Volume Profile (Maps) [LuxAlgo]The Pine Script® developers have unleashed "maps"!
Volume Profile (Maps) displays volume, associated with price, above and below the latest price, by using maps
The largest and second-largest volume is highlighted.
🔶 USAGE
The proposed script can highlight more frequent closing prices/prices with the highest volume, potentially highlighting more liquid areas. The prices with the highest associated volume (in red and orange in the indicator) can eventually be used as support/resistance levels.
Voids within the volume profile can highlight large price displacements (volatile variations).
🔶 CONCEPTS
🔹 Maps
A map object is a collection that consists of key - value pairs
Each key is unique and can only appear once. When adding a new value with a key that the map already contains, that value replaces the old value associated with the key .
You can change the value of a particular key though, for example adding volume (value) at the same price (key), the latter technique is used in this script.
Volume is added to the map, associated with a particular price (default close, can be set at high, low, open,...)
When the map already contains the same price (key), the value (volume) is added to the existing volume at the associated price.
A map can contain maximum 50K values, which is more than enough to hold 20K bars (Basic 5K - Premium plan 20K), so the whole history can be put into a map.
🔹 Visible line/box limit
We can only display maximum 500 line.new() though.
The code locates the current (last) close, and displays volume values around this price, using lines, for example 250 lines above and 250 lines below current price.
If one side contains fewer values, the other side can show more lines, taking the maximum out of the 500 visible line limitation.
Example (max. 500 lines visible)
• 100 values below close
• 2000 values above close
-> 100 values will be displayed below close
-> 400 remaining -> 400 values will be displayed above close
Pushing the limits even further, when ' Amount of bars ' is set higher than 500, boxes - box.new() - will be used as well.
These have a limit of 500 as well, bringing the total limit to 1000.
Note that there are visual differences when boxes overlap against lines.
If this is confusing, please keep ' Amount of bars ' at max. 500 (then only lines will be used).
🔹 Rounding function
This publication contains 2 round functions, which can be used to widen the Volume Profile
Round
• "Round" set at zero -> nothing changes to the source number
• "Round" set below zero -> x digit(s) after the decimal point, starting from the right side, and rounded.
• "Round" set above zero -> x digit(s) before the decimal point, starting from the right side, and rounded.
Example: 123456.789
0->123456.789
1->123456.79
2->123456.8
3->123457
-1->123460
-2->123500
Step
Another option is custom steps.
After setting "Round" to "Step", choose the desired steps in price,
Examples
• 2 -> 1234.00, 1236.00, 1238.00, 1240.00
• 5 -> 1230.00, 1235.00, 1240.00, 1245.00
• 100 -> 1200.00, 1300.00, 1400.00, 1500.00
• 0.05 -> 1234.00, 1234.05, 1234.10, 1234.15
•••
🔶 FEATURES
🔹 Adjust position & width
🔹 Table
The table shows the details:
• Size originalMap : amount of elements in original map
• # higher: amount of elements, higher than last "close" (source)
• index "close" : index of last "close" (source), or # element, lower than source
• Size newMap : amount of elements in new map (used for display lines)
• # higher : amount of elements in newMap, higher than last "close" (source)
• # lower : amount of elements in newMap, lower than last "close" (source)
🔹 Volume * currency
Let's take as example BTCUSD, relative to USD, 10 volume at a price of 100 BTCUSD will be very different than 10 volume at a price of 30000 (1K vs. 300K)
If you want volume to be associated with USD, enable Volume * currency . Volume will then be multiplied by the price:
• 10 volume, 1 BTC = 100 -> 1000
• 10 volume, 1 BTC = 30K -> 300K
Disabled
Enabled
🔶 DETAILS
🔹 Put
When the map doesn't contain a price, it will be added, using map.put(id, key, value)
In our code:
map.put(originalMap, price, volume)
or
originalMap.put(price, volume)
A key (price) is now associated with a value (volume) -> key : value
Since all keys are unique, we don't have to know its position to extract the value, we just need to know the key -> map.get(id, key)
We use map.get() when a certain key already exists in the map, and we want to add volume with that value.
if originalMap.contains(price)
originalMap.put(price, originalMap.get(price) + volume)
-> At the last bar, all prices (source) are now associated with volume.
🔹 Copy & sort
Next, every key of the map is copied and sorted (array of keys), after which the index (idx) is retrieved of last (current) price.
copyK = originalMap.keys().copy()
copyK.sort()
idx = copyK.binary_search_leftmost(src)
Then left and right side of idx is investigated to show a maximum amount of lines at both sides of last price.
🔹 New map & display
The keys (from sorted array of copied keys) that will be displayed are put in a new map, with the associated volume values from the original map.
newMap = map.new()
🔹 Re-cap
• put in original amp (price key, volume value)
• copy & sort
• find index of last price
• fetch relevant keys left/right from that index
• put keys in new map and fetch volume associated with these keys (from original map)
Simple example (only show 5 lines)
bar 0, price = 2, volume = 23
bar 1, price = 4, volume = 3
bar 2, price = 8, volume = 21
bar 3, price = 6, volume = 7
bar 4, price = 9, volume = 13
bar 5, price = 5, volume = 85
bar 6, price = 3, volume = 13
bar 7, price = 1, volume = 4
bar 8, price = 7, volume = 9
Original map:
Copied keys array:
Sorted:
-> 5 keys around last price (7) are fetched (5, 6, 7, 8, 9)
-> keys are placed into new map + volume values from original map
Lastly, these values are displayed.
🔶 SETTINGS
Source : Set source of choice; default close , can be set as high , low , open , ...
Volume & currency : Enable to multiply volume with price (see Features )
Amount of bars : Set amount of bars which you want to include in the Volume Profile
Max lines : maximum 1000 (if you want to use only lines, and no boxes -> max. 500, see Concepts )
🔹 Round -> ' Round/Step '
Round -> see Concepts
Step -> see Concepts
🔹 Display Volume Profile
Offset: shifts the Volume Profile (max. 500 bars to the right of last bar, see Features )
Max width Volume Profile: largest volume will be x bars wide, the rest is displayed as a ratio against largest volume (see Features )
Show table : Show details (see Features )
🔶 LIMITATIONS
• Lines won't go further than first bar (coded).
• The Volume Profile can be placed maximum 500 bar to the right of last price.
• Maximum 500 lines/boxes can be displayed
Educational
All Candlestick Patterns on Backtest [By MUQWISHI]▋ INTRODUCTION :
The “All Candlestick Patterns on Backtest” indicator generates a table that offers a clear visualization of the historical return percentages for each candlestick pattern strategy over a specified time period. This table serves as an organized resource, serving as a launching point for in-depth research into candle formations. It may help to rectify any misconceptions surrounding candlestick patterns, refine trading approaches, and it could be foundation to make informed decisions in trading journey.
_______________________
▋ OVERVIEW:
_______________________
▋ CREDIT:
Credit to public technical “*All Candlestick Patterns*” indicator.
