Price Strength Index + RSI Buy/Sell ZonesThe Price Strength Index + RSI Buy/Sell Zones indicator is a technical analysis tool designed to evaluate the strength of a financial asset's price movement by comparing it with a series of Volume Weighted Moving Averages (VWMAs) of different lengths calculated from historical data.
Hypothesis :
The core hypothesis behind this indicator is that assessing the relationship between the current price and a range of VWMAs with varying lengths can provide valuable insights into the strength and direction of a price trend. Additionally, it incorporates Relative Strength Index (RSI) conditions to further refine potential buy and sell signals.
How It Works :
Multiple VWMA Calculation: The indicator calculates multiple VWMAs, each with a different length, using historical price data and volume. These VWMAs represent weighted moving averages over various periods, helping to capture different aspects of the price trend.
Comparison with Current Price : For each of these VWMAs, the indicator compares the current bar's price with the VWMA value. This comparison is crucial in understanding how the current price relates to historical averages, shedding light on the strength and direction of the prevailing trend.
SMA of Percentage Above VWMA : The indicator calculates the Simple Moving Average (SMA) of the percentage of prices above the various VWMAs over a specified period. This moving average smoothens out the percentage data, providing a clearer trend signal.
Buy and Sell Zones : User-defined upper and lower thresholds for the percentage of prices above the VWMAs are used to define buy and sell zones. When the percentage falls below the lower threshold, it signals a potential buy zone, suggesting a weakening trend. Conversely, when it exceeds the upper threshold, it signifies a potential sell zone, indicating a strengthening trend.
RSI Integration : The RSI is calculated for the selected price source with a specified length. When the SMA of the percentage above VWMAs falls within the buy zone and the RSI is below the lower RSI threshold, it indicates an oversold condition, potentially signaling a buy opportunity. Conversely, when the SMA falls within the sell zone and the RSI is above the upper RSI threshold, it suggests an overbought condition, possibly signaling a sell opportunity.
Color Coding : The indicator employs color-coding to visually represent the buy and sell zones, as well as extreme RSI conditions. Green color denotes the buy zone, red represents the sell zone, and orange lines indicate the median and potential reversal points.
In summary, the Price Strength Index + RSI Buy/Sell Zones indicator leverages multiple VWMAs of different lengths to assess the relationship between current prices and historical moving averages. This comprehensive analysis, coupled with RSI conditions, aids traders in identifying potential buy and sell zones, as well as extreme RSI points within those zones, enhancing the evaluation of price strength and potential trend reversals.
移動平均線
VWMA/SMA Delta Volatility (Statistical Anomaly Detector)The "VWMA/SMA Delta Volatility (Statistical Anomaly Detector)" indicator is a tool designed to detect and visualize volatility in a financial market's price data. The indicator calculates the difference (delta) between two moving averages (VWMA/SMA) and uses statistical analysis to identify anomalies or extreme price movements. Here's a breakdown of its components:
Hypothesis:
The hypothesis behind this indicator is that extreme price movements or anomalies in the market can be detected by analyzing the difference between two moving averages and comparing it to a statistically derived normal distribution. When the MA delta (the difference between two MAs: VWMA/SMA) exceeds a certain threshold based on standard deviation and the Z-score coefficient, it may indicate increased market volatility or potential trading opportunities.
Calculation of MA Delta:
The indicator calculates the MA delta by subtracting a simple moving average (SMA) from a volume-weighted moving average (VWMA) of a selected price source. This calculation represents the difference in the market's short-term and long-term trends.
Statistical Analysis:
To detect anomalies, the indicator performs statistical analysis on the MA delta. It calculates a moving average (MA) of the MA delta and its standard deviation over a specified sample size. This MA acts as a baseline, and the standard deviation is used to measure how much the MA delta deviates from the mean.
Delta Normalization:
The MA delta, lower filter, and upper filter are normalized using a function that scales them to a specific range, typically from -100 to 100. Normalization helps in comparing these values on a consistent scale and enhances their visual representation.
Visual Representation:
The indicator visualizes the results through histograms and channels:
The histogram bars represent the normalized MA delta. Red bars indicate negative and below-lower-filter values, green bars indicate positive and above-upper-filter values, and silver bars indicate values within the normal range.
It also displays a Z-score channel, which represents the upper and lower filters after normalization. This channel helps traders identify price levels that are statistically significant and potentially indicative of market volatility.
In summary, the "MA Delta Volatility (Statistical Anomaly Detector)" indicator aims to help traders identify abnormal price movements in the market by analyzing the difference between two moving averages and applying statistical measures. It can be a valuable tool for traders looking to spot potential opportunities during periods of increased volatility or to identify potential market anomalies.
Dynamic GANN Square Of 9 BandsDynamic GANN Square Of 9 Bands
Created on 3 Sept 2023
Adjust Increment Value:
Customize increment to match symbol and price characteristics for accuracy.
Green Line:
200 EMA. Identifies trend direction; moves with the prevailing trend.
Red Lines:
Mark prominent reversal levels closer to the red range; ideal for mean reversion strategies.
Crossing red levels may indicate trend continuation to the next red level.
Grey Lines:
Show immediate target reversal levels; watch for potential reversals.
Key Features:
Levels are different from Standard Deviation Lines.
Levels remain fixed and parallel, unaffected by volatility.
Despite its dynamism, it can serve as a leading indicator, revealing potential trend changes.
Primarily designed for trend-following strategies.
Additional Tips:
Use additional confirmations
Manage predefined risk and quantity
Additional Resources:
GANN Square Of 9 Pivots:
Fib TSIFib TSI = Fibonacci True Strength Index
The Fib TSI indicator uses Fibonacci numbers input for the True Strength Index moving averages. Then it is converted into a stochastic 0-100 scale.
