Forex Multi-Factor IndicatorMoving Averages (MA):
Two moving averages are plotted on the chart: a fast MA (blue line) and a slow MA (red line).
The fast MA is calculated using a shorter period (10 periods by default), while the slow MA is calculated using a longer period (30 periods by default).
Moving averages help identify trends by smoothing out price fluctuations. When the fast MA crosses above the slow MA, it suggests a bullish trend, and when the fast MA crosses below the slow MA, it suggests a bearish trend.
Relative Strength Index (RSI):
The RSI indicator (orange line) is plotted on a separate axis.
RSI measures the speed and change of price movements and oscillates between 0 and 100.
RSI values above 70 are considered overbought, indicating a potential reversal to the downside, while RSI values below 30 are considered oversold, indicating a potential reversal to the upside.
Volume Moving Average (Volume MA):
The volume moving average (purple line) is plotted on the same axis as the volume.
The volume moving average is calculated over a specified period (20 periods by default).
Volume analysis provides insights into the strength of price movements. When the volume increases along with price movements, it suggests strong conviction from traders.
Buy and Sell Signals:
Buy signals (green triangle) are generated when all of the following conditions are met:
The fast MA crosses above the slow MA (indicating a bullish trend).
The RSI is below the oversold level (indicating potential upward momentum).
The current price is above the fast MA, and the volume is higher than the volume MA (indicating positive volume trend).
Sell signals (red triangle) are generated when all of the following conditions are met:
The fast MA crosses below the slow MA (indicating a bearish trend).
The RSI is above the overbought level (indicating potential downward momentum).
The current price is below the fast MA, and the volume is lower than the volume MA (indicating negative volume trend).
Overall, this multi-factor indicator combines moving averages, RSI, and volume analysis to identify potential buying and selling opportunities in the Forex market. Traders can use the signals generated by this indicator as part of their trading strategy, but it's important to consider other factors such as risk management and market conditions before making trading decisions
Cari dalam skrip untuk "MA Cross"
QuantBot 3:Ultimate MA CrossoverTHIS IS A SAMPLE CODE TO AUTOMATE WITH QUANTBOT
The moving average strategy is a popular and widely used technique in financial analysis and trading. It involves the calculation and analysis of moving averages, which are mathematical indicators that smooth out price data over a specified period. This strategy is primarily applied in the context of stock trading, but it can be used for other financial instruments as well.
The concept behind the moving average strategy is to identify trends and potential entry or exit points in the market. By calculating and analyzing moving averages of different timeframes, traders aim to capture the overall direction of the price movement and filter out short-term fluctuations or noise.
To implement the moving average strategy, a trader typically selects two or more moving averages with different periods. The most common combinations include the 50-day and 200-day moving averages. The shorter-term moving average is considered more reactive to price changes, while the longer-term moving average provides a smoother trend line. When the shorter-term moving average crosses above the longer-term moving average, it generates a buy signal, indicating a potential upward trend. Conversely, when the shorter-term moving average crosses below the longer-term moving average, it generates a sell signal, indicating a potential downward trend.
Traders can use various variations of the moving average strategy based on their trading objectives and risk tolerance. For instance, some traders may prefer to use exponential moving averages (EMAs) instead of simple moving averages (SMAs) to give more weight to recent price data. Others may incorporate additional indicators or filters to confirm signals or avoid false signals.
One of the strengths of the moving average strategy is its simplicity and ease of interpretation. It provides a clear visual representation of the trend direction and potential entry or exit points. However, it's important to note that the moving average strategy is a lagging indicator, meaning that it relies on past price data. Therefore, it may not always accurately predict future market movements or capture sudden reversals.
Like any trading strategy, the moving average strategy is not foolproof and carries risks. It is crucial for traders to conduct thorough analysis, consider other relevant factors, and manage their risk through proper position sizing and risk management techniques. Additionally, it's important to adapt the strategy to specific market conditions and combine it with other complementary strategies or indicators for improved decision-making.
Overall, the moving average strategy serves as a valuable tool for traders to identify and follow trends in financial markets, aiding in the analysis of price movements and potential trading opportunities.
TCG AI ToolsIntroduction:
This script is a result of an AI recommended created trading strategy that is design to offer new traders’ easy access to trend information and oversold/overbought conditions. Here we have combined commonly used indicators into a single unique visualization that quickly identifies trend changes and both RSI and Bollinger Band based overbought and oversold conditions, and allows all three indicators to be used simultaneously while taking up limited space on the chart.
The value in combining these three indicators is found in the harmony and clarity they are able to provide new traders. Trend changes can be difficult to identify based solely on candlestick analysis, therefore using the moving averages allows the trader to simplify the process of establishing bullish or bearish trends. Once a trend is established it can be very attractive for new traders to establish entries at the wrong time. For this reason, it is useful to include two different overbought and oversold indicators. The Bollinger Bands are included as one of the methods for establishing extreme prices that often result in reversals, and the relative strength index is similarly utilized as a second means to warn traders of extreme conditions.
Using the Indicator
1. MA10 MA20 Trend Indicator
The large red/green horizontal bar located at the 0 line on the X axis is the trend direction indicator. This visualization compares the 10 and 20 period moving averages to establish trend. When the MA10 is above the MA20 the trend is considered bullish and supportive of long positions and indicates such by changing the color of the horizontal bar to green. When the MA10 is below MA20 the trend is considered bearish and indicates such by changing the color of the horizontal bar to red. Color changes occur at the moment of a MA crossover/under.
