Divergence Detector [TradingFinder] RSI + MACD + AO Oscillator 🔵 Introduction
🟣 Understanding Divergence
As mentioned, divergence occurs in technical analysis when a stock's price behaves contrary to indicators on the price chart. Divergence can signify either a reversal of the stock's trend or a continuation of the previous trend correction.
Divergences can act as reversal patterns or continuation patterns. Moreover, divergences can be utilized to identify potential support and resistance levels.
For instance, when an indicator is trending upwards and positive, but the price is declining and trending downwards, divergence occurs. Divergence in a stock indicates trader indecision in buying and selling and warns traders to reconsider their decisions regarding buying or holding the stock.
Divergence aids analysts in identifying critical price points. In indicator divergences, it serves as a potent signal in the realm of technical analysis.
🟣 Types of Divergence
1.Regular Divergence
o Positive Regular Divergence (RD+)
o Negative Regular Divergence (RD-)
2.Hidden Divergence
o Positive Hidden Divergence (HD+)
o Negative Hidden Divergence (HD-)
3.Time Divergence
Key Note : This indicator is specifically designed to identify "Regular Divergence" only. Therefore, the following explanation pertains to this type of divergence.
🔵 Regular Divergence/Convergence
Regular Divergence(Convergence) occurs due to conflicting behavior between the indicator and the price chart, typically at the end of a trend. Recognizing Regular Divergence suggests an anticipation of a trend reversal or a pattern resembling a reversal.
🟣 Positive Regular Divergence (RD+)
In contrast to negative divergence, positive Regular Divergence occurs at the end of a downtrend and between two price lows. It manifests when the price forms a new low on the price chart, but the indicator fails to recognize it.
Positive Regular Divergence indicates strong buying pressure and weak selling pressure. Following the identification of positive divergence on the chart, one can anticipate a price increase for the examined stock.
🟣 Negative Regular Divergence (RD-)
This type of Regular Divergence emerges between two price highs during an uptrend. A new high is formed on the price chart, but the indicator fails to acknowledge it. This scenario indicates negative Regular Divergence.
The likelihood of a subsequent market downturn is high. Negative divergence signifies strong selling pressure and weak buying pressure, suggesting an unfavorable future for the stock.
🔵 How to use
By utilizing the "Fractal Period" input, you can specify your desired periods for identifying divergences.
Additionally, through the "Divergence Detect Method" feature, you can choose which oscillators (MACD, RSI, or AO) to base divergence identification on.
Divergence in MACD Oscillator :
Divergence in the MACD indicator occurs when the price chart and the MACD line form a noticeable opposing pattern, meaning the price moves contrary to the MACD line. In this scenario, one expects a reversal in price direction.
Divergence in RSI Oscillator :
If divergence occurs during a downtrend on the price chart (two consecutive lows, with the second low being lower) and on the corresponding RSI point (two consecutive lows, with the second low being higher), it signifies positive Regular Divergence and implies a buying signal.
Conversely, if divergence occurs during an uptrend on the price chart (two consecutive highs, with the second high being higher) and on the corresponding RSI point (two consecutive highs, with the second high being lower), it indicates negative Regular Divergence, signaling a selling opportunity.
Divergence in AO Oscillator :
The AO indicator calculates histograms similar to the AO base. It calculates the difference between the simple moving averages of 5 and 34 periods based on the median of each bar. Then, it plots the bars based on the difference.
It then compares the histograms to detect peaks and troughs in the AO histograms and compares the identified peaks and troughs to the price. Whenever divergence is detected, it plots lines and arrows.
🔵 Table
The table contains information on the functional features of this oscillator that you can utilize. Four categories of information are presented in the table: "Exist," "Consecutive," "Divergence Quality," and "Change Phase Indicator."
Exist :
If divergence exists, you'll see "+" in this row.
Consecutive :
Divergences may occur consecutively. If same-type divergences form within short intervals, you can observe the count in this row.
Divergence Quality : Based on the number of consecutive divergences, their quality can be evaluated. If one divergence exists, its quality is considered "Normal." If two divergences exist, the quality is "Good," and if three or more divergences exist, the quality is considered "Strong."
Change Phase Indicator : If a phase change occurs between two oscillation peaks formed based on divergence, this change is identified and displayed in this row.
在腳本中搜尋" TABLE "
WTI Crude Oil Lot Size Calculator by AdrianFx94Indicator on Trading Chart: Once you add this script to your trading chart (specifically a WTI Crude Oil chart), it appears as an indicator. This means it runs alongside the price data and other technical analysis tools you might be using.
Input Your Trading Parameters:
Balance (USD): You need to enter your trading account balance in USD. This is the amount of money you have in your account.
Risk Percentage (%): This is where you define the percentage of your account balance that you're willing to risk in a single trade. For example, if your account balance is $5000 and you set the risk percentage to 1%, you're willing to risk $50 on a trade.
Stop Loss Pip Size (Pip): Here, you enter the size of your stop loss in pips. A pip is a small measure of change in a currency pair in the forex market. In the context of WTI Crude Oil trading, it represents a small change in the price.
Automated Lot Size Calculation: Based on the inputs you provide, the script automatically calculates the lot size you should use for your trade. The calculation takes into account the balance you're willing to risk, the percentage of risk, and the stop loss size. This helps in managing risk by suggesting the amount of WTI Crude Oil you should trade (in lots) that aligns with your risk tolerance.
Display Results in a Table: The script generates a table displayed on the top right corner of your chart. This table shows:
Your entered balance (in USD).
The risk percentage you've set.
The calculated lot size, which indicates how many lots of WTI Crude Oil you can trade based on your risk management parameters.
Real-Time Updates: As this script is part of an indicator on your chart, it updates in real time. This means if your account balance changes or if you decide to adjust your risk parameters, you can re-enter these values, and the script will update the lot size accordingly.
This tool is particularly useful for WTI Crude Oil traders who follow strict risk management rules. By automating the calculation of the lot size, it saves time and helps in making informed and disciplined trading decisions.
Day/Week/Month Metrics (Zeiierman)█ Overview
The Day/Week/Month Metrics (Zeiierman) indicator is a powerful tool for traders looking to incorporate historical performance into their trading strategy. It computes statistical metrics related to the performance of a trading instrument on different time scales: daily, weekly, and monthly. Breaking down the performance into daily, weekly, and monthly metrics provides a granular view of the instrument's behavior.
The indicator requires the chart to be set on a daily timeframe.
