The Ultimate Buy and Sell IndicatorThis indicator should be used in conjunction with a solid risk management strategy that does not over-leverage positions and uses stop-losses. You can not rely 100% on the signals provided by this indicator (or any other for that matter).
With that said, this indicator can provide some excellent signals.
It has been designed with a large number of customization options intended for advanced traders, but you do not HAVE to be an advanced user to simply use the indicator. I have tried to make it easy to understand, and this section will provide you with a better understanding of how to use it.
NOTE:
While NOT REQUIRED, I would recommend also finding my indicator called, "Ultimate RSI", which is designed to work together with this indicator (visually). They both contain the same settings and allow you to visualize changes made in this indicator that can not be displayed on the main chart.
This indicator creates it's own candles(bars), so you have to go into your main settings and turn off the "body, border and wick" color settings. Using a dark background is also recommended.
How does it work?
The indicator mainly relies on the RSI indicator with Bollinger Bands for signals. (Though not entirely)
First, there are something that I call "Watch Signals", which are various Bollinger Band crossing events. This could be the price crossing Bollinger Bands or the RSI crossing Bollinger Bands.
There are separate watch signals for buys and sells. Buy watch signals are colored orange to match the BUY signal candle color and Fuchsia (kind of a bright purple) to match SELL signal candles.
In order for most buy or sell signals to be created, there must first be a watch signal. There is a lookback period (or length) for watch signals to be used, and after that many candles (bars) have passed, they will be ignored. You can set a length to look back as well as a time to wait before creating any.
What this means is that if there has previously been (for instance) a sell signal. You can tell it to wait 10 bars before creating any buy watch signals. You can then also tell it that it should look back 10 bars from the current one in order to find any buy watch signals. This means that if you had it set up that way 10 to wait and 10 to validate, it would start allowing buy watch signals 11 bars after a sell, and then once you hit 20 bars, it will start leaving a gap (invisible to you) as the 10 bar lookback period starts moving forward with each new bar. This is useful in order to keep signals more spaced apart as some bad signals come quickly after another one.
Example: You may get a sell signal where the Bollinger bands are tight, then the price easily drops down into the lower band creating a buy watch signal, then you get a "fake" or short pump up and it says buy, but then drops dramatically afterwards. The wait period can ensure that the sell stays in effect longer before a buy is considered by blocking any buy watch signals for a period of time.
After you get a watch signal, the system then looks for various other things to happen to create buy or sell signals. This could be the RSI crossing the (slow) RSI Basis line (from its Bollinger bands), it could be the price crossing its basis line, it could be MACD crosses, it could even be RSI crossing certain levels. All of these are options. If you like the MACD strategy and want it to give you buy and sell signals from just MACD crosses, simply select that option for signals.
It is also able to use the first of any of the options that takes place.
I included an option to force alternating buy and sell signals, rather than showing groups of, or subsequent buy, buy, buy signals, for instance.
Moving on....
You can change the moving average that is used to calculate the RSI. The standard moving average for RSI is the RMA (aka SWMA). Changes to this can dramatically change your signals. You also have the option to change the moving average type used in the Bollinger bands calculation. You can change the length of these as well. The same goes for the Bollinger bands over the Price chart. I added an ATR option for the RSI Bollinger bands to play with, as well. You are able to adjust the standard deviation (multiplier) of the bands as well, which will of course affect the signals.
The ways you can play with signals are nearly infinite, so have fun figuring it out.
The indicator allows for moving averages to be shown as well, with a variety of types to choose from. The standard numbers are 5, 10, 20, 50, 100 and 200, with the addition of a custom moving average of your choice. You can also change the color of this one. You can choose to show them all or any of them you want to show, in any combination, although the TYPE of moving average (SMA, EMA, WMA, etc.) will apply to all of them.
You may also notice the Bollinger Bands over the Price are colored, and become more or less transparent.
The color is derived from the trend of the RSI or the RSI basis (your choice). It looks back at the value however many bars you want and compares the values and that's how it determines if it is trending up or down. Since RSI is a directional momentum indicator, this can be quite useful. If you see the bands are getting darker, this will explain why.