2. Relative Strength Index.
The vertical red and green bars that make up the background of the panel indicate conditions wherein the RSI is considered overbought or oversold. When the vertical bar is red it indicates that RSI is below 30 suggesting that current conditions are oversold and supportive of long entries. When the vertical bar is green it suggests that the current conditions are overbought and are supportive of short entries.
3. Bollinger Band Extremes
Within the horizontal red/green bar there are red and green arrows. These arrows represent periods where the price is exceeding the upper or lower Bollinger bands and indicate overbought/oversold conditions. When a green arrow appears, it indicates that the price has crossed below the lower BB and is supportive of long entries. If a red arrow appears it indicates that the price has crossed above the upper Bollinger band and conditions are supportive of short entries.
RSI with Slow and Fast MA Crossing Strategy (by Coinrule)This strategy utilises 3 different conditions that have to be met to buy and 1 condition to sell. This strategy works best on the ETH/USDT pair on the 4-hour timescale.
In order for the strategy to enter the trade, it must meet all of the conditions listed below:
ENTRY
RSI increases by 5
RSI is lower than 70
MA9 crosses above MA50
To exit a trade, the below condition must be met:
EXIT
MA50 crosses above MA9
This strategy works well on LINK/USDT on the 1-day timeframe, MIOTA/USDT on the 2-hour timeframe, BTC/USDT on the 4-hour timeframe, and BEST/USDT on the 1-day timeframe (and 4h).
Back-tested from 1 January 2020.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
Squeeze Momentum Strategy [LazyBear] Buy Sell TP SL Alerts-Modified version of Squeeze Momentum Indicator by @LazyBear.
-Converted to version 5,
-Taken inspiration from @KivancOzbilgic for its buy sell calculations,
-Used @Bunghole strategy template with Take Profit, Stop Loss and Enable/Disable Toggles
-Added Custom Date Backtesting Module
------------------------------------------------------------------------------------------------------------------------
All credit goes to above
Problem with original version:
The original Squeeze Momentum Strategy did not have buy sell signals and there was alot of confusion as to when to enter and exit.
There was no proper strategy that would allow backtesting on which further analysis could be carried out.
There are 3 aspects this strategy:
1 ) Strategy Logic (easily toggleable from the dropdown menu from strategy settings)
- LazyBear (I have made this simple by using Kivanc technique of Momentums Moving Average Crossover, BUY when MA cross above signal line, SELL when crossdown signal line)
- Zero Crossover Line (BUY signal when crossover zero line, and SELL crossdown zero line)
2) Long Short TP and SL
- In strategies there is usually only 1 SL and 1 TP, and it is assumed that if a 2% SL giving a good profit %, then it would be best for both long and short. However this is not the case for many. Many markets/pairs, go down with much more speed then they go up with. Hence once we have a profitable backtesting setting, then we should start optimizing Long and Short SL's seperately. Once that is done, we should start optimizing for Long and Short TP's separately, starting with Longs first in both cases.
3) Enable and Disable Toggles of Long and Short Trades
- Many markets dont allow short trades, or are not suitable for short trades. In this case it would be much more feasible to disable "Short" Trading and see results of Long Only as a built in graphic view of backtestor provides a more easy to understand data feed as compared to the performance summary in which you have to review long and short profitability separately.
4) Custom Data Backtesting
- One of most crucial aspects while optimizing for backtesting is to check a strategies performance on uptrends, downtrend and sideways markets seperately as to understand the weak points of strategy.
- Once you enable custom date backtesting, you will see lines on the chart which can be dragged left right based on where you want to start and end the backtesting from and to.
Note:
- Not a financial advise
- Open to feedback, questions, improvements, errors etc.
- More info on how the squeeze momentum works visit LazyBear indicator link:
Happy Trading!
Cheers
M Tahreem Alam @mtahreemalam
RSI + rCalcThis is a modification of the TradingView RSI.
I have added HMA and ALMA options to the MA settings and also the option for a colour change on RSI cross.
A reverse calc has also been added. This will display the MA cross/Overbought/Oversold price predictions. There is also the option to display an entered RSI or Price for a prediction display.
All colours and modifications can be turned on/off.
Enjoy! :)
MA VisualizerThe MA Visualizer is made up of 5 Moving Averages (MA)
All MA change color when the price closes above or below the MA line.
The background between the MA line and price will also change color, this creates the Visualizer.
When two or more MA are selected the two visualizer's will combine and create a gradient effect.
Each MA can be adjusted with 6 source selection's to choose from (SMA , EMA , WMA , HMA , RMA , WVMA).
The Visualizer can be turned off while leaving the MA lines turned on and vice versa.
Their is also a MA Cross indicator built-in.
Instrument-Z (3Commas Bot)Instrument-Z is what I am currently using as my 3Commas Bot.
It allows you to customize signals from 3 indicators; Crossing MA's, Stochastic RSI, and WaveTrend.
Better yet, it allows you to setup these signals separately depending on whether the Trend MA is going up or down.
So there are 2 sets of inputs for everything, Uptrend inputs and Downtrend inputs.
I have realized that we can't expect a strategy to work the same way in an uptrend vs downtrend, so the inputs should be separated too.
In my testing, separating increased the net profit by 60% on average.
You can select whether you are trading Long or Short.
You can choose your stop loss and take profit levels as well as trade expiration.
You can choose if you only want to trade with the trend (making the opposing signals irrelevant).