The Fibonacci sequence is the series of numbers where each number is the sum of the two preceding numbers. 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610...
TSI uses moving averages of the underlying momentum of a financial instrument.
Stochastic is calculated by a formula of high and low over a length of time on a scale of 0-100.
How to use Fib TSI:
100 = overbought
0 = oversold
Rising = bullish
Falling = bearish
crossover 50 = bullish
crossunder 50 = bearish
The default input settings are:
2 = Stoch D smoothing
3 = TSI signal
TSI uses 2 moving averages compared with each other.
5 = TSI fastest
TSI uses 2 moving averages compared with each other.
Default value is 3/5.
color = white
8 = TSI fast
TSI uses 2 moving averages compared with each other.
Default value is 5/8.
color = blue
13 = TSI mid
TSI uses 2 moving averages compared with each other.
Default value is 8/13.
color = orange
21 = TSI slow
TSI uses 2 moving averages compared with each other.
Default value is 13/21.
color = purple
34 = TSI slowest
TSI uses 2 moving averages compared with each other.
Default value is 21/34.
color = yellow
55 = Stoch K length
All total / 5 = All TSI
color rising above 50 = bright green
color falling above 50 = mint green
color falling below 50 = bright red
color rising below 50 = pink
Up bullish reversal = green arrow up
bullish trend = green dots
Down bearish reversal = red arrow down
bearish trend = red dots
Horizontal lines:
100
75
50
25
0
2 different visual options example snapshot:
Zaree - FX Index Spread IndicatorDescription:
The "Zaree - FX Index Spread Indicator" (FISI) is a powerful technical analysis tool designed to provide insights into the spread between two selected currency indices. By calculating and visualizing the percentage difference between the values of a primary and a secondary currency index, traders can gain valuable information about potential market dynamics and trends.
Details of the Indicator:
The indicator calculates the spread percentage between a primary and a secondary currency index, allowing traders to understand the relative strength of the two indices.
Traders can choose from a list of currency indices to use as the primary and secondary indices for comparison.
The indicator offers multiple methods for setting thresholds to identify potential trading opportunities, including standard deviations, percentile ranks, historical highs and lows, and fixed thresholds.
Users can customize the length of the calculation period and choose whether to display the primary index, secondary index, and the spread percentage on the chart.
Shaded areas on the chart indicate regions where the spread percentage is above or below predefined thresholds, helping traders identify potential trading signals.
How to Use the Indicator:
Select the primary and secondary currency indices you want to compare from the provided dropdown menus. These indices will be used to calculate the spread percentage.
Choose the method for setting thresholds by selecting one of the options: "Standard Deviations," "Percentile Ranks," "Historical Highs and Lows," or "Fixed Thresholds."
Depending on the selected method, configure the relevant threshold parameters, such as historical threshold percentage, upper and lower fixed thresholds, upper and lower percentile thresholds, or the standard deviation multiplier.
Choose whether to visualize the primary index, secondary index, and spread percentage on the chart by enabling the respective options.
Observe the chart to identify potential trading signals based on the interactions between the spread percentage and the predefined thresholds.
Example of Usage:
Suppose you're interested in trading currency pairs involving the US Dollar (USD) and Euro (EUR), and you want to monitor the spread between the USD Index (USDINX) and the EUR Index (EURINX). Here's how you can use the FISI indicator:
Select "USDINX" as the primary index and "EURINX" as the secondary index.
Choose the method for setting thresholds based on your strategy. For instance, you can select "Standard Deviations" and adjust the standard deviation multiplier.
Enable the visualization of the primary index, secondary index, and spread percentage on the chart.
Observe the shaded areas on the chart. If the spread percentage crosses above the upper threshold, it may indicate a potential market overextension. Conversely, if the spread percentage crosses below the lower threshold, it could suggest an oversold market condition.
Look for instances where the spread percentage approaches or crosses the predefined thresholds. Consider these instances as potential entry or exit points for your trades.
Remember that the FISI indicator is a tool to assist you in your analysis. It's recommended to combine its insights with other technical and fundamental factors before making trading decisions. Adjust the indicator settings and thresholds based on your trading strategy and preferences.
As with any trading tool, practice and observation are key. Over time, you can refine your trading strategy by analyzing historical data and observing how the indicator performs in different market conditions.
Feel free to experiment with different settings and methods to find the configuration that aligns best with your trading style and goals.
Trade Tool VDWMA + OI RSI BasedThis indicator works only for symbols where open interest data is available.
The idea was to create a combination of Volume Delta, Open Interest, RSI, Moving Average and Support / Resistance as a unified tool.
I created a Weighted Moving Average based on the Volume Delta (VDWMA). The idea behind this was to reflect the moving average on the difference between buy and sell volume.
There are two VDWMA to determine a trend. Fast and Slow. The principle is the same as with conventional moving averages. For visualization, the candles are colored based on the following logic:
up trend = Fast VDWMA is above the Slow VDWMA and the price is above the Fast VWDWMA.
down Trend = Fast VDWMA is below the Slow VDWMA and the Short is below the Fast VDWMA
Further, support and resistance zones were defined based on the close and high prices as well as close and low prices.
A simple logic looks for divergences between RSI and price to generate first signals for possible price reversals.
Another RSI was created based on the open interest.
In combination with the conventional RSI, oversold and overbought zones were defined based on the following logic, which are marked by vertical zones on the chart.