█ Key Statistics
⚪ Day in month
The performance of financial markets can show variability across different days within a month. This phenomenon, often referred to as the "monthly effect" or "turn-of-the-month effect," suggests that certain days of the month, especially the first and last days, tend to exhibit higher than average returns in many stock markets around the world. This effect is attributed to various factors including payroll contributions, investment of monthly dividends, and psychological factors among traders and investors.
⚪ Edge
The Edge calculation identifies days within a month that consistently outperform the average monthly trading performance. It provides a statistical advantage by quantifying how often trading on these specific days yields better returns than the overall monthly average. This insight helps traders understand not just when returns might be higher, but also how reliable these patterns are over time. By focusing on days with a higher "Edge," traders can potentially increase their chances of success by aligning their strategies with historically more profitable days.
⚪ Month
Historically, the stock market has exhibited seasonal trends, with certain months showing distinct patterns of performance. One of the most well-documented patterns is the "Sell in May and go away" phenomenon, suggesting that the period from November to April has historically brought significantly stronger gains in many major stock indices compared to the period from May to October. This pattern highlights the potential impact of seasonal investor sentiment and activities on market performance.
⚪ Day in week
Various studies have identified the "day-of-the-week effect," where certain days of the week, particularly Monday and Friday, show different average returns compared to other weekdays. Historically, Mondays have been associated with lower or negative average returns in many markets, a phenomenon often linked to the settlement of trades from the previous week and negative news accumulation over the weekend. Fridays, on the other hand, might exhibit positive bias as investors adjust positions ahead of the weekend.
⚪ Week in month
The performance of markets can also vary within different weeks of the month, with some studies suggesting a "week of the month effect." Typically, the first and the last week of the month may show stronger performance compared to the middle weeks. This pattern can be influenced by factors such as the timing of economic reports, monthly investment flows, and options and futures expiration dates which tend to cluster around these periods, affecting investor behavior and market liquidity.
█ How It Works
⚪ Day in Month
For each day of the month (1-31), the script calculates the average percentage change between the opening and closing prices of a trading instrument. This metric helps identify which days have historically been more volatile or profitable.
It uses arrays to store the sum of percentage changes for each day and the total occurrences of each day to calculate the average percentage change.
⚪ Month
The script calculates the overall gain for each month (January-December) by comparing the closing price at the start of a month to the closing price at the end, expressed as a percentage. This metric offers insights into which months might offer better trading opportunities based on historical performance.
Monthly gains are tracked using arrays that store the sum of these gains for each month and the count of occurrences to calculate the average monthly gain.
⚪ Day in Week
Similar to the day in the month analysis, the script evaluates the average percentage change between the opening and closing prices for each day of the week (Monday-Sunday). This information can be used to assess which days of the week are typically more favorable for trading.
The script uses arrays to accumulate percentage changes and occurrences for each weekday, allowing for the calculation of average changes per day of the week.
⚪ Week in Month
The script assesses the performance of each week within a month, identifying the gain from the start to the end of each week, expressed as a percentage. This can help traders understand which weeks within a month may have historically presented better trading conditions.
It employs arrays to track the weekly gains and the number of weeks, using a counter to identify which week of the month it is (1-4), allowing for the calculation of average weekly gains.
█ How to Use
Traders can use this indicator to identify patterns or trends in the instrument's performance. For example, if a particular day of the week consistently shows a higher percentage of bullish closes, a trader might consider this in their strategy. Similarly, if certain months show stronger performance historically, this information could influence trading decisions.
Identifying High-Performance Days and Periods
Day in Month & Day in Week Analysis: By examining the average percentage change for each day of the month and week, traders can identify specific days that historically have shown higher volatility or profitability. This allows for targeted trading strategies, focusing on these high-performance days to maximize potential gains.
Month Analysis: Understanding which months have historically provided better returns enables traders to adjust their trading intensity or capital allocation in anticipation of seasonally stronger or weaker periods.
Week in Month Analysis: Identifying which weeks within a month have historically been more profitable can help traders plan their trades around these periods, potentially increasing their chances of success.
█ Settings
Enable or disable the types of statistics you want to display in the table.
Table Size: Users can select the size of the table displayed on the chart, ranging from "Tiny" to "Auto," which adjusts based on screen size.
Table Position: Users can choose the location of the table on the chart
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
MACD_TRIGGER_CROSS_TRIANGLEMACD Triangle Trigger Indicator by thebearfib
Overview
The MACD Cross Triangle Indicator is a powerful tool for traders who rely on the MACD's signal line crossovers to make informed trading decisions. This indicator enhances the traditional MACD by allowing users to customize triggers for bullish and bearish signals and by displaying these signals directly on the chart with visually distinctive labels.
Features
Customizable Color Scheme: Choose distinct colors for bullish and bearish signals to fit your chart's theme or your personal preference.
Flexible Trigger Conditions: Select from a variety of trigger conditions based on MACD and signal line behaviors over a specified number of bars back.
Visual Signal Indicators: Bullish and bearish signals are marked with upward and downward triangles, making it easy to spot potential entry or exit points.
Detailed Trigger Descriptions: A comprehensive table lists all available triggers and their descriptions, aiding in selection and understanding of each trigger's mechanism.
Configuration Options
Bullish and Bearish Colors: Customize the color of the labels for bullish (upward) and bearish (downward) signals.
Trend Lookback Period: Choose how far back (in bars) the indicator should look to determine the trend, affecting the calculation of certain triggers.
Trigger Selection for Bullish and Bearish Signals: Pick specific triggers for both bullish and bearish conditions from a list of 10 different criteria, ranging from MACD crossovers to historical comparisons of MACD, signal line, and histogram values.
Label Size and Font Settings: Adjust the size of the signal labels on the chart and the font size of the trigger descriptions table to ensure readability and fit with your chart layout.
Trigger Descriptions Table Position and Color: Customize the position and color of the trigger descriptions table to match your chart's aesthetic and layout preferences.
Trigger Mechanisms
Trigger 1 to 10: Each trigger corresponds to a specific condition involving the MACD line, signal line, and histogram. These include crossovers, directional changes compared to previous bars, and comparisons of current values to historical values.
Usage
1. Select Trigger Conditions: Choose the desired triggers for bullish and bearish signals based on your trading strategy.
2. Customize Visuals: Set your preferred colors for the bullish and bearish labels, adjust label and font sizes, and configure the trigger descriptions table.
3. Analyze Signals: Watch for the upward (bullish) and downward (bearish) triangles to identify potential trading opportunities based on MACD crossover signals.