The trend is based on the Trend MA.
This script is specifically for cryptocurrencies.
I've noticed that MA crosses on other asset classes are unreliable because the fluctuations are not strong enough to push the MA's across each other in a meaningful way.
If you want to use this as a 3Commas Bot, then you will have to copy the code of the strategy and paste it into your own personal script.
Then you have to change the alert messages at the bottom of the script.
Make sure to change your alert message from this;
{"message_type": "bot", "bot_id": 0000000, "email_token": "0b000a0a-0aa0-00aa-0aa0-000a00000a0a", "delay_seconds": 0}
To this;
{\n\"message_type\": \"bot\",\n\"bot_id\": 0000000,\n\"email_token\": \"0a000a0a-0aa0-00aa-0aa0-000a00000a0a\",\n\"delay_seconds\": 0\n}
With \n after each new line and \ before each quotation.
In the Alert setup, select "alert() function calls only".
This indicator is like a middle ground of complexity between the Juicy Trend indicator and the Instrument-A indicator.
And because it does not feature my neural network project, I have made it open script.
Enjoy!
Portfolio Backtester Engine█ OVERVIEW
Portfolio Backtester Engine (PBTE). This tool will allow you to backtest strategies across multiple securities at once. Allowing you to easier understand if your strategy is robust. If you are familiar with the PineCoders backtesting engine , then you will find this indicator pleasant to work with as it is an adaptation based on that work. Much of the functionality has been kept the same, or enhanced, with some minor adjustments I made on the account of creating a more subjectively intuitive tool.
█ HISTORY
The original purpose of the backtesting engine (`BTE`) was to bridge the gap between strategies and studies . Previously, strategies did not contain the ability to send alerts, but were necessary for backtesting. Studies on the other hand were necessary for sending alerts, but could not provide backtesting results . Often, traders would have to manage two separate Pine scripts to take advantage of each feature, this was less than ideal.
The `BTE` published by PineCoders offered a solution to this issue by generating backtesting results under the context of a study(). This allowed traders to backtest their strategy and simultaneously generate alerts for automated trading, thus eliminating the need for a separate strategy() script (though, even converting the engine to a strategy was made simple by the PineCoders!).
Fast forward a couple years and PineScript evolved beyond these issues and alerts were introduced into strategies. The BTE was not quite as necessary anymore, but is still extremely useful as it contains extra features and data not found under the strategy() context. Below is an excerpt of features contained by the BTE:
"""
More than `40` built-in strategies,
Customizable components,
Coupling with your own external indicator,
Simple conversion from Study to Strategy modes,
Post-Exit analysis to search for alternate trade outcomes,
Use of the Data Window to show detailed bar by bar trade information and global statistics, including some not provided by TV backtesting,
Plotting of reminders and generation of alerts on in-trade events.
"""
Before I go any further, I want to be clear that the BTE is STILL a good tool and it is STILL very useful. The Portfolio Backtesting Engine I am introducing is only a tangental advancement and not to be confused as a replacement, this tool would not have been possible without the `BTE`.
█ THE PROBLEM
Most strategies built in Pine are limited by one thing. Data. Backtesting should be a rigorous process and researchers should examine the performance of their strategy across all market regimes; that includes, bullish and bearish markets, ranging markets, low volatility and high volatility. Depending on your TV subscription The Pine Engine is limited to 5k-20k historical bars available for backtesting, which can often leave the strategy results wanting. As a general rule of thumb, strategies should be tested across a quantity of historical bars which will allow for at least 100 trades. In many cases, the lack of historical bars available for backtesting and frequency of the strategy signals produces less than 100 trades, rendering your strategy results inconclusive.
█ THE SOLUTION
In order to be confident that we have a robust strategy we must test it across all market regimes and we must have over 100 trades. To do this effectively, researchers can use the Portfolio Backtesting Engine (PBTE).
By testing a strategy across a carefully selected portfolio of securities, researchers can now gather 5k-20k historical bars per security! Currently, the PTBE allows up to 5 securities, which amounts to 25k-100k historical bars.
█ HOW TO USE
1 — Add the indicator to your chart.
• Confirm inputs. These will be the most important initial values which you can change later by clicking the gear icon ⚙ and opening up the settings of the indicator.
2 — Select a portfolio.
• You will want to spend some time carefully selecting a portfolio of securities.
• Each security should be uncorrelated.
• The entire portfolio should contain a mix of different market regimes.
You should understand that strategies generally take advantage of one particular type of market regime. (trending, ranging, low/high volatility)
For example, the default RSI strategy is typically advantageous during ranging markets, whereas a typical moving average crossover strategy is advantageous in trending markets.
If you were to use the standard RSI strategy during a trending market, you might be selling when you should be buying.
Similarily, if you use an SMA crossover during a ranging market, you will find that the MA's may produce many false signals.
Even if you build a strategy that is designed to be used only in a trending market, it is still best to select a portfolio of all market regimes
as you will be able to test how your strategy will perform when the market does something unexpected.
3 — Test a built-in strategy or add your own.
• Navigate to gear icon ⚙ (settings) of strategy.
• Choose your options.
• Select a Main Entry Strat and Alternate Entry Strat .
• If you want to add your own strategy, you will need to modify the source code and follow the built-in example.
• You will only need to generate (buy 1 / sell -1/ neutral 0) signals.
• Select a Filter , by default these are all off.
• Select an Entry Stop - This will be your stop loss placed at the trade entry.