Oversold zone = RSI is below 30 and OI RSI is above 70 or below 30 and OI opening is not greater than OI closing price
Overbought zone = RSI is above 70 and OI RSI is above 70 or below 30 and OI opening is not smaller than OI closing price
Based on this, buy and sell signals were defined.
First, the support or resistance zone must remain the same for two candles, which signals that the zone has not been breached. In addition, a divergence must occur in the RSI and the price must bounce.
newsell = resistance == resistance and high >= resistance and close < resistance and bearishDiv
newbull = support == support and low <= support and close > support and bullishDiv
The OI signaling was deliberately not included as well as the trend function. The tool should be suitable for scalping as well as for swinging. Thus, depending on the tradestyle itself to decide which points you want to trade.
Have fun with it
[sphx] FWMAI've developed a cool indicator. The indicator calculates a Fibonacci-weighted moving average (FWMA) based on a specific length. What sets it apart is that it assists me in identifying potential trend reversals. When the indicator's color changes - from red to light red or from green to light green - it's an indication that the trend might be shifting.
What makes the indicator even more interesting: While I'm keeping an eye on these color changes, I'm also observing the price behavior. I check whether the price is in a consolidation phase during the color transition. This not only helps me detect potential trend changes but also to see whether the market is in a phase of price consolidation. The combination of this information aids me in making well-informed trading decisions.
I find the indicator so useful that I've decided to make it available to the community. You can use the code and adapt it to your own trading strategies. I hope it's as helpful to you as it has been to me. Wishing all of you successful trades and the best outcomes! Let's understand the market together and trade successfully.
Adaptive MA-Bollinger HistogramVisualize two of your favorite moving averages in a fun new way.
This script calculates the distance (or difference) between the price and two moving averages of your choosing and then creates two histograms.
The two histograms are plotted inversely, so if the price is over both moving averages, one will be positive above the centerline while the other still positive will be below the centerline.
(In a future update you will have the option to have them both positive at the same time)
Next, what it does is apply Bollinger Bands (optional) to each of the histograms.
This creates a very interesting effect that can highlight areas of interest you may miss with other indicators.
You have plenty of options for coloring, the type of moving average, Bollinger Band length, and toggling features on and off.
Give it a few minutes of your time to study, and see what information you can learn from watching this indicator by comparing it with the chart.
Here is a full user guide:
Adaptive MA-Bollinger Histogram Indicator User Guide
Welcome to the user guide for the **Adaptive MA-Bollinger Histogram** indicator. This custom indicator is designed to help traders analyze trends and potential reversals in a financial instrument's price movements. The indicator combines two Moving Averages (MA) and Bollinger Bands to provide valuable insights into market conditions.
### Indicator Overview
The Adaptive MA-Bollinger Histogram indicator comprises the following components:
1. **Moving Averages (MA1 and MA2):** The indicator uses two moving averages, namely MA1 and MA2, to track different time periods. MA1 has a user-defined length (default: 50) and MA2 has a longer user-defined length (default: 100). These moving averages can be calculated using different methods such as Simple Moving Average (SMA), Exponential Moving Average (EMA), Weighted Moving Average (WMA), Volume Weighted Moving Average (VWMA), or Smoothed Moving Average (RMA).
2. **Histograms:** The indicator displays histograms based on the differences between the price source and the respective moving averages. Positive values of the histogram for MA1 are plotted in one color (default: green), while negative values are plotted in another color (default: red). Similarly, positive values of the histogram for MA2 are plotted in one color (default: blue), while negative values are plotted in another color (default: yellow). It's important to note that the histogram for MA1 is plotted positively, while the histogram for MA2 is plotted inversely.
3. **Bollinger Bands:** The indicator also features Bollinger Bands calculated based on the differences between the price source and the respective moving averages (dist1 and dist2). Bollinger Bands consist of three lines: the middle band, upper band, and lower band. These bands help visualize the potential volatility and overbought/oversold levels of the instrument's price.
### Understanding the Indicator
- **Histograms:** The histograms highlight the divergence between the price and the two moving averages. When the histogram for MA1 is positive, it indicates that the price is above the MA1. Conversely, when the histogram for MA1 is negative, it suggests that the price is below the MA1. Similarly, the histogram for MA2 is plotted inversely.
- **Bollinger Bands:** The Bollinger Bands consist of three lines. The middle band represents the moving average (MA1 or MA2), while the upper and lower bands are calculated based on the standard deviation of the differences between the price source and the moving average. The bands expand during periods of higher volatility and contract during periods of lower volatility.
### Possible Trading Ideas
1. **Trend Confirmation:** When the histograms for both MA1 and MA2 are consistently positive, it may indicate a strong bullish trend. Conversely, when both histograms are consistently negative, it may suggest a strong bearish trend.
2. **Divergence:** Divergence between price and the histograms could signal potential reversals. For example, if the price is making new highs while the histogram is declining, it might indicate a bearish divergence and a possible upcoming trend reversal.
3. **Bollinger Bands Squeeze:** A narrowing of the Bollinger Bands indicates lower volatility and often precedes a significant price movement. Traders might consider a potential breakout trade when the bands start to expand again.
4. **Overbought/Oversold Levels:** Prices touching or exceeding the upper Bollinger Band could suggest overbought conditions, while prices touching or falling below the lower Bollinger Band could indicate oversold conditions. Traders might look for reversals or corrections in such scenarios.
### Customization
- You can adjust the parameters such as MA lengths, Bollinger Bands length, width, and colors to suit your preferences and trading strategy.
### Conclusion
The **Adaptive MA-Bollinger Histogram** indicator provides a comprehensive view of price trends, divergences, and potential reversal points. Traders can use the information from this indicator to make informed decisions in their trading strategies. However, like any technical tool, it's recommended to combine this indicator with other forms of analysis and risk management techniques for optimal results.