_______________________
▋ TABLE:
_______________________
▋ CHART:
_______________________
▋ INDICATOR SETTINGS:
#Section One: Table Setting
#Section Two: Backtest Setting
(1) Backtest Starting Period.
Note: If the datetime of the first candle on the chart is after the entreated datetime, the calculation will start from the first candle on the chart.
(2) Initial Equity ($).
(3) Leverage: Current Equity x Leverage Value.
(4) Entry Mode:
- “At Close”: Execute entry order as soon as the candle confirmed.
- “Breakout High (Low for Short)”: Stop limit buy order, entry order will be executed as soon as the next candle breakout the high of last pattern’s candle (low for short)
(5) Cancel Entry Within Bars: This option is applicable with {Entry Mode = Breakout High (Low for Short)}, to cancel the Entry Order if it's not executed within certain selected number of bars.
(6) Stoploss Range: the range refers to high of pattern - low of pattern.
(7) Risk:Reward: the calculation of risk:reward range start from entry price level. For example: A pattern triggered with range 10 points, and entry price is 100.
- For 1:1~risk:reward would the stoploss at 90 and takeprofit at 110.
- For 1:3~risk:reward would the stoploss at 90 and takeprofit at 130.
#Section Three: Technical & Candle Patterns
_______________________
▋ Comments:
This table was developed for research and educational purposes.
Candlestick patterns are almost similar as seen in “*All Candlestick Patterns*” indicator.
The table results should not be taken as a major concept to build a trading decision.
Personally, I see candlestick patterns as a means to comprehend the psychology of the market, and help to follow the price action.
Please let me know if you have any questions.
Thank you.
CE - 42MACRO Equity Factor Table This is Part 1 of 2 from the 42MACRO Recreation Series
The CE - 42MACRO Equity Factor Table is a whole toolbox packaged in a single indicator.
It aims to provide a probabilistic insight into the market realized GRID Macro Regime, use a multiplex of important Assets and Indices to form a high probability Implied Correlation expectation and allows to derive extra market insights by showing the most important aggregates and their performance over multiple timeframes... and what that might mean for the whole market direction, as well as the underlying asset.
WARNING
By the nature of the macro regimes, the outcomes are more accurate over longer Chart Timeframes (Week to Months).
However, it is also a valuable tool to form a proper,
market realized, short to medium term bias.
NOTE
This Indicator is intended to be used alongside the 2nd part "CE - 42MACRO Yield and Macro"
for a more wholistic approach and higher accuracy.
Due to coding limitations they can not be merged into one Indicator.
Methodology:
The Equity Factor Table tracks specifically chosen Assets to identify their performance and add the combined performances together to visualize 42MACRO's GRID Equity Model.
For this it uses the below Assets, with more to come:
Dividend Compounders ( AMEX:SPHD )
Mid Caps ( AMEX:VO )
Emerging Markets ( AMEX:EEM )
Small Caps ( AMEX:IWM )
Mega Cap Growth ( NASDAQ:QQQ )
Brazil ( AMEX:EWZ )
United Kingdom ( AMEX:EWU )
Growth ( AMEX:IWF )
United States ( AMEX:SPY )
Japan ( AMEX:DXJ )
Momentum ( AMEX:MTUM )
China ( AMEX:FXI )
Low Beta ( AMEX:SPLV )
International ex-US ( NASDAQ:ACWX )
India ( AMEX:INDA )
Eurozone ( AMEX:EZU )
Quality ( AMEX:QUAL )
Size ( AMEX:OEF )
Functionalities:
1. Correlations
Takes a measure of Cross Market Correlations
2. Implied Trend
Calculates the trend for each Asset and uses the Correlation to obtain the Implied Trend for the underlying Asset
There are multiple functionalities to enhance Signal Speed and precision...
Reading a signal only over a certain threshold, otherwise being colored in gray to signal noise or unclear market behavior
Normalization of Signal
Double Normalization of Signal for more Speed... ideal for the Crypto Market
Using an additional Hull Moving Average to enhance Signal Speed
Additional simple Background coloring to get a Signal from the HMA
Barcoloring based on the Implied Correlation
3. Equity Factor Table
Shows market realized Asset performance
Provides the approximate realized GRID market regimes
Informs about "Risk ON" and "Risk OFF" market states
Now into the juicy stuff...
Visuals:
There is a variety of options to change visual settings of what is plotted and where
+ additional considerations.
Everything that is relevant in the underlying logic which can improve comprehension can be visualized with these options.
More to come
Market Correlation:
The Market Correlation Table takes the Correlation of all the Assets to the Asset on the Chart,
it furthermore uses the Normalized KAMA Oscillator by IkkeOmar to analyse the current trend of every single Asset.
(To enhance the Signal you can apply the mentioned Indicator on the relevant Assets to find your target Asset movements that you intend to capture...
and then change the length of the Indicator in here)
It then Implies a Correlation based on the Trend and the Correlation to give a probabilistically adjusted expectation for the future Chart Asset Movement.
This is strengthened by taking the average of all Implied Trends.
Thus the Correlation Table provides valuable insights about probabilistically likely Movement of the Asset over the defined time duration,
providing alpha for Traders and Investors alike.
Equity Factors:
The table provides valuable information about the current market environment (whether it's risk on or risk off),
the rough GRID models from 42MACRO and the actual market performance.
This allows you to obtain a deeper understanding of how the market works and makes it simple to identify the actual market direction,
makes it possible to derive overall market Health and shows market strength or weakness.
Utility:
The Equity Factor Table is divided in 4 Sections which are the GRID regimes:
Economic Growth:
Goldilocks
Reflation
Economic Contraction:
Inflation
Deflation
Top 5 Equity Factors:
Are the values green for a specific Column?
If so then the market reflects the corresponding GRID behavior.
Bottom 5 Equity Factors:
Are the values red for a specific Column?
If so then the market reflects the corresponding GRID behavior.
So if we have Goldilocks as current regime we would see green values in the Top 5 Goldilocks Cells and red values in the Bottom 5 Goldilocks Cells.
You will find that Reflation will look similar, as it is also a sign of Economic Growth.
Same is the case for the two Contraction regimes.
This whole Indicator, as well as the second part, is based to a majority on 42MACRO's models.
I only brought them into TV and added things on top of it.
If you have questions or need a more in-depth guide DM me.
Will make a guide to all functionalities if necessity becomes apparent.
GM
ICT Clean Midnight [dR-Algo]
Are you a trader who values clean charts and precise indicators? Are you an avid follower of ICT Concepts? If so, the Midnight Marker is tailored for you. This ultra-simple, highly effective TradingView script draws a nearly transparent blue line at midnight on your chart, keeping your interface as clean as possible while delivering essential information.
Why is "ICT Clean Midnight" so Special?
Focus on Price Action: The minimalist design ensures that you can focus solely on price action, which is a core principle of ICT teachings.
Easy Back Testing: Whether you're trading live or back-testing strategies, the midnight marker helps you quickly identify key time points.
Customizable: Though designed to be subtle, the line's color and opacity can be easily customized to suit your charting needs.