• Select Pyamiding - This will allow you to stack positions. By default this is off.
• Select Hard Exits - You can also think of these as Take Profits.
• Let the strategy run and take note of the display tables results.
• Portfolio - Shows each security.
• The strategy runs on each asset in your portfolio.
• The initial capital is equally distributed across each security.
So if you have 5 securities and a starting capital of 100,000$ then each security will run the strategy starting with 20,000$
The total row will aggregate the results on a bar by bar basis showing the total results of your initial capital.
• Net Profit (NP) - Shows profitability.
• Number of Trades (#T) - Shows # of trades taken during backtesting period.
• Typically will want to see this number greater than 100 on the "Total" row.
• Average Trade Length (ATL) - Shows average # of days in a trade.
• Maximum Drawdown (MD ) - Max peak-to-valley equity drawdown during backtesting period.
• This number defines the minimum amount of capital required to trade the system.
• Typically, this shouldn’t be lower than 34% and we will want to allow for at least 50% beyond this number.
• Maximum Loss (ML) - Shows largest loss experienced on a per-trade basis.
• Normally, don’t want to exceed more than 1-2 % of equity.
• Maximum Drawdown Duration (MDD) - The longest duration of a drawdown in equity prior to a new equity peak.
• This number is important to help us psychologically understand how long we can expect to wait for a new peak in account equity.
• Maximum Consecutive Losses (MCL) - The max consecutive losses endured throughout the backtesting period.
• Another important metric for trader psychology, this will help you understand how many losses you should be prepared to handle.
• Profit to Maximum Drawdown (P:MD) - A ratio for the average profit to the maximum drawdown.
• The higher the ratio is, the better. Large profits and small losses contribute to a good PMD.
• This metric allows us to examine the profit with respect to risk.
• Profit Loss Ratio (P:L) - Average profit over the average loss.
• Typically this number should be higher in trend following systems.
• Mean reversion systems show lower values, but compensate with a better win %.
• Percent Winners (% W) - The percentage of winning trades.
• Trend systems will usually have lower win percentages, since statistically the market is only trending roughly 30% of the time.
• Mean reversion systems typically should have a high % W.
• Time Percentage (Time %) - The amount of time that the system has an open position.
• The more time you are in the market, the more you are exposed to market risk, not to mention you could be using that money for something else right?
• Return on Investment (ROI) - Your Net Profit over your initial investment, represented as a percentage.
• You want this number to be positive and high.
• Open Profit (OP) - If the strategy has any open positions, the floating value will be represented here.
• Trading Days (TD) - An important metric showing how many days the strategy was active.
• This is good to know and will be valuable in understanding how long you will need to run this strategy in order to achieve results.
█ FEATURES
These are additional features that extend the original `BTE` features.
- Portfolio backtesting.
- Color coded performance results.
- Circuit Breakers that will stop trading.
- Position reversals on exit. (Simulating the function of always in the market. Similar to strategy.entry functionality)
- Whipsaw Filter
- Moving Average Filter
- Minimum Change Filter
- % Gain Equity Exit
- Popular strategies, (MACD, MA cross, supertrend)
Below are features that were excluded from the original `BTE`
- 2 stage in-trade stops with kick-in rules (This was a subjective decision to remove. I found it to be complex and thwarted my use of the `BTE` for some time.)
- Simple conversion from Study to Strategy modes. (Not possible with multiple securities)
- Coupling with your own external indicator (Not really practical to use with multiple securities, but could be used if signals were generated based on some indicator which was not based on the current chart)
- Use of the Data Window to show detailed bar by bar trade information and global statistics.
- Post Exit Analysis.
- Plotting of reminders and generation of alerts on in-trade events.
- Alerts (These may be added in the future by request when I find the time.)
█ THANKS
The whole PineCoders team for all their shared knowledge and original publication of the BTE and Richard Weismann for his ideas on building robust strategies.
═════════════════════════════════════════════════════════════════════════
% Sensitivity MA Cross [racer8]This is my third published indicator on % Sensitivity MA, if you're not familiar with it, go check out my first one.
This time its a cross between 2 % Sensitivity MAs.
Moving Average CrossNote: This is just an idea, I did not test this for trading.
MA Cross normally uses close as source in the moving averages, this script uses highs and lows as source.
In an uptrend you will see the 20 period high EMA and 50 period low EMA, once they cross, the indicator will switch to 20 period low EMA and 50 period high EMA. This gives it way less fake crosses as you see in the image on BTC.
As i said above, this is just an idea. If you change the settings, they might not cross at all.. so do your own testing.
Hope this code can help someone.
MultiType Shifting Predictive Moving Averages (MA) CrossoverJust 2 Moving Averages with adjustable settings and shifting capability, plus signals and predicting continuations.
At the time of publish these different types of MAs are supported:
- SMA (Simple)
- EMA (Exponential)
- DEMA (Double Exponential)
- TEMA (Triple Exponential)
- RMA (Adjusted Exponential)
- WMA (Weighted)
- VWMA (Volume Weighted)
- SWMA (Symmetrically Weighted)
- HMA (Hull)
I'm looking forward to any idea about filtering the signals. Thanks.
