when central banks are injecting additional liquidity, which could signal higher prices.
It allows you to see trends in the money supply, which informs potential changes in inflation and the economic cycle.
Combining both sets of data provides a more complete picture – both in the short and long term – which makes it easier to predict upcoming price movements.
This allows investors to better respond to changes in central bank policy and broader monetary trends, increasing their chances of making better investment decisions.
Data Collection
The script retrieves money supply data for key markets such as the USA (USM2), Europe (EUM2), China (CNM2), and Japan (JPM2). It also offers additional money supply series for other markets—like Canada (CAM2), Great Britain (GBM2), Russia (RUM2), Brazil (BRM2), Mexico (MXM2), and New Zealand (NZM2)—with extra options (e.g., Australia, India, Korea, Indonesia, Malaysia, Sweden) disabled by default. Moreover, you can enable data for central bank liquidity (such as FED, RRP, TGA, ECB, PBC, BOJ, and other central banks), which are also disabled by default.
Index Calculation
The indicator calculates the index by adding together all the enabled money supply series (and the central bank data if activated) and then scales the sum by dividing it by 1,000,000,000,000 (one trillion). This scaling makes the resulting values more manageable and easier to read on the chart.
Time Offset Feature
A key feature of the script is the time offset. With the input parameter "Time Offset (days)", the user can shift the plotted index line by a specific number of days. The script converts the given offset in days into a number of bars based on the current chart's timeframe. This allows you to adjust for the delay between liquidity changes and their effect on asset prices.
Overall, the indicator plots a line on your chart representing the global liquidity and money supply index, allowing you to visually monitor trends and better understand how liquidity and central bank actions may influence market movements.
What makes this script different from others?
Every supported market—both major regions (USA, Eurozone, China, Japan, etc.) and additional ones—is available. You can toggle each series on or off, so you can view only Money Supply data, only Central Bank Liquidity, or any custom combination.
Separated Data Groups. Inputs are organized into clear groups (“Money Supply”, “Other Money Supply”, “Central Bank Liquidity”), making it easy to focus on just the data you need without clutter.
True Day‑Based Offset. This script converts your chosen “Time Offset (days)” into actual days regardless of timeframe. Whether you’re on a 5‑minute or daily chart, the index is always shifted by exactly the number of days you specify.
在腳本中搜尋"Cycle"
[iQ]PRO Ultimate Financial Analysis Tool And System SynergyUltimate Financial Analysis Tool And System Synergy (UFATASS)
Advanced Market Insights with Cycle Analysis, Trend Forecasting, and Risk Monitoring
The Ultimate Financial Analysis Tool And System Synergy (UFATASS) is a powerful indicator designed to give traders a deeper understanding of market dynamics. By blending cutting-edge techniques from signal processing, statistics, and dynamical systems theory, UFATASS provides a unique, all-in-one solution for technical analysis.
Key Features
Cycle Detection:
Pinpoints dominant market cycles using advanced spectral analysis, helping you identify potential turning points.
Trend Analysis:
Delivers multiple regression lines to capture short-term and long-term market trends, with a customizable complexity setting for precision.
Probability Forecasts:
Uses Monte Carlo simulations to estimate the likelihood of future price movements, offering a probabilistic edge for decision-making.
Risk Monitoring:
Tracks volatility and market stability, featuring an experimental chaos indicator based on Lyapunov exponents to assess price predictability.
Customization Options
Adjust the indicator to fit your trading style:
Cycle and regression lookback periods
Complexity factor for regression sensitivity
Volatility calculation window
Forecast horizon for price predictions
Visual Outputs
Price and regression lines plotted on the main chart
Cycle details and wave visuals in a separate pane
A summary label on the last bar with key metrics (e.g., cycle length, probabilities)
Background color alerts to signal risk levels
How to Use
Incorporate UFATASS into your strategy to:
Anticipate reversals with cycle analysis
Confirm trends using regression insights
Plan entries and exits with probability forecasts
Monitor market conditions and adjust risk exposure
GKD-C APA Adaptive Fisher Transform [Loxx]The Giga Kaleidoscope GKD-C APA Adaptive Fisher Transform is a confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System."
█ GKD-C APA Adaptive Fisher Transform
APA Adaptive Fisher Transform is an adaptive cycle Fisher Transform using Ehlers Autocorrelation Periodogram Algorithm to calculate the dominant cycle period.
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average ( KAMA ) and Tushar Chande’s variable index dynamic average ( VIDYA ) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index ( RSI ), commodity channel index ( CCI ), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
What is Fisher Transform?
The Fisher Transform is a technical indicator created by John F. Ehlers that converts prices into a Gaussian normal distribution.
The indicator highlights when prices have moved to an extreme, based on recent prices. This may help in spotting turning points in the price of an asset. It also helps show the trend and isolate the price waves within a trend.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
8. Metamorphosis - a technical indicator that produces a compound signal from the combination of other GKD indicators*
*(not part of the NNFX algorithm)
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, and the Average Directional Index (ADX).
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
What is an Metamorphosis indicator?
The concept of a metamorphosis indicator involves the integration of two or more GKD indicators to generate a compound signal. This is achieved by evaluating the accuracy of each indicator and selecting the signal from the indicator with the highest accuracy. As an illustration, let's consider a scenario where we calculate the accuracy of 10 indicators and choose the signal from the indicator that demonstrates the highest accuracy.
The resulting output from the metamorphosis indicator can then be utilized in a GKD-BT backtest by occupying a slot that aligns with the purpose of the metamorphosis indicator. The slot can be a GKD-B, GKD-C, or GKD-E slot, depending on the specific requirements and objectives of the indicator. This allows for seamless integration and utilization of the compound signal within the GKD-BT framework.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
6. GKD-M - Metamorphosis module (Metamorphosis, Number 8 in the NNFX algorithm, but not part of the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal.
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Multi-Ticker CC Backtest
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Advance Trend Pressure as shown on the chart above
Confirmation 2: uf2018
Continuation: Coppock Curve
Exit: Rex Oscillator
Metamorphosis: Baseline Optimizer
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, GKD-M, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system.
? Giga Kaleidoscope Modularized Trading System Signals
Standard Entry
1. GKD-C Confirmation gives signal
2. Baseline agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
1-Candle Standard Entry
1a. GKD-C Confirmation gives signal
2a. Baseline agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
7. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
1-Candle Baseline Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Volatility/Volume Entry
1. GKD-V Volatility/Volume gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Volatility/Volume Entry
1a. GKD-V Volatility/Volume gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSVVC Bars Back' prior
Next Candle
1b. Price retraced
2b. Volatility/Volume agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Baseline agrees
Confirmation 2 Entry
1. GKD-C Confirmation 2 gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Volatility/Volume agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Confirmation 2 Entry
1a. GKD-C Confirmation 2 gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSC2C Bars Back' prior
Next Candle
1b. Price retraced
2b. Confirmation 2 agrees
3b. Confirmation 1 agrees
4b. Volatility/Volume agrees
5b. Baseline agrees
PullBack Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price is beyond 1.0x Volatility of Baseline
Next Candle
1b. Price inside Goldie Locks Zone Minimum
2b. Price inside Goldie Locks Zone Maximum
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Continuation Entry
1. Standard Entry, 1-Candle Standard Entry, Baseline Entry, 1-Candle Baseline Entry, Volatility/Volume Entry, 1-Candle Volatility/Volume Entry, Confirmation 2 Entry, 1-Candle Confirmation 2 Entry, or Pullback entry triggered previously
2. Baseline hasn't crossed since entry signal trigger
4. Confirmation 1 agrees
5. Baseline agrees
6. Confirmation 2 agrees
Descending Elliot Wave Patterns [theEccentricTrader]█ OVERVIEW
This indicator automatically draws descending Elliot Wave patterns and price projections derived from the ranges that constitute the patterns.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a close price equal to or above the price it opened.