The indicator has a lookback period for determining the widest the bands (which measure volatility) have been over that period of time. This is the baseline. It then will make the bands disappear (by making them more transparent) if the volatility is low. This indicates that a change in volatility is coming and that price isn't really changing much compared to the past (default 500) bars. If they become bright, this is because price has started trending in a direction and volatility is increasing.
I should also note that the candles are colored based on RSI levels.
If you use the Ultimate Companion indicator, you will be able to see the RSI levels (zones) that the colors are based on. As RSI moves into a new range, the candle color will change.
I have created a yellow zone where the candles turn yellow. This is when RSI is between (default) 45 and 55, indicating there is basically no momentum and price is going sideways. This is a good place to get trapped in bad trades, and there is a Yellow RSI Filter to block signals in this area to keep you from entering bad trades.
Green candles indicate values over 55 (getting brighter as RSI rises) and red candles are RSI values under 45 (getting brighter as RSI values get lower). If you see white, this means RSI is either over 80 or under 20. A sharp reversal is almost always imminent at this stage.
When we talk about Buy and Sell Signals, they draw a green or red triangle and it literally says BUY or SELL. There is an option to color the background for added visibility. These signals do not "repaint", what this means is that they can be late. To account for this, I have included a background color that will flash as a warning that a buy or sell could be imminent, although it may fail to break through and set a buy or sell signal. This is simply an advanced warning. The reason is that sometimes a candle may be very large and you won't be told to buy or sell during the candle until the move is completely over and now you're getting in on the next one. That's not a great feeling, so I made it repaint the background color and not repaint the completed signal. You get the best of both worlds.
This indicator also uses complex logic to handle things.
When there is a buy signal, it enters into a state of having been bought, or a "bought state". The same for sells. If Force alternating signals is off, you could have more than one buy in a bought state, or more than one sell in a sell state. There is an option to color the background green during the full duration of a bought state, or red during the full duration of a sold state.
I have added divergence.
This shows that the lows or highs of RSI and PRICE are different. If RSI is making higher highs but the price is not, then the price is likely to follow this bullish divergence, if the opposite happens, it's bearish. It will draw a line on the chart connecting the highs and lows and call it bearish or bullish. You can adjust this as well.
I have an RSI High/Low filter. If the RSI basis (or average) is very high or low, you can block signal from this area since the price is likely to continue in that direction before actually reversing.
You can change the settings of the MACD if you choose to use it for signals, and if you want to see it, you'll have to run that indicator below the chart and match the settings to see what is going on, just like the RSI.
Going back to Watch Signals. You can also choose to require more than one watch signal if you choose. You can skip watch signals, so it will ignore the first or second one, whatever you want to do. You can color the background to show you where watch signals have been skipped.
Regarding the wait period for creating watch signals after a sell or after a buy, you can also color the background to see where these were blocked by the wait period.
Lastly you can choose which type of watch signals to use, or keep them from being shown on the chart. This allows you to study the history of how the asset you are trading behaves and customize the behavior of signals based on your study of it.
Everything in the settings area has tooltips, which will explain what that thing does to help you along this journey.
I hope this indicator (and perhaps Ultimate RSI alongside this) will help you take your trading to the next level.
Cerca negli script per "股价在8元左右净利润为正市值小于80亿的热门股票有哪些"
Statistics TableStrategy Statistics
This library will add a table with statistics from your strategy. With this library, you won't have to switch to your strategy tester tab to view your results and positions.
Usage:
You can choose whether to set the table by input fields by adding the below code to your strategy or replace the parameters with the ones you would like to use manually.
// Statistics table options.
statistics_table_enabled = input.string(title='Show a table with statistics', defval='YES', options= , group='STATISTICS')
statistics_table_position = input.string(title='Position', defval='RIGHT', options= , group='STATISTICS')
statistics_table_margin = input.int(title='Table Margin', defval=10, minval=0, maxval=100, step=1, group='STATISTICS')
statistics_table_transparency = input.int(title='Cell Transparency', defval=20, minval=1, maxval=100, step=1, group='STATISTICS')
statistics_table_text_color = input.color(title='Text Color', defval=color.new(color.white, 0), group='STATISTICS')
statistics_table_title_cell_color = input.color(title='Title Cell Color', defval=color.new(color.gray, 80), group='STATISTICS')
statistics_table_cell_color = input.color(title='Cell Color', defval=color.new(color.purple, 0), group='STATISTICS')
// Statistics table init.
statistics.table(strategy.initial_capital, close, statistics_table_enabled, statistics_table_position, statistics_table_margin, statistics_table_transparency, statistics_table_text_color, statistics_table_title_cell_color, statistics_table_cell_color)
Sample:
If you are interested in the strategy used for this statistics table, you can browse the strategies on my profile.