SW System - EMAs - Pivots v2//=========================================================
// Indicator Name: SW System - Traditional Pivots and MA cross alerts - Plus Psychological Sup/Res
// Type: Main panel
// Version: 2
// Description: MA cross alerts - Plus Psychological Sup/Res
// Traditional Pivots in any time frame
// Author: Sergio Waldoke (Argentina)
// First Release: June 23rd, 2019
// Last Release: June 27 th, 2020
//
// This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © galileogalilei1 (Sergio Waldoke)
//==========================================================
Set of tendence and Support/Resistance with Pivots and psychological S/R in main prices. Four moving averages are provide which may be chosen between EMA or simple Moving Average.
Some alerts in crosses are provide.
Enjoy!
Hull 2xPlots 2 Hull MA's, 1 Fast and 1 Slow
Can Paint Bars according to Hull MA Cross
Buy / Sell Alerts for MA Crossing
Fast-Slow MA Cross on custom timeframe (with alerts)A simple script for tracking your moving average crossing with an option for a fixed time frame and a 3 additional MAs for reference.
Bitazu MA 5,10Displays 5,10 MAs on a single indicator.
Useful for Crypto trading and reduced the number of indicators needed to view multiple EMAs
When shorter MA crosses over the longer it's a good sign of Bullish/Bearish reversal.
This sentiment is more true at longer timeframes, such as daily candles, as the trend has more momentum.
Bitazu MA 10,20Displays 10, 20 MAs on a single indicator.
Useful for Crypto trading and reduced the number of indicators needed to view multiple MAs
When shorter MA crosses over the longer it's a good sign of Bullish/Bearish reversal.
This sentiment is more true at longer timeframes, such as daily candles, as the trend has more momentum.
Market Sentiment Index US Top 40 [Pt]▮Overview
Market Sentiment Index US Top 40 [Pt} shows how the largest US stocks behave together. You pick one simple measure—High Low breakouts, Above Below moving average, or RSI overbought/oversold—and see how many of your chosen top 10/20/30/40 NYSE or NASDAQ names are bullish, neutral, or bearish.
This tool gives you a quick view of broad-market strength or weakness so you can time trades, confirm trends, and spot hidden shifts in market sentiment.
▮Key Features
► Three Simple Modes
High Low Index: counts stocks making new highs or lows over your lookback period
Above Below MA: flags stocks trading above or below their moving average
RSI Sentiment: marks overbought or oversold stocks and plots a small histogram
► Universe Selection
Top 10, 20, 30, or 40 symbols from NYSE or NASDAQ
Option to weight by market cap or treat all symbols equally
► Timeframe Choice
Use your chart’s timeframe or any intraday, daily, weekly, or monthly resolution
► Histogram Smoothing
Two optional moving averages on the sentiment bars
Markers show when the faster average crosses above or below the slower one
► Ticker Table
Optional on-chart table showing each ticker’s state in color
Grid or single-row layout with adjustable text size and color settings
▮Inputs
► Mode and Lookback
Pick High Low, Above Below MA, or RSI Sentiment
Set lookback length (for example 10 bars)
If using Above Below MA, choose the moving average type (EMA, SMA, etc.)
► Universe Setup
Market: NYSE or NASDAQ
Number of symbols: 10, 20, 30, or 40
Weights: on or off
Timeframe: blank to match chart or pick any other
► Moving Averages on Histogram
Enable fast and slow averages
Set their lengths and types
Choose colors for averages and markers
► Table Options
Show or hide the symbol table
Select text size: tiny, small, or normal
Choose layout: grid or one-row
Pick colors for bullish, neutral, and bearish cells
Show or hide exchange prefixes
▮How to Read It
► Sentiment Bars
Green means bullish
Red means bearish
Near zero means neutral
► Zero Line
Separates bullish from bearish readings
► High Low Line (High Low mode only)
Smooth ratio of highs versus lows over your lookback
► MA Crosses
Fast MA above slow MA hints rising breadth
Fast MA below slow MA hints falling breadth
► Ticker Table
Each cell colored green, gray, or red for bull, neutral, or bear
▮Use Cases
► Confirm Market Trends
Early warning when price makes highs but breadth is weak
Catch rallies when breadth turns strong while price is flat
► Spot Sector Rotation
Switch between NYSE and NASDAQ to see which group leads
Watch tech versus industrial breadth to track money flow
► Filter Trade Signals
Enter longs only when breadth is bullish
Consider shorts when breadth turns negative
► Combine with Other Indicators
Use RSI Sentiment with trend tools to spot overextended moves
Add volume indicators in High Low mode for breakout confirmation
► Timeframe Analysis
Daily for big-picture bias
Intraday (15-min) for precise entries and exits
[blackcat] L3 Ichimoku FusionCOMPREHENSIVE ANALYSIS OF THE L3 ICHIMOKU FUSION INDICATOR
🌐 Overview:
The L3 Ichimoku Fusion is a sophisticated multi-layered technical analysis tool integrating classic Japanese market forecasting techniques with enhanced dynamic elements designed specifically for identifying potential turning points in financial instruments' pricing action.
Key Purpose:
To provide traders with an intuitive yet powerful framework combining established ichimoku principles while incorporating additional validation checkpoints derived from cross-timeframe convergence studies.