• A red candle is one that closes with a close price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Peak and Trough Prices (Basic)
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Historic Peaks and Troughs
The current, or most recent, peak and trough occurrences are referred to as occurrence zero. Previous peak and trough occurrences are referred to as historic and ordered numerically from right to left, with the most recent historic peak and trough occurrences being occurrence one.
Range
The range is simply the difference between the current peak and current trough prices, generally expressed in terms of points or pips.
Support and Resistance
• Support refers to a price level where the demand for an asset is strong enough to prevent the price from falling further.
• Resistance refers to a price level where the supply of an asset is strong enough to prevent the price from rising further.
Support and resistance levels are important because they can help traders identify where the price of an asset might pause or reverse its direction, offering potential entry and exit points. For example, a trader might look to buy an asset when it approaches a support level , with the expectation that the price will bounce back up. Alternatively, a trader might look to sell an asset when it approaches a resistance level , with the expectation that the price will drop back down.
It's important to note that support and resistance levels are not always relevant, and the price of an asset can also break through these levels and continue moving in the same direction.
Upper Trends
• A return line uptrend is formed when the current peak price is higher than the preceding peak price.
• A downtrend is formed when the current peak price is lower than the preceding peak price.
• A double-top is formed when the current peak price is equal to the preceding peak price.
Lower Trends
• An uptrend is formed when the current trough price is higher than the preceding trough price.
• A return line downtrend is formed when the current trough price is lower than the preceding trough price.
• A double-bottom is formed when the current trough price is equal to the preceding trough price.
Muti-Part Upper and Lower Trends
• A multi-part return line uptrend begins with the formation of a new return line uptrend, or higher peak, and continues until a new downtrend, or lower peak, completes the trend.
• A multi-part downtrend begins with the formation of a new downtrend, or lower peak, and continues until a new return line uptrend, or higher peak, completes the trend.
• A multi-part uptrend begins with the formation of a new uptrend, or higher trough, and continues until a new return line downtrend, or lower trough, completes the trend.
• A multi-part return line downtrend begins with the formation of a new return line downtrend, or lower trough, and continues until a new uptrend, or higher trough, completes the trend.
Double Trends
• A double uptrend is formed when the current trough price is higher than the preceding trough price and the current peak price is higher than the preceding peak price.
• A double downtrend is formed when the current peak price is lower than the preceding peak price and the current trough price is lower than the preceding trough price.
Muti-Part Double Trends
• A multi-part double uptrend begins with the formation of a new uptrend that proceeds a new return line uptrend, and continues until a new downtrend or return line downtrend ends the trend.
• A multi-part double downtrend begins with the formation of a new downtrend that proceeds a new return line downtrend, and continues until a new uptrend or return line uptrend ends the trend.
Wave Cycles
A wave cycle is here defined as a complete two-part move between a swing high and a swing low, or a swing low and a swing high. The first swing high or swing low will set the course for the sequence of wave cycles that follow; for example a chart that begins with a swing low will form its first complete wave cycle upon the formation of the first complete swing high and vice versa.
Figure 1.
Fibonacci Retracement and Extension Ratios
The Fibonacci sequence is a series of numbers in which each number is the sum of the two preceding numbers, starting with 0 and 1. For example 0 + 1 = 1, 1 + 1 = 2, 1 + 2 = 3, and so on. Ultimately, we could go on forever but the first few numbers in the sequence are as follows: 0 , 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144.
The extension ratios are calculated by dividing each number in the sequence by the number preceding it. For example 0/1 = 0, 1/1 = 1, 2/1 = 2, 3/2 = 1.5, 5/3 = 1.6666..., 8/5 = 1.6, 13/8 = 1.625, 21/13 = 1.6153..., 34/21 = 1.6190..., 55/34 = 1.6176..., 89/55 = 1.6181..., 144/89 = 1.6179..., and so on. The retracement ratios are calculated by inverting this process and dividing each number in the sequence by the number proceeding it. For example 0/1 = 0, 1/1 = 1, 1/2 = 0.5, 2/3 = 0.666..., 3/5 = 0.6, 5/8 = 0.625, 8/13 = 0.6153..., 13/21 = 0.6190..., 21/34 = 0.6176..., 34/55 = 0.6181..., 55/89 = 0.6179..., 89/144 = 0.6180..., and so on.
1.618 is considered to be the 'golden ratio', found in many natural phenomena such as the growth of seashells and the branching of trees. Some now speculate the universe oscillates at a frequency of 0,618 Hz, which could help to explain such phenomena, but this theory has yet to be proven.
Traders and analysts use Fibonacci retracement and extension indicators, consisting of horizontal lines representing different Fibonacci ratios, for identifying potential levels of support and resistance. Fibonacci ranges are typically drawn from left to right, with retracement levels representing ratios inside of the current range and extension levels representing ratios extended outside of the current range. If the current wave cycle ends on a swing low, the Fibonacci range is drawn from peak to trough. If the current wave cycle ends on a swing high the Fibonacci range is drawn from trough to peak.
Elliot Wave Patterns
Ralph Nelson Elliott, authored his book on Elliott wave theory titled "The Wave Principle" in 1938. In this book, Elliott presented his theory of market behaviour, which he believed reflected the natural laws that govern human behaviour.
The Elliott Wave Theory is based on the principle that waves have a tendency to unfold in a specific sequence of five waves in the direction of the trend, followed by three waves leading in the opposite direction. This pattern is called a 5-3 wave pattern and is the foundation of Elliott's theory.
The five waves in the direction of the trend are labelled 1, 2, 3, 4, and 5, while the three waves in the opposite direction are labelled A, B, and C. Waves 1, 3, and 5 are impulse waves, while waves 2 and 4 are corrective waves. Waves A and C are also corrective waves, while wave B is an impulse wave.
According to Elliott, the pattern of waves is fractal in nature, meaning that it occurs on all time frames, from the smallest to the largest.
In Elliott Wave Theory, the distance that waves move from each other depends on the specific market conditions and the amplitude of the waves involved. There is no fixed rule or limit for how far waves should move from each other, however, there are several guidelines to help identify and measure wave distances. One of the most common guidelines is the Fibonacci ratios, which can be used to describe the relationships between wave lengths. For example, Elliott identified that wave 3 is typically the strongest and longest wave, and it tends to be 1.618 times the length of wave 1. Meanwhile, wave 2 tends to retrace between 50% and 78.6% of wave 1, and wave 4 tends to retrace between 38.2% and 78.6% of wave 3.
