Six PillarsGeneral Overview
The "Six Pillars" indicator is a comprehensive trading tool that combines six different technical analysis methods to provide a holistic view of market conditions.
These six pillars are:
Trend
Momentum
Directional Movement (DM)
Stochastic
Fractal
On-Balance Volume (OBV)
The indicator calculates the state of each pillar and presents them in an easy-to-read table format. It also compares the current timeframe with a user-defined comparison timeframe to offer a multi-timeframe analysis.
A key feature of this indicator is the Confluence Strength meter. This unique metric quantifies the overall agreement between the six pillars across both timeframes, providing a score out of 100. A higher score indicates stronger agreement among the pillars, suggesting a more reliable trading signal.
I also included a visual cue in the form of candle coloring. When all six pillars agree on a bullish or bearish direction, the candle is colored green or red, respectively. This feature allows traders to quickly identify potential high-probability trade setups.
The Six Pillars indicator is designed to work across multiple timeframes, offering a comparison between the current timeframe and a user-defined comparison timeframe. This multi-timeframe analysis provides traders with a more comprehensive understanding of market dynamics.
Origin and Inspiration
The Six Pillars indicator was inspired by the work of Dr. Barry Burns, author of "Trend Trading for Dummies" and his concept of "5 energies." (Trend, Momentum, Cycle, Support/Resistance, Scale) I was intrigued by Dr. Burns' approach to analyzing market dynamics and decided to put my own twist upon his ideas.
Comparing the Six Pillars to Dr. Burns' 5 energies, you'll notice I kept Trend and Momentum, but I swapped out Cycle, Support/Resistance, and Scale for Directional Movement, Stochastic, Fractal, and On-Balance Volume. These changes give you a more dynamic view of market strength, potential reversals, and volume confirmation all in one package.
What Makes This Indicator Unique
The standout feature of the Six Pillars indicator is its Confluence Strength meter. This feature calculates the overall agreement between the six pillars, providing traders with a clear, numerical representation of signal strength.
The strength is calculated by considering the state of each pillar in both the current and comparison timeframes, resulting in a score out of 100.
Here's how it calculates the strength:
It considers the state of each pillar in both the current timeframe and the comparison timeframe.
For each pillar, the absolute value of its state is taken. This means that both strongly bullish (2) and strongly bearish (-2) states contribute equally to the strength.
The absolute values for all six pillars are summed up for both timeframes, resulting in two sums: current_sum and alternate_sum.
These sums are then added together to get a total_sum.
The total_sum is divided by 24 (the maximum possible sum if all pillars were at their strongest states in both timeframes) and multiplied by 100 to get a percentage.
The result is rounded to the nearest integer and capped at a minimum of 1.
This calculation method ensures that the Confluence Strength meter takes into account not only the current timeframe but also the comparison timeframe, providing a more robust measure of overall market sentiment. The resulting score, ranging from 1 to 100, gives traders a clear and intuitive measure of how strongly the pillars agree, with higher scores indicating stronger potential signals.
This approach to measuring signal strength is unique in that it doesn't just rely on a single aspect of price action or volume. Instead, it takes into account multiple factors, providing a more robust and reliable indication of potential market moves. The higher the Confluence Strength score, the more confident traders can be in the signal.
The Confluence Strength meter helps traders in several ways:
It provides a quick and easy way to gauge the overall market sentiment.
It helps prioritize potential trades by identifying the strongest signals.
It can be used as a filter to avoid weaker setups and focus on high-probability trades.
It offers an additional layer of confirmation for other trading strategies or indicators.
By combining the Six Pillars analysis with the Confluence Strength meter, I've created a powerful tool that not only identifies potential trading opportunities but also quantifies their strength, giving traders a significant edge in their decision-making process.
How the Pillars Work (What Determines Bullish or Bearish)
While developing this indicator, I selected and configured six key components that work together to provide a comprehensive view of market conditions. Each pillar is set up to complement the others, creating a synergistic effect that offers traders a more nuanced understanding of price action and volume.
Trend Pillar: Based on two Exponential Moving Averages (EMAs) - a fast EMA (8 period) and a slow EMA (21 period). It determines the trend by comparing these EMAs, with stronger trends indicated when the fast EMA is significantly above or below the slow EMA.
Directional Movement (DM) Pillar: Utilizes the Average Directional Index (ADX) with a default period of 14. It measures trend strength, with values above 25 indicating a strong trend. It also considers the Positive and Negative Directional Indicators (DI+ and DI-) to determine trend direction.