THEORETICAL FOUNDATION EXPLAINED
🎓 Conceptual Background:
:
• Conversion & Base Lines tracking intermediate term averages
• Lagging Span providing delayed feedback mechanism
• Lead Spans projecting future equilibrium states
:
• Adaptive parameter scaling options
• Automated labeling system for critical junctures
• Real-time alert infrastructure enabling immediate response capability
PARAMETER CONFIGURATION GUIDE
⚙️ Input Parameters Explained In Detail:
Regional Setting Selection:**
→ Oriental Configuration: Standardized approach emphasizing slower oscillation cycles
→ Occidental Variation: Optimized settings reducing lag characteristics typical of original methodology
Multiplier Adjustment Functionality:**
↔ Allows fine-graining oscillator responsiveness without altering core relationship dynamics
↕ Enables adaptation to various instrument volatility profiles efficiently
Displacement Value Control:**
↓ Controls lead/lag offset positioning relative to current prices
↑ Provides flexibility in adjusting visual representation alignment preferences
DYNAMIC CALCULATION PROCESSES
💻 Algorithmic Foundation:
:
Utilizes highest/lowest extremes over specified lookback windows
Produces more responsive conversions compared to simple MAs
:
→ Confirms directional bias across multiple independent criteria
← Ensures higher probability outcomes reduce random noise influence
:
♾ Creates persistent annotations documenting significant events
🔄 Handles complex state transitions maintaining historical record integrity
VISUALIZATION COMPONENTS OVERVIEW
🎨 Display Architecture Details:
:
→ Solid colored trendlines representing conversion/base relationships
↑ Fill effect overlay differentiating expansion/compression phases
↔ Offset spans positioned according to calculated displacement values
:
→ Green shading indicates positive configuration scenarios
↘ Red filling highlights negative arrangement situations
⟳ Orange transition areas mark transitional periods requiring caution
:
✔️ LE: Long Entry opportunity confirmed
❌ SE: Short Setup validated
☑ XL/XS: Position closure triggers active
✓ RL/RS: Potential re-entry chances emerging
STRATEGIC APPLICATION FRAMEWORK
📋 Practical Deployment Guidelines:
Initial Integration Phase:
Select appropriate timeframe matching trading horizon preference
Configure input parameters aligning with target asset behavior traits
Test thoroughly under simulated conditions prior to live usage
Active Monitoring Procedures:
• Regular observation of cloud formation evolution
• Tracking label placements against actual price movements
• Noting pattern development leading up to signaled entry/exit moments
Decision Making Process Flowchart:
→ Identify clear breakout/crossover events exceeding confirmation thresholds
← Evaluate contextual factors supporting/rejecting indicated direction
↑ Execute trades only after achieving required number of confirming inputs
PERFORMANCE OPTIMIZATION TECHNIQUES
🚀 Refinement Strategies:
Calibration Optimization Approach:
→ Start testing with default suggested configurations
↓ Gradually adjust individual components observing outcome changes
↑ Document findings systematically building personalized version profile
Context Adaptability Methods:
➕ Add supplementary indicators enhancing overall reliability
➖ Remove unnecessary complexity layers if causing confusion
✨ Incorporate custom rules adapting to specific security behaviors
Efficiency Improvement Tactics:
🔧 Streamline redundant processing routines where possible
♻️ Leverage shared data streams whenever feasible
⚡ Optimize refresh frequencies balancing update speed vs computational load
RISK MITIGATION PROTOCOLS
🛡️ Safety Measures Implementation Guide:
Position Sizing Principles:
∅ Never exceed preset maximum exposure limits defined by risk tolerance
± Scale positions proportionally per account size/market capitalization
× Include slippage allowances within planning stages accounting for liquidity variations
Validation Requirements Hierarchy:
☐ Verify signals meet minimum number of concurrent validations
⛔ Ignore isolated occurrences lacking adequate evidence backing
▶ Look for convergent evidence strengthening conviction level
Emergency Response Planning:
↩ Establish predefined exit strategies including trailing stops mechanisms
🌀 Plan worst-case scenario responses ahead avoiding panic reactions
⇄ Maintain contingency plans addressing unexpected adverse developments
USER EXPERIENCE ENHANCEMENT FEATURES
🌟 Additional Utility Functions:
Alert System Infrastructure:
→ Automatic notifications delivered directly to user devices
↑ Message content customized explaining triggered condition specifics
↔ Timing optimization ensuring minimal missed opportunities due to latency issues
Historical Review Capability:
→ Ability to analyze past performance retrospectively
↓ Assess effectiveness across varying market regimes objectively
↗ Generate statistics measuring success/failure rates quantitatively
Community Collaboration Support:
↪ Share personal optimizations benefiting wider trader community
↔ Exchange experiences improving collective understanding base
✍️ Provide constructive feedback aiding ongoing refinement process
CONCLUSION AND NEXT STEPS
This comprehensive guide serves as your roadmap toward mastering the capabilities offered by the L3 Ichimoku Fusion indicator effectively. Success relies heavily on disciplined application combined with continuous learning and adjustment processes throughout implementation journey.
Wishing you prosperous trading endeavors! 👋💰
Indiq 2.0The functionality of the indicator includes the following features:
Moving Averages (MA):
The ability to adjust periods for short (short_ma_length) and long (long_ma_length) moving averages.
Display of moving averages on the chart:
Short MA (blue line).
Long MA (red line).
Generation of buy and sell signals:
Buy (BUY): When the short MA crosses the long MA from below.
Sell (SELL): When the short MA crosses the long MA from above.
Visualization of signals on the chart:
Buy is displayed as a green BUY marker below the candle.
Sell is displayed as a red SELL marker above the candle.
Liquidity Heatmap:
Liquidity levels:
Levels are calculated based on the closing price and a step (liquidity_step).
Levels are grouped by the nearest price values.