In general, the patterns are quite rare and the distances that the waves move in relation to one another is subject to interpretation. For such reasons, I have simply included the ratios of the current ranges as ratios of the preceding ranges in the wave labels and it will, ultimately, be up to the user to decide whether or not the patterns qualify as valid.
█ FEATURES
Inputs
• Show Projections
• Pattern Color
• Label Color
• Extend Current Projection Lines
█ LIMITATIONS
All green and red candle calculations are based on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. This may cause some unexpected behaviour on some markets and timeframes. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with.
Ascending Elliot Wave Patterns [theEccentricTrader]█ OVERVIEW
This indicator automatically draws ascending Elliot Wave patterns and price projections derived from the ranges that constitute the patterns.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a close price equal to or above the price it opened.
• A red candle is one that closes with a close price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Peak and Trough Prices (Basic)
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Historic Peaks and Troughs
The current, or most recent, peak and trough occurrences are referred to as occurrence zero. Previous peak and trough occurrences are referred to as historic and ordered numerically from right to left, with the most recent historic peak and trough occurrences being occurrence one.
Range
The range is simply the difference between the current peak and current trough prices, generally expressed in terms of points or pips.
Support and Resistance
• Support refers to a price level where the demand for an asset is strong enough to prevent the price from falling further.
• Resistance refers to a price level where the supply of an asset is strong enough to prevent the price from rising further.
Support and resistance levels are important because they can help traders identify where the price of an asset might pause or reverse its direction, offering potential entry and exit points. For example, a trader might look to buy an asset when it approaches a support level , with the expectation that the price will bounce back up. Alternatively, a trader might look to sell an asset when it approaches a resistance level , with the expectation that the price will drop back down.
It's important to note that support and resistance levels are not always relevant, and the price of an asset can also break through these levels and continue moving in the same direction.
Upper Trends
• A return line uptrend is formed when the current peak price is higher than the preceding peak price.
• A downtrend is formed when the current peak price is lower than the preceding peak price.
• A double-top is formed when the current peak price is equal to the preceding peak price.
Lower Trends
• An uptrend is formed when the current trough price is higher than the preceding trough price.
• A return line downtrend is formed when the current trough price is lower than the preceding trough price.
• A double-bottom is formed when the current trough price is equal to the preceding trough price.
Muti-Part Upper and Lower Trends
• A multi-part return line uptrend begins with the formation of a new return line uptrend, or higher peak, and continues until a new downtrend, or lower peak, completes the trend.
• A multi-part downtrend begins with the formation of a new downtrend, or lower peak, and continues until a new return line uptrend, or higher peak, completes the trend.
• A multi-part uptrend begins with the formation of a new uptrend, or higher trough, and continues until a new return line downtrend, or lower trough, completes the trend.
• A multi-part return line downtrend begins with the formation of a new return line downtrend, or lower trough, and continues until a new uptrend, or higher trough, completes the trend.
Double Trends
• A double uptrend is formed when the current trough price is higher than the preceding trough price and the current peak price is higher than the preceding peak price.
• A double downtrend is formed when the current peak price is lower than the preceding peak price and the current trough price is lower than the preceding trough price.
Muti-Part Double Trends
• A multi-part double uptrend begins with the formation of a new uptrend that proceeds a new return line uptrend, and continues until a new downtrend or return line downtrend ends the trend.
• A multi-part double downtrend begins with the formation of a new downtrend that proceeds a new return line downtrend, and continues until a new uptrend or return line uptrend ends the trend.
Wave Cycles
A wave cycle is here defined as a complete two-part move between a swing high and a swing low, or a swing low and a swing high. The first swing high or swing low will set the course for the sequence of wave cycles that follow; for example a chart that begins with a swing low will form its first complete wave cycle upon the formation of the first complete swing high and vice versa.
Figure 1.
Fibonacci Retracement and Extension Ratios
The Fibonacci sequence is a series of numbers in which each number is the sum of the two preceding numbers, starting with 0 and 1. For example 0 + 1 = 1, 1 + 1 = 2, 1 + 2 = 3, and so on. Ultimately, we could go on forever but the first few numbers in the sequence are as follows: 0 , 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144.
The extension ratios are calculated by dividing each number in the sequence by the number preceding it. For example 0/1 = 0, 1/1 = 1, 2/1 = 2, 3/2 = 1.5, 5/3 = 1.6666..., 8/5 = 1.6, 13/8 = 1.625, 21/13 = 1.6153..., 34/21 = 1.6190..., 55/34 = 1.6176..., 89/55 = 1.6181..., 144/89 = 1.6179..., and so on. The retracement ratios are calculated by inverting this process and dividing each number in the sequence by the number proceeding it. For example 0/1 = 0, 1/1 = 1, 1/2 = 0.5, 2/3 = 0.666..., 3/5 = 0.6, 5/8 = 0.625, 8/13 = 0.6153..., 13/21 = 0.6190..., 21/34 = 0.6176..., 34/55 = 0.6181..., 55/89 = 0.6179..., 89/144 = 0.6180..., and so on.
1.618 is considered to be the 'golden ratio', found in many natural phenomena such as the growth of seashells and the branching of trees. Some now speculate the universe oscillates at a frequency of 0,618 Hz, which could help to explain such phenomena, but this theory has yet to be proven.
Traders and analysts use Fibonacci retracement and extension indicators, consisting of horizontal lines representing different Fibonacci ratios, for identifying potential levels of support and resistance. Fibonacci ranges are typically drawn from left to right, with retracement levels representing ratios inside of the current range and extension levels representing ratios extended outside of the current range. If the current wave cycle ends on a swing low, the Fibonacci range is drawn from peak to trough. If the current wave cycle ends on a swing high the Fibonacci range is drawn from trough to peak.
Elliot Wave Patterns
Ralph Nelson Elliott, authored his book on Elliott wave theory titled "The Wave Principle" in 1938. In this book, Elliott presented his theory of market behaviour, which he believed reflected the natural laws that govern human behaviour.
The Elliott Wave Theory is based on the principle that waves have a tendency to unfold in a specific sequence of five waves in the direction of the trend, followed by three waves leading in the opposite direction. This pattern is called a 5-3 wave pattern and is the foundation of Elliott's theory.
The five waves in the direction of the trend are labelled 1, 2, 3, 4, and 5, while the three waves in the opposite direction are labelled A, B, and C. Waves 1, 3, and 5 are impulse waves, while waves 2 and 4 are corrective waves. Waves A and C are also corrective waves, while wave B is an impulse wave.
According to Elliott, the pattern of waves is fractal in nature, meaning that it occurs on all time frames, from the smallest to the largest.