Bitcoin Halving Cycle ProfitThe Bitcoin Halving Cycle Profit indicator, developed by Kevin Svenson , unveils a consistent and predetermined profit-taking cycle triggered by each Bitcoin halving event. This indicator streamlines the analysis of halving occurrences, providing explicit signals for both profit-taking and Dollar-Cost Averaging strategies.
Following each Bitcoin halving event, a fixed number of weeks consistently mark the period of maximum profitability for profit-taking:
🔄 Halving Cycle Profit Timeline Explained:
• 40 Weeks (Post-Halving) = Start of the optimal profit-taking zone.
• 80 Weeks (Post-Halving) = "Last Call" for profit-taking before the onset of a bear market.
• 125 Weeks (Post-Halving) = The optimal timeframe to begin Dollar-Cost Averaging.
(Bitcoin Weekly Chart using Halving Cycle Profit)
One standout feature of this indicator is its inherent clarity and comprehensive labeling. This quality makes it exceptionally easy to discern the locations of key factors and turning points, enhancing your understanding of the market dynamics it highlights.
(Bitcoin Daily Chart using Halving Cycle Profit)
🚀 This indicator doesn't limit its effectiveness to just Bitcoin; it seamlessly integrates with top blue-chip altcoins like Ethereum and most household names in the crypto industry.
( Ethereum Weekly Chart using Halving Cycle Profit)
🛠️ Customizable display options are availible. Users have the flexibility to toggle/adjust labels, lines, and color fills according to their preferences.
📑 In summary, the Bitcoin Halving Cycle Profit indicator is a versatile and user-friendly tool, offering clarity and customization for traders navigating both Bitcoin and top altcoins.
⚠️ It's important to note that while the Bitcoin Halving Cycle Profit indicator provides historical insights, past performance does not guarantee future results. Timing profitability in the cryptocurrency market involves inherent risks, and this indicator should not be construed as financial advice. Users are encouraged to exercise caution, conduct thorough research, and make informed decisions based on their individual risk tolerance and financial goals.
[blackcat] L3 SuperJThe SuperJ indicator is a powerful tool that utilizes VWMA (Volume Weighted Moving Average) and ALMA (Arnaud Legoux Moving Average) to filter and enhance the KDJ indicator, resulting in a smoother J line and the creation of the SuperJ indicator. By incorporating TVMA (Triggered Volume Moving Average), the SuperJ indicator can generate trigger signals that can form bullish and bearish crossovers with the J line, creating an oscillating pattern.
The combination of VWMA and ALMA helps to remove noise from the market and provides clearer trading signals. This is particularly useful when the market is highly volatile or the trend is ambiguous. The oscillations of the J line can help traders identify the true trend and avoid being misled by false signals.
Furthermore, by considering the values and trends of the J line in conjunction with other technical analysis tools, traders can make more accurate assessments of market trends and price movements. For example, when combined with moving averages, the SuperJ indicator can enhance the ability to identify price reversal points.
The SuperJ indicator also offers benefits in assessing overbought and oversold conditions in the market. By observing the values and trends of the J line, traders can more accurately evaluate market sentiment and strength. When the J line is above 80, it may indicate an overly optimistic market with a risk of overbought conditions. Conversely, when the J line is below 20, it may indicate an overly pessimistic market with an opportunity for oversold conditions. These signals can assist traders in determining when to buy or sell.
In summary, the SuperJ indicator, derived from the combination of VWMA, ALMA, and TVMA, provides traders with a valuable tool for identifying overbought and oversold conditions, predicting price reversals, and generating high-quality trading signals. Its application as a "buy low, sell high" strategy element is highly effective in maximizing trading opportunities and optimizing profitability.