This indicator embodies ICT's principle of maintaining a clutter-free, focus-driven trading environment. Perfect for both novice traders wanting to adopt ICT concepts and seasoned traders looking for minimalistic yet effective tools.
Linear On MACDUnlocking the Magic of Linear Regression in TradingView
In the ever-evolving world of financial markets, traders and investors seek effective tools to gauge price movements, make informed decisions, and achieve their financial goals. One such tool that has proven its worth over time is linear regression, a mathematical concept that has found its way into technical analysis and trading strategies. In this blog post, we will explore the magic behind linear regression, delve into its history, and understand how it's widely used as a technical indicator.
The Birth of Linear Regression: From Mathematics to Trading
Linear regression is a statistical method that aims to model the relationship between two variables by fitting a linear equation to observed data. The formula for a linear regression line is typically expressed as y = a + bx, where y is the dependent variable, x is the independent variable, a is the intercept, and b is the slope.
While the roots of linear regression trace back to the field of statistics, it didn't take long for traders and investors to recognize its potential in the financial world. By applying linear regression to historical price data, traders can identify trends, assess the relationship between variables, and even predict potential future price levels.
The Linear On MACD Strategy
Let's take a closer look at a powerful example of how linear regression is employed in a trading strategy right within TradingView. The "Linear On MACD" strategy harnesses the potential of linear regression in conjunction with the Moving Average Convergence Divergence (MACD) indicator. The goal of this strategy is to generate buy and sell signals based on the interactions between the predicted stock price and the MACD indicator.
Here's a breakdown of the strategy's components:
Calculation of Linear Regression: The strategy begins by calculating linear regression coefficients for the historical stock price based on volume. This helps predict potential future price levels.
Predicted Stock Price: The linear regression results are then used to plot the predicted stock price on the chart. This provides a visual representation of where the price could trend based on historical data.
Buy and Sell Signals: The strategy generates buy signals when certain conditions are met. These conditions include the predicted stock price being between the open and close prices, a rising MACD, and other factors that suggest a potential bullish trend. On the other hand, sell signals are generated based on MACD trends and predicted price levels.
Risk Management: The strategy also incorporates risk tolerance levels to determine entry and exit points. This ensures that traders take into account their risk appetite when making trading decisions.
Embracing the Magic of Linear Regression
As we explore the "Linear On MACD" strategy, we uncover the power of linear regression in aiding traders and investors. Linear regression, a mathematical marvel, seamlessly merges with technical analysis to provide insights into potential price movements. Its historical significance in statistics blends perfectly with the demands of modern financial markets.
Whether you're a seasoned trader or a curious investor, the Linear On MACD strategy exemplifies how a robust mathematical concept can be harnessed to make informed trading decisions. By embracing the magic of linear regression, you're tapping into a tool that continues to evolve alongside the financial world it empowers.
Disclaimer: The information provided in this blog post is for educational purposes only and does not constitute financial advice. Trading and investing carry risks, and it's important to conduct thorough research and consider seeking professional advice before making any trading decisions.
AlpHay : ToolKitToolKit:
First Impressions for Securities; (like crime scene investigators) 🧐
Our first job is to understand "What did happen here?" (historically, like Price Ranges or Price Performances) 🤔
Secondly, we try to figure out "where are we now?" (like common indicators or Moving Averages) 🤔
Then "What was the chain of events?" (macro, local, fundamentals, shorts, etc.)
Note: There are a lot of useful scripts out there, but If you want to see my approach for "Fundamentals" or "Finra Short Report" scripts, have a look.
Now we have a Clue. 😎
Includes;
1. Daily Metrics (Price performance, Price Difference, Volume, Trade)
2. Historic Price Performances
3. Historic Price ranges
4. RSI and MACD (you can change) Indicators for four "Time Frame" (you can change also)
5. Moving Averages (also shows daily values on the chart)
* Easy to customize.
* You can be positioned where ever you need. (be careful about overlays)
* You can turn on/off tables for your daily usage.
* You can flip Horizontally for some of the tables.
* Always look at tooltips (mouse over for Averages etc.)
I hope you enjoy it.
Disclaimer and Warning!
* Do not forget this is my Interpolation of the data sets. You can't invest in relying on this indicator. This is just a visual representation of the data sets.
* Just be careful what you wish for. And search for anomalies.
// ToDO List.
* Pre/Post Market Price and Volume
PDHL levels with INTRADAY Auto FIBThe present script includes Previous day High/low levels and once the PDH or PDL breaks the present bar's background changes color according to the direction of price breakout.
It's helpful when working on lower timeframe charts with small screen space, so that the user can know that the PDHL has been taken out in one glance at the chart instead of scrolling all around to find out whether the PDH or PDL are broken or not.
The high and low of day before yesterday are also plotted for reference.
The intraday fib levels get drawn taking present day's high and low into account, useful to mark support/retest levels.
The color of the intraday AUTO FIB high and low lines also change from gray to respective assigned colors once the present day price crosses PDH or PDL this is helpful while viewing charts on mobile app.
Disclaimer: Only for studying price movement ideas, trading is not advised.
IND-Range Box [Salar Kamjoo]Hello to all dear traders,
One of the trading methods in financial markets is Range Box Trading. Ranges are specific price levels where the market reaches equilibrium, meaning the buying force is roughly equal to the selling force. Consequently, the market neither moves significantly upwards nor downwards; it oscillates within a particular range. The indicator I have designed for you is based on this concept. It utilizes the number of candles and their oscillations to identify specific ranges on the chart. These ranges are drawn based on the maximum and minimum of the box.
The optimal time for trading and using this indicator is when the market is less volatile, specifically outside of the overlapping London and New York sessions. Additionally, be cautious during news releases as they might lead to stop-hunting scenarios. Therefore, the best time to employ this indicator is when the market is relatively calm.
This indicator has 4 settings:
Setting Number 1: Number of Candles
This setting determines the number of candles involved in calculating the range boxes. A higher value indicates longer range boxes will be identified for you, while a lower value results in quicker recognition of range boxes. However, a smaller value may reduce the reliability of the identified range boxes. The recommended value for this setting may vary for each currency pair and time frame.
s3.tradingview.com
Setting Number 2: Range Percentage
This setting determines the maximum percentage difference between the high and low of the identified range box. (These settings are interconnected with Setting Number 3, as your choice in Setting Number 3—whether to base the range box calculation on the high or low, or on the candle close—will impact how this range percentage is applied.)
s3.tradingview.com
Setting Number 3: Calculation Basis
This setting determines whether the maximum width of the range box is based on the highest or lowest points, or if it is calculated based on the closing prices of the candles.
s3.tradingview.com
s3.tradingview.com
Setting Number 4: Number of Extended Candles
This visual setting determines the extension of your range box forward by a specified number of candles.
Another valuable feature of this indicator is the ability to configure alerts. By setting up alerts, you can promptly receive notifications whenever a range box is identified on the chart. This ensures that you are promptly informed about potential trading opportunities.