In Elliott Wave Theory, the distance that waves move from each other depends on the specific market conditions and the amplitude of the waves involved. There is no fixed rule or limit for how far waves should move from each other, however, there are several guidelines to help identify and measure wave distances. One of the most common guidelines is the Fibonacci ratios, which can be used to describe the relationships between wave lengths. For example, Elliott identified that wave 3 is typically the strongest and longest wave, and it tends to be 1.618 times the length of wave 1. Meanwhile, wave 2 tends to retrace between 50% and 78.6% of wave 1, and wave 4 tends to retrace between 38.2% and 78.6% of wave 3.
In general, the patterns are quite rare and the distances that the waves move in relation to one another is subject to interpretation. For such reasons, I have simply included the ratios of the current ranges as ratios of the preceding ranges in the wave labels and it will, ultimately, be up to the user to decide whether or not the patterns qualify as valid.
█ FEATURES
Inputs
• Show Projections
• Pattern Color
• Label Color
• Extend Current Projection Lines
█ LIMITATIONS
All green and red candle calculations are based on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. This may cause some unexpected behaviour on some markets and timeframes. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with.
TradingWolf Premium OscillatorsThe TradingWolf Premium Oscillators is a unique and enhanced selection of oscillators designed to help give you an edge on the markets.
Within this one indicator you will have access to RSI, Stochastic, MACD, Awesome Oscillator, Wavetrend, Zig Zag Pivots and DPO.
Including Divergence and Hidden Divergence signals for them.
Below each indicator is explained along with its enhancements to help you understand it better.
This script comes with the 'TradingWolf Premium' to get access, read the Author’s Instructions below.
There are extensive explanations on how to use these oscillators in our documentation on the website but we will give a simple overview here.
RSI
We try not to mess with these too much because if used correctly, they are very powerful tools. The main differences you will notice is that we have highlighted the areas where you should be paying attention to the oscillator with reversal/continuation zones.
The most popular feature from these will be the 4 divergences which can be toggled on or off in the settings.
Stochastic
Stochastic we have tried to keep as similar to the original as possible, main features are being able to select alternate timeframes for it to be calculated on as well as displaying divergences.
We have created a highlighted zone for when price enters the overbought/sold territory. A lot of traders will look for crossovers happening in these areas however from our tests we have discovered entering trades as the Stochastic comes out of these areas has hugely reduced losing trades, still not a perfect strategy but it does often show that the trend is showing weakening momentum and its commonly followed by a period of sideways action before continuing in a new direction.
MACD
We have calculated a dynamic extreme range for the MACD, you will notice the green/red bars as the bottom and top of the Oscillator. These levels help adjust with the assets volatility so they will work universally on all assets and timeframes. When these levels get more narrow, this indicates there is a potential larger move to come, similar thought process to a Bollinger band squeeze.
We like the Divergence signals you receive whilst in this OB/OS range as they give more confluence behind the divergence signal that price has over extended and is looking to retrace or consolidate.
Awesome Oscillator
The Awesome Oscillator is based on some pretty simple calculations but is hugely powerful.
The 3 main use cases are crossing the 0 value, showing weakening momentum and divergence signals.
We Particularly like the Divergence signals it gives us as they tend to be more accurate than any other oscillator.
Wavetrend
Wavetrend we try describe as a more dynamic Stochastic/MACD, it moves smoother and quicker without giving too many false signals.
Conditions we use the Wavetrend for are similar to the MACD where we are looking for crossovers or divergences in the extreme bands, these shouldn’t be used to trade alone and should be paired with other pieces of confluence for a higher probability trade however this is one of our favourites.
We also have a VWAP extreme detector which we pair with the Wavetrend, helping us identify areas where price should start cooling off.
Zig Zag
The main purpose of the standard Zig Zag is to analyse historical data to be able to observe cycle's in a market's movement, this requires a bit more explanation than we can include here so please refer to our documentation on the website for further guidance.
DPO
The detrended price oscillator is unlike other oscillators, such as the Stochastic or MACD the DPO is not a momentum indicator. It instead highlights peaks and troughs in price, which are used to estimate buy and sell points in line with the historical cycle.
We personally think this is the most under-rated oscillator out there, if you simply followed the DPO above 0 for long and below for short on higher timeframes you can outperform the buy and hold return of Bitcoin (BTCUSDT)...
This is just one simple way of using the DPO there are other more in depth methods of using it within our documentation.
APA Adaptive Fisher Transform [Loxx]APA Adaptive Fisher Transform is an adaptive cycle Fisher Transform using Ehlers Autocorrelation Periodogram Algorithm to calculate the dominant cycle period.
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average ( KAMA ) and Tushar Chande’s variable index dynamic average ( VIDYA ) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index ( RSI ), commodity channel index ( CCI ), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
What is Fisher Transform?
The Fisher Transform is a technical indicator created by John F. Ehlers that converts prices into a Gaussian normal distribution.
The indicator highlights when prices have moved to an extreme, based on recent prices. This may help in spotting turning points in the price of an asset. It also helps show the trend and isolate the price waves within a trend.
Included:
Zero-line and signal cross options for bar coloring
Customizable overbought/oversold thresh-holds
Alerts
Signals
Financial Astrology Uranus SpeedWhen Uranus is accelerating in speed from retrograde to direct phase, there is a quick acceleration of price change. We can observe very clearly that in BTCUSD the most relevant price growth periods happened after the retrogradation period, when Uranus was moving direct and accelerating. Additionally, is very clear that when Uranus is decelerating in speed a period of correction or price congestion occurs. Very similar speed effect pattern was observed for multiples planets speed cycles so is clear that what is good for price growth is that most of the planets are in direct motion.
Note: The Uranus speed indicator is based on an ephemeris array that covers years 2010 to 2030, prior or after this years the speed is not available, this daily ephemeris are based on UTC time so in order to align properly with the price bars times you should set UTC as your chart timezone.
Oracle v2.0 [Market Vision]This algorithm uses Fibonacci Cycles to identify high probability reversal zones. It works on Crypto, Forex and Stocks. All timeframes are supported.
It contains several modes, such as "Equinox", "Regular", "Scalp" and "Fib". Use these modes to adjust the script to your favourite asset and timeframe.
This is a premium algorithm , that can be rented on a monthly basis.
PM if you are interested.
-Hawk
Some additional pictures:
15 minute 'Fib'
1 hour 'Equinox'
Financial Astrology Mercury LongitudeMercury energy influence the mind, the intellect and mental temperament, in mundane astrology is well know that rules: news, science, debating, trading, commerce, contracts. telecommunication, short-distance travels, among others. W. D. Gann discovered that the Mercury speed phases (stationary, retrograde, direct) transitions was very relevant as trading signals, he used the Sun conjunction retrograde Mercury to confirm the formation of top and bottoms that seems to be a relevant leading indicator in multiples markets.
As part of the Financial Astrology Research Group experiments, we created hundreds of machine learning models that try to predict daily trend direction for a research portfolio of 10 crypto-currencies and is confirmed that including the Mercury speed and aspects features (variables) in the models increase the accuracy in a consistent manner. Therefore, there is enough evidence that Mercury is one of the most powerful mid term trading cycles.