@tk · fractal emas█ OVERVIEW
This script is an indicator that plots short, medium and long moving averages for multiple fractals. This script was based on sharks EMAs by rlvs indicator, that plots multiple rays for each fractals into the chart. The main feature of this indicator is the customizability. The calculation itself is simple as moving average.
█ MOTIVATION
The trader can customize all aspects of the plotted data. The text size, extended line length, the moving average type — exponential, simple, etc... — the length of fractal rays, line style, line width and visibility. To keep minimalist, this indicator simplifies the logic of line colors based on the purpose of each moving averages. To prevent overnoise the chart with multiple lines with multiple colors for each fractal timefraes, the trader needs to keep in mind that the all lines with the "short" moving average color for example, will represents the short moving averages lines for all fractals. This logic is applied for medium and long moving averages either.
█ CONCEPT
The trading concept to use this indicator is to make entries on uptrend or downtrend pullbacks when the asset price reaches the short, medium or long moving averages price levels. But this strategy don't works alone. It needs to be aligned together with others indicators like RSI, Chart Patterns, Support and Resistance, and so on... Even more confluences that you have, bigger are your chances to increase the probability for a successful trade. So, don't use this indicator alone. Compose a trading strategy and use it to improve your analysis.
█ CUSTOMIZATION
This indicator allows the trader to customize the following settings:
GENERAL
Text size
Changes the font size of the labels to improve accessibility.
Type: string
Options: `tiny`, `small`, `normal`, `large`.
Default: `small`
SHORT
Type
Select the Short Moving Average calculation type.
Type: string
Options: `EMA`, `SMA`, `HMA`, `VWMA`, `WMA`.
Default: `EMA`
Length
Changes the base length for the Short Moving Average calculation.
Type: int
Default: 12
Source
Changes the base source for the Short Moving Average calculation.
Type: float
Default: close
Color
The base color that will represent the Short Moving Average.
Type: color
Default: color.rgb(255, 235, 59) (yellow)
Fractal Style
The fractal ray line style.
Type: string
Options: `dotted`, `dashed`, `solid`.
Default: `dotted`
Fractal Width
The fractal ray line width.
Type: string
Options: `1px`, `2px`, `3px`, `4px`.
Default: `1px`
Fractal Ray Length
The fractal ray line length.
Type: int
Default: 12
MEDIUM
Type
Select the Medium Moving Average calculation type.
Type: string
Options: `EMA`, `SMA`, `HMA`, `VWMA`, `WMA`.
Default: `EMA`
Length
Changes the base length for the Medium Moving Average calculation.
Type: int
Default: 26
Source
Changes the base source for the Medium Moving Average calculation.
Type: float
Default: close
Color
The base color that will represent the Short Moving Average.
Type: color
Default: color.rgb(0, 230, 118) (lime)
Fractal Style
The fractal ray line style.
Type: string
Options: `dotted`, `dashed`, `solid`.
Default: `dotted`
Fractal Width
The fractal ray line width.
Type: string
Options: `1px`, `2px`, `3px`, `4px`.
Default: `1px`
Fractal Ray Length
The fractal ray line length.
Type: int
Default: 12
LONG
Type
Select the Long Moving Average calculation type.
Type: string
Options: `EMA`, `SMA`, `HMA`, `VWMA`, `WMA`.
Default: `EMA`
Length
Changes the base length for the Long Moving Average calculation.
Type: int
Default: 200
Source
Changes the base source for the Long Moving Average calculation.
Type: float
Default: close
Color
The base color that will represent the Short Moving Average.
Type: color
Default: color.rgb(255, 82, 82) (red)
Fractal Style
The fractal ray line style.
Type: string
Options: `dotted`, `dashed`, `solid`.
Default: `dotted`
Fractal Width
The fractal ray line width.
Type: string
Options: `1px`, `2px`, `3px`, `4px`.
Default: `1px`
Fractal Ray Length
The fractal ray line length.
Type: int
Default: 12
VISIBILITY
Show Fractal Rays · (Short)
Shows short moving average fractal rays.
Type: bool
Default: true
Show Fractal Rays · (Medium)
Shows short moving average fractal rays.
Type: bool
Default: true
Show Fractal Rays · (Long)
Shows short moving average fractal rays.
Type: bool
Default: true
█ FUNCTIONS
The script contains the following functions:
`fn_labelizeTimeFrame`
Labelize timeframe period in minutes and hours.
Parameters:
tf: (string) Timeframe period to be labelized.
Returns: (string) Labelized timeframe string.
`fn_builtInLineStyle`
Converts simple string to built-in line style variable value.
Parameters:
lineStyle: (string) The line style simple string.
Returns: (string) Built-in line style string value.
`fn_builtInLineWidth`
Converts simple pixel string to line width number value.
Parameters:
lineWidth: (string) The line width pixel simple string.
Returns: (string) Built-in line width number value.
`fn_requestFractal`
Requests fractal data based on `period` given an expression.
Parameters:
period: (string) The period timeframe of fractal.
expression: (series float) The expression to retrieve data from fractal.
Returns: (mixed) A result determined by `expression`.
`fn_plotRay`
Plots line after chart bars.
Parameters:
y: (float) Y axis line position.
label: (string) Label to be ploted after line.
color: (color) Line and label color.
length: (int) Line length.
show: (bool) Flag to display the line. (default: `true`)
lineStyle: (string) Line style to be applied. (default: `line.style_dotted`)
lineWidth: (int) Line width. (default: `1`)
Returns: void
`fn_plotEmaRay`
Plots moving average line for a specific period.