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!
Volatility Adjusted Composite RSI with SMA and EMA SignalsOverview
The script "VAC - RSI with SMA and EMA Signals" combines the traditional Relative Strength Index (RSI) with Time-based RSI (T-RSI), and adjusts it for volatility to create a Composite RSI (C-RSI). The script further uses Simple Moving Average (SMA) and Exponential Moving Average (EMA) to generate signals for potential trading opportunities. In the "VAC - RSI with SMA and EMA Signals" script, the combination of price, time, and volatility works as follows:
Price: The script calculates the traditional RSI based on price changes over a specified period.
Time: Alongside the price-based RSI, a Time-based RSI (T-RSI) is calculated, which considers the number of upward and downward closes over the same period.
Volatility: Volatility is integrated into the Composite RSI (C-RSI) by adjusting it with a Z-score based on a standard deviation of closing prices.
These three factors work together to create a more holistic and robust indicator.
How can it be used?
This script is used to identify potential overbought and oversold conditions in the market. It plots the VAC-RSI, SMA, and EMA on a chart, along with overbought and oversold levels, providing visual signals to the trader. When the EMA is below the SMA, it is a bullish signal, and vice versa for a bearish signal.
Default Values for Different Inputs:
Price RSI Weightage (%): 65
Unified Period for RSI & T-RSI: 14
C-RSI SMA Period: 13
C-RSI EMA Period: 33
C-RSI Bull Trend Support: 35
C-RSI Bear Trend Resistance: 65
Use Volatility Adjusted C-RSI (VAC-RSI): true
Standard Deviation Period: 14
Volatility Scaling Factor (α): 5
These values can be adjusted according to the trading strategy to optimize the signals for different assets or timeframes.
Strategies this Can be Used for:
The script can be used in various trading strategies including:
Trend Following: By observing the crosses of EMA and SMA, traders can follow the trend.
Reversion to the Mean: Using the overbought and oversold levels to identify potential reversal points.
Breakout: Identifying breakout points using the Bull and Bear Market Support and Resistance levels.
Comparison with the Standard Indicator:
Enhanced Sensitivity to Market Conditions
Improved Signal Quality
Versatility
Volatility Adjustment
Interpretation of Output Values:
VAC-RSI Value:
The script provides additional overbought (80) and oversold (20) lines to help identify extreme conditions.
SMA and EMA Values:
When the EMA is below the SMA, it is generally considered a bullish signal.
When the EMA is above the SMA, it is generally considered a bearish signal.
The cross of EMA and SMA can be used as a trigger for entry or exit points.
Bull and Bear Market Support and Resistance Lines:
The Bull Market VAC-RSI Support (default at 35) and Bear Market VAC-RSI Resistance (default at 65) lines can be used to identify potential breakout or breakdown points.
In a bull market, if the VAC-RSI stays above the support line, it indicates a strong uptrend.
In a bear market, if the VAC-RSI stays below the resistance line, it indicates a strong downtrend.
Cumulative Distribution of a Dataset [SS]This is the Cumulative Distribution of a Dataset indicator that also calculates the Kurtosis and Skewness for a selected dataset and determines the normality and distribution type.
What it does, in pragmatic terms?
In the most simplest terms, it calculates the cumulative distribution function (or CDF) of user-defined dataset.
The cumulative distribution function (CDF) is a concept used in statistics and probability to describe how the probability of a random variable taking on a certain value or less is distributed across the entire range of possible values. In simpler terms, you can conceptualize the CDF as this:
Imagine you have a list of data, such as test scores of students in a class. The CDF helps you answer questions like, "What's the probability that a randomly chosen student scored 80 or less on the test?"
Or in our case, say we are in a strong up or downtrend on a stock. The CDF can help us answer questions like "Based on this current xyz trend, what is the probability that a ticker will fall above X price or below Y price".
Within the indicator, you can manually assess a price of interest. Let's say, for NVDA, we want to know the probability NVDA goes above or below $450. We can enter $450 into the indicator and get this result:
Other functions:
Kurtosis and Skewness Functions:
In addition to calculating and plotting the CDF, we can also plot the kurtosis & Skewness.