If you have any questions feel free to ask in the comments section.
be profitable :)
Elliott Wave with Supertrend Exit - Strategy [presentTrading]## Introduction and How it is Different
The Elliott Wave with Supertrend Exit provides automated detection and validation of Elliott Wave patterns for algorithmic trading. It is designed to objectively identify high-probability wave formations and signal entries based on confirmed impulsive and corrective patterns.
* The Elliott part is mostly referenced from Elliott Wave by @LuxAlgo
Key advantages compared to discretionary Elliott Wave analysis:
- Wave Labeling and Counting: The strategy programmatically identifies swing pivot highs/lows with the Zigzag indicator and analyzes the waves between them. It labels the potential impulsive and corrective patterns as they form. This removes the subjectivity of manual wave counting.
- Pattern Validation: A rules-based engine confirms valid impulsive and corrective patterns by checking relative size relationships and fib ratios. Only confirmed wave counts are plotted and traded.
- Objective Entry Signals: Trades are entered systematically on the start of new impulsive waves in the direction of the trend. Pattern failures invalidate setups and stop out positions.
- Automated Trade Management: The strategy defines specific rules for profit targets at fib extensions, trailing stops at swing points, and exits on Supertrend reversals. This automates the entire trade lifecycle.
- Adaptability: The waveform recognition engine can be tuned by adjusting parameters like Zigzag depth and Supertrend settings. It adapts to evolving market conditions.
ETH 1hr chart
In summary, the strategy brings automation, objectivity and adaptability to Elliott Wave trading - removing subjective interpretation errors and emotional trading biases. It implements a rules-based, algorithmic approach for systematically trading Elliott Wave patterns across markets and timeframes.
## Trading Logic and Rules
The strategy follows specific trading rules based on the detected and validated Elliott Wave patterns.
Entry Rules
- Long entry when a new impulsive bullish (5-wave) pattern forms
- Short entry when a new impulsive bearish (5-wave) pattern forms
The key is entering on the start of a new potential trend wave rather than chasing.
Exit Rules
- Invalidation of wave pattern stops out the trade
- Close long trades on Supertrend downturn
- Close short trades on Supertrend upturn
- Use a stop loss of 10% of entry price (configurable)
Trade Management
- Scale out partial profits at Fibonacci levels
- Move stop to breakeven when price reaches 1.618 extension
- Trail stops below key swing points
- Target exits at next Fibonacci projection level
Risk Management
- Use stop losses on all trades
- Trade only highest probability setups
- Size positions according to chart timeframe
- Avoid overtrading when no clear patterns emerge
## Strategy - How it Works
The core logic follows these steps:
1. Find swing highs/lows with Zigzag indicator
2. Analyze pivot points to detect impulsive 5-wave patterns:
- Waves 1, 3, and 5 should not overlap
- Waves 3 and 5 must be longer than wave 1
- Confirm relative size relationships between waves
3. Validate corrective 3-wave patterns:
- Look for overlapping, choppy waves that retrace the prior impulsive wave
4. Plot validated waves and Fibonacci retracement levels
5. Signal entries when a new impulsive wave pattern forms
6. Manage exits based on pattern failures and Supertrend reversals
Impulsive Wave Validation
The strategy checks relative size relationships to confirm valid impulsive waves.
For uptrends, it ensures:
```
Copy code- Wave 3 is longer than wave 1
- Wave 5 is longer than wave 2
- Waves do not overlap
```
Corrective Wave Validation
The strategy identifies overlapping corrective patterns that retrace the prior impulsive wave within Fibonacci levels.
Pattern Failure Invalidation
If waves fail validation tests, the strategy invalidates the pattern and stops signaling trades.
## Trade Direction
The strategy detects impulsive and corrective patterns in both uptrends and downtrends. Entries are signaled in the direction of the validated wave pattern.
## Usage
- Use on charts showing clear Elliott Wave patterns
- Start with daily or weekly timeframes to gauge overall trend
- Optimize Zigzag and Supertrend settings as needed
- Consider combining with other indicators for confirmation
## Default Settings
- Zigzag Length: 4 bars
- Supertrend Length: 10 bars
- Supertrend Multiplier: 3
- Stop Loss: 10% of entry price
- Trading Direction: Both
Inflation-adjusted performanceOVERVIEW
The Inflation-adjusted performance indicator plots an adjusted closing price for the asset
on the main chart by multiplying the asset price by an inflation factor which is derived from CPI-U. The indicator has a `lookback` length, which is used to lookup the CPI-U index value from `lookback` years ago.
The inflation adjusted price is then calculated as `inflationAdjustedPrice = CPIToday / CPIBackThen * currentPrice`
CONCEPTS
This can be a useful tool to assess how an asset has performed as a store of value and inflation hedge over a given period.
The following are the key concepts and user inputs for the oscillator:
Input: The user can specify the lookback period, in years, using the `lookback` attribute on the settings widget. Defult is 13.
CPI Data: The indicator uses CPI data from tradingview's BLS feed.
Inflation Factor: An inflation factor is calculated by dividing today's CPI by the CPI from the lookback period. This factor represents the increase in prices due to inflation over the lookback period.
Inflation-adjusted Price: The offer price of the asset from `lookback` years ago is adjusted for inflation using the calculated inflation factor. This adjusted price represents what the offer price would be today if it had kept up with inflation.
ICT Kill Zones [dR-Algo]ICT Kill Zones Indicator by dR-Algo
Introducing the dR-Algo's ICT Kill Zones Indicator – a tool meticulously crafted to blend with the elegance of the ICT Concept of Kill Zones. Built for traders who seek clarity and focus, this unique indicator is tailored to highlight the essential time frames while ensuring minimal distraction from the core price action.
Key Features:
Three Kill Zones:
London Kill Zone: Kickstart your trading day with the London Kill Zone, highlighting the critical period between 03:00 to 04:00 (UTC-4). The London session, known for its volatility due to the overlapping of the Asian session, is captured precisely for your benefit.
NY AM Session: As the European markets gear towards close and the US markets come alive, our indicator emphasizes the activity from 10:00 to 11:00 (UTC-4). It’s a window where significant market moves often originate.
NY PM Session: Capture the late-day trading action between 14:00 to 15:00 (UTC-4). As markets prepare to close, this time frame can offer last-minute opportunities.
Subtle Yet Effective Visualization: Unlike many other indicators that bombard traders with an array of colors, our ICT Kill Zones Indicator is intentionally designed to be subtle. It provides just the right amount of visual emphasis without overwhelming the chart. The primary goal is to let traders focus on what truly matters: the price action.
User-Friendly Customization: The indicator's settings can be easily tailored to align with individual trading styles, allowing traders to adjust and tweak as per their preference.
Seamless Integration with Trading View: Smoothly integrates with your TradingView charts ensuring optimal performance and real-time responsiveness.
Why Choose Our ICT Kill Zones Indicator?
The market is flooded with indicators, each promising to be the 'next big thing.' What sets dR-Algo's ICT Kill Zones Indicator apart is its dedication to simplicity and effectiveness. It's not just about adding an indicator to your chart; it's about adding value to your trading experience. By seamlessly merging vital time frames without overshadowing the price action, we ensure traders get the best of both worlds.