Parameters:
period: (simple string) Period of fractal to retrieve
expression: (series float) The expression to retrieve data from fractal.
color: (color) Line and label color.
length: (int) Line length. (default: `12`)
show: (bool) Flag to display the line. (default: `true`)
lineStyle: (string) Line style to be applied. (default: `line.style_dotted`)
lineWidth: (string) Line width. (default: `1px`)
Returns: void
`fn_plotExtendedEmaRay`
Draws extended line for current timeframe moving average.
Parameters:
coordY: (float) Extended line Y axis position.
textValue: (simple string) Extended line label text.
textColor: (color) Extended line text color.
length: (int) Extended length. (default: `5`)
Returns: void
MA Directional Table"MA Directional Table" primary objective is to analyze the direction of the trend based on two Moving Averages (MA) for various timeframes and customizing the inputs to match your preferred style.
Features:
Moving Average Type: You can select which type of Moving Average to use (SMA, EMA, VWMA).
Moving Average Lengths: You can set the lengths for the short-term and long-term moving averages.
Table Position: The indicator provides a table which can be placed at the top or bottom, and to the left or right of the chart. It shows the trend status for multiple timeframes (1 min, 5 min, 15 min, 1 hour, 4 hours, 1 day).
Table Orientation: The table can be oriented either horizontally or vertically.
Price Condition: Optionally, the table color can be set to yellow if the current price deviates from the Moving Average trend and crosses MA1.
Cloud Settings: You can opt to show a cloud between the two moving averages. The color of the cloud changes based on the direction of the trend (bullish or bearish).
Extra MA: Optionally, an extra Moving Average can be plotted on the chart.
Hybrid EMA AlgoLearner⭕️Innovative trading indicator that utilizes a k-NN-inspired algorithmic approach alongside traditional Exponential Moving Averages (EMAs) for more nuanced analysis. While the algorithm doesn't actually employ machine learning techniques, it mimics the logic of the k-Nearest Neighbors (k-NN) methodology. The script takes into account the closest 'k' distances between a short-term and long-term EMA to create a weighted short-term EMA. This combination of rule-based logic and EMA technicals offers traders a more sophisticated tool for market analysis.
⭕️Foundational EMAs: The script kicks off by generating a 50-period short-term EMA and a 200-period long-term EMA. These EMAs serve a dual purpose: they provide the basic trend-following capability familiar to most traders, akin to the classic EMA 50 and EMA 200, and set the stage for more intricate calculations to follow.
⭕️k-NN Integration: The indicator distinguishes itself by introducing k-NN (k-Nearest Neighbors) logic into the mix. This machine learning technique scans prior market data to find the closest 'neighbors' or distances between the two EMAs. The 'k' closest distances are then picked for further analysis, thus imbuing the indicator with an added layer of data-driven context.
⭕️Algorithmic Weighting: After the k closest distances are identified, they are utilized to compute a weighted EMA. Each of the k closest short-term EMA values is weighted by its associated distance. These weighted values are summed up and normalized by the sum of all chosen distances. The result is a weighted short-term EMA that packs more nuanced information than a simple EMA would.
Dynamic Point of Control (POC)The Dynamic Point of Control (POC) indicator provides traders and analysts with insightful information about price levels, volume distribution, and sentiment within a specified historical range.
Instant Updates : POC recalculates with every new bar, keeping you ahead of the game.
Market Bias : Assess market sentiment through bullish volume share.
Customization : Tailor inputs to match your unique trading strategy.
Chart Presence : See POC and related data graphically on your price chart.
How to Use :
Traders can use the Dynamic POC indicator to identify Point of Control price level, understand volume distribution, and gauge market sentiment. The indicator's visual cues and customizable parameters make it a valuable tool for technical analysis and decision-making.
EMA 9/21 with Target Price [SS]Hey everyone,
Coming back with my EMA 9/21 indicator.
My original one was removed a long time ago because I didn't really realize that there were already plenty of similar indicators (my bad!) but this one is my unique, Steversteves edition haha.
About the Indicator:
Essentially, it just combines the 2 only EMA's I ever really use (the 9 and 21) with an ATR based analysis to calculate the average range a ticker undergoes after an EMA 9 / 21 Cross-over and Cross-under.
You can see the major example being in the chart above. I use this for dramatic effect as SPY just happened to have topped at the second expected bull target on the daily. But obviously the intention for this indicator is to be used on the smaller timeframes. Let's take a look at some examples with various tickers.
TSLA:
So let's just use the previous day as example (which was Friday). If we look to the chart below:
TSLA did an EMA 9/21 crossover (bullish) in premarket. This put the immediate TP at 234.59. If we play out the chart:
We shot right to it at open.
We then did a cross under with a TP of 225.93, but that was not realized as the sentiment was too bullish. We then cross back over to the upside, putthing next TP at 238.88 which was realized:
NVDA:
On Friday, NVDA was a bit of a mess, lots of whipsaw off open. But once we finally had a cross under with 3 consecutive closes below the EMA9/21 on the 5 minute chart, it solidified the likelihood of a short:
And this was the result:
We came down to the first target, held it actually as support before finally crossing back over, setting the next TP at 475.05. We got 3 consecutive closes above the EMA 9/21, so let's see what happened:
Nothing really, we closed before we got there, but we did make progress towards it.