Momentum Pillar: Uses the Moving Average Convergence Divergence (MACD) with customizable fast (12), slow (26), and signal (9) lengths. It compares the MACD line to the signal line to determine momentum strength and direction.
Stochastic Pillar: Employs the Stochastic oscillator with a default period of 13. It identifies overbought conditions (above 80) and oversold conditions (below 20), with intermediate zones between 60-80 and 20-40.
Fractal Pillar: Uses Williams' Fractal indicator with a default period of 3. It identifies potential reversal points by looking for specific high and low patterns over the given period.
On-Balance Volume (OBV) Pillar: Incorporates On-Balance Volume with three EMAs - short (3), medium (13), and long (21) periods. It assesses volume trends by comparing these EMAs.
Each pillar outputs a state ranging from -2 (strongly bearish) to 2 (strongly bullish), with 0 indicating a neutral state. This standardized output allows for easy comparison and aggregation of signals across all pillars.
Users can customize various parameters for each pillar, allowing them to fine-tune the indicator to their specific trading style and market conditions. The multi-timeframe comparison feature also allows users to compare pillar states between the current timeframe and a user-defined comparison timeframe, providing additional context for decision-making.
Design
From a design standpoint, I've put considerable effort into making the Six Pillars indicator visually appealing and user-friendly. The clean and minimalistic design is a key feature that sets this indicator apart.
I've implemented a sleek table layout that displays all the essential information in a compact and organized manner. The use of a dark background (#030712) for the table creates a sleek look that's easy on the eyes, especially during extended trading sessions.
The overall design philosophy focuses on presenting complex information in a simple, intuitive format, allowing traders to make informed decisions quickly and efficiently.
The color scheme is carefully chosen to provide clear visual cues:
White text for headers ensures readability
Green (#22C55E) for bullish signals
Blue (#3B82F6) for neutral states
Red (#EF4444) for bearish signals
This color coding extends to the candle coloring, making it easy to spot when all pillars agree on a bullish or bearish outlook.
I've also incorporated intuitive symbols (↑↑, ↑, →, ↓, ↓↓) to represent the different states of each pillar, allowing for quick interpretation at a glance.
The table layout is thoughtfully organized, with clear sections for the current and comparison timeframes. The Confluence Strength meter is prominently displayed, providing traders with an immediate sense of signal strength.
To enhance usability, I've added tooltips to various elements, offering additional information and explanations when users hover over different parts of the indicator.
How to Use This Indicator
The Six Pillars indicator is a versatile tool that can be used for various trading strategies. Here are some general usage guidelines and specific scenarios:
General Usage Guidelines:
Pay attention to the Confluence Strength meter. Higher values indicate stronger agreement among the pillars and potentially more reliable signals.
Use the multi-timeframe comparison to confirm signals across different time horizons.
Look for alignment between the current timeframe and comparison timeframe pillars for stronger signals.
One of the strengths of this indicator is it can let you know when markets are sideways – so in general you can know to avoid entering when the Confluence Strength is low, indicating disagreement among the pillars.
Customization Options
The Six Pillars indicator offers a wide range of customization options, allowing traders to tailor the tool to their specific needs and trading style. Here are the key customizable elements:
Comparison Timeframe:
Users can select any timeframe for comparison with the current timeframe, providing flexibility in multi-timeframe analysis.
Trend Pillar:
Fast EMA Period: Adjustable for quicker or slower trend identification
Slow EMA Period: Can be modified to capture longer-term trends
Momentum Pillar:
MACD Fast Length
MACD Slow Length
MACD Signal Length These can be adjusted to fine-tune momentum sensitivity
DM Pillar:
ADX Period: Customizable to change the lookback period for trend strength measurement
ADX Threshold: Adjustable to define what constitutes a strong trend
Stochastic Pillar:
Stochastic Period: Can be modified to change the sensitivity of overbought/oversold readings
Fractal Pillar:
Fractal Period: Adjustable to identify potential reversal points over different timeframes
OBV Pillar:
Short OBV EMA
Medium OBV EMA
Long OBV EMA These periods can be customized to analyze volume trends over different timeframes
These customization options allow traders to experiment with different settings to find the optimal configuration for their trading strategy and market conditions. The flexibility of the Six Pillars indicator makes it adaptable to various trading styles and market environments. Indicator
Volume Delta [hapharmonic]Volume Delta: Volume Delta is an indicator that simplifies how you analyze trading volumes and the percentage of buy-sell activities effortlessly.