Join the trading revolution with dR-Algo and embrace a focused approach to the markets.
Trading NotesThe "Trading Notes" indicator is a powerful and flexible tool designed to elevate your trading experience by enabling you to effortlessly create, manage, and personalize annotations directly on your trading chart. Whether it's jotting down crucial insights, strategies, risk management rules, or psychological cues, "Trading Notes" ensures that you never miss important details during your trading sessions.
Key Features:
Effortless Annotation: Seamlessly create custom annotations at any position on your chart, ensuring you capture vital trading information in real-time.
Tailored Appearance: Customize your annotations to match your preferences. Adjust text size, color, and alignment to create notes that stand out and are easily readable.
Flexible Positioning: Choose between top, middle, or bottom positions for your annotations, maintaining a clear view of price action while accessing your personalized notes.
Enhanced Focus and Discipline: Maintain trading discipline by keeping track of your trading rules, risk management strategies, and psychological reminders.
Luffy Gear 5To celebrate the reveal of Gear 5, decided to add luffy to tradingview
Have a mini companion on your chart, who better than the future pirate king??
Open source so people can experiment, thought it would be interesting to see users draw some pixel art, heres what I see as the optimized route:
Avoid long 3 things:
script length, opted for a 50x50
If statement length, break up the code
Length of main body, also links to above, functionalizing your code is good practice so put the 2 together and you have the below as an elementary implementation of pixel art!
(lower bit version of zenuchiha's work as mentioned on deviant art can be used with credit thank you im not much of an artist)
Normal Distribution CurveThis Normal Distribution Curve is designed to overlay a simple normal distribution curve on top of any TradingView indicator. This curve represents a probability distribution for a given dataset and can be used to gain insights into the likelihood of various data levels occurring within a specified range, providing traders and investors with a clear visualization of the distribution of values within a specific dataset. With the only inputs being the variable source and plot colour, I think this is by far the simplest and most intuitive iteration of any statistical analysis based indicator I've seen here!
Traders can quickly assess how data clusters around the mean in a bell curve and easily see the percentile frequency of the data; or perhaps with both and upper and lower peaks identify likely periods of upcoming volatility or mean reversion. Facilitating the identification of outliers was my main purpose when creating this tool, I believed fixed values for upper/lower bounds within most indicators are too static and do not dynamically fit the vastly different movements of all assets and timeframes - and being able to easily understand the spread of information simplifies the process of identifying key regions to take action.
The curve's tails, representing the extreme percentiles, can help identify outliers and potential areas of price reversal or trend acceleration. For example using the RSI which typically has static levels of 70 and 30, which will be breached considerably more on a less liquid or more volatile asset and therefore reduce the actionable effectiveness of the indicator, likewise for an asset with little to no directional volatility failing to ever reach this overbought/oversold areas. It makes considerably more sense to look for the top/bottom 5% or 10% levels of outlying data which are automatically calculated with this indicator, and may be a noticeable distance from the 70 and 30 values, as regions to be observing for your investing.
This normal distribution curve employs percentile linear interpolation to calculate the distribution. This interpolation technique considers the nearest data points and calculates the price values between them. This process ensures a smooth curve that accurately represents the probability distribution, even for percentiles not directly present in the original dataset; and applicable to any asset regardless of timeframe. The lookback period is set to a value of 5000 which should ensure ample data is taken into calculation and consideration without surpassing any TradingView constraints and limitations, for datasets smaller than this the indicator will adjust the length to just include all data. The labels providing the percentile and average levels can also be removed in the style tab if preferred.
Additionally, as an unplanned benefit is its applicability to the underlying price data as well as any derived indicators. Turning it into something comparable to a volume profile indicator but based on the time an assets price was within a specific range as opposed to the volume. This can therefore be used as a tool for identifying potential support and resistance zones, as well as areas that mark market inefficiencies as price rapidly accelerated through. This may then give a cleaner outlook as it eliminates the potential drawbacks of volume based profiles that maybe don't collate all exchange data or are misrepresented due to large unforeseen increases/decreases underlying capital inflows/outflows.
Thanks to @ALifeToMake, @Bjorgum, vgladkov on stackoverflow (and possibly some chatGPT!) for all the assistance in bringing this indicator to life. I really hope every user can find some use from this and help bring a unique and data driven perspective to their decision making. And make sure to please share any original implementaions of this tool too! If you've managed to apply this to the average price change once you've entered your position to better manage your trade management, or maybe overlaying on an implied volatility indicator to identify potential options arbitrage opportunities; let me know! And of course if anyone has any issues, questions, queries or requests please feel free to reach out! Thanks and enjoy.
Price Range BlockThe price range block indicator. User input divides the price into blocks (eg a block of 1 dollar) if the price would go from 1 dollar to greater than 1 dollar, the next block is drawn including the center line. Same for if it went down. Trading choices could be made through the behavior of the price in such a block.
US Recession IndicatorThe US Recession Indicator is designed to identify recessions as they happen, using two reputable indicators that have accurately foreseen all past recessions since 1969. Unlike the National Bureau of Economic Research (NBER) which determines recession dates after the fact, this indicator seeks to spot recessions in real-time. When both of these distinct metrics meet certain criteria, the chart's background becomes shaded, signifying a strong likelihood that the economy is in a recession. Furthermore, a built-in alert system keeps users updated without constant monitoring.
The first metric is the Smoothed Recession Probabilities developed by Marcelle Chauvet. It is based on a dynamic-factor markov-switching model that assesses four monthly coincident variables: non-farm payroll employment, the index of industrial production, real personal income excluding transfer payments and real manufacturing and trade sales. It offers a mathematical analysis of how recessions deviate from expansions. In essence, this index mirrors the probability of the prevailing true economic situation being a recession, grounded on the current GDP data.
The second metric is the Sahm Rule Recession Indicator developed by Claudia Sahm. It operates on the principle that changes in the unemployment rate can be used to identify the onset of a recession. According to this rule, if the three-month moving average of the unemployment rate rises by 0.5 percentage points or more above its lowest point from the preceding year, it flags a potential recession.
For this combined indicator, the thresholds are intentionally set lower than when each metric is used individually. Both metrics must simultaneously suggest a potential recession in order to send a signal. This stems from the realisation that neither metric is infallible and has, on occasion, sent false signals in the past. By requiring both to align, the likelihood of a false positive is reduced. However, it's crucial to understand that past performance does not guarantee future results, leaving the door open for potential false alerts which may not be confirmed by the NBER.
Global Liquidity IndexThe Global Liquidity Index offers a consolidated view of all major central bank balance sheets from around the world. For consistency and ease of comparison, all values are converted to USD using their relevant forex rates and are expressed in trillions. The indicator incorporates specific US accounts such as the Treasury General Account (TGA) and Reverse Repurchase Agreements (RRP), both of which are subtracted from the Federal Reserve's balance sheet to give a more nuanced view of US liquidity. Users have the flexibility to enable or disable specific central banks and special accounts based on their preference. Only central banks that both don’t engage in currency pegging and have reliable data available from late 2007 onwards are included in this aggregated liquidity model.