And last but not least SPY:
We opened the day with a bullish crossover and 3 consecutive closes above the EMA9/21, making our TP 441.38 (chart above). Let's see what happened:
We came just shy of it after the fed release volatility slammed it down, where we got a crossunder (bearish) to a TP of 436.21:
This ended up playing out, we did get a bullish crossover later in the day and so let's see what happened then:
So those are the real examples, most recent examples of trading using this. They are not all perfect, which is intentional because you need to use a bit of your own analysis, of course, when you are using this type of strategy or indicator. The EMA 9/21 is not sufficient generally on its own, but it is very helpful to gauge the immediate PA and whether the expected move aligns with your overall thesis on the day in terms of realistic target prices.
Customizability:
In terms of the customizability, this is a very basic indicator aside from the assessment of ranges. So there really is not a lot to customize.
You can toggle off and on the labels if you do not want them, you can also adjust the lookback length for the ATR assessment. The lookback length is defaulted to 500, I do really highly suggest you leave it at 500 because this has worked well for me and in back-testing, it has performed above my own expectations.
But, that said, you can take this and back-test as you wish with whatever parameters you feel are most appropriate. I haven't back-tested this on every stock known to man, my go to's are SPY, QQQ, sometimes MSFT and so it works well on those. But perhaps some others will have differing results.
Final Thoughts:
That is the indicator in a nutshell! It is really self explanatory and its likely a strategy most of you already know. This just helps to add realistic price targets and context to those cross-overs and cross-unders.
It also works fine on larger timeframes. We can see it on the 1 hour with MSFT:
On the 2 hour hour with QQQ:
And I am sure you can find other examples!
That's it everyone, safe trades!
Geometric Moving Average (GMA)Geometric Moving Average (SMA):
What it is: GMA represents a weighted average of prices over a period of time, giving more weight to new data.
How to use: Like other types of moving averages, the EMA can help identify trends. When the closing price is above GMA, it may indicate an uptrend, and when it is lower, it may indicate a downtrend.
Adaptive Trend Indicator [Quantigenics]Our Adaptive Trend Indicator is an advanced trading indicator using price and time series analysis to adapt to market trends. It calculates a weighted average of the median price and twice-smoothed average price, then applies a linear regression over twice the user-defined period, generating a trend line. This trend line represents the prevailing market direction and adjusts dynamically based on price fluctuations. When the Adaptive Trend value increases compared to the previous value, the line turns aqua, signaling an upward trend. Conversely, if it decreases, the line turns red, indicating a downward trend. This color coding provides visual guidance for traders. By combining advanced statistical techniques with real-time adaptation, the Adaptive Trend indicator provides timely trend information, supporting traders in navigating various market conditions.
Additionally, this indicator may be applied multiple times to the same chart. Traders may adjust the length of each instance to show a group of trendlines that can indicate when price action is overbought or oversold as well as support or resistance at different indicator lengths. Example below.
CRYPTO:BTCUSD
CRYPTO:BTCUSD
NASDAQ:TSLA
We hope you enjoy this indicator. Happy Trading!
AI Moving Average (Expo)█ Overview
The AI Moving Average indicator is a trading tool that uses an AI-based K-nearest neighbors (KNN) algorithm to analyze and interpret patterns in price data. It combines the logic of a traditional moving average with artificial intelligence, creating an adaptive and robust indicator that can identify strong trends and key market levels.
█ How It Works
The algorithm collects data points and applies a KNN-weighted approach to classify price movement as either bullish or bearish. For each data point, the algorithm checks if the price is above or below the calculated moving average. If the price is above the moving average, it's labeled as bullish (1), and if it's below, it's labeled as bearish (0). The K-Nearest Neighbors (KNN) is an instance-based learning algorithm used in classification and regression tasks. It works on a principle of voting, where a new data point is classified based on the majority label of its 'k' nearest neighbors.
The algorithm's use of a KNN-weighted approach adds a layer of intelligence to the traditional moving average analysis. By considering not just the price relative to a moving average but also taking into account the relationships and similarities between different data points, it offers a nuanced and robust classification of price movements.
This combination of data collection, labeling, and KNN-weighted classification turns the AI Moving Average (Expo) Indicator into a dynamic tool that can adapt to changing market conditions, making it suitable for various trading strategies and market environments.
█ How to Use
Dynamic Trend Recognition
The color-coded moving average line helps traders quickly identify market trends. Green represents bullish, red for bearish, and blue for neutrality.
Trend Strength
By adjusting certain settings within the AI Moving Average (Expo) Indicator, such as using a higher 'k' value and increasing the number of data points, traders can gain real-time insights into strong trends. A higher 'k' value makes the prediction model more resilient to noise, emphasizing pronounced trends, while more data points provide a comprehensive view of the market direction. Together, these adjustments enable the indicator to display only robust trends on the chart, allowing traders to focus exclusively on significant market movements and strong trends.
Key SR Levels
Traders can utilize the indicator to identify key support and resistance levels that are derived from the prevailing trend movement. The derived support and resistance levels are not just based on historical data but are dynamically adjusted with the current trend, making them highly responsive to market changes.
█ Settings
k (Neighbors): Number of neighbors in the KNN algorithm. Increasing 'k' makes predictions more resilient to noise but may decrease sensitivity to local variations.
n (DataPoints): Number of data points considered in AI analysis. This affects how the AI interprets patterns in the price data.
maType (Select MA): Type of moving average applied. Options allow for different smoothing techniques to emphasize or dampen aspects of price movement.
length: Length of the moving average. A greater length creates a smoother curve but might lag recent price changes.
dataToClassify: Source data for classifying price as bullish or bearish. It can be adjusted to consider different aspects of price information
dataForMovingAverage: Source data for calculating the moving average. Different selections may emphasize different aspects of price movement.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
L&S Volatility Index Refurbished█ Introduction
This is my second version of the L&S Volatility Index, hence the name "Refurbished".