This can help you look for outlier periods where the distribution of your dataset changed. It can potentially alert you to when a stock is behaving abnormally and when it is more stable and evenly distributed.
Tests of normality
The indicator will use the kurtosis and skewness to determine the normality of the dataset. The indicator is programmed to recognize up to 7 different distribution types and alert you to them and the implications they have in your overall assessment.
e.g. #1 AMC during short squeeze:
e.g. #2: BA during the COVID crash:
Plotting the standardized Z-Score of the Distribution Dataset
You can also standardize the dataset by converting it into Z-Score format:
Plot the raw, CDF results
Two values are plotting, the green and the red. The green represents the probability of a ticker going higher than the current value. The red represents the probability of a ticker going lower than the current value.
Limitations
There are some limitations of the indicator which I think are important to point out. They are:
The indicator cannot tell you timelines, it can only tell you the general probability that data within the dataset will fall above or below a certain value.
The indicator cannot take into account projected periods of consolidation. It is possible a ticker can remain in a consolidation phase for a very long time. This would have the effect of stabilizing the probability in one direction (if there was a lot of downside room, it can normalize the data out so that the extent of the downside probability is mitigated). Thus, its important to use judgement and other methods to assess the likelihood that a stock will pullback or continue up, based on the overall probability.
The indicator is only looking at an individual dataset.
Using this indicator, you have to omit a large amount of data and look at solely a confined dataset. In a way, this actually improves the accuracy, but can also be misleading, depending on the size and strength of the dataset being chosen. It is important to balance your choice of dataset time with such things as:
a) The strength of the uptrend or downtrend.
b) The length of the uptrend or downtrend.
c) The overall performance of the stock leading into the dataset time period
And that is the indicator in a nutshell.
Hopefully you find it helpful and interesting. Feel free to leave questions, comments and suggestions below.
Safe trades everyone and take care!
Stochastic StrategyThis strategy is designed to make trading decisions based on the Stochastic Oscillator (Stoch) indicator with settings of (7,2,2). The strategy opens a long (buy) position when the Stoch indicator crosses above the 50 level from below. Conversely, it opens a short (sell) position when the Stoch indicator crosses below the 50 level from above. Additionally, when a long position is opened, any existing short position is closed, and vice versa.
Key Parameters:
Stochastic Oscillator Settings: Length = 7, SmoothK = 2, SmoothD = 2.
Overbought Level: 80.
Oversold Level: 20.
Strategy Description:
The Stochastic Oscillator (Stoch) is calculated based on the closing price, high price, and low price with a period of 7, and both the %K and %D lines are smoothed with periods of 2.
When the %K line crosses above the oversold level (20), it generates a long (buy) signal.
When the %K line crosses below the overbought level (80), it generates a short (sell) signal.
The strategy visually marks long and short signals on the chart using upward and downward triangles, respectively.
The strategy automatically enters long or short positions when the respective conditions are met.
If a long position is opened, any existing short position is closed, and vice versa.
Please note that this is a basic example of a trading strategy and does not take into account all possible risk factors or optimizations. Before using this strategy in live trading, it's essential to thoroughly test and customize it to suit your specific needs, and carefully analyze the results. Trading carries risks, and it's important to use proper risk management techniques when implementing any trading strategy.
Price Variation and Projection IndicatorThis indicator calculates and visualizes various aspects of price variation and projection based on certain parameters such as rate of change, time interval, constant value, and more. It helps traders understand potential price movements and provides insights into potential support and resistance levels.
The indicator displays the following information:
Resistance and support levels based on the highest and lowest prices over a specified period.
∆P (Price Variation) calculated between two high oscillations.
∆t (Time Variation) calculated between two high oscillations.
Price variation rate.
Price projections based on rate of change and the most occurred variation.
Additionally, parallel lines are drawn to illustrate projected price ranges, and the most frequent ∆P value is shown for reference.
in short the indicator does it projects possible support and resistance for you to add a mark for example you see that it gave a projection you mark it on the chart with horizontal line or horizontal ray you can configure it by Period or by ∆t calculation limit au increase the period it will increase the projection of all targets interesting periods to use 20 50 80 120 200 since the ∆t calculation limit au decrease increases the projection in the Price projection that is showing the information in blue color when increasing it decreases the projection target ∆t calculation interesting limit to use 3 4 6 7 8 9
it works for all timeframes can be used for Swing trade or day trade
use I like to use it with a closed market that helps me to trace possible support and resistance can be used with open market as well
Choose your preferred language to display the information
Please note that this indicator is designed for educational and informational purposes. Always conduct your own analysis and consider risk management strategies before making trading decisions.