Global Liquidity Index = Federal Reserve System (FED) - Treasury General Account (TGA) - Reverse Repurchase Agreements (RRP) + European Central Bank (ECB) + People's Bank of China (PBC) + Bank of Japan (BOJ) + Bank of England (BOE) + Bank of Canada (BOC) + Reserve Bank of Australia (RBA) + Reserve Bank of India (RBI) + Swiss National Bank (SNB) + Central Bank of the Russian Federation (CBR) + Central Bank of Brazil (BCB) + Bank of Korea (BOK) + Reserve Bank of New Zealand (RBNZ) + Sweden's Central Bank (Riksbank) + Central Bank of Malaysia (BNM).
This tool is beneficial for anyone seeking to get a snapshot of global liquidity to interpret macroeconomic trends. By examining these balance sheets, users can deduce policy trajectories and evaluate the global economic climate. It also offers insights into asset pricing and assists investors in making informed capital allocation decisions. Historically, riskier assets, such as small caps and cryptocurrencies, have typically performed well during periods of rising liquidity. Thus, it may be prudent for investors to avoid additional risk unless there's a consistent upward trend in global liquidity.
All Candlestick Patterns Screener [By MUQWISHI]▋ INTRODUCTION :
The Candlestick Patterns Screener has been designed to offer an advanced monitoring solution for up to 40 symbols. Utilizing a log screener style, it efficiently gathers information on confirmed candlestick pattern occurrences and presents it in an organized table. This table includes essential details such as the symbol name, signal price, and the corresponding candlestick pattern name.
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▋ OVERVIEW:
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▋ CREDIT:
Credit to public technical “*All Candlestick Patterns*” indicator.
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▋ USAGE:
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▋ Final Comments:
For best performance, add the Candlestick Patterns Screener on active symbol chart like QQQ, SPY, AAPL, BTCUSDT, ES, EURUSD or …etc.
Candlestick patterns are not a major concept to build a trading decision.
Personally, I see candlestick patterns as a means to comprehend the psychology of the market, and help to follow the price action.
Please let me know if you have any questions.
Thank you.
MACDh with divergences & impulse system (overlayed on prices)-----------------------------------------------------------------
General Description:
This indicator ( the one on the top panel above ) consists on some lines, arrows and labels drawn over the price bars/candles indicating the detection of regular divergences between price and the classic MACD histogram (shown on the low panel). This script is special because it can be adjusted to fit several criteria when trading divergences filtering them according to the "height" and "width" of the patterns. The script also includes the "extra features" Impulse System and Keltner Channels, which you will hardly find anywhere else in similar classic MACD histogram divergence indicators.
The indicator helps to find trend reversals, and it works on any market, any instrument, any timeframe, and any market condition (except against really strong trends that do not show any other sign of reversion yet).
Please take on consideration that divergences should be taken with caution.
-----------------------------------------------------------------
Definition of classic Bullish and Bearish divergences:
* Bearish divergences occur in uptrends identifying market tops. A classical or regular bearish divergence occurs when prices reach a new high and then pull back, with an oscillator (MACD histogram in this case) dropping below its zero line. Prices stabilize and rally to a higher high, but the oscillator reaches a lower peak than it did on a previous rally.
In the chart above (weekly charts of NKE, Nike, Inc.), in area X (around August 2021), NKE rallied to a new bull market high and MACD-Histogram rallied with it, rising above its previous peak and showing that bulls were extremely strong. In area Y, MACD-H fell below its centerline and at the same time prices punched below the zone between the two moving averages. In area Z, NKE rallied to a new bull market high, but the rally of MACD-H was feeble, reflecting the bulls’ weakness. Its downtick from peak Z completed a bearish divergence, giving a strong sell signal and auguring a nasty bear market.
* Bullish divergences , in the other hand, occur towards the ends of downtrends identifying market bottoms. A classical (also called regular) bullish divergence occurs when prices and an oscillator (MACD histogram in this case) both fall to a new low, rally, with the oscillator rising above its zero line, then both fall again. This time, prices drop to a lower low, but the oscillator traces a higher bottom than during its previous decline.
In the example in the chart above (weekly charts of NKE, Nike, Inc.), you see a bearish divergence that signaled the October 2022 bear market bottom, giving a strong buy signal right near the lows. In area A, NKE (weekly charts) appeared in a free fall. The record low A of MACD-H indicated that bears were extremely strong. In area B, MACD-H rallied above its centerline. Notice the brief rally of prices at that moment. In area C, NKE slid to a new bear market low, but MACD-H traced a much more shallow low. Its uptick completed a bullish divergence, giving a strong buy signal.
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Some cool features included in this indicator:
1. This indicator also includes the “ Impulse System ”. The Impulse System is based on two indicators, a 13-day exponential moving average and the MACD-Histogram, and identifies inflection points where a trend speeds up or slows down. The moving average identifies the trend, while the MACD-Histogram measures momentum. This unique indicator combination is color coded into the price bars for easy reference.
Calculation:
Green Price Bar: (13-period EMA > previous 13-period EMA) and
(MACD-Histogram > previous period's MACD-Histogram)
Red Price Bar: (13-period EMA < previous 13-period EMA) and
(MACD-Histogram < previous period's MACD-Histogram)
Price bars are colored blue when conditions for a Red Price Bar or Green Price Bar are not met. The MACD-Histogram is based on MACD(12,26,9).
The Impulse System works more like a censorship system. Green price bars show that the bulls are in control of both trend and momentum as both the 13-day EMA and MACD-Histogram are rising (you don't have permission to sell). A red price bar indicates that the bears have taken control because the 13-day EMA and MACD Histogram are falling (you don't have permission to buy). A blue price bar indicates mixed technical signals, with neither buying nor selling pressure predominating (either both buying or selling are permitted).
2. Another "extra feature" included here is the " Keltner Channels ". Keltner Channels are volatility-based envelopes set above and below an exponential moving average.
3. It were also included a couple of EMAs.
Everything can be removed from the chart any time.
-----------------------------------------------------------------
Options/adjustments for this indicator:
*Horizontal Distance (width) between two tops/bottoms criteria.
Refers to the horizontal distance between the MACH histogram peaks involved in the divergence
*Height of tops/bottoms criteria (for Histogram).
Refers to the difference/relation/vertical distance between the MACH HISTOGRAM peaks involved in the divergence: 1st Histogram Peak is X times the 2nd.
*Height/Vertical deviation of tops/bottoms criteria (for Price).
Deviation refers to the difference/relation/vertical distance between the PRICE peaks involved in the divergence.
*Plot Regular Bullish Divergences?.
*Plot Regular Bearish Divergences?.
*Delete Previous Cancelled Divergences?.
*Shows a pair of EMAs.
*Shows Keltner Channels (using ATR)
Keltner Channels are volatility-based envelopes set above and below an exponential moving average.