The first version can be found at this link:
The reason I released a separate version is because I rewrote the source code from scratch with the aim of both improving the indicator and staying as close as possible to the original concept.
I feel that the first version was somewhat exotic and polluted in relation to the indicator originally described by the authors.
In short, the main idea remains the same, however, the way of presenting the result has been changed, reiterating what was said.
█ CONCEPTS
The L&S Volatility Index measures the volatility of price in relation to a moving average.
The indicator was originally described by Brazilian traders Alexandre Wolwacz (Stormer) and Fábio Figueiredo (Vlad) from L&S Educação Financeira.
Basically, this indicator can be used in two ways:
1. In a mean reversion strategy, when there is an unusual distance from it;
2. In a trend following strategy, when the price is in an acceptable region.
As an indicator of volatility, the greatest utility is shown in first case.
This is because it allows identifying abnormal prices, extremely stretched in relation to an average, including market crashes.
How the calculation is done:
First, the distance of the price from a given average in percentage terms is measured.
Then, the historical average volatility is obtained.
Finally the indicator is calculated through the ratio between the distance and the historical volatility.
According to the description proposed by the creators, when the L&S Volatility Index is above 30 it means that the price is "stretched".
The closer to 100 the more stretched.
When it reaches 0, it means the price is on average.
█ What to look for
Basically, you should look at non-standard prices.
How to identify it?
When the oscillator is outside the Dynamic Zone and/or the Fixed Zone (above 30), it is because the price is stretched.
Nothing on the market is guaranteed.
As with the RSI, it is not because the RSI is overbought or oversold that the price will necessarily go down or up.
It is critical to know when NOT to buy, NOT to sell or NOT to do anything.
It is always important to consider the context.
█ Improvements
The following improvements have been implemented.
It should be noted that these improvements can be disabled, thus using the indicator in the "purest" version, the same as the one conceived by the creators.
Resources:
1. Customization of limits and zones:
2. Customization of the timeframe, which can be different from the current one.
3. Repaint option (prints the indicator in real time even if the bar has not yet closed. This produces more signals).
4. Customization of price inputs. This affects the calculation.
5. Customization of the reference moving average (the moving average used to calculate the price distance).
6. Customization of the historical volatility calculation strategy.
- Accumulated ATR: calculates the historical volatility based on the accumulated ATR.
- Returns: calculates the historical volatility based on the returns of the source.
Both forms of volatility calculation have their specific utilities and applications.
Therefore, it is worthwhile to have both approaches available, and one should not necessarily replace the other.
Each method has its advantages and may be more appropriate in different contexts.
The first approach, using the accumulated ATR, can be useful when you want to take into account the implied volatility of prices over time,
reflecting broader price movements and higher impact events. It can be especially relevant in scenarios where unexpected events can drastically affect prices.
The second approach, using the standard deviation of returns, is more common and traditionally used to measure historical volatility.
It considers the variability of prices relative to their average, providing a more general measure of market volatility.
Therefore, both forms of calculation have their merits and can be useful depending on the context and specific analysis needs.
Having both options available gives users flexibility in choosing the most appropriate volatility measure for the situation at hand.
* When choosing "Accumulated ATR", if the indicator becomes difficult to see, there are 3 possibilities:
a) manually adjust the Fixed Zone value;
b) disable the Fixed Zone and use only the Dynamic Zone;
c) normalize the indicator.
7. Signal line (a moving average of the oscillator).
8. Option to normalize the indicator or not.
9. Colors to facilitate direction interpretation.
Since the L&S is a volatility indicator, it does not show whether the price is rising or falling.
This can sometimes confuse the user.
That said, the idea here is to show certain colors where the price is relative to the average, making it easier to analyze.
10. Alert messages for automations.
Volume-Weighted Kaufman's Adaptive Moving AverageThe Volume-Weighted Kaufman's Adaptive Moving Average (VW-KAMA) is a technical indicator that combines the Volume-Weighted Moving Average (VWMA) and the Kaufman's Adaptive Moving Average (KAMA) to create a more responsive and adaptable moving average.
Advantages:
Volume-Weighted: It takes into account the volume of trades, giving more weight to periods with higher trading volume, which can help filter out periods of low activity.
Adaptive: The indicator adjusts its smoothing constant based on market conditions, becoming more sensitive in trending markets and less sensitive in choppy or sideways markets.
Versatility: VW-KAMA can be used for various purposes, including trend identification, trend following, and determining potential reversal points and act as dynamic support and resistance level.
Papercuts Time Sampled Higher Timeframe EMA Without SecurityThis EMA uses a higher time sampled method instead of using security to gather higher timeframe data.
Its quite fast and worked well with the timeframes prescribed, up to 8hrs, after 8hrs, the formatting gets more complicated and i probably wouldn't use it anyway.
You can use this as a guide to avoid security and even f_security with this method.
NOTE: This includes the non repainting f_security call so that i woudl be able to check my results against what it does, thats not nessecary to keep at all.
There is some minor differences in data, but its so minor it doesnt bother me, though it would be interesting to know what the difference actually is. If anyone figures that out, leave a comment and let me know!
This is meant to be an example for others to build and learn and play with.. so enjoy!
Z-Score Weighted Moving Averages
Indicator: Z-Score Weighted Moving Averages
Another way of calculating moving average
This indicator calculates two types of weighted moving averages (WMAs) based on z-scores and inverse z-scores. The indicator's purpose is to provide traders with a unique perspective on price movements by assigning different weights to data points based on their deviations from the mean . The two types of WMAs generated are as follows:
Smoothed Weighted Moving Average (wma_smoothed):
Z-score is calculated as (price - SMA of price/(MAD*1.2533), where MAD is mean absolute deviation around the median).