As a trader or market analyst, understanding underlying volume and trade flows is critical. The Volume Delta indicator provides thorough insight into both the total volume and the percentage of buying versus selling within the current candlestick. This information is pivotal for those looking to gauge market momentum and sentiment more effectively.
Additionally, the Volume Delta indicator can plot the candlestick colors based on the percentage of the dominant buying or selling volume. The area between the open and close prices of the candlestick is considered 100% and fills with colors corresponding to the predominant volume at that percentage.
Volume Delta also integrates the concept of Net volume. This component is crucial as it reveals the real market sentiment by calculating the difference between the volume of trades executed at an uptick and those at a downtick.
🟠 Overview
This indicator now displays in two layouts. Recently, Tradingview introduced the "force_overlay=true" function in Pine Script , allowing plots to be moved to the main chart. Thus, all displays are from the same indicator.
🟠 USAGE
From the data displayed in 'plot.style_columns' , the peak area represents the entire volume, accounting for 100%. Within this area, there are two color levels indicating volume. If one type of volume, whether buying or selling, exceeds the other, the larger volume will be positioned behind and the smaller in front. This arrangement prevents the scenario where a higher buying volume obscures the smaller selling volume. Therefore, the two colors can be switched between the front and the back as needed.
As you can see, the 12 and 26-day Exponential Moving Averages (EMAs) are used, with the Volume Confirmation Length set at 6. Therefore, the crossing of the EMAs proceeds normally, but it is highlighted with three triangular arrows to indicate a high likelihood of a valid crossover. However, if the volume is insufficient, these markers won't be displayed, although the EMA crossover will still occur as usual. This can be useful for using volume to verify the significance of the EMA crossover.
🟠 Setting
If you enable the label, please be aware that the chart size will shrink, causing the candlestick display to become unclear. Therefore, you might need to select "Logarithmic" at the bottom right of your screen, or for mobile applications, press and hold on the price scale and choose "Logarithmic" to adjust the scale appropriately.
Enjoy! Indicator
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OrderBlock [kyleAlgo]The principle of this indicator
ATR (Average True Range) Setting: The code uses ATR to help calculate the Supertrend indicator.
Supertrend Trend Direction: Identify bullish and bearish trends with the Supertrend method.
Order Block Recognition: This part of the code recognizes and creates order blocks, visualizing them as boxes on the chart. If the number of blocks exceeds the maximum limit, old blocks will be deleted.
Function to prevent overlapping: check whether the new order block overlaps with the existing order block through the isOverlapping function.
Order block color setting: The code sets the color according to whether the block is bullish or bearish, and whether it breaks above or below. Afterwards the color of the existing order blocks will be updated.
Sensitivity settings: Through the input settings of factor and atrPeriod, the sensitivity of Supertrend and the detection of order blocks can be affected.
Visualization: Use PulseWire's box.new function to draw and visualize order blocks on the chart.
Practicality:
Support and Resistance Levels: Order blocks may represent areas of support and resistance in the market. By visualizing these areas, traders can better understand when price reversals are likely to occur.
Trading Signals: Traders may be able to identify trading signals based on the color changes of blocks and price breakouts. For example, if the price breaks above a bullish block, this could be a signal to buy.
Risk Management: By using ATR to adjust the sensitivity of Supertrend, the symbol helps traders to adjust their strategies according to market volatility. This can be used as a risk management tool to help identify stop loss and take profit points.
Multi-timeframe analysis: Although the code itself does not implement multi-timeframe analysis directly, it can be done by applying this indicator on different timeframes. This helps to analyze the market from different angles.
Flexibility and Customization: Through sensitivity settings, traders can customize the indicator according to their needs and trading style.
Reduced screen clutter: By removing overlapping order blocks and limiting the maximum number of order blocks, this code helps reduce clutter on charts, allowing traders to analyze the market more clearly.
Overall, this "Pine Script" can be a powerful analytical tool for trend traders and those looking to improve their trading decisions by visualizing key market areas. It can be used alone or combined with other indicators and trading systems for enhanced functionality.
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Extended Recursive Bands StrategyThe original indicator was created by alexgrover .
All credit goes to alexgrover for creating the indicator that this strategy uses.
This strategy was posted because there were multiple requests for it, and no strategy based on this indicator exists yet.
The Recursive Bands Indicator, an indicator specially created to be extremely efficient, I think you already know that calculation time is extra important in algorithmic trading, and this is the principal motivation for the creation of the proposed indicator. Originally described in Alex's paper "Pierrefeu, Alex (2019): Recursive Bands - A New Indicator For Technical Analysis", the indicator framework has been widely used in his previous uploaded indicators, however it would have been a shame to not upload it, however user experience being a major concern for me, I decided to add extra options, which explain the term "extended".