*This indicator also has the option to show the Impulse System over the price bars/candles.
MACDh with divergences & impulse system-----------------------------------------------------------------
General Description:
This indicator ( the one on the low panel ) is a classic MACD that also shows regular divergences between its histogram and the prices. This script is special because it can be adjusted to fit several criteria when trading divergences filtering them according to the "height" and "width" of the patterns. The script also includes the "extra feature" Impulse System, which you will hardly find anywhere else in similar classic MACD histogram divergence indicators.
The indicator helps to find trend reversals, and it works on any market, any instrument, any timeframe, and any market condition (except against really strong trends that do not show any other sign of reversion yet).
Please take on consideration that divergences should be taken with caution.
-----------------------------------------------------------------
Definition of classic Bullish and Bearish divergences:
* Bearish divergences occur in uptrends identifying market tops. A classical or regular bearish divergence occurs when prices reach a new high and then pull back, with an oscillator (MACD histogram in this case) dropping below its zero line. Prices stabilize and rally to a higher high, but the oscillator reaches a lower peak than it did on a previous rally.
In the chart above (weekly charts of NKE, Nike, Inc.), in area X (around August 2021), NKE rallied to a new bull market high and MACD-Histogram rallied with it, rising above its previous peak and showing that bulls were extremely strong. In area Y, MACD-H fell below its centerline and at the same time prices punched below the zone between the two moving averages. In area Z, NKE rallied to a new bull market high, but the rally of MACD-H was feeble, reflecting the bulls’ weakness. Its downtick from peak Z completed a bearish divergence, giving a strong sell signal and auguring a nasty bear market.
* Bullish divergences , in the other hand, occur towards the ends of downtrends identifying market bottoms. A classical (also called regular) bullish divergence occurs when prices and an oscillator (MACD histogram in this case) both fall to a new low, rally, with the oscillator rising above its zero line, then both fall again. This time, prices drop to a lower low, but the oscillator traces a higher bottom than during its previous decline.
In the example in the chart above (weekly charts of NKE, Nike, Inc.), you see a bearish divergence that signaled the October 2022 bear market bottom, giving a strong buy signal right near the lows. In area A, NKE (weekly charts) appeared in a free fall. The record low A of MACD-H indicated that bears were extremely strong. In area B, MACD-H rallied above its centerline. Notice the brief rally of prices at that moment. In area C, NKE slid to a new bear market low, but MACD-H traced a much more shallow low. Its uptick completed a bullish divergence, giving a strong buy signal.
-----------------------------------------------------------------
Extra feature: Impulse System
This indicator also includes the “ Impulse System ”. The Impulse System is based on two indicators, a 13-day exponential moving average and the MACD-Histogram, and identifies inflection points where a trend speeds up or slows down. The moving average identifies the trend, while the MACD-Histogram measures momentum. This unique indicator combination is color coded into the price bars or macd histogram bars for easy reference.
Calculation:
Green Price Bar: (13-period EMA > previous 13-period EMA) and
(MACD-Histogram > previous period's MACD-Histogram)
Red Price Bar: (13-period EMA < previous 13-period EMA) and
(MACD-Histogram < previous period's MACD-Histogram)
Histogram bars are colored blue when conditions for a Red Histogram Bar or Green Histogram Bar are not met. The MACD-Histogram is based on MACD(12,26,9).
The Impulse System works more like a censorship system. Green histogram bars show that the bulls are in control of both trend and momentum as both the 13-day EMA and MACD-Histogram are rising (you don't have permission to sell). A red histogram bar indicates that the bears have taken control because the 13-day EMA and MACD Histogram are falling (you don't have permission to buy). A blue histogram bar indicates mixed technical signals, with neither buying nor selling pressure predominating (either both buying or selling are permitted).
The impulse system can be removed from the chart any time.
-----------------------------------------------------------------
Options/adjustments for this indicator:
*Horizontal Distance (width) between two tops/bottoms criteria.
Refers to the horizontal distance between the MACH histogram peaks involved in the divergence
*Height of tops/bottoms criteria (for Histogram).
Refers to the difference/relation/vertical distance between the MACH HISTOGRAM peaks involved in the divergence: 1st Histogram Peak is X times the 2nd.
*Height/Vertical deviation of tops/bottoms criteria (for Price).
Deviation refers to the difference/relation/vertical distance between the PRICE peaks involved in the divergence.
*Plot Regular Bullish Divergences?.
*Plot Regular Bearish Divergences?.
*Delete Previous Cancelled Divergences?.
*This indicator also has the option to show the Impulse System over the MACD histogram bars
Risk Management GO8686: Stop Loss, Position Size & TargetFull Name: Risk Management GO8686: Stop Loss, Position Size & Target
What this indicator provides:
A dashboard to calculate Stop Loss, Position Size and Target, where users can customize Risk Management parameters in the setting.
Position Size: calculated from "initialCapital", "Leverage", "Max Loss", "feeMaker", "feeTaker".
Stop Loss Price: using pivots, default length is set to 3, with an extra ATR value controlled by "'Multiplier OF Extra ATR".
Target: calculated from entry price, risk reward, distance between entry and stop loss, fees
What the indicator does Not provides:
entries of positions: The Long/Short entries displayed are just MACD signal crossing zero, users can apply their own entry logic, by modifying ready2L / ready2S variables.
What the indicator does Not guarantee:
the integrity, timeliness, accuracy, and comprehensiveness of the data, calculation method, calculation results, etc.
Two types labels:
1. Automated labels: they are displayed when MACD signal crossing zero, use "Display History Labels" to toggle display or not.
2. Setup Manually label: located at the right side of the latest bar, to display results when users setup manually
The settings of the indicator:
"Toggle to Reload",
"InitialCapital", "Leverage", "Max Loss % per trade", "feeMaker", "feeTaker",
4 length inputs for Pivot, "Multiplier of Extra ATR for stop loss",
"Toggle To setup manually", "Toggle between Long / Short", "Entry Price, set manually", "Stop Loss Price, set manually", "Risk-Reward Ratio"
"Display History Labels"
---------- Disclaimer ----------
Before using or requesting access to the indicator, customers/users acknowledge that they have read and accepted that the indicator, any associated contents on all social medias and any communication with the indicator author, including but not limited to: product and service details, signals, alerts, data, calculation methods, calculation results, user manual, tutorials, ideas, videos, chats, messages, emails, blogs, tweets, etc. are provided solely for educational purpose and Not as financial advice. Customers/users understand and agree to use the aforementioned indicator and information at their own risk.
---------- Updates ----------
The latest updates override the previous content.
To activate a update, if it does not load as expected: close the indicator, save the chart, clear browser caches, restart the browser, reload the chart and apply the indicator to the chart.
Any Screener (Multiple)I suppose it's time to publish something relatively useful :). Here's the first try, Any Screener.
This script is an advanced version of the Alphatrend - Screener that I've coded as a humble "thank you" to Kıvanç Özbilgiç (KivancOzbilgic), who always inspired me.