This is the first open source PIneScript indicator that is able to plot the Mercury Tropical Longitude for the years 2010-2030, we publish as open source in order to support and simplify the research of the amazing astro-traders community at TradingView that have been working manually with annotations and lines to represent the Mercury longitude zodiac signs entries and the speed phases transitions. That manual work is over. Let's move faster in our cycles research!
We encourage all astro traders to continue researching and sharing your ideas of astro cycles trading strategies with us and contribute your experiments at our Github Financial Stats exploration project
so we can improve the cosmic energy models that influence traders behaviours.
Note: The Mercury longitude is based on an ephemeris array that covers years 2010 to 2030, prior or after this years the longitude is not available, this daily ephemeris are based on UTC time so in order to align properly with the price bars times you should set UTC as your chart reference timezone.
Others astro trading indicators from Financial Astrology Research Group:
[blackcat] L2 Ehlers Cyber Cycle Trading StrategyLevel: 2
Background
John F. Ehlers introuced Cyber Cycle Trading Strategy in his "Cybernetic Analysis for Stocks and Futures" chapter 4 on 2004.
Function
With cyber cycle alone, the Trigger lags the Cycle by one bar, so that their crossing introduces at least another bar of lag. Finally, Dr Ehler concluded that we can’t execute the trade until the bar after the signal is observed. In total, that means our trade execution will be at least four bars late. If we are working with an eight-bar cycle, that means the signal will be exactly wrong. We could do better to buy when the signal says sell, and vice versa.
The difficulties arising from the lag suggest a way to build an automatic trading strategy. Suppose we choose to use the trading signal in the opposite direction of the signal. That will work if we can introduce lag so the correct signal will be given in the more general case, not just the case of an eight-bar cycle. Therefore, the Cyber Cycle trading strategy was introduced by Dr. Ehlers. It starts exactly the same as the Cyber Cycle Indicator. Dr. Ehlers then introduce the variable Signal, which is an exponential moving average of the Cycle variable. The exponential moving average generates the desired lag in the trading signal. The relationship between the alpha of an exponential moving average and lag is alpha2 = 1/ (Lag+1). This relationship is used to create the variable alpha2 in the code and the variable Signal using the exponential moving average. The trading signals using the variable Signal crossing itself delayed by one bar are exactly the opposite of the trading signals I would have used if there were no delay. But, since the variable Signal is delayed such that the net delay is less than half a cycle, the trading signals are correct to catch the next cyclic reversal. The idea of betting against the correct direction by waiting for the next cycle reversal can be pretty scary because that reversal may “never” happen because the market takes off in a trend. For this reason Dr. Ehlers included two lines of code that are escape mechanisms if we were wrong in our entry signal. These last two Signal lines of code reverse the trading position if we have been in the trade for more than eight bars and the trade has an open position loss.
Key Signal
Cycle ---> Cyber Cycle fast line
Cycle (2) ---> Cyber Cycle slow line
Signal ---> Trading signal fast line
Signal(1) ---> Trading signal slow line
Pros and Cons
100% John F. Ehlers definition translation of original work, even variable names are the same. This help readers who would like to use pine to read his book. If you had read his works, then you will be quite familiar with my code style.
Remarks
The 25th script for Blackcat1402 John F. Ehlers Week publication.
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Bitcoin: Top & Bottom Mini-AlgoHere we have a mini-algorithm that tries to show absolute 4-year-cycle top and bottom zones for the case of the BraveNewCoin Liquid Index (BLX) for Bitcoin on the weekly (W) timeframe by using several oscillators as RSI, VPCI etc. employed with a custom logic. When the background gets red we might be near to a cycle peak, and when it gets green we might be near to the absolute bottom of the current cycle. Note that only absolute top/bottoms are indicated (at least since the end of 2013), so that the current strong drop in March 2020 was correctly not tagged, as it wasn't the lowest price of the current cycle.
It is best to combine this mini-algorithm with some of my boundary indicators for BLX, e.g. "Bitcoin: Price Action Integrals", for confluence . For the next peak one could then watch for the mini-algo to go red and for the price to hit the boundary. You can change the background transparency if you like to have this indicator be more unobstrusive on the chart.
For access please contact me via DM on TradingView or on Twitter (linked on my TradingView profile and my signature).
Bitcoin Pi Cycle Top Indicator - Daily Timeframe Only1 Day Timeframe Only
The Bitcoin Pi Cycle Top Indicator has garnered attention for its historical effectiveness in identifying the timing of Bitcoin's market cycle peaks with remarkable precision, typically within a margin of 3 days.
It utilizes a specific combination of moving averages—the 111-day moving average and a 2x multiple of the 350-day moving average—to signal potential tops in the Bitcoin market.
The 111-day moving average (MA): This shorter-term MA is chosen to reflect more recent price action and trends within the Bitcoin market.
The 350-day moving average (MA) multiplied by 2: This longer-term MA is adjusted to capture broader market trends and cycles over an extended period.
The key premise behind the Bitcoin Pi Cycle Top Indicator is that a potential market top for Bitcoin can be signaled when the 111-day MA crosses above the 350-day MA (which has been doubled). Historically, this crossover event has shown a remarkable correlation with the peaks of Bitcoin's price cycles, making it a tool of interest for traders and investors aiming to anticipate significant market shifts.
#Bitcoin
WaveTrend 3D█ OVERVIEW
WaveTrend 3D (WT3D) is a novel implementation of the famous WaveTrend (WT) indicator and has been completely redesigned from the ground up to address some of the inherent shortcomings associated with the traditional WT algorithm.
█ BACKGROUND
The WaveTrend (WT) indicator has become a widely popular tool for traders in recent years. WT was first ported to PineScript in 2014 by the user @LazyBear, and since then, it has ascended to become one of the Top 5 most popular scripts on TradingView.
The WT algorithm appears to have origins in a lesser-known proprietary algorithm called Trading Channel Index (TCI), created by AIQ Systems in 1986 as an integral part of their commercial software suite, TradingExpert Pro. The software’s reference manual states that “TCI identifies changes in price direction” and is “an adaptation of Donald R. Lambert’s Commodity Channel Index (CCI)”, which was introduced to the world six years earlier in 1980. Interestingly, a vestige of this early beginning can still be seen in the source code of LazyBear’s script, where the final EMA calculation is stored in an intermediate variable called “tci” in the code.
█ IMPLEMENTATION DETAILS
WaveTrend 3D is an alternative implementation of WaveTrend that directly addresses some of the known shortcomings of the indicator, including its unbounded extremes, susceptibility to whipsaw, and lack of insight into other timeframes.
In the canonical WT approach, an exponential moving average (EMA) for a given lookback window is used to assess the variability between price and two other EMAs relative to a second lookback window. Since the difference between the average price and its associated EMA is essentially unbounded, an arbitrary scaling factor of 0.015 is typically applied as a crude form of rescaling but still fails to capture 20-30% of values between the range of -100 to 100. Additionally, the trigger signal for the final EMA (i.e., TCI) crossover-based oscillator is a four-bar simple moving average (SMA), which further contributes to the net lag accumulated by the consecutive EMA calculations in the previous steps.