Conclusion
The MACD Cross Triangle Indicator offers a customizable and visually intuitive way to leverage MACD crossover signals for trading. With its flexible settings and clear signal indicators, traders can tailor the indicator to fit their strategy and improve their decision-making process on TradingView.
Smart DCA StrategyINSPIRATION
While Dollar Cost Averaging (DCA) is a popular and stress-free investment approach, I noticed an opportunity for enhancement. Standard DCA involves buying consistently, regardless of market conditions, which can sometimes mean missing out on optimal investment opportunities. This led me to develop the Smart DCA Strategy – a 'set and forget' method like traditional DCA, but with an intelligent twist to boost its effectiveness.
The goal was to build something more profitable than a standard DCA strategy so it was equally important that this indicator could backtest its own results in an A/B test manner against the regular DCA strategy.
WHY IS IT SMART?
The key to this strategy is its dynamic approach: buying aggressively when the market shows signs of being oversold, and sitting on the sidelines when it's not. This approach aims to optimize entry points, enhancing the potential for better returns while maintaining the simplicity and low stress of DCA.
WHAT THIS STRATEGY IS, AND IS NOT
This is an investment style strategy. It is designed to improve upon the common standard DCA investment strategy. It is therefore NOT a day trading strategy. Feel free to experiment with various timeframes, but it was designed to be used on a daily timeframe and that's how I recommend it to be used.
You may also go months without any buy signals during bull markets, but remember that is exactly the point of the strategy - to keep your buying power on the sidelines until the markets have significantly pulled back. You need to be patient and trust in the historical backtesting you have performed.
HOW IT WORKS
The Smart DCA Strategy leverages a creative approach to using Moving Averages to identify the most opportune moments to buy. A trigger occurs when a daily candle, in its entirety including the high wick, closes below the threshold line or box plotted on the chart. The indicator is designed to facilitate both backtesting and live trading.
HOW TO USE
Settings:
The input parameters for tuning have been intentionally simplified in an effort to prevent users falling into the overfitting trap.
The main control is the Buying strictness scale setting. Setting this to a lower value will provide more buying days (less strict) while higher values mean less buying days (more strict). In my testing I've found level 9 to provide good all round results.
Validation days is a setting to prevent triggering entries until the asset has spent a given number of days (candles) in the overbought state. Increasing this makes entries stricter. I've found 0 to give the best results across most assets.
In the backtest settings you can also configure how much to buy for each day an entry triggers. Blind buy size is the amount you would buy every day in a standard DCA strategy. Smart buy size is the amount you would buy each day a Smart DCA entry is triggered.
You can also experiment with backtesting your strategy over different historical datasets by using the Start date and End date settings. The results table will not calculate for any trades outside what you've set in the date range settings.
Backtesting:
When backtesting you should use the results table on the top right to tune and optimise the results of your strategy. As with all backtests, be careful to avoid overfitting the parameters. It's better to have a setup which works well across many currencies and historical periods than a setup which is excellent on one dataset but bad on most others. This gives a much higher probability that it will be effective when you move to live trading.
The results table provides a clear visual representation as to which strategy, standard or smart, is more profitable for the given dataset. You will notice the columns are dynamically coloured red and green. Their colour changes based on which strategy is more profitable in the A/B style backtest - green wins, red loses. The key metrics to focus on are GOA (Gain on Account) and Avg Cost .
Live Trading:
After you've finished backtesting you can proceed with configuring your alerts for live trading.
But first, you need to estimate the amount you should buy on each Smart DCA entry. We can use the Total invested row in the results table to calculate this. Assuming we're looking to trade on BITSTAMP:BTCUSD
Decide how much USD you would spend each day to buy BTC if you were using a standard DCA strategy. Lets say that is $5 per day
Enter that USD amount in the Blind buy size settings box
Check the Blind Buy column in the results table. If we set the backtest date range to the last 10 years, we would expect the amount spent on blind buys over 10 years to be $18,250 given $5 each day
Next we need to tweak the value of the Smart buy size parameter in setting to get it as close as we can to the Total Invested amount for Blind Buy
By following this approach it means we will invest roughly the same amount into our Smart DCA strategy as we would have into a standard DCA strategy over any given time period.
After you have calculated the Smart buy size , you can go ahead and set up alerts on Smart DCA buy triggers.
BOT AUTOMATION
In an effort to maintain the 'set and forget' stress-free benefits of a standard DCA strategy, I have set my personal Smart DCA Strategy up to be automated. The bot runs on AWS and I have a fully functional project for the bot on my GitHub account. Just reach out if you would like me to point you towards it. You can also hook this into any other 3rd party trade automation system of your choice using the pre-configured alerts within the indicator.
PLANNED FUTURE DEVELOPMENTS
Currently this is purely an accumulation strategy. It does not have any sell signals right now but I have ideas on how I will build upon it to incorporate an algorithm for selling. The strategy should gradually offload profits in bull markets which generates more USD which gives more buying power to rinse and repeat the same process in the next cycle only with a bigger starting capital. Watch this space!
MARKETS
Crypto:
This strategy has been specifically built to work on the crypto markets. It has been developed, backtested and tuned against crypto markets and I personally only run it on crypto markets to accumulate more of the coins I believe in for the long term. In the section below I will provide some backtest results from some of the top crypto assets.
Stocks:
I've found it is generally more profitable than a standard DCA strategy on the majority of stocks, however the results proved to be a lot more impressive on crypto. This is mainly due to the volatility and cycles found in crypto markets. The strategy makes its profits from capitalising on pullbacks in price. Good stocks on the other hand tend to move up and to the right with less significant pullbacks, therefore giving this strategy less opportunity to flourish.
Forex:
As this is an accumulation style investment strategy, I do not recommend that you use it to trade Forex.
STRATEGY IN ACTION
Here you see the indicator running on the BITSTAMP:BTCUSD pair. You can read the indicator as follows:
Vertical green bands on historical candles represents where buy signals triggered in the past
Table on the top right represents the results of the A/B backtest against a standard DCA strategy
Green Smart Buy column shows that Smart DCA was more profitable than standard DCA on this backtest. That is shown by the percentage GOA (Gain on Account) and the Avg Cost
Smart Buy Zone label marks the threshold which the entire candle must be below to trigger a buy signal (line can be changed to a box under plotting settings)
Green color of Smart Buy Zone label represents that the open candle is still valid for a buy signal. A signal will only be generated if the candle closes while this label is still green
Below is the same BITSTAMP:BTCUSD chart a couple of days later. Notice how the threshold has been broken and the Smart Buy Zone label has turned from green to red. No buy signal can be triggered for this day - even if the candle retraced and closed below the threshold before daily candle close.