The Indicator
The indicator displays one upper and one lower band, every common usages applied to bands indicators such as support/resistance , breakout, trailing stop, etc, can also be applied to this one. Length controls how reactive the bands are, higher values will make the bands cross the price less often.
In order to provide more flexibility for the user alexgrover added the option to use various methods for the calculation of the indicator, therefore the indicator can use the average true range , standard deviation, average high-low range, and one totally exclusive method specially designed for this indicator.
Added logic:
We have implemented a logic that checks whether the bands have been following in the same direction for a set amount of bars. This logic must be true before it can enter trades. This is completely new code that was written by us entirely, and it makes a huge difference on strategy performance.
Strategy Long conditions:
1 — Price low is below the the lower band.
2 — The lower band keeps increasing in value until the 'lookback' setting amount of bars is reached.
Strategy Short conditions:
1 — Price high is above the upper band.
2 — The upper band keeps decreasing in value until the 'lookback' setting amount of bars is reached.
Strategy Properties:
We have set a default commission of 0.06% because these are Bybit's fees. The strategy uses an order size of 10% of equity, since drawdown is very low like this. We also use a 10 tick slippage to keep results realistic and account for this. All other settings were left as default apart from initial capital, just to decrease the size of the numbers. Strategy
Relative Bi-Directional Volatility RangeThe basic math behind this Indicator is very similar to the math behind the Relative Strength Index without using a standard deviation as used for the Relative Volatility Index. The Volatility Range is calculated by utilizing the highs and lows. However not in the same way as in the Relative Volatility Index. This approach leads to different values, but the overall result clearly reveals the intrinsic Volatility of the chart, so the user can be aware, when something fundamentally is going on behind the scenes. If the Volatility rises on positive and negative range (-100 to 100) it implies that something fundamental is changing.
An advantage of using this kind of calculation is the possibility of separating the data into positive (buy pressure) and negative (sell pressure) components. The bi-directional character shows a slightly overhang in one of the directions, which can be used to detect a trend. A Moving Average of the users choice shell smoothen the overhang of the Relative Bi-Directional Volatility and show a trend direction. Similar to the math of the Relative Strength Index as standard a Relative Moving Average is preferred. If the Moving Average is in the positive range (0 to 100) it indicates a bullish trend, else if the Moving Average is in the negative range (0 to -100) it indicates a bearish trend. External Indicators can use a provided Trend Shift Signal which switches from 0 to 1, if the trend becomes bullish or from 0 to -1, if the trend becomes bearish.
The user should know, that in this Indicator the starting point of the Moving Averages always begins at the first bar, because the starting progress is approximated appropriately. Most Moving Averages require a minimum number of bars to be calculated, which is chosen with the Moving Average Length. In this cases the length used will be automatically reduced in the background until the number of bars is sufficient to match the chosen length. So if data history is very short, the Indicator can be used never the less as good as possible.
It is feasible to switch the Indicator on a higher timeframe, while staying in a lower timeframe on the chart. This can be useful for making the indication cleaner, if the Moving Average is to choppy and shows too many false signals. On the other hand the benefit of a higher timeframe (or a higher Moving Average Length) is paid with higher latency of the signaling. So the user has to decide what the best setting in his case is.
This Indicator can be used with all kinds of charts. Even charts with percentage or negative values should work fine. Indicator
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Statistical and Financial MetricsGood morning traders!
This time I want to share with you a little script that, thanks to the use of arrays, allows you to have interesting statistical and financial insights taken from the symbol on chart and compared to those of another symbol you desire (in this case the metrics taken from the perpetual future ETHUSDT are compared to those taken from the perpetual future BTCUSDT, used as a proxy for the direction of cryptocurrency market)
By enabling "prevent repainting", the data retrieved from the compared symbol won't be on real time but they will static since they will belong to the previous closed candle
Here are the metrics you can have by storing data from a variable period of candles (by default 51):
✓ Variance (of the symbol on chart in GREEN; of the compared symbol in WHITE)
✓ Standard Deviation (of the symbol on chart in OLIVE; of the compared symbol in SILVER)
✓ Yelds (of the symbol on chart in LIME; of the compared symbol in GRAY) → yelds are referred to the previous close, so they would be calculated as the the difference between the current close and the previous one all divided by the previous close
✓ Covariance of the two datasets (in BLUE)
✓ Correlation coefficient of the two datasets (in AQUA)
✓ β (in RED) → this insight is calculated in three alternative ways for educational purpose (don't worry, the output would be the same).