The core idea behind WT3D is to replace the EMA-based crossover system with modern Digital Signal Processing techniques. By assuming that price action adheres approximately to a Gaussian distribution, it is possible to sidestep the scaling nightmare associated with unbounded price differentials of the original WaveTrend method by focusing instead on the alteration of the underlying Probability Distribution Function (PDF) of the input series. Furthermore, using a signal processing filter such as a Butterworth Filter, we can eliminate the need for consecutive exponential moving averages along with the associated lag they bring.
Ideally, it is convenient to have the resulting probability distribution oscillate between the values of -1 and 1, with the zero line serving as a median. With this objective in mind, it is possible to borrow a common technique from the field of Machine Learning that uses a sigmoid-like activation function to transform our data set of interest. One such function is the hyperbolic tangent function (tanh), which is often used as an activation function in the hidden layers of neural networks due to its unique property of ensuring the values stay between -1 and 1. By taking the first-order derivative of our input series and normalizing it using the quadratic mean, the tanh function performs a high-quality redistribution of the input signal into the desired range of -1 to 1. Finally, using a dual-pole filter such as the Butterworth Filter popularized by John Ehlers, excessive market noise can be filtered out, leaving behind a crisp moving average with minimal lag.
Furthermore, WT3D expands upon the original functionality of WT by providing:
First-class support for multi-timeframe (MTF) analysis
Kernel-based regression for trend reversal confirmation
Various options for signal smoothing and transformation
A unique mode for visualizing an input series as a symmetrical, three-dimensional waveform useful for pattern identification and cycle-related analysis
█ SETTINGS
This is a summary of the settings used in the script listed in roughly the order in which they appear. By default, all default colors are from Google's TensorFlow framework and are considered to be colorblind safe.
Source: The input series. Usually, it is the close or average price, but it can be any series.
Use Mirror: Whether to display a mirror image of the source series; for visualizing the series as a 3D waveform similar to a soundwave.
Use EMA: Whether to use an exponential moving average of the input series.
EMA Length: The length of the exponential moving average.
Use COG: Whether to use the center of gravity of the input series.
COG Length: The length of the center of gravity.
Speed to Emphasize: The target speed to emphasize.
Width: The width of the emphasized line.
Display Kernel Moving Average: Whether to display the kernel moving average of the signal. Like PCA, an unsupervised Machine Learning technique whereby neighboring vectors are projected onto the Principal Component.
Display Kernel Signal: Whether to display the kernel estimator for the emphasized line. Like the Kernel MA, it can show underlying shifts in bias within a more significant trend by the colors reflected on the ribbon itself.
Show Oscillator Lines: Whether to show the oscillator lines.
Offset: The offset of the emphasized oscillator plots.
Fast Length: The length scale factor for the fast oscillator.
Fast Smoothing: The smoothing scale factor for the fast oscillator.
Normal Length: The length scale factor for the normal oscillator.
Normal Smoothing: The smoothing scale factor for the normal frequency.
Slow Length: The length scale factor for the slow oscillator.
Slow Smoothing: The smoothing scale factor for the slow frequency.
Divergence Threshold: The number of bars for the divergence to be considered significant.
Trigger Wave Percent Size: How big the current wave should be relative to the previous wave.
Background Area Transparency Factor: Transparency factor for the background area.
Foreground Area Transparency Factor: Transparency factor for the foreground area.
Background Line Transparency Factor: Transparency factor for the background line.
Foreground Line Transparency Factor: Transparency factor for the foreground line.
Custom Transparency: Transparency of the custom colors.
Total Gradient Steps: The maximum amount of steps supported for a gradient calculation is 256.
Fast Bullish Color: The color of the fast bullish line.
Normal Bullish Color: The color of the normal bullish line.
Slow Bullish Color: The color of the slow bullish line.
Fast Bearish Color: The color of the fast bearish line.
Normal Bearish Color: The color of the normal bearish line.
Slow Bearish Color: The color of the slow bearish line.
Bullish Divergence Signals: The color of the bullish divergence signals.
Bearish Divergence Signals: The color of the bearish divergence signals.
█ ACKNOWLEDGEMENTS
@LazyBear - For authoring the original WaveTrend port on TradingView
@PineCoders - For the beautiful color gradient framework used in this indicator
@veryfid - For the inspiration of using mirrored signals for cycle analysis and using multiple lookback windows as proxies for other timeframes
Bitcoin Logarithmic Growth Curve 2025 Z-Score"The Bitcoin logarithmic growth curve is a concept used to analyze Bitcoin's price movements over time. The idea is based on the observation that Bitcoin's price tends to grow exponentially, particularly during bull markets. It attempts to give a long-term perspective on the Bitcoin price movements.
The curve includes an upper and lower band. These bands often represent zones where Bitcoin's price is overextended (upper band) or undervalued (lower band) relative to its historical growth trajectory. When the price touches or exceeds the upper band, it may indicate a speculative bubble, while prices near the lower band may suggest a buying opportunity.
Unlike most Bitcoin growth curve indicators, this one includes a logarithmic growth curve optimized using the latest 2024 price data, making it, in our view, superior to previous models. Additionally, it features statistical confidence intervals derived from linear regression, compatible across all timeframes, and extrapolates the data far into the future. Finally, this model allows users the flexibility to manually adjust the function parameters to suit their preferences.
The Bitcoin logarithmic growth curve has the following function:
y = 10^(a * log10(x) - b)
In the context of this formula, the y value represents the Bitcoin price, while the x value corresponds to the time, specifically indicated by the weekly bar number on the chart.
How is it made (You can skip this section if you’re not a fan of math):
To optimize the fit of this function and determine the optimal values of a and b, the previous weekly cycle peak values were analyzed. The corresponding x and y values were recorded as follows:
113, 18.55
240, 1004.42
451, 19128.27
655, 65502.47
The same process was applied to the bear market low values:
103, 2.48
267, 211.03
471, 3192.87
676, 16255.15
Next, these values were converted to their linear form by applying the base-10 logarithm. This transformation allows the function to be expressed in a linear state: y = a * x − b. This step is essential for enabling linear regression on these values.
For the cycle peak (x,y) values:
2.053, 1.268
2.380, 3.002
2.654, 4.282
2.816, 4.816
And for the bear market low (x,y) values:
2.013, 0.394
2.427, 2.324
2.673, 3.504
2.830, 4.211
Next, linear regression was performed on both these datasets. (Numerous tools are available online for linear regression calculations, making manual computations unnecessary).
Linear regression is a method used to find a straight line that best represents the relationship between two variables. It looks at how changes in one variable affect another and tries to predict values based on that relationship.
The goal is to minimize the differences between the actual data points and the points predicted by the line. Essentially, it aims to optimize for the highest R-Square value.
Below are the results:
snapshot
snapshot
It is important to note that both the slope (a-value) and the y-intercept (b-value) have associated standard errors. These standard errors can be used to calculate confidence intervals by multiplying them by the t-values (two degrees of freedom) from the linear regression.