Volumes at levels:
Volume (volume) is accumulated for each liquidity level.
Levels with a volume less than min_volume_filter are not displayed.
Time filtering:
Levels that have not been updated within the last time_filter bars are not displayed.
Volatility filtering:
Levels are filtered by volatility (ATR) to exclude those outside the volatility range.
Color gradient:
The color of levels depends on volume (gradient from gradient_start_color to gradient_end_color).
Visualization:
Liquidity levels are displayed as horizontal lines.
Volumes at levels are shown as text labels.
RSI Filtering:
The ability to enable/disable RSI filtering (rsi_filter).
Liquidity levels are filtered based on overbought (rsi_overbought) and oversold (rsi_oversold) conditions.
Levels that do not meet RSI conditions are not displayed.
MACD Filtering:
The ability to enable/disable MACD filtering (macd_filter).
Liquidity levels are filtered based on the MACD histogram condition (e.g., only if the histogram is above zero).
Levels that do not meet MACD conditions are not displayed.
Display of Market Maker Buys:
Condition for market maker buys:
Volume exceeds the average volume over the last 20 bars by 2 times.
Closing price is above the opening price.
Market maker buys are displayed on the chart as orange MM Buy markers below the candle.
Indicator Settings:
Moving average parameters:
short_ma_length: Period for the short MA.
long_ma_length: Period for the long MA.
Liquidity heatmap parameters:
liquidity_step: Step between liquidity levels.
max_levels: Maximum number of levels to display.
time_filter: Time filter (last N bars).
min_volume_filter: Minimum volume for displaying a level.
volatility_filter: Volatility filter (ATR multiplier).
RSI parameters:
rsi_filter: Enable/disable RSI filtering.
rsi_overbought: Overbought RSI level.
rsi_oversold: Oversold RSI level.
MACD parameters:
macd_filter: Enable/disable MACD filtering.
Color settings:
gradient_start_color: Starting color of the gradient.
gradient_end_color: Ending color of the gradient.
Visualization:
Moving averages:
Short MA: Blue line.
Long MA: Red line.
Signals:
Buy: Green BUY marker.
Sell: Red SELL marker.
Liquidity heatmap:
Liquidity levels: Horizontal lines with a color gradient.
Volumes: Text labels at levels.
Market maker buys:
Orange MM Buy markers.
Alerts:
The ability to set alerts for signals:
Buy (BUY).
Sell (SELL).
Additional Features:
Flexible filter settings:
Filtering by time, volume, volatility, RSI, and MACD.
Extensibility:
The ability to add new filters (e.g., Stochastic, Volume Profile, etc.).
Visual customization:
Adjustment of colors, sizes, and display styles.
Summary:
The indicator provides a comprehensive tool for analyzing liquidity, generating trading signals, and tracking market maker activity. It combines:
A liquidity heatmap.
Signals based on moving averages.
Filtering by RSI and MACD.
Display of market maker buys.
Flexible settings and visualization.
This indicator is suitable for traders who want to analyze liquidity levels, identify entry and exit points, and monitor the actions of large market players.
Meme Coin Buy Signal Indicator by asharThis custom TradingView indicator is specifically designed for meme coins, using technical analysis indicators to identify optimal buy signals. It combines short-term moving averages, volume spikes, and Bitcoin trend alignment to pinpoint potential entry points during high-momentum periods.
Indicator Components:
Moving Averages (MA): A 5-period fast MA and a 13-period slow MA highlight short-term price momentum. Buy signals are generated when the fast MA crosses above the slow MA, indicating potential upward momentum.
Volume Spike Detection: The indicator detects high-volume periods using a multiplier. If the current volume exceeds the 10-period average volume by the set multiplier (default: 2.0), it indicates increased buying interest, which is crucial for meme coins.
Bitcoin Trend Alignment: The trend of Bitcoin, a market-wide sentiment indicator, is gauged with a 20-day moving average. Buy signals are validated only when Bitcoin is also in an uptrend, providing additional bullish confirmation for meme coins.
Buy Signal Criteria: A buy signal is triggered when:
The fast MA crosses above the slow MA.
Volume is above the average by the set multiplier.
The price is above the slow MA.
Bitcoin is trending up based on the 20-day moving average.
This indicator is ideal for meme coin traders looking to time entries with momentum-driven trends, aligning volume and trend indicators for a more comprehensive approach to high-risk assets.
Dynamic RSI Mean Reversion StrategyDynamic RSI Mean Reversion Strategy
Overview:
This strategy uses an RSI with ATR-Adjusted OB/OS levels in order to enhance the quality of it's mean reversion trades. It also incorporates a form of trend filtering in an effort to minimize downside and maximize upside. The backtest has fewer trades, as it uses substantial filtering to enhance trade quality. As you can see, I didn't cherry pick the results, so the results aren't the most beautiful thing you'll see in your life. I did this to ensure nobody gets misled. If you need a higher frequency of trades, consider removing the trend filter or increasing the length of the EMAs used for trend detection.
Features:
Dynamic OB/OS Levels: Uses ATR to adjust overbought and oversold thresholds dynamically, making the RSI more responsive in varying volatility conditions. This approach enhances signal strength by expanding the RSI range in high volatility and tightening it in low volatility.
Mean Reversion Focus: Designed for mean reversion but incorporates a trend-following filter to reduce countertrend trades. When the RSI is high, it often indicates an uptrend, so a trend filter prevents shorting in these cases and the same goes for downtrends and longing.