WHAT IS BETA (β)?
The BETA of an asset can be interpretated as the representation (in relative terms) of the systematic risk of an asset: in other terms, it allows you to understand how big is the risk (not eliminable with portfolio diversification) of an asset based on the volatilty of its yelds.
We say that this representation is made in relative terms since it is expressed according to the market portfolio: this portfolio is hypothetically the portfolio which maximizes the diversification effects in order to kill all the specific risk of that portfolio; in this way the standard deviation calculated from the yelds of this portfolio will represent just the not-eliminable risk (the systematic risk), without including the eliminable risk (the specific risk).
The BETA of an asset is calculated as the volatilty of this asset around the volatilty of the market portfolio: being more precise, it is the covariance between the yelds of the current asset and those of the market portfolio all divided by the variance of the yelds of market portfolio.
Covariance is calculated as the product between correlation coefficient, standard deviation of the first dataset and standard deviation of the second asset.
So, as the correlation coefficient and the standard deviation of the yelds of our asset increase (it means that the yelds of our asset are very similiar to those of th market portfolio in terms of sign and intensity and that the volatility of these yelds is quite high), the value of BETA increases as well
According to the Capital Asset Pricing Model (CAPM) promoted by William Sharpe (the guy of the "Sharpe Ratio") and Harry Markowitz, in efficient markets the yeld of an asset can be calculated as the sum between the risk-free interest rate and the risk premium. The risk premium of the specific asset would be the risk premium of the market portfolio multiplied with the value of beta. It is simple: if the volatility of the yelds of an asset around the yelds of market protfolio are particularly high, investors would ask for a higher risk premium that would be translated in a higher yeld.
In this way the expected yeld of an asset would be calculated from the linear expression of the "Security Market Line": r_i = r_f + β*(r_m-r_f)
where:
r_i = expected yeld of the asset
r_f = risk free interest rate
β = beta
r_m = yeld of market portfolio
I know that considering Bitcoin as a proxy of the market portfolio involved in the calculation of Beta would be an inaccuracy since it doesn't have the property of maximum diversification (since it is a single asset), but there's no doubt that it's tying the prices of altcoins (upward and downward) thanks to the relevance of its dominance in the capitalization of cryptocurrency market. So, in the lack of a good index of cryptocurrencies (as the FTSE MIB for the italian stock market), and as long the dominance of Bitcoin will persist with this intensity, we can use Bitcoin as a proxy of the market portfolio
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Consolidation Ranges [kingthies] Consolidation Range Analysis
Published by Eric Thies, January 2021
█ Indicator Summary
This tool calculates, analyzes and plots the visualization of a relative range over a given period of time
By adding to charts, users are enabled to see the impulsive nature of market cycles, along with their efforts to consolidate thereafter
The default period is 30, and should be adjusted to users preference
The default input is the current close price, on the chosen timeframe of the chart
█ Script Source
//
//@version=4
//© kingthies || This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
study("Consolidation Ranges ", shorttitle="CR ", overlay=true)
// !<------ User Inputs ----->
src = input(close, title='Range Input (Default set to Close'), lengthEMA=input(30,title='Length'),zoneToggle = input(true, title="Toggle Zone Highlights"), iCol = color.new(#FFFFFF, 100),
// !<---- Declarations & Calculations ---- >
trndUp = float(na),trndDwn = float(na), mid = float(na), e = ema(src, lengthEMA)
trndUp := src < nz(trndUp ) and src > trndDwn ? nz(trndUp ) : high, trndDwn := src < nz(trndUp ) and src > trndDwn ? nz(trndDwn ) : low, mid := avg(trndUp, trndDwn)
// !< ---- Plotting ----->
highRange = plot(trndUp == nz(trndUp ) ? trndUp : na, color=color.white, linewidth=2, style=plot.style_linebr, title="Top of Period Range")
lowRange = plot(trndDwn == nz(trndDwn ) ? trndDwn : na, color=color.white, linewidth=2, style=plot.style_linebr, title="Bottom of Period Range")
xzone = plot(zoneToggle ? src > e ? trndDwn : trndUp : na, color=iCol, style=plot.style_circles, linewidth=0, editable=false)
fill(highRange, xzone, color=color.lime,transp=70), fill(xzone, lowRange, color=color.red,transp=70)
//
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