Notice how the green vertical bands tend to be present after significant pullbacks in price. This is the reason the strategy works! Below is the same BITSTAMP:BTCUSD chart, but this time zoomed out to present a clearer picture of the times it would invest vs times it would sit out of the market. You will notice it invests heavily in bear markets and significant pullbacks, and does not buy anything during bull markets.
Finally, to visually demonstrate the indicator on an asset other than BTC, here is an example on CRYPTO:ETHUSD . In this case the current daily high has not touched the threshold so it is still possible for this to be a valid buy trigger on daily candle close. The vertical green band will not print until the buy trigger is confirmed.
BACKTEST RESULTS
Now for some backtest results to demonstrate the improved performance over a standard DCA strategy using all non-stablecoin assets in the top 30 cryptos by marketcap.
I've used the TradingView ticker (exchange name denoted as CRYPTO in the symbol search) for every symbol tested with the exception of BTCUSD because there was some dodgy data at the beginning of the TradingView BTCUSD chart which overinflated the effectiveness of the Smart DCA strategy on that ticker. For BTCUSD I've used the BITSTAMP exchange data. The symbol links below will take you to the correct chart and exchange used for the test.
I'm using the GOA (Gain on Account) values to present how each strategy performed.
The value on the left side is the standard DCA result and the right is the Smart DCA result.
✅ means Smart DCA strategy outperformed the standard DCA strategy
❌ means standard DCA strategy outperformed the Smart DCA strategy
To avoid overfitting, and to prove that this strategy does not suffer from overfitting, I've used the exact same input parameters for every symbol tested below. The settings used in these backtests are:
Buying strictness scale: 9
Validation days: 0
You can absolutely tweak the values per symbol to further improve the results of each, however I think using identical settings on every pair tested demonstrates a higher likelihood that the results will be similar in the live markets.
I'm presenting results for two time periods:
First price data available for trading pair -> closing candle on Friday 26th Jan 2024 (ALL TIME)
Opening candle on Sunday 1st Jan 2023 -> closing candle on Friday 26th Jan 2024 (JAN 2023 -> JAN 2024)
ALL TIME:
BITSTAMP:BTCUSD 80,884% / 133,582% ✅
CRYPTO:ETHUSD 17,231% / 36,146% ✅
CRYPTO:BNBUSD 5,314% / 2,702% ❌
CRYPTO:SOLUSD 1,745% / 1,171% ❌
CRYPTO:XRPUSD 2,585% / 4,544% ✅
CRYPTO:ADAUSD 338% / 353% ✅
CRYPTO:AVAXUSD 130% / 160% ✅
CRYPTO:DOGEUSD 13,690% / 16,432% ✅
CRYPTO:TRXUSD 414% / 466% ✅
CRYPTO:DOTUSD -16% / -7% ✅
CRYPTO:LINKUSD 1,161% / 2,164% ✅
CRYPTO:TONUSD 25% / 47% ✅
CRYPTO:MATICUSD 1,769% / 1,587% ❌
CRYPTO:ICPUSD 70% / 50% ❌
CRYPTO:SHIBUSD -20% / -19% ✅
CRYPTO:LTCUSD 486% / 718% ✅
CRYPTO:BCHUSD -4% / 3% ✅
CRYPTO:LEOUSD 102% / 151% ✅
CRYPTO:ATOMUSD 46% / 91% ✅
CRYPTO:UNIUSD -16% / 1% ✅
CRYPTO:ETCUSD 283% / 414% ✅
CRYPTO:OKBUSD 1,286% / 1,935% ✅
CRYPTO:XLMUSD 1,471% / 1,592% ✅
CRYPTO:INJUSD 830% / 1,035% ✅
CRYPTO:OPUSD 138% / 195% ✅
CRYPTO:NEARUSD 23% / 44% ✅
Backtest result analysis:
Assuming we have an initial investment amount of $10,000 spread evenly across each asset since the creation of each asset, it would have provided the following results.
Standard DCA Strategy results:
Average percent return: 4,998.65%
Profit: $499,865
Closing balance: $509,865
Smart DCA Strategy results:
Average percent return: 7,906.03%
Profit: $790,603
Closing balance: $800,603
JAN 2023 -> JAN 2024:
BITSTAMP:BTCUSD 47% / 66% ✅
CRYPTO:ETHUSD 26% / 33% ✅
CRYPTO:BNBUSD 15% / 17% ✅
CRYPTO:SOLUSD 272% / 394% ✅
CRYPTO:XRPUSD 7% / 12% ✅
CRYPTO:ADAUSD 43% / 59% ✅
CRYPTO:AVAXUSD 116% / 151% ✅
CRYPTO:DOGEUSD 8% / 14% ✅
CRYPTO:TRXUSD 48% / 65% ✅
CRYPTO:DOTUSD 24% / 35% ✅
CRYPTO:LINKUSD 83% / 124% ✅
CRYPTO:TONUSD 7% / 21% ✅
CRYPTO:MATICUSD -3% / 7% ✅
CRYPTO:ICPUSD 161% / 196% ✅
CRYPTO:SHIBUSD 1% / 8% ✅
CRYPTO:LTCUSD -15% / -7% ✅
CRYPTO:BCHUSD 47% / 68% ✅
CRYPTO:LEOUSD 9% / 11% ✅
CRYPTO:ATOMUSD 1% / 15% ✅
CRYPTO:UNIUSD 9% / 23% ✅
CRYPTO:ETCUSD 27% / 40% ✅
CRYPTO:OKBUSD 21% / 30% ✅
CRYPTO:XLMUSD 11% / 19% ✅
CRYPTO:INJUSD 477% / 446% ❌
CRYPTO:OPUSD 77% / 91% ✅
CRYPTO:NEARUSD 78% / 95% ✅
Backtest result analysis:
Assuming we have an initial investment amount of $10,000 spread evenly across each asset for the duration of 2023, it would have provided the following results.
Standard DCA Strategy results:
Average percent return: 61.42%
Profit: $6,142
Closing balance: $16,142
Smart DCA Strategy results:
Average percent return: 78.19%
Profit: $7,819
Closing balance: $17,819
Divergence AnalyzerUnlock the potential of your trading strategy with the Divergence Analyzer, a sophisticated indicator designed to identify divergence patterns between two financial instruments. Whether you're a seasoned trader or just starting, this tool provides valuable insights into market trends and potential trading opportunities.