Gradient Money Flow Divergence DetectorThe "Gradient Money Flow Divergence Detector" indicator has several use cases for traders. Let's explore the main use cases:
1. Money Flow Analysis : The primary purpose of this indicator is to analyze money flow in a particular asset. The Money Flow Index (MFI) is a momentum indicator that uses price and volume data to assess the buying and selling pressure in a market. Traders can use the MFI to identify overbought and oversold conditions, potential trend reversals, and divergences between the MFI and price movement.
2. Divergence Detection : The indicator incorporates a divergence detection mechanism for multiple timeframes (micro, sub-mid, mid, and macro). Divergence occurs when the price movement and an indicator (MFI in this case) move in opposite directions, signaling a potential shift in the price trend. Traders can use divergences to anticipate trend reversals or trend continuation.
3. Multiple Lookback Analysis : The indicator allows traders to assess divergences and money flow trends across various time horizons by providing divergence detection for different lengths. This can help traders identify confluence areas where divergences align on multiple timeframes, strengthening the potential signal.
4. Overbought and Oversold Conditions : The indicator plots horizontal lines at MFI levels of 20, 50, and 80. These levels can be used to identify overbought (MFI above 80) and oversold (MFI below 20) conditions. Traders may look for potential reversal signals when the MFI reaches extreme levels.
5. Confirmation of Price Trends : The indicator's color gradient visually represents the MFI value, which can help traders confirm the strength of a prevailing price trend. For example, an uptrend with a consistently high MFI might suggest strong buying pressure, reinforcing the bullish bias.
6. Fine-Tuning Divergence Signals : Traders can adjust the parameters of divergence detection (e.g., pivot points, rangeUpper, rangeLower) to fine-tune the sensitivity of the divergence signals. This allows for greater customization based on individual trading preferences.
7. Combining with Other Indicators : The indicator can be used in combination with other technical indicators or price action analysis to strengthen trading decisions. For example, traders may look for divergences in conjunction with support and resistance levels or chart patterns to increase the probability of successful trades.
8. Trend Reversal Confirmation : When a divergence is detected, it may indicate a potential trend reversal. Traders can use other confirmation signals (e.g., candlestick patterns, trendline breaks) to validate the reversal before making trading decisions.
Remember that no single indicator should be used in isolation, and it's essential to use the indicator in combination with other confirmations such as support and resistance, and analysis methods for more robust trading strategies. Additionally, thorough backtesting and practice in a demo environment are recommended before using the indicator in live trading.
Pseudo-Entropy Oscillator with Standard Deviation (modified)Intuition: The Pseudo-Entropy Oscillator with Standard Deviation (PEO_SD) was created to provide traders with a way to analyze market momentum and potential reversals. It combines the concepts of entropy, standard deviation, and moving averages to offer insights into market behavior.The oscillator's core idea is to measure the pseudo-entropy of the market using standard deviation. Pseudo-entropy refers to the degree of disorder or randomness in the price data. By calculating the standard deviation of the closing prices over a specified period, the oscillator quantifies the market's volatility.To enhance the usefulness of the pseudo-entropy measurement, the oscillator incorporates moving averages. The entropy delta is calculated by applying momentum analysis to the pseudo-entropy values. This helps identify short-term changes in the entropy, indicating shifts in market sentiment or momentum.The oscillator further smoothes the pseudo-entropy values by calculating the simple moving average (SMA) over a specified length. This helps filter out noise and provides a clearer representation of the market's overall momentum.
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The "Pseudo-Entropy Oscillator with Standard Deviation" (PEO_SD) is a custom indicator designed to help traders analyze market momentum and potential reversal points. It can be applied to various markets like stocks, commodities, forex, or cryptocurrencies. By using this indicator, you can gain insights into the market's behavior and make more informed trading decisions.