These t-values can be found in a t-distribution table. For the top cycle confidence intervals, we used t10% (0.133), t25% (0.323), and t33% (0.414). For the bottom cycle confidence intervals, the t-values used were t10% (0.133), t25% (0.323), t33% (0.414), t50% (0.765), and t67% (1.063).
The final bull cycle function is:
y = 10^(4.058 ± 0.133 * log10(x) – 6.44 ± 0.324)
The final bear cycle function is:
y = 10^(4.684 ± 0.025 * log10(x) – -9.034 ± 0.063)
The main Criticisms of growth curve models:
The Bitcoin logarithmic growth curve model faces several general criticisms that we’d like to highlight briefly. The most significant, in our view, is its heavy reliance on past price data, which may not accurately forecast future trends. For instance, previous growth curve models from 2020 on TradingView were overly optimistic in predicting the last cycle’s peak.
This is why we aimed to present our process for deriving the final functions in a transparent, step-by-step scientific manner, including statistical confidence intervals. It's important to note that the bull cycle function is less reliable than the bear cycle function, as the top band is significantly wider than the bottom band.
Even so, we still believe that the Bitcoin logarithmic growth curve presented in this script is overly optimistic since it goes parly against the concept of diminishing returns which we discussed in this post:
This is why we also propose alternative parameter settings that align more closely with the theory of diminishing returns."
Now with Z-Score calculation for easy and constant valuation classification of Bitcoin according to this metric.
Created for TRW
HHT Signal Analyzer (Refined)HHT Signal Analyzer
The HHT Signal Analyzer provides a real-time, smoothed approximation of the Hilbert-Huang Transform (HHT), designed to reveal adaptive cycles and phase changes in price action. It emulates Intrinsic Mode Functions (IMFs) using a double exponential moving average (EMA) filter to extract short-term oscillatory signals from price.
This indicator is helpful for identifying subtle shifts in market behavior, such as when a trend is transitioning or weakening, and is especially effective when paired with trend-based tools like GRJMOM.
How it works:
Applies a double EMA to the price (EMA of EMA)
Calculates the difference between the fast and slow EMA to emulate IMF behavior
Amplifies the signal for clear visual feedback
Highlights cycle slope changes with background coloring (green = rising, red = falling)
Use Cases:
Use slope direction to detect early phase shifts in the market
Combine with trend indicators to confirm or fade moves
Helps visualize when the market is entering a cycle crest or trough
Best for:
Traders looking to capture short-term reversals, cycle timing, or divergence with smooth and adaptive signals
Can be used on any timeframe
Ehlers Stable Dominant Cycle Length [graylange]Stable Dominant Cycle Length – Adaptive Cycle Detection for Market Timing
This script calculates the dominant cycle length of the market using an improved version of John Ehlers' Hilbert Transform approach. Unlike traditional implementations, this version includes advanced smoothing techniques to reduce noise and prevent erratic spikes, making it more reliable for adaptive cycle-based strategies.
🔥 Key Features:
✅ Noise-Reduced Cycle Detection – Uses a Weighted Moving Average (WMA) detrending method instead of raw Hilbert Transform values to enhance stability.
✅ Adaptive Smoothing – Applies an Exponential Moving Average (EMA) to the instantaneous period, reducing excessive volatility in cycle length calculations.
✅ Phase Wrapping & Constraints – Clamps phase changes to prevent unrealistic cycle swings and division errors.
✅ Dynamic Cycle Adjustment – The dominant cycle length updates in real time, constrained within a reasonable range (6 to 50 bars) to avoid extreme peaks.
📌 How to Use It:
Identify Market Cycles – Use the dominant cycle length to determine optimal trend-following vs. mean-reversion strategies.
Enhance MESA Filters – Apply the detected cycle length to adjust Ehlers’ MESA Adaptive Moving Average (MAMA) dynamically.
Fine-Tune Alpha Settings – Reduce overfitting in cycle-based indicators by basing parameters on a stable dominant cycle estimate.
AuriumFlowAURIUM (GOLD-Weighted Average with Fractal Dynamics)
Aurium is a cutting-edge indicator that blends volume-weighted moving averages (VWMA), fractal geometry, and Fibonacci-inspired calculations to deliver a precise and holistic view of market trends. By dynamically adjusting to price and volume, Aurium uncovers key levels of confluence for trend reversals and continuations, making it a powerful tool for traders.
Key Features:
Dynamic Trendline (GOLD):
The central trendline is a weighted moving average based on price and volume, tuned using Fibonacci-based fast (34) and slow (144) exponential moving average lengths. This ensures the trendline adapts seamlessly to the flow of market dynamics.
Formula:
GOLD = VWMA(34) * Volume Factor + VWMA(144) * (1 - Volume Factor)
Fractal Highs and Lows:
Detects pivotal market points using a fractal lookback period (default 5, odd-numbered). Fractals identify local highs and lows over a defined window, capturing the structure of market cycles.
Trend Background Highlighting:
Bullish Zone: Price above the GOLD line with a green background.
Bearish Zone: Price below the GOLD line with a red background.
Buy and Sell Alerts:
Generates actionable signals when fractals align with GOLD. Bullish fractals confirm continuation or reversal in an uptrend, while bearish fractals validate a downtrend.
The Math Behind Aurium:
Volume-Weighted Adjustments:
By integrating volume into the calculation, Aurium dynamically emphasizes price levels with greater participation, giving traders insight into zones of institutional interest.
Formula:
VWMA = EMA(Close * Volume) / EMA(Volume)
Fractal Calculations:
Fractals are identified as local maxima (highs) or minima (lows) based on the surrounding bars, leveraging the natural symmetry in price behavior.
Fibonacci Relationships:
The 34 and 144 EMA lengths are Fibonacci numbers, offering a natural alignment with price cycles and market rhythms.
Ideal For:
Traders seeking a precise and intuitive indicator for aligning with trends and detecting reversals.
Strategies inspired by Bill Williams, with added volume and fractal-based insights.
Short-term scalpers and long-term trend-followers alike.
Unlock deeper market insights and trade with precision using Aurium!
Fight Or Flight Index [log] - LTF [MethodAlgo]Introduction:
"Fight Or Flight" is a robust yet user-friendly indicator designed for long-term cycle analysis and gauging market sentiment. Excluded from our Premium Indicator Collection, we are delighted to offer this tool to the community for free.
Before Use:
- This is a first-layer analysis tool, identifying potential over/under-valued price areas, not predicting future market movements.
- Tailored for long-term investment analysis. Designed for use on timeframes "1D" and above; unsupported timeframes will display nothing.
- If the asset has less 2 years of data, indicator will display nothing.
Concept:
Fight Or Flight utilizes a 2-year Moving Average (MA) as a baseline (neon white), with reference lines at 2.5x and 5x of the MA (white and neon red). By tracking asset movements through bear and bull market cycles, the indicator simplifies the identification of these cycles for long-term investors.
Instructions:
- Supported timeframes: 1D, 3D, 1W, 2W, 3W, 9W, 1M, 3M, 6M, 12M; auto-adjusts MA parameters for listed timeframes for the same result.
- Recommended to use log chart for clearer views; supports all chart types but functions optimally in log mode. or the upper channel line will look odd (but not wrong).