Key Features:
1. Versatility in Symbol Selection:
- Choose from a wide range of symbols for comparison, including popular indices like XAUUSD and SPX.
- Seamlessly toggle between symbols to analyze divergences and make informed trading decisions.
2. Flexible Calculation Options:
- Customizable options allow you to use a different symbol for calculation instead of the chart symbol.
- Fine-tune your analysis by selecting specific symbols for comparison based on your trading preferences.
3. Logarithmic Scale Analysis:
- Utilizes logarithmic scales for accurate representation of price movements.
- Linear regression coefficients are calculated on the logarithmic scale, providing a comprehensive view of trend strength.
4. Dynamic Length and Smoothing:
- Adjust the length parameter to adapt the indicator to different market conditions.
- Smoothed linear regression with exponential moving averages enhances clarity and reduces noise.
5. Standard Deviation Normalization:
- Normalizes standard deviations over 200 periods, offering a standardized view of price volatility.
- Easily compare volatility levels across different symbols for effective divergence analysis.
6. Color-Coded Divergence Visualization:
- Clearly distinguish positive and negative divergences with customizable color options.
- Visualize divergence deltas with an intuitive color scheme for quick and effective interpretation.
7. Symbol Information Table:
- An included table provides at-a-glance information about the selected symbols.
- Identify Symbol 1 and Symbol 2, along with their corresponding positive and negative divergence colors.
How to Use:
1. Select symbols for analysis using the user-friendly inputs.
2. Customize calculation options based on your preferences.
3. Analyze the divergence delta plot for clear visual indications.
4. Refer to the symbol information table for a quick overview of selected instruments.
Empower your trading strategy with the Divergence Analyzer and gain a competitive edge in the dynamic world of financial markets. Start making more informed decisions today!
SandTigerSandTiger is an auto-counting tool that counts naturally occurring events in a price series. This version has been reduced to 377 lines of code and should run faster than previous versions. Although not shown here, I highly recommend running my 'ELB' script with SandTiger. ELB is an 'event locator' and will mark all points that SandTiger numbers - giving you visual cues as to where these points are located. ELB also displays support/resistance levels.
SandTiger is designed to be used with MAGENTA - a counting system for Forex and other markets.
MAGENTA is a free and open framework for understanding and explaining price movement in financial markets. Any materials associated with MAGENTA are strictly for educational purposes only.
SandTiger tracks Component Values, Dyads, and Sum Table Values (STV's) over straight and curved trends, allowing a trader to discern where directional shifts are likely to occur.
SandTiger requires just 3 things to function accurately:
1) A correct starting point (this will typically be an obvious trend turn high or low in a series of price moves).
2) A 'push 1' count ('push 1' runs from the starting point to the event prior to the first terminal of the first FCT or Fractured Counter-Trend).
3) A 'high prime' value (the high prime count runs from the starting point through to the second terminal of the first FCT with no skips).
FRAMEWORK OVERVIEW: 'Component' values are filtered from the prime set (including the half prime and further reductions). Once we have the comp table we add the values to get a 'total'. With the 'total' we divide and multiply by two to get two additional values. 'Derivatives' are based on various calculations using these three values.
We're looking for 'total/2' to count into either itself, 'total', 'total*2', or a derivative. Comp counts are in Tx form and counted from trend start. If the trend doesn't turn on a comp value it will likely turn on a Dyad or STV value. If that also doesn't happen it's likely you have a 'curved' trend/sequence that will turn on one of the above after moving away from its high/low. This can also be traded using SandTiger's 'Seg Terminals' skip option.
Sum tables and Dyad values are drawn from the 'primes' and Dyads use the 'push1' value as well. In a structural trend, primes are gotten by counting pushpulls 1 & 2 in 'Ti' form. Comps, Sum table values, and Dyads are equivalent, sequences can turn on either value type belonging to the 1st or 2nd prime set. Both STV's and Dyads are counted in 'Tx' form (except where count-through signals occur).
Types and antitypes correlate and are associated with a 12-count 'cycle.' (Ti = 'Terminals Included'; Tx = 'Terminals eXcluded'; both refer to FCT terminals)
THE STRATEGY:
For Structures: Trade Comps, Dyads, and STV's from sets 1 (all) and 2 (Dyads and STV's only) in the 'main' segment then on the 'carry-over' by skipping segment terminals. If a PC or cycle caps the sequence, trade that as well.
For NSM's: Trade movements that flash a signal prior to the end of the initial cycle. The mark will be the push1 value. Twelve will be the 'high prime.' Skip interrupts and trade carry-over values.
The first version of SandTiger was conceived/planned/authored by Erek A.D. and coded by Erek A.D. and @SimpleCryptoLife beginning in August 2022 and finishing in Dec. 2022
The current version was written and developed July 3, 2023 and has been refined and upgraded by Erek A.D. through Jan. 2024...
Z-ScoreThe "Z-Score" indicator is a unique and powerful tool designed to help traders identify overbought and oversold conditions in the market. Below is an explanation of its features, usefulness, and what makes it special:
Features:
Z-Score Calculation: The indicator calculates the Z-Score, a statistical measure that represents how far the current price is from the moving average (MA) in terms of standard deviations. It helps identify extreme price movements.
Customizable Parameters: Traders can adjust key parameters such as the Z-Score threshold, the type of MA (e.g., SMA, EMA), and the length of the moving average to suit their trading preferences.
Signal Options: The indicator offers flexibility in terms of signaling. Traders can choose whether to trigger signals when the Z-Score crosses the specified threshold or when it moves away from the threshold.
Visual Signals : Z-Score conditions are represented visually on the chart with color-coded background highlights. Overbought conditions are marked with a red background, while oversold conditions are indicated with a green background.
Information Table: A dynamic information table displays essential details, including the MA type, MA length, MA value, standard deviation, current price, and Z-Score. This information table helps traders make informed decisions.
Usefulness:
Overbought and Oversold Signals: Z-Score is particularly valuable for identifying overbought and oversold market conditions. Traders can use this information to potentially enter or exit positions.
Statistical Analysis: The Z-Score provides a statistical measure of price deviation, offering a data-driven approach to market analysis.
Customization: Traders can customize the indicator to match their trading strategies and preferences, enhancing its adaptability to different trading styles.
Visual Clarity: The visual signals make it easy for traders to quickly spot potential trade opportunities on the price chart.
In summary, the Z-Score indicator is a valuable tool for traders looking to incorporate statistical analysis into their trading strategies. Its customizability, visual signals, and unique statistical approach make it an exceptional choice for identifying overbought and oversold market conditions and potential trading opportunities.