The PEO_SD indicator plots three lines on your chart: the fast pseudo-entropy line, the medium pseudo-entropy line, and the slow pseudo-entropy line. Each line represents the combined pseudo-entropy values, which are calculated using standard deviation and moving averages.
The lines are color-coded for easy identification. The fast line is represented by blue, the medium line by yellow, and the slow line by red. Additionally, three horizontal reference lines are plotted: the mid line (at 50), the lower bound (at 20), and the upper bound (at 80).
To use this indicator effectively, you can observe the interactions of the lines with the reference lines. For example, when any of the lines cross above the mid line, it might indicate a bullish signal, suggesting an upward price movement. Conversely, a crossover below the mid line could be a bearish signal, indicating a potential downward price movement. If the lines reach the upper bound, it might suggest that the market is overbought, and a reversal could be imminent. Conversely, reaching the lower bound may indicate that the market is oversold, possibly leading to a price reversal.
By applying the PEO_SD indicator and studying the lines' movements, you can gain valuable insights into market momentum, identify potential reversal points, and make more informed trading decisions.
adaptive_mfi
█ Description
Money flow an indexed value-based price and volume for the specified input length (lookback period). In summary, a momentum indicator that attempt to measure the flow of money (identify buying/selling pressure) through the asset within a specified period of time. MFI will oscillate between 0 to 100, oftentimes comprehend the analysis with oversold (20) or overbought (80) level, and a divergence that spotted to signaling a further change in trend/direction. As similar to many other indicators that use length (commonly a fixed value) as an input parameter, can be optimized by applied an adaptive filter (Ehlers), to solve the measuring cycle period. In this indicator, the adaptive measure of dominant cycle as an input parameter for the lookback period/n, will be applied to the money flow index.
█ Money Flow Index
mfi = 100 - (100/(1 + money_flow_ratio))
where:
n = int(dominant_cycle)
money_flow_ratio = n positive raw_money_flow / n negative raw_money_flow
raw_money_flow = typical_price * volume
typical_price = hlc3
█ Feature
The indicator will have a specified default parameter of: hp_period = 48; source = ohlc4
Horizontal line indicates positive/negative money flow
MFI Color Scheme: Solid; Normalized
RSI Dot Party - All Lengths From 1 To 120The RSI Dot Party indicator displays all RSI lengths from 1 to 120 as different colored dots on the chart.
🔶 Purpose
Show the reversal point of price action to time entries and exits.
🔶 USAGE
When a dot displays it is a indication of the reversal of the price/trend. The larger the dot the more likely it is to reverse.
The Default settings generates dots for extreme cases where the RSI is over = 90 or under = 10 for every RSI length in the range of 1-120.
Example if the RSI of length 1 or 2 or 3 or 4 or ... or 15 or 16 or 17 or ... or 80 or 81 or 82 or ... if any of does RSI crosses a boundary a dot is shown.
A boundary is the over/under the RSI oscillates in.
Customize the settings until the dots match up with the high and lows of past price action.
🔶 SETTINGS
🔹 Source
Source 1: Is the First Source RSI is calculated from
Source 2: Is the Second Source RSI is calculated from
🔹 Meta Settings
Hours back to draw: To speed up the script calculate it only draws a set number of hours back, default is 300 hours back in time to draw then it cuts off.
Show Dots: Show or disable dots
Show Bar Color: Color the bars for each RSI incident
Filter Cross: Filters and only shows dots when the RSI crosses above or bellow a boundary. If not all candles above or bellow the boundaries will display a dot.
Dots Location Absolute: Instead of showing the dots above or bellow the candle, the dots will show up on the top and bottom of the window.
🔹 7 RSI Groups
There are a total of 7 RSI colors.
Range Very Tiny: Default Color Green
Range Tiny: Default Color Purple
Range Small: Default Color Yellow
Range Normal: Default Color Red
Range Large: Default Color Blue
Range Huge: Default Color Dark Purple
Range Very Huge: Default Color White
🔹 RSI Group Settings
Hi/Low Color: Change the Color of that group.