INTRODUCTION
I developed this version with a unique method because I couldn't find an example with the following features:
It presents the valid signal status of multiple indicators for 15 different symbols in the form of a report.
It indicates how many bars have passed after the signal has occurred.
It indicates the signal direction with dynamic colors and chars.
It can also be used for data (just indicator value) that is only intended to be displayed as text. (Default color is grey).
Long and short signals can optionally be ploted on the chart.
It includes advanced configuration settings.
USAGE OF PANEL
The screener panel is simple to use. On the far left, assets are listed. The names of the indicators appear at the top. In the column with the name of each indicator, the signals of that indicator appear as green or red. The green ones represent the long signals (uptrend) and the red ones represent the short signals (down trend). The numbers in square brackets indicate how many bars have passed after the last signal has occurred. (For example: According to the indicator at the top, when the green bullish triangle and 21 appeared on allign of BTCUSDT, Bitcoin switched to buy signal 21 bars ago. A tip : If the signal distance is 0, the signal occurred at the current bar. It is recommended to wait for the bar to close before entering the trade). Signal distance is an essential output for both manual and algorithmic trading. Users often require mentioned data the most during real time trading.
THE SCRIPT
There are two sections in the script; indicators and screener.
SECTION 1 : "INDICATORS"
In the indicator section, you'll find efficient details about switch methods, normalization, avoid pyramyding (in momentum oscillators) etc. On the other hand, I intended to present a "how to example" of a multiple screener, so it has to include more than one indicator.
OTT : Optimized Trend Tracker is developed by dear Anıl Özekşi, known as the "Old Fisherman" :). In my opinion, it is a pretty cool trend-following indicator that offers a mathematical elegance. This indicator aim to detect the current market trend direction, the indicator detect an up-trending market when the support line is superior to the OTT, and a down trending market when the support line is inferior to the OTT. It has three parameters; moving average type, length and percentage. In this version when the percentage parameter is set to 0.0, OTT turns into the selected moving average. And the signals are generated by the crossing of the closing price. It means, this screener is able to compile and present status of moving averages as well. Also VAR (VIDYA) and EVWMA has been re-designed, both moving averages no longer start at zero at the beginning of the chart (That was a big problem for backtests).
PSAR : J. Welles Wilder's Parabolic Stop And Reversal is an important trend following indicator. PSAR detects an up-trending market when below the market price and a down-trend when above. It can work in harmony with OTT according to the parameter combinations.
OSCILLATORS : Also optional three momentum oscillators have been added. MFI (Money Flow Index), RSI (Relative Strength Index) and STOCH (Stochastic %k). All three oscillators are widely used in markets and quite successful in explaining price movements by using different sources. Oscillators generate long and short signals based on oversold and overbought parameters.
VOLATILITY & TREND : There are three optional indicators. ADX (Average Directional Index), BBW-N (Normalized Bollinger Bandwidth) and REG-N (Normalized value of standard error of linear regression). These three indicators don't generate any long or short signals. Instead, they are used to measure the strength of trends and volatility. Therefore, only the numerical results (0-100) are displayed in screener panel and it is grey. (Note : The second length parameter of ADX has the same value with the first one. Bollinger Bandwith's multiplier is 2.0. REG-N is a variable that developed by Paul Kirshenbaum for Kirshenbaum Bands.)
SECTION 2 : "SCREENER"
The second section processes the main idea. This Screener model is based on generating an integer direction variable from boolean signals. The direction value serves multiple purposes: calculating the distance of signal, determining the color based on the direction, and creating "clean" data for the security function. The final step is to present the obtained data as text to the user.
HOW CAN I "SCREEN" MY CONDITIONS?
That's piece a cake, delete the Section 1 in the script :). If you change totally 11 variables according to your own strategy, you can create your new screener! The method is explained at lines 169-171.
SINCERELY THANKS
To allanster for patiently answering my primitive questions,
And to KivancOzbilgic for mind blowing suggestions (especially while we're drinking Raki) :)...
DISCLEIMER
This is just an indicator, nothing more. The script is for informational and educational purposes only. The use of the script does not constitute professional and/or financial advice. The responsibility for risks associated with the use of the script is solely owned by the user. Do not forget to manage your risk. And trade as safely as possible. Good luck!
Ahsan Tufail Precise MA Crossover Filter for Reliable SignalsIntroduction:
In the ever-evolving world of Forex trading, strategies that provide a competitive edge are highly sought after. The Moving Average (MA) crossover technique is a popular long-term approach, but its vulnerability to false signals can lead to potential losses. To overcome this challenge, we introduce a game-changing MA crossover filter designed to weed out false signals and unlock the full potential of this strategy. In this article, we delve into the mechanics of this filter, providing a comprehensive analysis of its components and how it enhances the accuracy of buy and sell signals.
The Power of the MA Crossover Filter:
The essence of our MA crossover filter lies in the integration of a specialized indicator that operates on a scale of 0 to 100. This ingenious indicator dynamically measures the distance between the middle Bollinger band and either the upper or lower Bollinger band. By analyzing the values of the last 504 candlesticks, it maps the range from 50 to 100 for the largest and smallest distances between the middle and upper Bollinger bands. Similarly, for values ranging from 0 to 50, it measures the distance between the middle and lower Bollinger bands.
Unveiling the Signal Execution Process:
The brilliance of this filter is revealed in its meticulous execution of buy and sell signals, which significantly reduces false crossovers. Let's explore the process step-by-step:
Buy Signal Precision:
To initiate a buy signal, the price must be positioned above the 200-period Simple Moving Average (SMA).
The filter validates the crossover by checking the indicator's value, ensuring it falls below the threshold of 25.
Sell Signal Accuracy:
For a sell signal, the price must be below the 200-period Simple Moving Average (SMA).
The filter confirms the crossover by verifying the indicator's value, which should exceed the threshold of 75.
This selective approach ensures that only high-confidence crossovers are considered, maximizing the potential for profitable trades.
Fine-Tuning the Filter for Optimal Performance:
While the MA crossover filter exhibits its prowess in GBPUSD and EURUSD currency pairs, it may require adjustments for other pairs. Currency pairs possess unique characteristics, and adapting the filter to specific behavior is crucial for its success.
To fine-tune the filter for alternative currency pairs, traders should conduct rigorous backtesting and analyze historical price data. By experimenting with indicator threshold values, traders can calibrate the filter to accurately match the dynamics of the target currency pair. This iterative process allows for customization, ultimately resulting in a finely-tuned filter that aligns with the unique behavior of the selected market.
Conclusion:
The MA crossover filter represents a paradigm shift in long-term Forex trading strategies. By intelligently filtering false signals, this precision tool unleashes the true potential of the MA crossover technique, elevating its profitability and enhancing overall trading performance. While no strategy guarantees absolute success, incorporating this filter empowers traders with a heightened level of confidence in their buy and sell signals. Embracing the power of this innovative filter can be a transformative step towards mastering Forex profits and staying ahead in the dynamic world of currency trading.