Time Matrix [Pro+] (DRxICT)Description:
The Time Matrix Pro is an automated Time-based trading tool adaptable to futures, forex, and bond markets. This indicator is inspired by concepts taught by the Inner Circle Trader (ICT) and ICT_Concepts.
ICT’s repertoire encompasses the concepts of liquidity and couples them with Time. The Time Matrix helps the analyst to locate key Time-based price levels to determine bias and recurring price patterns within the market. Analysts can use levels like Previous Day’s Highs and Lows, Weekly Highs and Lows, Session Openings, and Macros to base and qualify Premium and Discount arrays in intraday analysis.
Session Boxes are Time opportunities of the day that identify the market mechanics of consolidation, expansion, retracement, and reversals.
ICT_Concepts's Session Boxes are described as the Premarket, AM Session, PM session:
Premarket is defined as 9:30pm to 1:30am
AM session is defined as 4:00am to 11:00am
PM Session is defined as 11:30am to 2:15pm
Understanding how Time is crucial for identifying intraday profiling, the analyst is able to toggle price levels in conjunction with Time-based macros. These help analyze key market turning points that can correspond to unique market mechanics.
Beyond the Time-based liquidity levels, and the Time macros, there are also predefined Time clusters.
These clusters highlight a significant lower Timeframe candle which was found to hold significant value by ICT_Concepts. Very much alike Time-based liquidity levels, analysts will notice how price reacts to support or negate existing orderflow, trend and direction.
Key Features:
Customizable Extension: the analyst is given the choice to toggle the ending Time Offset to either Noon NY Time or at the end of the trading day.
Time-Based Toggles: choose individual Time-based prices to highlight on your chart.
Time Table: depending on the Timeframe, the Time Table will display the number of bars and the Time elapsed since the Time-based liquidity levels were established.
Other Features
Customize Session Boxes Color
Customize Time-Based Liquidity Line Style
Customize Time-Based Liquidity Level Color
Customize Time-Based Liquidity Line Width
Customize Table Size and Location
Usage Guidance:
Add Time Matrix to your Tradingview chart.
Customize your desired settings of Time-Based Liquidity Levels to align with your personal preference.
Observe where the Time-Based Liquidity Levels as well as Previous Day, Week, and Macros play a role in intraday narrative.
Analysts can choose to utilize Time-Based Liquidity Levels as automated framework to organize models and layouts.
These tools are available ONLY on the TradingView platform.
Terms and Conditions
Our charting tools are products provided for informational and educational purposes only and do not constitute financial, investment, or trading advice. Our charting tools are not designed to predict market movements or provide specific recommendations. Users should be aware that past performance is not indicative of future results and should not be relied upon for making financial decisions. By using our charting tools, the purchaser agrees that the seller and the creator are not responsible for any decisions made based on the information provided by these charting tools. The purchaser assumes full responsibility and liability for any actions taken and the consequences thereof, including any loss of money or investments that may occur as a result of using these products. Hence, by purchasing these charting tools, the customer accepts and acknowledges that the seller and the creator are not liable nor responsible for any unwanted outcome that arises from the development, the sale, or the use of these products.
Finally, the purchaser indemnifies the seller from any and all liability. If the purchaser was invited through the Friends and Family Program, they acknowledge that the provided discount code only applies to the first initial purchase of the Toodegrees Premium Suite subscription. The purchaser is therefore responsible for cancelling – or requesting to cancel – their subscription in the event that they do not wish to continue using the product at full retail price. If the purchaser no longer wishes to use the products, they must unsubscribe from the membership service, if applicable. We hold no reimbursement, refund, or chargeback policy. Once these Terms and Conditions are accepted by the Customer, before purchase, no reimbursements, refunds or chargebacks will be provided under any circumstances.
By continuing to use these charting tools, the user acknowledges and agrees to the Terms and Conditions outlined in this legal disclaimer.
3x MTF MACD v3.0MACD's on 3 different Time Frames
Indicator Information
- Each Time Frame shows start of Trend and end of trend of the MACD vs the Signal Cross
- They are labled 1,2,3 with respective up or down triangle for possible direction.
User Inputs
- configure the indicator by specifying various inputs. These inputs include colors for bullish
and bearish conditions, the time frame to use, whether to show a Simple Moving Average
(SMA) line, and other parameters.
- Users can choose time frames for analysis (like 30 minutes, 1 hour, etc.)
but they must be in mintues.
- The code also allows users to customize how the indicator looks on the chart by providing
options for position and color.
Main Calculations
- The script calculates the Simple Moving Average (SMA) based on the user-defined time
frame.
- It then determines the color of the plot (line) based on certain conditions, such as whether
the SMA is rising or falling. These conditions help users quickly identify market trends.
Label Creation
- The code creates labels that can be displayed on the chart.
These labels indicate whether there's a bullish or bearish signal.
Level Detection
- The script determines and labels key levels or points of interest in the chart based on
certain conditions.
- It can show labels like "①" and "▲" for bullish conditions and "▼" for bearish conditions.
Table Display
- There's an option to show a table on the chart that displays information about the MACD
indicator Chosen and the NUmber Bubble assocated with that time frame
- The table can include information like which time frame is being analyzed, whether the SMA
line is shown, and other relevant data.
Plotting on the Chart
- The script plots the Simple Moving Average (SMA) on the chart. The color of this line
changes based on the calculated trend conditions.
ATR (Average True Range)
- The script also plots the Average True Range (ATR) on the chart. ATR is used to measure
market volatility.
"In essence, this script is a highly customizable MACD and SMA indicator for traders. It assists traders in comprehending market trends, offering insights into different MACD cycles concerning various timeframes.
Users can configure it to match their trading strategies, and it presents information in a user-friendly manner with colors, labels, and tables.
This simplifies market analysis, allowing traders to make more informed decisions without the distraction of multiple indicators."
Quadratic & Linear Time Series Regression [SS]Hey everyone,
Releasing the Quadratic/Linear Time Series regression indicator.
About the indicator:
Most of you will be familiar with the conventional linear regression trend boxes (see below):
This is an awesome feature in Tradingview and there are quite a few indicators that follow this same principle.
However, because of the exponential and cyclical nature of stocks, linear regression tends to not be the best fit for stock time series data. From my experience, stocks tend to fit better with quadratic (or curvlinear) regression, which there really isn't a lot of resources for.
To put it into perspective, let's take SPX on the 1 month timeframe and plot a linear regression trend from 1930 till now:
You can see that its not really a great fit because of the exponential growth that SPX has endured since the 1930s. However, if we take a quadratic approach to the time series data, this is what we get:
This is a quadratic time series version, extended by up to 3 standard deviations. You can see that it is a bit more fitting.
Quadratic regression can also be helpful for looking at cycle patterns. For example, if we wanted to plot out how the S&P has performed from its COVID crash till now, this is how it would look using a linear regression approach:
But this is how it would look using the quadratic approach:
So which is better?
Both linear regression and quadratic regression are pivotal and important tools for traders. Sometimes, linear regression is more appropriate and others quadratic regression is more appropriate.
In general, if you are long dating your analysis and you want to see the trajectory of a ticker further back (over the course of say, 10 or 15 years), quadratic regression is likely going to be better for most stocks.
If you are looking for short term trades and short term trend assessments, linear regression is going to be the most appropriate.
The indicator will do both and it will fit the linear regression model to the data, which is different from other linreg indicators. Most will only find the start of the strongest trend and draw from there, this will fit the model to whatever period of time you wish, it just may not be that significant.
But, to keep it easy, the indicator will actually tell you which model will work better for the data you are selecting. You can see it in the example in the main chart, and here:
Here we see that the indicator indicates a better fit on the quadratic model.
And SPY during its recent uptrend:
For that, let's take a look at the Quadratic Vs the Linear, to see how they compare:
Quadratic:
Linear:
Functions:
You will see that you have 2 optional tables. The statistics table which shows you:
The R Squared to assess for Variance.
The Correlation to assess for the strength of the trend.
The Confidence interval which is set at a default of 1.96 but can be toggled to adjust for the confidence reading in the settings menu. (The confidence interval gives us a range of values that is likely to contain the true value of the coefficient with a certain level of confidence).
The strongest relationship (quadratic or linear).
Then there is the range table, which shows you the anticipated price ranges based on the distance in standard deviations from the mean.
The range table will also display to you how often a ticker has spent in each corresponding range, whether that be within the anticipated range, within 1 SD, 2 SD or 3 SD.
You can select up to 3 additional standard deviations to plot on the chart and you can manually select the 3 standard deviations you want to plot. Whether that be 1, 2, 3, or 1.5, 2.5 or 3.5, or any combination, you just enter the standard deviations in the settings menu and the indicator will adjust the price targets and plotted bands according to your preferences. It will also count the amount of time the ticker spent in that range based on your own selected standard deviation inputs.
Tips on Use:
This works best on the larger timeframes (1 hour and up), with RTH enabled.
The max lookback is 5,000 candles.
If you want to ascertain a longer term trend (over years to months), its best to adjust your chart timeframe to the weekly and/or monthly perspective.
And that's the indicator! Hopefully you all find it helpful.
Let me know your questions and suggestions below!
Safe trades to all!
Market Open - Relative VolumeThe indicator calculates the Pre-market volume percentage of the current day, relative to the average volume being traded in the trading session (14 days), displayed in Table Row 1, Table Cell 1, as V%. Pre-market volume between 15% & 30% has a orange background color. Pre-market volume percentage above 30% has a green background color.
The indicator calculates the relative volume per candle relative to the average volume being traded in that time period (14 days) (e.g., "1M," "2M," up to "5M"), displayed in a table. Relative volume between 250% & 350% has a orange background color. Relative volume above 350% has a green background color.
FYI >> Indicator calculations are per candle, not time unit (due to pine script restrictions). Meaning, the indicator current table data is only accurate in the 1M chart. If you are using the indicator in a higher timeframe, e.g., on the 5M chart, then the values in table cells >> (1M value == relative volume of the first 5-minute candle) (5M value = relative volume of the first five 5-minute candles) and so on. (Future versions will have a dynamic table).
RSI Screener Multi Timeframe [5ema]This indicator is the simple version of my indicator: RSI Screener and Divergence .
Only show table with values, signals at 5 custom timeframes.
-----
I reused some functions, made by (i believe that):
©paaax: The table position function.
@kingthies: The RSI divergence function.
@QuantNomad: The function calculated value and array screener for 40+ instruments.
I have commented in my code. Thanks so much!
-----
How it works:
1. Input :
Length of RSI => calculate RSI.
Upper/lower => checking RSI overbought/oversold.
Right bars / left bars => returns price of the pivot low & high point => checking divergence.
Range upper / lower bars => compare the low & high point => checking divergence.
Timeframe => request.security another time frame.
Table position => display screener table.
2. Input bool:
Regular Bearish divergence.
Hidden Bullish divergence .
Hidden Bearish divergence.
3. Basic calculated:
Make function for RSI , pivot low & high point of RSI and price.
Request.security that function for earch time frame.
Result RSI, Divergence.
4. Condition of signal:
Buy condition:
RSI oversold (1)
Bullish divergence (2).
=> Buy if (1) and (2), review buy (1) or (2).
Sell condition:
RSI overbought (3).
Bearish divergence (4).
=> Sell if (3) and (4), review sell (3) or (4).
-----
Table screener:
Time frame.
RSI (green - oversold, red - overbought)
Divergence (>> - regular bullish , << regular bearish , > - hidden bullish , < - hidden bearish ).
Signal (green ⦿ - Buy, red ⦿ - Sell, green 〇 - review buy, red 〇 - review sell).
- Regular Bearish divergence:
- Regular Bullish divergence:
- Regular Bullish divergence + RSI overSold
- Regular Bearish divergence + RSI overBought
-----
This indicator is for reference only, you need your own method and strategy.
If you have any questions, please let me know in the comments.
Earnings_MFCThe Earnings_MFC indicator displays statistical information of the price movement of the selected asset as follows:
TAGS: Label on each "earning day" with information on the movement that the price has made from the close of the day before the announcement to:
the opening of the next day (Close to Open - GAP)
the close of the next day (Close to Close - CTC)
HISTOGRAM: Histogram of the times the price has moved in each price band (number of configurable bands).
Each movement has been taken and represented in histogram format, so that visually you can see the number of times the price has exceeded a certain value. Within each band is numbered the number of times the price has reached that area
The histogram has two overlapping data:
....+ A main histogram (red/green stripes)
....+ A secondary histogram (black stripes)
....+ This is so that you can configure which data to see in each one: the GAP movement data or the CTC movement data
The maximum and minimum movement has been indicated (for the main histogram)
It has been indicated, both for positive and negative movements, which is their first (gray) and second (red/green) standard deviation (for the main histogram)
TABLE: A table is included with the following information (you can hide this table):
Summary of statistical data:
....+ Number of samples
....+ Maximum UP movement and average (for both CAP and CTC)
....+ Maximum DOWN movement and average (for both CAP and CTC)
....+ Maximum movement UP or DOWN and average (both for CAP and CTC)
List of all past Earnings (according to the history available in the chart) with their movements
HOW TO USE:
For Options traders it can come in handy to position themselves with Sell PUTs / Sell CALLs / Spreads or Iron Condors. Considering the probabilities of the movement (taking into account that past movements do not ensure future movements), this indicator can help in the decision making for sell strikes.
REMARKS:
Use only in Daily timeframe
Depending on the history of the asset (whether the user is PRO or not FREE) there will be more data
Price Range Volume Profile [Pt]█ Introduction
The Price Range Volume Profile (PRVP) is a revolutionary indicator. This tool stands out from its peers due to its unique ability to capture the entire price chart history, thus providing a comprehensive volume profile of the entire asset's trading history, as available on TradingView chart. It's worth noting that I believe this tool is the first of its kind to accomplish such a feat. A much recommended tool if you are a volume profile trader.
█ Main Features
► Historical Lookback: This feature dives deep into the past, grasping all the historical data of an asset. It's equipped to handle up to 20,000 bars, although users without a premium TradingView account are advised to keep it at a maximum of 10,000 bars, or just use the "Full Historical Lookback" feature.
► Volume Profile / POC: Displays the distribution of volume across price levels for the selected price range. The Point of Control (POC), which is the price level with the highest traded volume, is also highlighted.
► Customization: Users have the flexibility to adjust the profile's appearance, including profile width, horizontal offset, and the option to fill the background of the profile range.
► Time Weighting: This feature allows users to give more weight to recent trading activity, which can be especially useful for intraday traders or during times of high volatility. Note that this feature will impact the volume profile and POC level.
► Settings Table: A settings table is displayed on the chart for users to quickly reference their input parameters.
█ Input Parameters
► Lookback Timeframe: Determines the period for which the volume profile is generated.
► Price Range: The percentage distance to consider for the profile, adjusted above and below the current closing price.
► Profile Step size: The granularity of the volume profile. Users can opt for automatic step size based on a predefined calculation or set their preferred tick step size.
► Historical Bars Lookback: Determines the number of bars to include in the volume profile calculation.
► Profile Visuals: Adjust the appearance and layout of the volume profile on the chart.
► Extra: Additional settings including the display of a settings table and its location.
█ Basic Understanding of Volume Profile - How to use PRVP?
Volume Profile is a valuable tool for traders who want insights into where the majority of trading activity has occurred. Here are some tips to make the most of it:
► Understand the Basics: Before using the Volume Profile, ensure you understand the difference between it and the standard volume histogram. While both represent volume, the former displays it against price while the latter shows it against time.
► Identify High Volume Nodes (HVN) and Low Volume Nodes (LVN):
◊ HVN: Areas where there's a lot of trading activity and where the price has spent a lot of time. These areas can act as strong support or resistance.
◊ LVN: Areas where there's a lack of trading activity. Prices might move quickly through these areas, and they can act as potential breakpoints or accelerators for price movement.
► Locate the Point of Control (POC): This is the price level with the highest traded volume for a specified period. It often acts as a magnet for price, and it can serve as a pivot or reference point.
► Trend Confirmation: A shift in the volume profile from one price level to another can confirm a trend. For instance, if higher volume starts to build at higher price levels, it may indicate a strong uptrend.
► Watch for Volume Gaps: If there's a significant gap in the volume profile, prices may move quickly through these levels as there's little historical trading activity to act as support or resistance.
█ Other Usage Tips
◊ For optimal performance, ensure that the chosen timeframe aligns closely with the chart timeframe. Differences in timeframes may lead to minor discrepancies in the volume profile.
◊ To address any errors arising from too many levels displayed on the volume profile, consider increasing the Profile Step size or reducing the Price Range.
AI-Bank-Nifty Tech AnalysisThis code is a TradingView indicator that analyzes the Bank Nifty index of the Indian stock market. It uses various inputs to customize the indicator's appearance and analysis, such as enabling analysis based on the chart's timeframe, detecting bullish and bearish engulfing candles, and setting the table position and style.
The code imports an external script called BankNifty_CSM, which likely contains functions that calculate technical indicators such as the RSI, MACD, VWAP, and more. The code then defines several table cell colors and other styling parameters.
Next, the code defines a table to display the technical analysis of eight bank stocks in the Bank Nifty index. It then defines a function called get_BankComponent_Details that takes a stock symbol as input, requests the stock's OHLCV data, and calculates several technical indicators using the imported CSM_BankNifty functions.
The code also defines two functions called get_EngulfingBullish_Detection and get_EngulfingBearish_Detection to detect bullish and bearish engulfing candles.
Finally, the code calculates the technical analysis for each bank stock using the get_BankComponent_Details function and displays the results in the table. If the engulfing input is enabled, the code also checks for bullish and bearish engulfing candles and displays buy/sell signals accordingly.
The FRAMA stands for "Fractal Adaptive Moving Average," which is a type of moving average that adjusts its smoothing factor based on the fractal dimension of the price data. The fractal dimension reflects self-similarity at different scales. The FRAMA uses this property to adapt to the scale of price movements, capturing short-term and long-term trends while minimizing lag. The FRAMA was developed by John F. Ehlers and is commonly used by traders and analysts in technical analysis to identify trends and generate buy and sell signals. I tried to create this indicator in Pine.
In this context, "RS" stands for "Relative Strength," which is a technical indicator that compares the performance of a particular stock or market sector against a benchmark index.
The "Alligator" is a technical analysis tool that consists of three smoothed moving averages. Introduced by Bill Williams in his book "Trading Chaos," the three lines are called the Jaw, Teeth, and Lips of the Alligator. The Alligator indicator helps traders identify the trend direction and its strength, as well as potential entry and exit points. When the three lines are intertwined or close to each other, it indicates a range-bound market, while a divergence between them indicates a trending market. The position of the price in relation to the Alligator lines can also provide signals, such as a buy signal when the price crosses above the Alligator lines and a sell signal when the price crosses below them.
In addition to these, we have several other commonly used technical indicators, such as MACD, RSI, MFI (Money Flow Index), VWAP, EMA, and Supertrend. I used all the built-in functions for these indicators from TradingView. Thanks to the developer of this TradingView Indicator.
I also created a BankNifty Components Table and checked it on the dashboard.