Trend Filtering: A moving average cross trend filter checks for the trend direction, with the RSI signal line color-coded to reflect trend shifts. Entries occur when the RSI crosses above or below the dynamic thresholds and is not a countertrend trade.
Stop Losses: Stop losses are set based on ATR distance from the entry price, providing volatility-adjusted protection.
Note:
If you're using this strategy on assets with a higher price, remember to increase the initial capital in the strategy settings. Otherwise, the strategy won't generate any (or many) trades and you'll end up with some inaccurate results.
Recommended Use:
Test it on different assets and timeframes. I’ve found the best results with standard RSI inputs, a relatively slow ATR, and a slower MA cross for trend filtering. Thus, the defaults are set that way. If the trend metrics are too slow, you’ll filter out too many good trades while allowing crummy ones; if too fast, most trades may be filtered out. As always, this has a lot of configurability so experiment to find the balance that works for your trading style.
XAUUSD Multi-Timeframe Trend AnalyzerOverview
The "XAUUSD Multi-Timeframe Trend Analyzer" is an advanced script designed to provide a comprehensive analysis of the XAUUSD (Gold/US Dollar) trend across multiple timeframes simultaneously. By combining several key technical indicators, this tool helps traders quickly assess the market direction and trend strength for M15, M30, H1, H4, and D1 timeframes.
Multi-Timeframe Analysis: Displays the trend direction and strength across M15, M30, H1, H4, and D1 timeframes, allowing for a complete overview in a single glance.
Comprehensive Indicator Blend: Utilizes six popular technical indicators to determine the trend—Moving Averages, RSI, MACD, Bollinger Bands, DMI, and Parabolic SAR.
Trend Strength Scoring: Provides a numerical trend strength score (from -6 to 6) based on the alignment of the indicators, with positive values indicating uptrends and negative values for downtrends.
Visual Table Display: Displays results in a color-coded table (green for uptrend, red for downtrend, yellow for neutral) with a strength score for each timeframe, helping traders quickly assess market conditions.
How It Works
This script calculates the overall trend and its strength for each selected timeframe by analyzing six widely-used technical indicators:
Moving Averages (MA): The script uses a Fast and a Slow Moving Average. When the Fast MA crosses above the Slow MA, it indicates an uptrend. When the Fast MA crosses below, it signals a downtrend.
Relative Strength Index (RSI): The RSI is used to assess momentum. An RSI value above 50 suggests bullish momentum, while a value below 50 suggests bearish momentum.
Moving Average Convergence Divergence (MACD): MACD measures momentum and trend direction. When the MACD line crosses above the signal line, it signals bullish momentum; when it crosses below, it signals bearish momentum.
Bollinger Bands: These measure price volatility. When the price is above the middle Bollinger Band, the script considers the trend to be bullish, and when it's below, bearish.
Directional Movement Index (DMI): The DMI compares positive directional movement (DI+) and negative directional movement (DI-). A stronger DI+ over DI- signals an uptrend and vice versa.
Parabolic SAR: This indicator is used for determining potential trend reversals and setting stop-loss levels. If the price is above the Parabolic SAR, it indicates an uptrend, and if below, a downtrend.
Trend Strength Calculation
The script calculates a trend strength score for each timeframe:
Each indicator adds or subtracts 1 to the score based on whether it aligns with an uptrend or a downtrend.
A score of 6 indicates a Strong Uptrend, with all indicators aligned bullishly.
A score of -6 indicates a Strong Downtrend, with all indicators aligned bearishly.
Intermediate scores (e.g., 2 or -2) indicate Weak Uptrend or Weak Downtrend, suggesting that not all indicators are in agreement.
A score between 1 and -1 indicates a Neutral trend, suggesting uncertainty in the market.
How to Use
Assess Trend Direction and Strength: The table provides an easy-to-read summary of the trend and its strength on different timeframes. Look for timeframes where the strength is high (either 6 for a strong uptrend or -6 for a strong downtrend) to confirm the market’s overall direction.
Use in Conjunction with Other Strategies: This indicator is designed to provide a comprehensive view of the market. Traders should combine it with other strategies, such as price action analysis or candlestick patterns, to further confirm their trades.
Trend Reversal or Continuation: A weak trend (e.g., a strength of 2 or -2) could signal a possible reversal or a trend that has lost momentum. Strong trends (with a strength of 6 or -6) indicate higher confidence in trend continuation.
Multiple Timeframe Confirmation: Look for alignment across multiple timeframes to confirm the strength and direction of the trend before entering trades. For example, if M15, M30, and H1 are all showing a strong uptrend, it suggests a higher probability of the trend continuing.
Customization Options
- Adjustable Indicators: Users can modify the length and parameters of the Moving Averages, RSI, MACD, Bollinger Bands, DMI, and Parabolic SAR to suit their trading style.
- Flexible Timeframes: You can toggle between different timeframes (M15, M30, H1, H4, D1) to focus on the intervals most relevant to your strategy.
Ideal For
- Traders looking for a detailed, multi-timeframe trend analysis tool for XAUUSD.
- Traders who rely on trend-following strategies and need confirmation across multiple timeframes.
- Those who prefer a multi-indicator approach to avoid false signals and improve the accuracy of their trades.
Disclaimer
This indicator is for informational and educational purposes only. It is recommended to combine this with proper risk management strategies and your own analysis. Past performance does not guarantee future results. Always perform your own due diligence before making trading decisions.