- Set up advice: Use the indicator in a separate chart with a fixed timeframe.
UI:
- Neon White: Indicates market bottom, a 2-year MA auto-adjusted for the supported timeframe.
- Neon Red: Indicates market top, set at 5x the 2-year MA.
- White: Sits between the top and bottom lines, serving as a support, resistance, or equilibrium line.
- Filled Area: Red (Flight) signals an overheated market, suggesting an exit; White (Fight) denotes an undervalued market, suggesting an possible entry.
Use Case:
Traders can observe price levels in comparison to the MA levels provided by the indicator for cycle analysis:
- Below Neon White: Indicates undervalue, over-pessimistic market conditions; potential for outsized returns.
- Near or above Neon Red: Suggests an overvalued or overexcited market; plan your exit strategy.
Risk Disclaimer:
Trading is inherently risky; this indicator provides indications based on historical data, and past performance does not guarantee future results. Use it as part of your confluence reference and avoid making trading decisions solely based on one indicator.
AMD-PO3-Goldbach levels [promuckaj]This script is developed on time & price, algorithmic market theory that is well explained in the book "Demystifying ICT" by Hopiplaka.
Indicators main features:
*PO3 - Goldbach(IPDA) levels which is based on the size of a price range (dealing range) as a factor of power of three (3^n).
There is PO3 numbers starting from 3 to 177147 as predefined, but also there is field for custom one so that users can experiment.
By selecting the PO3 number script calculate range low and range high using PO3 formula based on the current price and represent it on the chart into multiple levels of Goldbach numbers. At each this levels it is expected to see price that form block, fair value gap etc..., as defined in concept by ICT.
Levels:
Ext => External range
Low => Range low
High => Range high
FVG => Fair value gap
RB => Rejection block
OB => Order block
LV => Liquidity void
BR => Breaker
MB => Mitigation block
*AMD (Accumulation, Manipulation, Distribution) cycles, that can be modified by changing timings and colors.
Using PO3-Goldbach levels to identify where at the current time profile price is, there can be done trades in line with AMD cycles.
Default timings are set for Forex pairs.
*FVG, HIPPO, Displacement is well known parts of a market structure, so those three are also implemented here with some possible changes for them (colors, extension, labels...).
FVG => Fair value gap, imbalances in the market, or when buying and selling are not equal, in most cases can become a magnet for the price.
HIPPO => Hidden interbank price point objective, invention by Hopiplaka to demonstrate meaning of this "hidden" order block. It basically take the wicks of 2 consecutive bars that create a fair value gap.
DISPLACEMENT => It is practically similar to FVG but with option to measure length and strength, where in combination it will calculate and mark candle by looking back to the bars to determine the candle range standard deviation.
FEATURES:
-Multiple PO3 numbers, including special option to set your custom one
-Color and style customization
-Main levels mode, only Low, High and Equilibrium levels
-PO3 table with all PO3 calcs from multiple numbers, and mark the same levels from multiple
-Option to shift DR up or down
-Option to show you always upper/lower main DR levels (Low/High/Eq.)
NOTE:
-First of all special thanks to fxdmn that gives me idea from his indicator, how to present this through my own script.
-GB levels requires the correct symbols price calculation to work properly, everything is done by auto calc, tested well on EURUSD,SP500,DXY,Gold and BTC.
Moonhub Cycle IndexMoonhub Cycle Index is a composite index derived from three popular technical analysis indicators: Moving Average Convergence Divergence (MACD), Schaff Trend Cycle (STC), and Detrended Price Oscillator (DPO). The indicator is designed to help identify potential trends and market sentiment by combining the unique characteristics of each indicator.
Key components of the indicator include:
Input Parameters:
COEMA Length (len_DIema): The length of the Exponential Moving Average (EMA) applied to the Custom Index. Default is set to 9.
COSMA Length (len_DIsma): The length of the Simple Moving Average (SMA) applied to the Custom Index. Default is set to 30.
Indicators:
MACD: A momentum oscillator that shows the relationship between two moving averages of a security's price. It is calculated using the difference between the 12-period and 26-period EMA, and a 9-period EMA (signal line) of the MACD.
STC: A cyclic indicator that identifies cyclical trends in the market. It is calculated using the Stochastic oscillator formula applied to the close, high, and low prices over a 10-period lookback window.
DPO: A price oscillator that eliminates the trend from price data to focus on underlying cycles. It is calculated using a custom function that shifts the price by half the length and subtracts the SMA from the shifted price.
Custom Index: The composite index is calculated by taking the average of the MACD line, STC, and DPO.
COEMA and COSMA: Exponential and Simple Moving Averages applied to the Custom Index using the lengths specified by the input parameters (len_DIema and len_DIsma).
Plots: The Custom Index, COEMA, and COSMA are plotted with different colors and line widths to visualize their interaction and provide insights into potential market trends.
This Custom Index Indicator can be useful for traders who want to analyze the market using a combination of these indicators to make more informed decisions. It can also help identify potential trends and market sentiment by combining the unique characteristics of each indicator.
Price Action AverageThis indicator is perfect for scalping in 1 minute, it consists of a channel and a line that is made up of the average of the highs and lows of the price in 12 and 64 cycles.
The channel has as its center a 7 cycles SMA, when the average line (Called Signal, the purple one) crosses the upper band it is time to make a Long.
If it crosses the lower band it is time to make a short, if the line returns to the channel a signal appears to close the operation.
The indicator works with all timeframes, I use it on the 1 hour chart and I do the trades in 1 minute.
PA-Adaptive TRIX Log [Loxx]PA-Adaptive TRIX Log is a Phase Accumulation Adaptive TRIX Log indicator. This adaptation smooths the signal to catch larger trends.
What is TRIX?
TRIX is a momentum oscillator that displays the percent rate of change of a TEMA . It was developed in the early 1980's by Jack Hutson, an editor for "Technical Analysis of Stocks and Commodities" magazine. With its triple smoothing, TRIX is designed to filter insignificant price movements. In his article he uses a logarithm of a price (which is in many versions, left out).
What is the Phase Accumulation Cycle?
The phase accumulation method of computing the dominant cycle is perhaps the easiest to comprehend. In this technique, we measure the phase at each sample by taking the arctangent of the ratio of the quadrature component to the in-phase component. A delta phase is generated by taking the difference of the phase between successive samples. At each sample we can then look backwards, adding up the delta phases.When the sum of the delta phases reaches 360 degrees, we must have passed through one full cycle, on average.The process is repeated for each new sample.
The phase accumulation method of cycle measurement always uses one full cycle’s worth of historical data.This is both an advantage and a disadvantage.The advantage is the lag in obtaining the answer scales directly with the cycle period.That is, the measurement of a short cycle period has less lag than the measurement of a longer cycle period. However, the number of samples used in making the measurement means the averaging period is variable with cycle period. longer averaging reduces the noise level compared to the signal.Therefore, shorter cycle periods necessarily have a higher out- put signal-to-noise ratio.
Included
Bar coloring
2 signal options
Alerts