Weights are assigned to each data point based on the inverse of (1 + absolute value of the z-scores). This emphasizes points closer to the mean and reduces the influence of extreme deviations.
The weighted moving average is computed using the calculated weights, giving more importance to data points with smaller z-scores and, therefore, points that are closer to the mean.
Dynamic Weighted Moving Average (wma_dynamic):
Z-scores are still calculated in the same way.
Weights are assigned based on the absolute value of the z-scores. This emphasizes data points with significant deviations from the mean, without considering the direction of deviation.
The weighted moving average is computed using these dynamic weights, giving more weight to data points that have larger absolute z-scores, irrespective of whether they are above or below the mean.
Moving Average Continuity [QuantVue]"Moving Average Continuity," is designed to compare the position of two Moving Averages (MAs) across multiple timeframes.
The user can select three timeframes and determine the length and type of both a fast and slow moving average.
The indicator will display a small table in a user selected location.
This table helps traders quickly determine if, for their selected timeframes, the faster moving average is trending above or below the slower moving average.
The “Moving Average Continuity” indicator can also send you three types of alerts;
1. All moving averages are aligned bullish
2. All moving averages are aligned bearish
3. Moving averages are mixed
Key Features:
1. Timeframes: The user can select up to three distinct timeframes to compare the moving averages.
2. Moving Average Inputs: For each MA, users can determine:
• Length of the MA
• Type of the MA - Options include EMA (Exponential Moving Average), SMA (Simple Moving Average), HMA (Hull Moving Average), WMA (Weighted Moving Average), and VWMA (Volume Weighted Moving Average).
3. Positioning: Users have the ability to adjust the table's positioning (top, middle, or bottom) and horizontal alignment (right, center, or left) on the chart overlay.
4. Runtime Error Prevention: The indicator will throw an error if the chart's timeframe exceeds the maximum selected timeframe, ensuring that comparisons are done correctly.
Give this indicator a BOOST and COMMENT your thoughts!
We hope you enjoy.
Cheers.
FIRST-HOUR TOOL V.1.8.08.23Three horizontal lines are drawn on the chart to represent session prices. These prices are calculated based on the user-specified session:
"FirstHour Session High" represents the highest price reached during the firsthour session.
"FirstHour Session Open" represents the opening price of the firsthour session
"FirstHour Session Low" represents the lowest price reached during the firsthour session.
These prices are respectively colored with light blue, light yellow, and light pink.
The chart background can change color based on whether the current time is within the specified session. If the current time is within the session, the background will be colored in semi-transparent aqua green. Otherwise, it will remain transparent.
Upward-pointing triangle markers are used to highlight points where the closing price crosses above (crossover) or below (crossunder) the session levels.
These markers appear below the corresponding bar.
They are colored based on the type of crossover:
Yellow for crossover above the "FirstHour High"
Red for crossover above the "FirstHour Open"
Green for crossover above the "FirstHour Low"
Alerts:
Alert messages are generated when crossovers or crossunders of the closing price relative to the session levels occur.
The alerts appear once per bar. Alerts are generated for the following events:
Crossover of the price above the "Session High" with the message "High First Hour Crossover."
Crossunder of the price below the "Session Open" with the message "Open First Hour Crossunder."
Crossunder of the price below the "Session Low" with the message "Low First Hour Crossunder."
Crossover of the price above the "Session Low" with the message "Low First Hour Crossover."
In summary, this indicator provides a visual representation of session prices and events, helping traders spot significant crossovers and crossunders relative to key price levels.
Author @tumiza999
White NoiseThe "White Noise" indicator is designed to visualize the dispersion of price movements around a moving average, providing insights into market noise and potential trend changes. It highlights periods of increased volatility or noise compared to the underlying trend.
Code Explanation:
Inputs:
mlen: Input for the length of the noise calculation.
hlen: Input for the length of the Hull moving average.
col_up: Input for the color of the up movement.
col_dn: Input for the color of the down movement.
Calculations:
ma: Calculate the simple moving average of the high, low, and close prices (hlc3) over the specified mlen period.
dist: Calculate the percentage distance between the hlc3 and the moving average ma, then scale it by 850. This quantifies the deviation from the moving average as a value.
sm: Smooth the calculated dist values using a weighted moving average (WMA) twice, with different weights, and subtract one from the other. This provides a smoothed representation of the dispersion.
Coloring:
col_wn: Determine the color of the bars based on whether dist is positive or negative and whether it's greater or less than the smoothed sm value. This creates color-coded columns indicating upward or downward movements with varying opacity.
col_switch: Define the color for the current trend state. It switches color when the smoothed sm crosses above or below its previous value, indicating potential trend changes.
col_switch2: Define the color for the horizontal line that separates the two trend states. It switches color based on the same crossover and crossunder conditions as col_switch.
Plots:
plot(dist): Plot the dispersion values as columns with color defined by col_wn.
plot(sm): Plot the smoothed dispersion line with a white color and thicker linewidth.
plot(sm ): Plot the previous smoothed dispersion value with a lighter white color to create a visual distinction.
Usage:
This indicator can help traders identify periods of increased market noise, visualize potential trend reversals, and assess the strength of price movements around the moving average. The colored columns and smoothed line offer insights into the ebb and flow of market sentiment, aiding in decision-making.
ps. This can be used as a long-term TPI component if you dabble in Modern Portfolio Theory (MPT)
Recommended for timeframes on the 1D or above:
