Mean Reversion Watchlist [Z score]Hi Traders !
What is the Z score:
The Z score measures a values variability factor from the mean, this value is denoted by z and is interpreted as the number of standard deviations from the mean.
The Z score is often applied to the normal distribution to “standardize” the values; this makes comparison of normally distributed random variables with different units possible.
This popular reversal based indicator makes an assumption that the sample distribution (in this case the sample of price values) is normal, this allows for the interpretation that values with an extremely high or low percentile or “Z” value will likely be reversal zones.
This is because in the population data (the true distribution) which is known, anomaly values are very rare, therefore if price were to take a z score factor of 3 this would mean that price lies 3 standard deviations from the mean in the positive direction and is in the ≈99% percentile of all values. We would take this as a sign of a negative reversal as it is very unlikely to observe a consecutive equal to or more extreme than this percentile or Z value.
The z score normalization equation is given by
In Pine Script the Z score can be computed very easily using the below code.
// Z score custom function
Zscore(source, lookback) =>
sma = ta.sma(source, lookback)
stdev = ta.stdev(source, lookback, true)
zscore = (source - sma) / stdev
zscore
The Indicator:
This indicator plots the Z score for up to 20 different assets ( Note the maximum is 40 however the utility of 40 plots in one indicator is not much, there is a diminishing marginal return of the number of plots ).
Z score threshold levels can also be specified, the interpretation is the same as stated above.
The timeframe can also be fixed, by toggling the “Time frame lock” user input under the “TIME FRAME LOCK” user input group ( Note this indicator does not repain t).
חפש סקריפטים עבור "泰国一寺庙被曝藏有40多具尸体"
Goldmine Wealth Builder - DKK/SKKGoldmine Wealth Builder
Version 1.0
Introduction to Long-Term Investment Strategies: DKK, SKK1 and SKK2
In the dynamic realm of long-term investing, the DKK, SKK1, and SKK2 strategies stand as valuable pillars. These strategies, meticulously designed to assist investors in building robust portfolios, combine the power of Super Trend, RSI (Relative Strength Index), Exponential Moving Averages (EMAs), and their crossovers. By providing clear alerts and buy signals on a daily time frame, they equip users with the tools needed to make well-informed investment decisions and navigate the complexities of the financial markets. These strategies offer a versatile and structured approach to both conservative and aggressive investment, catering to the diverse preferences and objectives of investors.
Each part of this strategy provides a unique perspective and approach to the accumulation of assets, making it a versatile and comprehensive method for investors seeking to optimize their portfolio performance. By diligently applying this multi-faceted approach, investors can make informed decisions and effectively capitalize on potential market opportunities.
DKK Strategy for ETFs and Funds:
The DKK system is a strategy designed for accumulating ETFs and Funds as long-term investments in your portfolio. It simplifies the process of identifying trend reversals and opportune moments to invest in listed ETFs and Funds, particularly during bull markets. Here's a detailed explanation of the DKK system:
Objective: The primary aim of the DKK system is to build a long-term investment portfolio by focusing on ETFs and Funds. It facilitates the identification of stocks that are in the process of reversing their trends, allowing investors to benefit from upward price movements in these financial instruments.
Stock Selection Criteria: The DKK system employs specific criteria for selecting ETFs and Funds:
• 200EMA (Exponential Moving Average): The system monitors whether the prices of ETFs and Funds are consistently below the 200-day Exponential Moving Average. This is considered an indicator of weakness, especially on a daily time frame.
• RSI (Relative Strength Index): The system looks for an RSI value of less than 40. An RSI below 40 is often seen as an indication of a weak or oversold condition in a financial instrument.
Alert Signal: Once the DKK system identifies ETFs and Funds meeting these criteria, it provides an alert signal:
• Red Upside Triangle Sign: This signal is automatically generated on the daily chart of ETFs and Funds. It serves as a clear indicator to investors that it's an opportune time to accumulate these financial instruments for long-term investment.
It's important to note that the DKK system is specifically designed for ETFs and Funds, so it should be applied to these types of investments. Additionally, it's recommended to track index ETFs and specific types of funds, such as REITs (Real Estate Investment Trusts) and INVITs (Infrastructure Investment Trusts), in line with the DKK system's approach. This strategy simplifies the process of identifying investment opportunities within this asset class, particularly during periods of market weakness.
SKK1 Strategy for Conservative Stock Investment:
The SKK 1 system is a stock investment strategy tailored for conservative investors seeking long-term portfolio growth with a focus on stability and prudent decision-making. This strategy is meticulously designed to identify pivotal market trends and stock price movements, allowing investors to make informed choices and capitalize on upward market trends while minimizing risk. Here's a comprehensive overview of the SKK 1 system, emphasizing its suitability for conservative investors:
Objective: The primary objective of the SKK 1 system is to accumulate stocks as long-term investments in your portfolio while prioritizing capital preservation. It offers a disciplined approach to pinpointing potential entry points for stocks, particularly during market corrections and trend reversals, thereby enabling you to actively participate in bullish market phases while adopting a conservative risk management stance.
Stock Selection Criteria: The SKK 1 system employs a stringent set of criteria to select stocks for investment:
• Correction Mode: It identifies stocks that have undergone a correction, signifying a decline in stock prices from their recent highs. This conservative approach emphasizes the importance of seeking stocks with a history of stability.
• 200EMA (Exponential Moving Average): The system diligently analyses daily stock price movements, specifically looking for stocks that have fallen to or below the 200-day Exponential Moving Average. This indicator suggests potential overselling and aligns with a conservative strategy of buying low.
Trend Reversal Confirmation: The SKK 1 system doesn't merely pinpoint stocks in correction mode; it takes an extra step to confirm a trend reversal. It employs the following indicators:
• Short-term Downtrends Reversal: This aspect focuses on identifying the reversal of short-term downtrends in stock prices, observed through the transition of the super trend indicator from the red zone to the green zone. This cautious approach ensures that the trend is genuinely shifting.
• Super Trend Zones: These zones are crucial for assessing whether a stock is in a bullish or bearish trend. The system consistently monitors these zones to confirm a potential trend reversal.
Alert & Buy Signals: When the SKK 1 system identifies stocks that have reached a potential bottom and are on the verge of a trend reversal, it issues vital alert signals, aiding conservative investors in prudent decision-making:
• Orange Upside Triangle Sign: This signal serves as a cautious heads-up, indicating that a stock may be poised for a trend reversal. It advises investors to prepare funds for potential investment without taking undue risks.
• Green Upside Triangle Sign: This is the confirmation of a trend reversal, signifying a robust buy signal. Conservative investors can confidently enter the market at this point, accumulating stocks for a long-term investment, secure in the knowledge that the trend is in their favor.
In summary, the SKK 1 system is a systematic and conservative approach to stock investing. It excels in identifying stocks experiencing corrections and ensures that investors act when there's a strong indication of a trend reversal, all while prioritizing capital preservation and risk management. This strategy empowers conservative investors to navigate the intricacies of the stock market with confidence, providing a calculated and stable path toward long-term portfolio growth.
Note: The SKK1 strategy, known for its conservative approach to stock investment, also provides an option to extend its methodology to ETFs and Funds for those investors who wish to accumulate assets more aggressively. By enabling this feature in the settings, you can harness the SKK1 strategy's careful criteria and signal indicators to accumulate aggressive investments in ETFs and Funds.
This flexible approach acknowledges that even within a conservative strategy, there may be opportunities for more assertive investments in assets like ETFs and Funds. By making use of this option, you can strike a balance between a conservative stance in your stock portfolio while exploring an aggressive approach in other asset classes. It offers the versatility to cater to a variety of investment preferences, ensuring that you can adapt your strategy to suit your financial goals and risk tolerance.
SKK 2 Strategy for Aggressive Stock Investment:
The SKK 2 strategy is designed for those who are determined not to miss significant opportunities within a continuous uptrend and seek a way to enter a trend that doesn't present entry signals through the SKK 1 strategy. While it offers a more aggressive entry approach, it is ideal for individuals willing to take calculated risks to potentially reap substantial long-term rewards. This strategy is particularly suitable for accumulating stocks for aggressive long-term investment. Here's a detailed description of the SKK 2 strategy:
Objective: The primary aim of the SKK 2 strategy is to provide an avenue for investors to identify short-term trend reversals and seize the opportunity to enter stocks during an uptrend, thereby capitalizing on a sustained bull run. It acknowledges that there may not always be clear entry signals through the SKK 1 strategy and offers a more aggressive alternative.
Stock Selection Criteria: The SKK 2 strategy utilizes a specific set of criteria for stock selection:
1. 50EMA (Exponential Moving Average): It targets stocks that are trading below the 50-day Exponential Moving Average. This signals a short-term reversal from the top and indicates that the stock is in a downtrend.
2. RSI (Relative Strength Index): The strategy considers stocks with an RSI of less than 40, which is an indicator of weakness in the stock.
Alert Signals: The SKK 2 strategy provides distinct alert signals that facilitate entry during an aggressive reversal:
• Red Downside Triangle Sign: This signal is triggered when the stock is below the 50EMA and has an RSI of less than 40. It serves as a clear warning of a short-term reversal from the top and a downtrend, displayed on the daily chart.
• Purple Upside Triangle Sign: This sign is generated when a reversal occurs through a bullish candle, and the RSI is greater than 40. It signifies the stock has bottomed out from a short-term downtrend and is now reversing. This purple upside triangle serves as an entry signal on the chart, presenting an attractive opportunity to accumulate stocks during a strong bullish phase, offering a chance to seize a potentially favorable long-term investment.
In essence, the SKK 2 strategy caters to aggressive investors who are willing to take calculated risks to enter stocks during a continuous uptrend. It focuses on identifying short-term reversals and provides well-defined signals for entry. While this strategy is more aggressive in nature, it has the potential to yield substantial rewards for those who are comfortable with a higher level of risk and are looking for opportunities to build a strong long-term portfolio.
Introduction to Strategy Signal Information Chart
This chart provides essential information on strategy signals for DKK, SKK1, and SKK2. By quickly identifying "Buy" and "Alert" signals for each strategy, investors can efficiently gauge market conditions and make informed decisions to optimize their investment portfolios.
In Conclusion
These investment strategies, whether conservative like DKK and SKK1 or more aggressive like SKK2, offer a range of options for investors to navigate the complex world of long-term investments. The combination of Super Trend, RSI, and EMAs with their crossovers provides clear signals on a daily time frame, empowering users to make well-informed decisions and potentially capitalize on market opportunities. Whether you're looking for stability or are ready to embrace more risk, these strategies have something to offer for building and growing your investment portfolio.
Machine Learning: MFI Heat Map [YinYangAlgorithms]Overview:
MFI Heat Maps are a visually appealing way to display the values of 29 different MFIs at the same time while being able to make sense of it. Each plot within the Indicator represents a different MFI value. The higher you get up, the longer the length that was used for this MFI. This Indicator also features the use of Machine Learning to help balance the MFI levels. It doesn’t solely rely upon Machine Learning but instead incorporates a growing length MFI averaged with the Machine Learning MFI at any given index.
For instance, say we are calculating the 10th plot from the bottom, the MFI would be an average of:
MFI(source, 11)
Machine Learning MFI at Index of 10
We do it this way as they both help smooth each other out without relying solely on just one calculation method.
Due to plot limitations, you are capped at 28 Plot Amounts within this indicator, but that is still quite a bit of information you can glean from a Heat Map.
The Machine Learning used in this indicator is of the K-Nearest Neighbor (KNN). It uses a Fast and Slow MFI calculation then sorts through them over Machine Learning Length and calculates the differences between them. It then slices off KNN length to create our Max/Min Distances allotted. It adds the average between Fast and Slow MFIs to a Viable Distances array if their distances are within the KNN Min/Max distance. It then averages all distances in the Viable Distances array and returns the result.
The result of the KNN Function is saved to another ML Data array whose length is that of Plot Amount (Heat Map Size). This way each Index of the ML Data array can be indexed according to the Heat Map Size.
The Average of the ML Data array is the MFI line (white) that you’ll see plotted on the Indicator. There is also the SMA of the MFI Average (orange) which is likewise plotted. These plots allow you to visualize where the ML MFI is sitting and can potentially be useful for seeing when the MFI Average and SMA cross over and under each other.
We’ve heard many people talk highly of RSI, but sadly not too many even refer to MFI. MFI oftentimes may be overlooked, especially with new traders who may not even know what it is. Essentially MFI is an RSI but it also incorporates Volume into its calculations, which in our opinion leads to a more accurate reading; afterall, what is price movement without Volume.
Tutorial:
You may be thinking, this Indicator looks appealing to the eye, but how do I benefit from it trading wise?
Before we get into our visual examples, let's talk briefly about what makes Heat Maps in general a useful tool for trading. Heat Maps give us the ability to visualize and understand lots of data while removing the clutter. We can understand the data of 29 different MFIs without having to look at and decipher 29 different MFI plots. When you overlay too many MFI lines on top of each other, they can be very difficult to read and oftentimes end up actually hindering your Technical Analysis. For this reason, we have a simple solution to this problem; Heat Maps. This MFI Heat Map allows you to easily know (in a relative %) what the MFI level is for varying lengths. For Instance, the First (bottom) plot indexes an MFI of (K(0) (loop of Plot Amount) + Smoothing Length (default 1)) = 1. Since this is indexing (usually) a very low length, it will change much quicker. Whereas the Last (top) plot indexes an MFI of (K(27) (loop of Plot Amount) + Smoothing Length (default 1)) = 28. This is indexing a much higher length of MFI which results in the MFI the higher you go up in the Heat Map to move much slower.
Heat Maps give us the ability to see changes happening over multiple MFIs at the same time, which can be very useful for seeing shifts in MFI / Momentum. Remember, MFI incorporates Volume, so even if the price goes up a lot, if there was low volume, the MFI won’t move as much as an RSI would. However, likewise, if there is high volume but low price movement, the MFI will move slightly more than the RSI.
Heat Maps change color based on their MFI level. If the MFI is >= 90 it is HOT (red), if the MFI <= 9 it is COLD (teal, think of ICE). Green represents an MFI of 50-59 and Dark Blue represents an MFI of 40-49. Green and Dark blue are the most common colors as all the others are more ‘Extreme’ MFI levels.
Okay, time to get to the Examples :
Since there is so much going on in Heat Maps, we’ve decided to focus this tutorial to this specific area and talk about individual locations before talking about it as a whole.
If you refer to the example above where there are 2 white circles; these white circles are highlighting a key location you’ll be wanting to identify within your Heat Maps, many things are happening here:
The MFI crossed over the SMA (bullish).
The Heat Map started changing from mid/dark Blue (30-50 MFI) to Green (50-59 MFI) around the midline (the 50% dashed like).
The Lower levels of the Heat Map are turning Yellow/Orange/Red (60-100 MFI).
The Upper Levels of the Heat Map are still Light Blue - Green (10-50 MFI).
The 4 Key points above, all point towards potential Bullish Momentum changes. You’re likely wondering, but why? Let's discuss about each one in more specific detail:
1. The MFI crossed over the SMA (bullish): What this tells us is that the current MFI Average is now greater than its average over the last (default) 16 bars. This means there's been a large amount of Money Flow (Price and Volume) recently (subjectively based on the last (default) 16 average). This is one of the leading Bullish / Bearish signals you will see within this Indicator. You can enable Signals within the Settings and/or even add Alerts for when these crossings occur.
2. The Heat Map started changing from mid/dark Blue (30-50 MFI) to Green (50-59 MFI) around the midline (the 50% dashed like): This shows us that the index’s in the mid (if using all 28 heat map plots it would be at 14) has already received some of this momentum change. If you look at the second white circle (right), you’ll also notice the higher MFI plot indexes are also green. This is because since their length is long they still have some momentum and strength from the first white circle (left). Just because the first white circle failed in its bullish push, doesn’t mean it didn’t achieve momentum that would later on help to push the price up.
3. The Lower levels of the Heat Map are turning Yellow/Orange/Red (60-100 MFI): It occurred somewhat in the left white circle, but mainly in the right white circle. This shows us the MFI is very high on the lower lengths, this may lead to the current, middle and higher length MFIs following suit soon. Remember it has to work its way up, the higher levels can’t go red unless the lower levels go red first and the higher levels can also lag quite a bit behind and take awhile to catch up, this is normal, expected and meant to happen. Vice versa is also true with getting higher levels to go cold (light teal (think of ICE)).
4. The Upper Levels of the Heat Map are still Light Blue - Green (10-50 MFI): You might think at first that this is a bad thing, but it's not! Remember you want to be Fearful when others are Greedy and Greedy when others are Fearful! You don’t want to buy when the higher levels have a high MFI, you want to buy when you see the momentum pushing up in the lower MFI levels (getting yellow/orange/red in the low levels) while it is still Cold in the higher levels (BLUE OR GREEN, nothing higher than green as it is already slightly too high). There will be many times that it is Yellow or possibly Orange in the high levels and the bullish push still happens, but this is much more risky! The key to trading is to minimize risks while maximizing potential.
Hopefully now you’re getting an idea of how to spot potential bullish momentum changes, but what about bearish momentum changes? Technically they are the exact opposite, so we don’t need to go into as much detail, but lets still take a look at a few examples:
In the example above we marked the 3 times where it was displaying overly bullish characteristics. We marked the bullish momentum occurring with arrows. If you look closely at the start of the arrow to where it finishes, you’ll notice how the heat (HOT)(RED) works its way up from the lower levels to the higher levels. We then see the MFI to SMA cross under. In all 3 of these examples the heat made it all the way to the top of the chart. These are all very bearish signals that represent a bearish momentum movement that may occur soon.
Also, please note, the level the MFI is at DOES matter! That line isn’t there simply for you to see when there are crosses over and under. The MFI is considered to be Overbought when it is greater than 70 (the upper white dashed line, it is just formatted to be on a different scale cause there are 28 plots, but it represents 70). The MFI is considered to be Oversold when it is less than 30 (the lower white dashed line).
If we look to the left a little here where a big drop in price occurred shortly after our MFI and SMA crossed, would we have been able to identify it using the Heat Maps? Likely, No. There was some color change in the lower levels a few bars prior that went yellow/orange/red but before this cross happened they all went back to Dark Blue. In the middle section when the cross happened it was only Green and Yellow and in the upper section we are Blue. This would be a very risky trade to go on as the only real Bearish Indication was the MFI to SMA cross under. Remember, you want to reduce risk, you don’t want to simply trade on everytime the MFI and SMA cross each other or you’ll be getting yourself into many risky trades based on false signals.
Based on what you’ve learned above, can you see the signs that are indicating where this white circle may have potential for a bullish momentum change?
Now that we are more zoomed in, you may also be noticing there are colors to the price bars. This can be disabled in the settings, but just so you know what they mean, let’s zoom in a little more and talk about it.
We’ve condensed the Indicator a bit so you can see the bars better here. The colors that are displayed on these bars are the Heat Map value for your MFI (the white line in the Indicator). This way you can better see when the Price is Hot and Cold. As you may see while looking, the colors generally go from cold to hot when bullish momentum is happening and hot to cold when bearish momentum is happening. We don’t recommend solely looking at the bars as indicators to MFI momentum change, as seeing the Heat Map will give you much more data; however it can be nice to see the Heat Map projected on the bars rather than trying to eyeball it yourself or hover over each bar specifically to see their levels.
We will conclude our Tutorial here. Hopefully this has given you some insight to how useful Heat Maps can be and why it works well with a Machine Learning (KNN) Model applied to the MFI.
PLEASE NOTE: You can adjust the line width for the Heat Map within the settings. If you condense the Indicator a lot or have a small screen, likely use a length of 1-2. If you have it stretched out or a large screen, a length of 2-3 will work nice. You just don’t want to have the lines overlapping or it defeats the purpose of a Heat Map. Also, the bigger the linewidth, generally you’ll want to increase the Transparency within the Settings also as it can get quite bright and hurt your eyes over time.
Settings:
MFI:
Show MFI and SMA Crossing Signals: MFI and SMA Crossing is one of the leading Bullish and Bearish Signals in this Indicator. You can also add alerts for these signals.
Plot Amount: How many plots are used in this Heat Map. (2 - 28).
Source: The Source to use in all MFI calculations.
Smooth Initial MFI Length: How much to smooth the Fast and Slow MFI calculation by. 1 = No smoothing.
MFI SMA Length: What length we smooth the MFI Average over to get our MFI SMA.
Machine Learning:
Average MFI data by adding a lookback to the Source: While populating our Heat Map with the MFI's, should use use the Source each MFI Length increase or should we also lookback a Source each MFI Length Increase.
KNN Distance Requirement: To be a valid KNN, it needs to abide by a Distance calculation. Generally only Max is used, but you can change it if it suits your trading style better.
Machine Learning Length: How much ML data should we store? The longer the length generally the smoother the result; which may not be as accurate for something like a Heat Map, so keeping this relatively low may lead to more accurate results.
KNN Length: How many KNN are used in the slice to calculate max/min distance allowed.
Fast Length: Fast MFI length used in KNN to calculate distances by comparing its distance with the Slow MFI Length.
Slow Length: Slow MFI length used in KNN to calculate distances by comparing its distance with the Fast MFI Length.
Smoothing Length: When populating our Heat Map, at what length do we start our MFI calculations with (A Higher value with result in a slower and more smoothed MFI / Heat Map).
Colors:
Change Bar Color: Change bar colors to MFI Avg Color.
Heat Map Transparency: If there isn't any transparency it can be a little hard on the eyes. The Greater the Line Width, generally the more transparency you'll want for your eyes.
Line Width: Set how wide the Heat Map lines are
MFI 90-100 Color: Color when the MFI is between these levels.
MFI 80-89 Color: Color when the MFI is between these levels.
MFI 70-79 Color: Color when the MFI is between these levels.
MFI 60-69 Color: Color when the MFI is between these levels.
MFI 50-59 Color: Color when the MFI is between these levels.
MFI 40-49 Color: Color when the MFI is between these levels.
MFI 30-39 Color: Color when the MFI is between these levels.
MFI 20-29 Color: Color when the MFI is between these levels.
MFI 10-19 Color: Color when the MFI is between these levels.
MFI 0-100 Color: Color when the MFI is between these levels.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
Divergences RefurbishedJust as "a butterfly can flap its wings over a flower in China and cause a hurricane in the Caribbean" (Edward Lorenz), small divergences in markets can signal big trading opportunities.
█Introduction
This is a script forked from LonesomeTheBlue's Divergence for Many Indicators v4.
It is a script that checks for divergence between price and many indicators.
In this version, I added more indicators and also added 40 symbols to check for divergences.
More info on the original script can be found here:
█ Improvements
The following improvements have been implemented over v4:
1. Added parameters to customize indicators.
2. Added new indicators:
- Stoch RSI
- Volume Oscillator
- PVT (Price Volume Trend)
- Ultimate Oscillator
- Fisher Transform
- Z-Score/T-Score
3. Now there is the possibility of using 2 external indicators.
4. New option to show tooltips inside labels.
This allows you to save space on the screen if you choose the option to only show the number of divergences or just the abbreviations.
5. New option to show additional text next to the indicator name.
This allows for grouping of indicators and symbols and better visualization, whether through emojis, for example.
6. Added 40 customizable symbols to check for divergences.
7. Option "show only the first letter" of the indicator replaced by: "show the abbreviation of the indicator".
Reason: the indicator abbreviation is more informative and easier to read.
8. Script converted to PineScript version 5.
█ CONCEPTS
Below I present a brief description of the available indicators.
1. Moving Average Convergence/Divergence (MACD):
Shows the difference between short-term and long-term exponential moving averages.
2. MACD Histogram:
Shows the difference between MACD and its signal line.
3. Relative Strength Index (RSI):
Measures the relative strength of recent price gains to recent price losses of an asset.
4. Stochastic Oscillator (Stoch):
Compares the current price of an asset to its price range over a specified time period.
5. Stoch RSI:
Stochastic of RSI.
6. Commodity Channel Index (CCI):
Measures the relationship between an asset's current price and its moving average.
7. Momentum: Shows the difference between the current price and the price a few periods ago.
Shows the difference between the current price and the price of a certain period in the past.
8. Chaikin Money Flow (CMF):
A variation of A/D that takes into account the daily price variation and weighs trading volume accordingly. Accumulation/Distribution (A/D) identifies buying and selling pressure by tracking the flow of money into and out of an asset based on volume patterns.
9. On-Balance Volume (OBV):
Identify divergences between trading volume and an asset's price.
Sum of trading volume when the price rises and subtracts volume when the price falls.
10. Money Flow Index (MFI):
Measures volume pressure in a range of 0 to 100.
Calculates the ratio of volume when the price goes up and when the price goes down.
11. Volume Oscillator (VO):
Identify divergences between trading volume and an asset's price. Ratio of change of volume, from a fast period in relation to a long period.
12. Price-Volume Trend (PVT):
Identify the strength of an asset's price trend based on its trading volume. Cumulative change in price with volume factor. The PVT calculation is similar to the OBV calculation, but it takes into account the percentage price change multiplied by the current volume, plus the previous PVT value.
13. Ultimate Oscillator (UO):
Combines three different time periods to help identify possible reversal points.
14. Fisher Transform (FT):
Normalize prices into a Gaussian normal distribution.
15. Z-Score/T-Score: Shows the difference between the current price and the price a few periods ago. I is a statistical measurement that indicates how many standard deviations a data point is from the mean of a data set.
When to use t-score instead of z-score? When the sample size is small (length < 30).
Here, the use of z-score or t-score is chosen automatically based on the length parameter.
█ What to look for
The operation is simple. The script checks for divergences between the price and the selected indicators.
Now with the possibility of using multiple symbols, it is possible to check divergences between different assets.
A well-described view on divergences can be found in this cheat sheet:
◈ Examples with SPY ETF versus indicators:
1. Regular bullish divergence with external indicator:
1. Regular bearish divergence with Fisher Transform:
1. Positive hidden divergence with Momentum indicator:
1. Negative hidden divergence with RSI:
◈ Examples with SPY ETF versus other symbols:
1. Regular bearish divergence with European Stoch Market:
2. Regular bearish divergence with DXY inverted:
3. Regular bullish divergence with Taiwan Dollar:
4. Regular bearish divergence with US10Y (10-Year US Treasury Note):
5. Regular bullish divergence with QQQ ETF (Nasdaq 100):
6. Regular bullish divergence with ARKK ETF (ARK Innovation):
7.Positive hidden divergence with RSP ETF (S&P 500 Equal Weight):
8. Negative hidden divergence with EWZ ETF (Brazil):
◈ Examples with BTCUSD versus other symbols:
1. Regular bearish divergence with BTCUSDLONGS from Bitfinex:
2. Regular bearish divergence with BLOK ETF (Amplify Transformational Data Sharing):
3. Negative hidden divergence with NATGAS (Natural Gas):
4. Positive hidden divergence with TOTALDEFI (Total DeFi Market Cap):
█ Conclusion
The symbols available to check divergences were chosen in such a way as to cover the main markets, in the most generic way possible.
You can adjust them according to your needs.
A trader in the American market, for example, could add more ETFs, American stocks, and sectoral indices, such as the XLF (Financial Select Sector SPDR Fund), the XLK (Technology Select Sector SPDR), etc.
On the other hand, a cryptocurrency trader could add more currency pairs and sector indicators, such as BTCUSDSHORTS (Bitfinex), USDT.D (Tether Dominance), etc.
If the chart becomes too cluttered, you can use the option to show only the number of divergences or only the indicator abbreviations.
Or even disable certain indicators and symbols, if they are not of interest to you.
I hope this script is useful.
Don't forget to support LonesomeTheBlue's work too.
TradeLibrary "Trade"
A Trade Tracking Library
Monitor conditions with less code by using Arrays. When your conditions are met in chronologically, a signal is returned and the scanning starts again.
Create trades automatically with Stop Loss, Take Profit and Entry. The trades will automatically track based on the market movement and update when the targets are hit.
Sample Usage
Enter a buy trade when RSI crosses below 70 then crosses above 80 before it crosses 40.
Note: If RSI crosses 40 before 80, No trade will be entered.
rsi = ta.rsi(close, 21)
buyConditions = array.new_bool()
buyConditions.push(ta.crossunder(rsi, 70))
buyConditions.push(ta.crossover(rsi, 80))
buy = Trade.signal(buyConditions, ta.crossunder(rsi, 40))
trade = Trade.new(close-(100*syminfo.mintick), close +(200*syminfo.mintick), condition=buy)
plot(trade.takeprofit, "TP", style=plot.style_circles, linewidth=4, color=color.lime)
alertcondition(trade.tp_hit, "TP Hit")
method signal(conditions, reset)
Signal Conditions
Namespace types: bool
Parameters:
conditions (bool )
reset (bool)
Returns: Boolean: True when all the conditions have occured
method update(this, stoploss, takeprofit, entry)
Update Trade Parameters
Namespace types: Trade
Parameters:
this (Trade)
stoploss (float)
takeprofit (float)
entry (float)
Returns: nothing
method clear(this)
Clear Trade Parameters
Namespace types: Trade
Parameters:
this (Trade)
Returns: nothing
method track(this, _high, _low)
Track Trade Parameters
Namespace types: Trade
Parameters:
this (Trade)
_high (float)
_low (float)
Returns: nothing
new(stoploss, takeprofit, entry, _high, _low, condition, update)
New Trade with tracking
Parameters:
stoploss (float)
takeprofit (float)
entry (float)
_high (float)
_low (float)
condition (bool)
update (bool)
Returns: a Trade with targets and updates if stoploss or takeprofit is hit
new()
New Empty Trade
Returns: an empty trade
Trade
Fields:
stoploss (series__float)
takeprofit (series__float)
entry (series__float)
sl_hit (series__bool)
tp_hit (series__bool)
open (series__integer)
Expected Move from RSI [SS]Publishing this experimental indicator.
What it does:
The indicator uses a user-defined lookback period on a user-defined timeframe to lookback at all instances of RSI. It breaks RSI down as follows:
RSI between
0 - 10
10 - 20
20 - 30
30 - 40
40 - 50
50 - 60
60 - 70
70 - 80
80 - 90
90 - 100
From there, it stores the ticker's move from open to high and open to low. It will then use this data to look at the current RSI based on the specified timeframe and plot the expected move based on the average move the ticker does with a similar RSI reading.
It will plot the expected range, with the high range being plotted in green and the low range being plotted in red.
It will also display an infographic that dictates the current RSI based on the selected time frame, the anticipated up move and the anticipated down move. This infographic will also tell you the strength of the relationship (correlation) RSI has with the ticker's high or low price:
From there the user can determine whether this RSI reading is traditionally bullish or bearish for the ticker. A greater down move indicates that the RSI traditionally elicits a bearish response. A greater up move indicates the inverse.
The user can also view a chart of a breakdown of the anticipated moves based on RSI. If the option to "Show Expected Move Table" is select in the settings menu, the following table will appear:
From here you can see the average up move and down move a ticker does based on its corresponding RSI reading.
NOTE: When using the table, please adjust your chart timeframe to the selected timeframe on the indicator. Thus, if you are looking at the 1 hour levels, please adjust your chart to the 1 hour timeframe to use the chart.
Additional Note: When using the table, an "NaN" means that there are no instances of the ticker being at that RSI level within the designated timeframe period. You can extend your lookback period to up to 500 candles to see if it finds additional instances of similar RSI. Otherwise, you can adjust the selected timeframe.
Uses:
The indicator can be used on all timeframes. It can help give you an idea as to whether the RSI indicates a bearish or bullish sentiment.
It can signal a potential reversal or continuation. It can also help you with determining target prices for day trades and scalp trades.
And that is the indicator. Its pretty straight forward. It is experimental and new, so feel free to play around with it and let me know your thoughts.
Safe trades everyone and thank you for reading!
LYGLibraryLibrary "LYGLibrary"
A collection of custom tools & utility functions commonly used with my scripts
getDecimals()
Calculates how many decimals are on the quote price of the current market
Returns: The current decimal places on the market quote price
truncate(number, decimalPlaces)
Truncates (cuts) excess decimal places
Parameters:
number (float)
decimalPlaces (simple float)
Returns: The given number truncated to the given decimalPlaces
toWhole(number)
Converts pips into whole numbers
Parameters:
number (float)
Returns: The converted number
toPips(number)
Converts whole numbers back into pips
Parameters:
number (float)
Returns: The converted number
getPctChange(value1, value2, lookback)
Gets the percentage change between 2 float values over a given lookback period
Parameters:
value1 (float)
value2 (float)
lookback (int)
av_getPositionSize(balance, risk, stopPoints, conversionRate)
Calculates OANDA forex position size for AutoView based on the given parameters
Parameters:
balance (float)
risk (float)
stopPoints (float)
conversionRate (float)
Returns: The calculated position size (in units - only compatible with OANDA)
bullFib(priceLow, priceHigh, fibRatio)
Calculates a bullish fibonacci value
Parameters:
priceLow (float) : The lowest price point
priceHigh (float) : The highest price point
fibRatio (float) : The fibonacci % ratio to calculate
Returns: The fibonacci value of the given ratio between the two price points
bearFib(priceLow, priceHigh, fibRatio)
Calculates a bearish fibonacci value
Parameters:
priceLow (float) : The lowest price point
priceHigh (float) : The highest price point
fibRatio (float) : The fibonacci % ratio to calculate
Returns: The fibonacci value of the given ratio between the two price points
getMA(length, maType)
Gets a Moving Average based on type (MUST BE CALLED ON EVERY CALCULATION)
Parameters:
length (simple int)
maType (string)
Returns: A moving average with the given parameters
getEAP(atr)
Performs EAP stop loss size calculation (eg. ATR >= 20.0 and ATR < 30, returns 20)
Parameters:
atr (float)
Returns: The EAP SL converted ATR size
getEAP2(atr)
Performs secondary EAP stop loss size calculation (eg. ATR < 40, add 5 pips, ATR between 40-50, add 10 pips etc)
Parameters:
atr (float)
Returns: The EAP SL converted ATR size
barsAboveMA(lookback, ma)
Counts how many candles are above the MA
Parameters:
lookback (int)
ma (float)
Returns: The bar count of how many recent bars are above the MA
barsBelowMA(lookback, ma)
Counts how many candles are below the MA
Parameters:
lookback (int)
ma (float)
Returns: The bar count of how many recent bars are below the EMA
barsCrossedMA(lookback, ma)
Counts how many times the EMA was crossed recently
Parameters:
lookback (int)
ma (float)
Returns: The bar count of how many times price recently crossed the EMA
getPullbackBarCount(lookback, direction)
Counts how many green & red bars have printed recently (ie. pullback count)
Parameters:
lookback (int)
direction (int)
Returns: The bar count of how many candles have retraced over the given lookback & direction
getBodySize()
Gets the current candle's body size (in POINTS, divide by 10 to get pips)
Returns: The current candle's body size in POINTS
getTopWickSize()
Gets the current candle's top wick size (in POINTS, divide by 10 to get pips)
Returns: The current candle's top wick size in POINTS
getBottomWickSize()
Gets the current candle's bottom wick size (in POINTS, divide by 10 to get pips)
Returns: The current candle's bottom wick size in POINTS
getBodyPercent()
Gets the current candle's body size as a percentage of its entire size including its wicks
Returns: The current candle's body size percentage
isHammer(fib, colorMatch)
Checks if the current bar is a hammer candle based on the given parameters
Parameters:
fib (float)
colorMatch (bool)
Returns: A boolean - true if the current bar matches the requirements of a hammer candle
isStar(fib, colorMatch)
Checks if the current bar is a shooting star candle based on the given parameters
Parameters:
fib (float)
colorMatch (bool)
Returns: A boolean - true if the current bar matches the requirements of a shooting star candle
isDoji(wickSize, bodySize)
Checks if the current bar is a doji candle based on the given parameters
Parameters:
wickSize (float)
bodySize (float)
Returns: A boolean - true if the current bar matches the requirements of a doji candle
isBullishEC(allowance, rejectionWickSize, engulfWick)
Checks if the current bar is a bullish engulfing candle
Parameters:
allowance (float)
rejectionWickSize (float)
engulfWick (bool)
Returns: A boolean - true if the current bar matches the requirements of a bullish engulfing candle
isBearishEC(allowance, rejectionWickSize, engulfWick)
Checks if the current bar is a bearish engulfing candle
Parameters:
allowance (float)
rejectionWickSize (float)
engulfWick (bool)
Returns: A boolean - true if the current bar matches the requirements of a bearish engulfing candle
isInsideBar()
Detects inside bars
Returns: Returns true if the current bar is an inside bar
isOutsideBar()
Detects outside bars
Returns: Returns true if the current bar is an outside bar
barInSession(sess, useFilter)
Determines if the current price bar falls inside the specified session
Parameters:
sess (simple string)
useFilter (bool)
Returns: A boolean - true if the current bar falls within the given time session
barOutSession(sess, useFilter)
Determines if the current price bar falls outside the specified session
Parameters:
sess (simple string)
useFilter (bool)
Returns: A boolean - true if the current bar falls outside the given time session
dateFilter(startTime, endTime)
Determines if this bar's time falls within date filter range
Parameters:
startTime (int)
endTime (int)
Returns: A boolean - true if the current bar falls within the given dates
dayFilter(monday, tuesday, wednesday, thursday, friday, saturday, sunday)
Checks if the current bar's day is in the list of given days to analyze
Parameters:
monday (bool)
tuesday (bool)
wednesday (bool)
thursday (bool)
friday (bool)
saturday (bool)
sunday (bool)
Returns: A boolean - true if the current bar's day is one of the given days
atrFilter(atrValue, maxSize)
Parameters:
atrValue (float)
maxSize (float)
fillCell(tableID, column, row, title, value, bgcolor, txtcolor)
This updates the given table's cell with the given values
Parameters:
tableID (table)
column (int)
row (int)
title (string)
value (string)
bgcolor (color)
txtcolor (color)
Returns: A boolean - true if the current bar falls within the given dates
Cobra's CryptoMarket VisualizerCobra's Crypto Market Screener is designed to provide a comprehensive overview of the top 40 marketcap cryptocurrencies in a table\heatmap format. This indicator incorporates essential metrics such as Beta, Alpha, Sharpe Ratio, Sortino Ratio, Omega Ratio, Z-Score, and Average Daily Range (ADR). The table utilizes cell coloring resembling a heatmap, allowing for quick visual analysis and comparison of multiple cryptocurrencies.
The indicator also includes a shortened explanation tooltip of each metric when hovering over it's respected cell. I shall elaborate on each here for anyone interested.
Metric Descriptions:
1. Beta: measures the sensitivity of an asset's returns to the overall market returns. It indicates how much the asset's price is likely to move in relation to a benchmark index. A beta of 1 suggests the asset moves in line with the market, while a beta greater than 1 implies the asset is more volatile, and a beta less than 1 suggests lower volatility.
2. Alpha: is a measure of the excess return generated by an investment compared to its expected return, given its risk (as indicated by its beta). It assesses the performance of an investment after adjusting for market risk. Positive alpha indicates outperformance, while negative alpha suggests underperformance.
3. Sharpe Ratio: measures the risk-adjusted return of an investment or portfolio. It evaluates the excess return earned per unit of risk taken. A higher Sharpe ratio indicates better risk-adjusted performance, as it reflects a higher return for each unit of volatility or risk.
4. Sortino Ratio: is a risk-adjusted measure similar to the Sharpe ratio but focuses only on downside risk. It considers the excess return per unit of downside volatility. The Sortino ratio emphasizes the risk associated with below-target returns and is particularly useful for assessing investments with asymmetric risk profiles.
5. Omega Ratio: measures the ratio of the cumulative average positive returns to the cumulative average negative returns. It assesses the reward-to-risk ratio by considering both upside and downside performance. A higher Omega ratio indicates a higher reward relative to the risk taken.
6. Z-Score: is a statistical measure that represents the number of standard deviations a data point is from the mean of a dataset. In finance, the Z-score is commonly used to assess the financial health or risk of a company. It quantifies the distance of a company's financial ratios from the average and provides insight into its relative position.
7. Average Daily Range: ADR represents the average range of price movement of an asset during a trading day. It measures the average difference between the high and low prices over a specific period. Traders use ADR to gauge the potential price range within which an asset might fluctuate during a typical trading session.
Utility:
Comprehensive Overview: The indicator allows for monitoring up to 40 cryptocurrencies simultaneously, providing a consolidated view of essential metrics in a single table.
Efficient Comparison: The heatmap-like coloring of the cells enables easy visual comparison of different cryptocurrencies, helping identify relative strengths and weaknesses.
Risk Assessment: Metrics such as Beta, Alpha, Sharpe Ratio, Sortino Ratio, and Omega Ratio offer insights into the risk associated with each cryptocurrency, aiding risk assessment and portfolio management decisions.
Performance Evaluation: The Alpha, Sharpe Ratio, and Sortino Ratio provide measures of a cryptocurrency's performance adjusted for risk. This helps assess investment performance over time and across different assets.
Market Analysis: By considering the Z-Score and Average Daily Range (ADR), traders can evaluate the financial health and potential price volatility of cryptocurrencies, aiding in trade selection and risk management.
Features:
Reference period optimization, alpha and ADR in particular
Source calculation
Table sizing and positioning options to fit the user's screen size.
Tooltips
Important Notes -
1. The Sharpe, Sortino and Omega ratios cell coloring threshold might be subjective, I did the best I can to gauge the median value of each to provide more accurate coloring sentiment, it may change in the future.
The median values are : Sharpe -1, Sortino - 1.5, Omega - 20.
2. Limitations - Some cryptos have a Z-Score value of NaN due to their short lifetime, I tried to overcome this issue as with the rest of the metrics as best I can. Moreover, it limits the time horizon for replay mode to somewhere around Q3 of 2021 and that's with using the split option of the top half, to remain with the older cryptos.
3. For the beginner Pine enthusiasts, I recommend scimming through the script as it serves as a prime example of using key features, to name a few : Arrays, User Defined Functions, User Defined Types, For loops, Switches and Tables.
4. Beta and Alpha's benchmark instrument is BTC, due to cryptos volatility I saw no reason to use SPY or any other asset for that matter.
Custom Group Financials [Technimentals]This script allows the user to build custom groups and combine the same financial data from 40 different symbols simultaneously and plot it data as a total or as an average.
By default, the top 40 symbols in the QQQ are used. Between them they account for the majority of the index. This is a good workaround for the lack of ETF financial data in TradingView.
This functions much like any other financial indicator. You choose the financial data and period:
FY = Financial Year
FQ = Financial Quarter
TTM = Trailing Twelve Months
Bare in mind that some data only exists in FY data.
Thanks to @LucF for writing most of this code!
Enjoy!
Stochastic Momentum Index (SMI) of Money Flow Index (MFI)"He who does not know how to make predictions and makes light of his opponents, underestimating his ability, will certainly be defeated by them."
(Sun Tzu - The Art of War)
▮ Introduction
The Stochastic Momentum Index (SMI) is a technical analysis indicator that uses the difference between the current closing price and the high or low price over a specific time period to measure price momentum.
On the other hand, the Money Flow Index (MFI) is an indicator that uses volume and price to measure buying and selling pressure.
When these two indicators are combined, they can provide a more comprehensive view of price direction and market strength.
▮ Improvements
By combining SMI with MFI, we can gain even more insights into the market. One way to do this is to use the MFI as an input to the SMI, rather than just using price.
This means we are measuring momentum based on buying and selling pressure rather than just price.
Another way to improve this indicator is to adjust the periods to suit your specific trading needs.
▮ What to look
When using the SMI MFI indicator, there are a few things to look out for.
First, look at the SMI signal line.
When the line crosses above -40, it is considered a buy signal, while the crossing below +40 is considered a sell signal.
Also, pay attention to divergences between the SMI MFI and the price.
If price is rising but the SMI MFI is showing negative divergence, it could indicate that momentum is waning and a reversal could be in the offing.
Likewise, if price is falling but the SMI MFI is showing positive divergence, this could indicate that momentum is building and a reversal could also be in the offing.
In the examples below, I show the use in conjunction with the price SMI, in which the MFI SMI helps to anticipate divergences:
In summary, the SMI MFI is a useful indicator that can provide valuable insights into market direction and price strength.
By adjusting the timeframes and paying attention to divergences and signal line crossovers, traders can use it as part of a broader trading strategy.
However, remember that no indicator is a magic bullet and should always be used in conjunction with other analytics and indicators to make informed trading decisions.
Stochastic Momentum Index (SMI) Refurbished▮Introduction
Stochastic Momentum Index (SMI) Indicator is a technical indicator used in technical analysis of stocks and other financial instruments.
It was developed by William Blau in 1993 and is considered to be a momentum indicator that can help identify trend reversal points.
Basically, it's a combination of the True Strength Index with a signal line to help identify turning points in the market.
SMI uses the stochastic formula to compare the current closing price of an asset with the maximum and minimum price range over a specific period.
He then compares this ratio to a short-term moving average to create an indicator that oscillates between -100 and +100.
When the SMI is above 0, it is considered positive, indicating that the current price is above the short-term moving average.
When it is below 0, it is considered negative, indicating that the current price is below the short-term moving average.
Traders use the SMI to identify potential trend reversal points.
When the indicator reaches an extreme level above +40 or below -40, a trend reversal is possible.
Furthermore, traders also watch for divergences between the SMI and the asset price to identify potential trading opportunities.
It is important to remember that the SMI is a technical indicator and as such should be used in conjunction with other technical analysis tools to get a complete picture of the market situation.
▮ Improvements
The following features were added:
1. 7 color themes, for TSI, Signal and Histogram.
2. Possibility to customize moving average type for TSI/Signal.
3. Dynamic Zones.
4. Crossing Alerts.
5. Alert points on specific ranges.
5. Coloring of bars according to TSI/Signal/Histogram.
▮ Themes
Examples:
▮ About Dynamic Zones
'Most indicators use a fixed zone for buy and sell signals.
Here's a concept based on zones that are responsive to the past levels of the indicator.'
The concept of Dynamic Zones was described by Leo Zamansky ( Ph .D.) and David Stendahl, in the magazine of Stocks & Commodities V15:7 (306-310).
Basically, a statistical calculation is made to define the extreme levels, delimiting a possible overbought/oversold region.
Given user-defined probabilities, the percentile is calculated using the method of Nearest Rank.
It is calculated by taking the difference between the data point and the number of data points below it, then dividing by the total number of data points in the set.
The result is expressed as a percentage.
This provides a measure of how a particular value compares to other values in a data set, identifying outliers or values that are significantly higher or lower than the rest of the data.
▮ What to look for
1. Divergences/weakening of a trend/reversal:
2. Supports, resistances, pullbacks:
3. Overbought/Oversold Points:
▮ Thanks and Credits
- TradingView and PineCoders: for SMI and Moving Averages
- allanster: for Dynamic Zones
Delta Ladder [Kioseff Trading]Hello!
This script presents volume delta data in various forms!
Features
Classic mode: Volume delta boxes oriented to the right of the bar (sell closer / buy further)
On Bar mode: Volume delta boxes oriented on the bar (sell left / buy right)
Pure Ladder mode: Pure volume delta ladder
PoC highlighting
Color-coordinated delta boxes. Marginal volume differences are substantially shaded while large volume differences are lightly shaded.
Volume delta boxes can be merged and delta values removed to generate a color-only canvas reflecting vol. delta differences in price blocks.
Price bars can be split up to 497 times - allowing for greater precision.
Total volume delta for the bar and timestamp included
The image above shows Classic mode - delta blocks are oriented left/right contingent on positive/negative values!
The image above shows the same price sequence; however, delta blocks are superimposed on the price bar. Left-side blocks reflect negative delta while right-side blocks reflect positive delta! To apply this display method - select "On Bar" for the "Data Display Method" setting!
The image above shows "Pure Ladder" mode. Delta blocks remain color-coordinated; however, all delta blocks retain the same x-axis as the price bar they were calculated for!
Additionally, you can select to remove the delta values and merge the delta boxes to generate a color-based canvas indicative of volume delta at traded price levels!
The image above shows the same price sequence; however, the "Volume Assumption" setting is activated.
When active, the indicator assumes a 60/ 40 split when a level is traded at and only one metric - "buy volume" or "sell volume" is recorded. This means there shouldn't be any levels recorded where "buy volume" is greater than 0 and "sell volume" equals 0 and vice versa. While this assumption was performed arbitrarily, it may help better replicate volume delta and OI delta calculations seen on other charting platforms.
This option is configurable; you can select to have the script not assume a 60/ 40 split and instead record volume "as is" at the corresponding price level!
I plan to roll out additional features for the indicator - particularly tick-based price blocks! Stay tuned (:
Thank you!
Market TrendThis indicator show how is the trend of 40 stock in SET Index Thailand ordered by market capitalization.
RSI, Moving Average and MACD is used to calculate vale of each stocks.
The trend will be assigned and cumulative as 1 represent uptrend while -1 represents downtrend.
For example RSI
If RSI > RSI moving average, it will be uptrend and return 1.
If RSI < RSI moving average, it will be downtrend and return-1.
The calculation will return positive and negative of total 40 stocks (or other tickers).
If positive is greater than negative, it mean that the market is uptrend and vise versa.
Here some examples
RSI
Moving Average
MACD
You can change to other tickers.
Enjoy..
RSI Multi Alerts MTFThis indicator won't plot anything to the chart.
Please follow steps below to set your alarms based on RSI oversold and overbought levels:
1) Add indicator to the chart
2) Go to settings
3) Choose up to 8 different symbols to get alert notification
4) Choose up to 4 different timeframes
5) Set overbought and oversold levels
6) Once all is set go back to the chart and click on 3 dots to set alert in this indicator, rename your alert and confirm
7) You can remove indicator after alert is set and it'll keep working as expected
What is does:
This indicator will generate alerts based on symbols, timeframes and RSI levels settings.
It will consider overbought and oversold levels to alert in each symbol and each timeframe selected. Once these levels are achieved it will send an alert with the following information:
- Symbol name (BTC, ETH, LTC)
- Specific RSI level achieved (e.g: RSI 30, RSI 70 or any custom level)
- Timeframe (e.g: 5m, 1h, 1D)
- Current symbol price
This script will request RSI OB/OS information through request.security() function from all different symbols and timeframes settings. It also requests symbols' price (close).
Due to Tradingview limitation (40 requests calls) it can only request information for 8 symbols for this script (8 symbols X 4 timeframes = 32 + 8 symbols' price (close) = 40)
Standard symbols are Binance USDT-M Futures but you can choose any symbol from Tradingview.
Standard timeframes are 5m|15m|1h|4h but you can choose from a list.
Standard overbought and oversold levels are 70 and 30 but you can change it to other integer values.
Feel free to give feedbacks on comments section below.
Enjoy!
Financial Data Spreadsheet [By MUQWISHI]The Financial Data Spreadsheet indicator displays tables in the form of a spreadsheet containing a set of selected financial performances of a company within the most recent reported period. Analyzing Financial data is one of the classic methods to evaluate whether the company’s stock price is overvalued or undervalued based on its income statement, balance sheet, and cash flow statement. This indicator might be practical to investors to collect needed data of a company to analyze and compare it with other companies on a TradingView chart or print it in spreadsheet form.
█ OVERVIEW
█ BEST PRACTICES
Due to strict limitations on calling request.financial() function, I tried to develop the table with the best ways to be more dynamic to move and the ability to join multiple tables into a spreadsheet. Users can add up to 20 instruments and 2 financial metrics per table. However, it’s possible to add many tables with other financial metrics, then connect them to the main table.
Credits: The idea of joining multiple tables inspired by @QuantNomad Screener for 40+ instruments
█ INDICATOR SETTINGS
1- Moving Table toward right-left up-down from its origin.
2- Hiding Column Title checkmark. Useful for adding a joined table underneath with additional instruments.
3- Hiding Instruments Title checkmark. Useful for adding a joined table on the right with other financial metrics.
4- Shade Alternate Rows checkmark. I believe it’ll make the table easier to read.
5- Selecting Financial Period. (Year, Quarter).
6- Entering a currency.
7- Choosing a financial ID for each column. There’re over 200 financial IDs. Source: What financial data is available in Pine? — TradingView
8- Optional to highlight values in between.
9- Entering the ticker’s symbol with the ability to activate/deactivate.
█ TIP
For best technical performance, use the indicator in a 1D timeframe.
Please let me know if you have any questions.
Thank you.
I11L - Meanreverter 4h---Overview---
The system buys fear and sells greed.
Its relies on a Relative Strength Index (RSI) and moving averages (MA) to find oversold and overbought states.
It seems to work best in market conditions where the Bond market has a negative Beta to Stocks.
Backtests in a longer Timeframe will clearly show this.
---Parameter---
Frequency: Smothens the RSI curve, helps to "remember" recent highs better.
RsiFrequency: A Frequency of 40 implies a RSI over the last 40 Bars.
BuyZoneDistance: Spacing between the different zones. A wider spacing reduces the amount of signals and icnreases the holding duration. Should be finetuned with tradingcosts in mind.
AvgDownATRSum: The multiple of the Average ATR over 20 Bars * amount of opentrades for your average down. I choose the ATR over a fixed percent loss to find more signals in low volatility environments and less in high volatility environments.
---Some of my thoughts---
Be very careful about the good backtesting performance in many US-Stocks because the System had a favourable environment since 1970.
Be careful about the survivorship bias as well.
52% of stocks from the S&P500 were removed since 2000.
I discount my Annual Results by 5% because of this fact.
You will find yourself quite often with very few signals because of the high market correlation.
My testing suggests that there is no expected total performance difference between a signal from a bad and a signal from a good market condition but a higher volatility.
I am sharing this strategy because i am currently not able to implement it as i want to and i think that meanreversion is starting to be taken more serious by traders.
The challange in implementing this strategy is that you need to be invested 100% of the time to retrieve the expected annual performance and to reduce the fat tail risk by market crashes.
Volume Profile Volume Delta OI Delta [Kioseff Trading]Hello!
This script serves to distinguish volume delta for any asset and open interest delta for Binance perpetual futures.
The image above provides further explanation of functionality and color correspondence.
The image above shows the indicator calculating volume at each tick level and displaying the metric.
The label color outline (neon effect) is configurable; the image above is absent the feature.
The image above shows Open Interest (OI) Delta calculated - similar to how the script calculates volume delta - for a Binance Perpetual Future pair.
This feature only works for Binance Futures pairs; the script will not load when trying to calculate OI Delta on other assets.
Additionally, a heatmap is displayable should you configure the indicator to calculate it.
The image above shows a heatmap using volume delta calculations.
The image above shows a heatmap using OI delta calculations.
Of course, these calculations - when absent requisite data - require some assumptions to better replicate calculations with access to requisite data.
The indicator assumes a 60/40 split when a tick level is traded at and only one metric - "buy volume" or "sell volume" is recorded. This means there shouldn't be any levels recorded where "buy volume" is greater than 0 and "sell volume" equals 0 and vice versa. While this assumption was performed arbitrarily, it may help better replicate volume delta and OI delta calculations seen on other charting platforms.
This option is configurable; you can select to have the script not assume a 60/40 split and instead record volume "as is" at the corresponding tick level.
The script also divides volume and open interest if a one-minute bar violates multiple tick levels. The volume or open interest generated on the one-minute bar will be divided by the number of tick levels it exceeds. The results are, subsequently, appended to the violated tick levels.
Further, the script can be set to recalculate after a user-defined time threshold is exceeded. You can also define the percentage or tick distance between levels.
Also, it'd be great if this indicator can nicely replicate volume delta indicators on other charting platforms. If you've any ideas on how price action can be used to better assume volume at the corresponding price area please let me know!
Thank you (:
ICT IPDA Look BackThis script automatically calculates and updates ICT's daily IPDA look back time intervals and their respective discount / equilibrium / premium, so you don't have to :)
IPDA stands for Interbank Price Delivery Algorithm. Said algorithm appears to be referencing the past 20, 40, and 60 days intervals as points of reference to define ranges and related PD arrays.
Intraday traders can find most value in the 20 Day Look Back box, by observing imbalances and points of interest.
Longer term traders can reference the 40 and 60 Day Look Back boxes for a clear indication of current market conditions.
FATL, SATL, RFTL, & RSTL Digital Filters Raw [Loxx]FATL, SATL, RFTL, & RSTL Digital Filters Raw is an indicator to showcase FATL, SATL, RFTL, & RSTL Digital Filters with their raw output values. The coefficients used here are for an idealized environment. This is tuned for Forex.
What is FATL?
FATL (Fast Adaptive Trend Line) is calculated using low frequency digital filter (FLF-1).
FLF-1 filter is necessary for high frequency noises suppression and reduction of market cycles with a very short volatility periods that can also be considered as a noise.
Filters of low frequency FLF-1 and FLF-2 provide attenuation in the stop band with no less than 40 dB and absolutely don’t distort the amplitude and phase of entry discontinuous price series in the pass band (bandwidth). These properties of the digital filters provide significantly improved (in comparison with simple moving average) noise suppression that in its turn allows reducing sharply the probability of appearance "false" signals for buy and sell.
There are no analogues to FATL among widely known technical instruments. It is not a moving "average", but just the adaptive lines estimates of the short-term trends. Unlike moving "average", FATL has no any phase delay with regard to current prices.
What is SATL?
Slow Adaptive Trend Line (SATL) is formed with the digital filter of the low frequency FLF-2.
Filter FLF-2 serves to suppress noises and market cycles with longer periods of oscillation. Filters of low frequency FLF-1 and FLF-2 provide attenuation in the stop band with no less than 40 dB and absolutely don’t distort the amplitude and phase of entry discontinuous price series in the pass band (bandwidth).
These properties of the digital filters provide significantly improved (in comparison with simple moving average) noise suppression that in its turn allows reducing sharply the probability of appearance of "false" signals for purchase and sell.
There are no analogues to SATL among widely known technical instruments. This is not a moving "average", but just the adaptive line estimate of a long-term trend.
Unlike moving average, SATL has no any phase delay with regard to current prices.
What is RFTL?
Reference Fast Trend Line (RFTL) is a response of FLF-1 and FLF-2 digital filters to the input discrete sequence. This response is set with the delay equal to the Nyquist TNi range.
RFTL reference line is an equivalent of simple moving "averages" from the viewpoint of their delay relative to the current prices. Mentioned similarity would have been complete, in case we use an impulse parameter having 1/N weights that corresponds to the procedure of the dotted moving smoothing instead of the complicated FLF impulse parameters.
What is RSTL?
Reference Slow Trend Line (RSTL) is a response of the SATL digital filter to the series of input prices with a delay equal to the Nyquist interval of 1/2F.
FATL, SATL, RFTL, & RSTL Digital Signal Filter Smoother [Loxx]FATL, SATL, RFTL, & RSTL Digital Signal Filter (DSP) Smoother is is a baseline indicator with DSP processed source inputs
What are digital indicators: distinctions from standard tools, types of filters.
To date, dozens of technical analysis indicators have been developed: trend instruments, oscillators, etc. Most of them use the method of averaging historical data, which is considered crude. But there is another group of tools - digital indicators developed on the basis of mathematical methods of spectral analysis. Their formula allows the trader to filter price noise accurately and exclude occasional surges, making the forecast more effective in comparison with conventional indicators. In this review, you will learn about their distinctions, advantages, types of digital indicators and examples of strategies based on them.
Two non-standard strategies based on digital indicators
Basic technical analysis indicators built into most platforms are based on mathematical formulas. These formulas are a reflection of market behavior in past periods. In other words, these indicators are built based on patterns that were discovered as a result of statistical analysis, which allows one to predict further trend movement to some extent. But there is also a group of indicators called digital indicators. They are developed using mathematical analysis and are an algorithmic spectral system called ATCF (Adaptive Trend & Cycles Following). In this article, I will tell you more about the components of this system, describe the differences between digital and regular indicators, and give examples of 2 strategies with indicator templates.
ATCF - Market Spectrum Analysis Method
There is a theory according to which the market is chaotic and unpredictable, i.e. it cannot be accurately analyzed. After all, no one can tell how traders will react to certain news, or whether some large investor will want to play against the market like George Soros did with the Bank of England. But there is another theory: many general market trends are logical, and have a rationale, causes and effects. The economy is undulating, which means it can be described by mathematical methods.
Digital indicators are defined as a group of algorithms for assessing the market situation, which are based exclusively on mathematical methods. They differ from standard indicators by the form of analysis display. They display certain values: price, smoothed price, volumes. Many standard indicators are built on the basis of filtering the minute significant price fluctuations with the help of moving averages and their variations. But we can hardly call the MA a good filter, because digital indicators that use spectral filters make it possible to do a more accurate calculation.
Simply put, digital indicators are technical analysis tools in which spectral filters are used to filter out price noise instead of moving averages.
The display of traditional indicators is lines, areas, and channels. Digital indicators can be displayed both in the form of lines and in digital form (a set of numbers in columns, any data in a text field, etc.). The digital display of the data is more like an additional source of statistics; for trading, a standard visual linear chart view is used.
All digital models belong to the category of spectral analysis of the market situation. In conventional technical indicators, price indications are averaged over a fixed period of time, which gives a rather rough result. The use of spectral analysis allows us to increase trading efficiency due to the fact that digital indicators use a statistical data set of past periods, which is converted into a “frequency” of the market (period of fluctuations).
Fourier theory provides the following spectral ranging of the trend duration:
low frequency range (0-4) - a reflection of a long trend of 2 months or more
medium frequency range (5-40) - the trend lasts 10-60 days, thus it is referred to as a correction
high frequency range (41-130) - price noise that lasts for several days
The ATCF algorithm is built on the basis of spectral analysis and includes a set of indicators created using digital filters. Its consists of indicators and filters:
FATL: Built on the basis of a low-frequency digital trend filter
SATL: Built on the basis of a low-frequency digital trend filter of a different order
RFTL: High frequency trend line
RSTL: Low frequency trend line
Inclucded:
4 DSP filters
Bar coloring
Keltner channels with variety ranges and smoothing functions
Bollinger bands
40 Smoothing filters
33 souce types
Variable channels
RSI Trend Heatmap in Multi TimeframesRSI Trend Heatmap in Multi Timeframes
Description
Sometimes you want to look at the RSI Trend across multiple time frames.
You have to waste time browsing through them.
So we've put together every time frame you want to see in one indicator.
We have 10 layers of RSI Trend heatmap available for you.
You can set the timeframe as you want on the Settings page.
Description of Parameter RSI Setting ** You can change it by setting.
RSI Trend Length : (Default 50)
Source : (Default close)
RSI Sideways Length : (Default 2 = RSI between 48 .. 52)
Description of Parameter RSI Timeframe ** You can change it by setting.
""=None,
"M"=1Month, "2W"=2Weeks, "W"=1Week,
"3D"=3Days, "2D"=2Days, "D"=1Day,
"720"=12Hours, "480"=4Hours, "240"=4Hours, "180"=3Hours, "120"=2Hours,
"60"=60Minutes, "30"=30Minutes, "15"=15Minutes, "5"=5Minutes, "1"=1Minute
Default Configurate of RSI Timeframe (for a time frame of 1 hour to 1 day)
"W"= Timeframe 1 month shown in line 90-100 --> Represent Long Trend of RSI
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"D2"= Timeframe 2 days shown in line 70-80 --> Represent Trend of RSI
"D"= Timeframe 1 day shown in line 60-70 --> Represent Trend of RSI
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"240"= Timeframe 3 hours shown in line 40-50 --> Represent Signal Up/Signal Down/Divergence of RSI
"120"= Timeframe 2 hours shown in line 30-40 --> Represent Signal Up/Signal Down/Divergence of RSI
"60"= Timeframe 1 hour shown in line 20-30 --> Represent Signal Up/Signal Down/Divergence of RSI
"30"= Timeframe 30 minutes shown in line 10-20 --> Represent Signal Up/Signal Down/Divergence of RSI
"15"= Timeframe 15 minutes shown in line 00-10 --> Represent Signal Up/Signal Down/Divergence of RSI
Description of Colors
Dark Bule = Extreme Uptrend / Overbought / Bull Market (RSI > 67)
Light Bule = Uptrend (RSI between 50-52 .. 67)
Yellow = Sideways Trend / Trend Reversal (RSI between 48 .. 52) ** You can change it by setting.
Light Red = Downtrend (RSI between 33 .. 48-50)
Dark Red = Extreme Downtrend / Oversold / Bear Market (RSI < 33)
How to use
1. You must first know what the main trend of the RSI is (look at the 60-80 line). If it is red, it is a downtrend. and if it's blue shows that it is an uptrend
2. Throughout the period of the main trend There will always be a reversal of the sub-trend. (Can see from the 0-50 line), but eventually will return to follow the main trend.
3. Unless the sub trend persists for a long time until the main trend changes.
Nifty & BN 2 Candle Theory Back Testing and Alert Notification How To Initiate Long Trade-in Index Future/ Buy Call Options – 3 Min TF
▪ If The Index Futures Trades Above The VWAP, the Following Parameters are Checked For 2 Candle Theory on the long side
▪ RSI Trades Above 50 & Between 50-75/80
▪ Volume Of 2 Consecutive Bars Is Above 50 K for BN & 125 K For Nifty
▪ All the indicators (Parabolic SAR, Super Trend, VMA, VWAP) Below the Candles
▪ When the above conditions are met enter In 3rd Candle, With 1st Candle High As SL
How I Initiate Short Trade-In Index Future/ Buy Put Options – 3 Min TF
▪ If The Index Futures Trades Below The VWAP, the Following Parameters are Checked For 2 Candle Theory on the short side
▪ RSI Trades Below 40 & Between 40-25/20
▪ Volume Of 2 Consecutive Bars Is Above 50 K for BN & 125 K For Nifty
▪ All the Indicators (Parabolic SAR, Super Trend, VMA, VWAP) Above The Candles
▪ When the above conditions are met enter In 3rd Candle, With 1st Candle High As SL
The indicator checks the above and notifies to enter a long trade and short trade respectively. There is also volume cutoff and change in the volumes respectively, also non-trading times that can be set.
RSI Swing Trading Setup (2-Period)A simple script that adjusts the RSI visibly in order to better accommodate swing trading and certain swing trading setups/strategies.
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Best used in conjunction with "Linear Regression Channel by LonesomeTheBlue" with 2.2σ (std.dev) and Show Fib Levels.
^Click image for a redirect to that script.
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In certain price action patterns:
A bearish reversal from a previously bullish move can indicate tops of a rally if the RSI moves from 0-40 to 60 (1)
A bullish reversal from a previously bearish move can indicate bottoms of a pullback if the RSI moves from 60-100 to 40 (2)
(USE THE LINEAR REGRESSION CHANNEL TO VALIDIFY THE RETRACEMENTS)
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(1)
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(2)
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