Start/End: The Start and End range of this RSI color. Example if start = 5 and end = 10 the RSI of 5,6,7,8,9,10 will be displayed on the chart for that color, if any of does RSI goes above or bellow the boundary a dot is displayed on that candle.
Delay: The RSI needs to be above or bellow a boundary for x number of candles before displaying a dot. For example if delay = 2 and the RSI is over = 70 for 2 candles then it will display a dot.
Under/Over: Boundaries that indicate when to draw a dot, if over = 70 and RSI crosses above 70 a dot is displayed.
🔹 Show
Section that allows you to disable RSI grounds you dont want to see, this also removes them from the alert signal generated.
Show Low: Show or disable Low RSI dots
Show High: Show or disable High RSI dots
🔶 ALERTS
Alert for all New RSIs Dots Created in real time
The alert generated depends on what groups are showing or not, if the green group is disabled for example the alert will not be generated.
🔶 Warning
When a dot shows up it can continue moving. For example if a purple dot shows itself above a 15 minute candle, if that candle/price continue to extend up the dot will move up with it.
Dots can also disappear occasionally if the RSI moves in and out of a boundary within that candles life span.
🔶 Community
I hope you guys find this useful, if you have any questions or feature requests leave me a comment! Take care :D
SmartVPSGTitle: Identifying Volume Spikes, Price Movements and Gap Ups: A TradingView Script
Introduction:
In the world of trading, identifying volume spikes and price movements can provide valuable insights into market trends and potential trading opportunities. In this article, we'll explore a TradingView script that helps traders visualize volume spikes, price up moves with volume spikes, and gap-up days on their charts.
Detecting Price Up Moves:
The script starts by calculating price up moves. It compares the current day's closing price with the previous day's closing price and checks if it has increased by 3% or more. This helps traders spot significant upward price movements.
Detecting Volume Spurts:
Next, the script focuses on detecting volume spikes, which are often associated with increased market activity and potential trading opportunities. It compares the current day's volume with the highest volume of the previous nine sessions. If the current volume exceeds all the volumes of the previous nine sessions, it is considered a volume spurt.
Example:
Let's consider a hypothetical scenario where we have the following volume data for a stock:
Day 1: 100,000
Day 2: 80,000
Day 3: 120,000
Day 4: 150,000
Day 5: 200,000
Day 6: 90,000
Day 7: 110,000
Day 8: 130,000
Day 9: 140,000
Day 10: 250,000 (current day)
To determine if there is a volume spurt on Day 10, the script compares the current day's volume (250,000) with the highest volume of the previous nine sessions. In this case, the highest volume among the previous nine sessions is 200,000 (on Day 5). Since the current day's volume (250,000) exceeds the highest volume of the previous nine sessions (200,000), it is considered a volume spurt.
Identifying Gap-Up Days:
Gap-up days occur when the market opens significantly higher than the previous day's close. To identify these days, the script compares the current day's low price with the previous day's high price. If the low price is greater than the previous day's high, it is marked as a gap-up day.
Visualizing the Findings:
To provide a clear visual representation of the identified patterns, the script uses different shapes and colors. First, it plots small red dots above the candles whenever a volume spurt is detected. These dots help traders quickly identify periods of increased volume activity.
For price up moves with volume spikes, the script utilizes blue triangular shapes below the candles. This allows traders to pinpoint instances where both price and volume are showing positive signs, indicating potential bullish movements.
Additionally, the script incorporates green candles to represent gap-up days. These candles help traders recognize days when the market opens with a significant upward gap, suggesting a potential shift in market sentiment.
Conclusion:
The TradingView script discussed in this article provides traders with a visual representation of volume spikes , price up moves with volume spikes , and gap-up days . By incorporating these visual cues into their analysis, traders can gain valuable insights into market trends and potential trading opportunities.
Remember, this script should be used for educational and informational purposes only and does not serve as financial advice or recommendations. Traders are encouraged to customize and modify the script according to their specific trading strategies and risk tolerance.
Share this script with other traders on TradingView to enhance their chart analysis and trading decisions.
PS: This TradingView script is designed to work specifically on the daily timeframe (daily candles). It calculates and identifies volume spurts based on the volume data of the daily timeframe. Since it is designed for the daily timeframe, it may not produce accurate results or work as intended on other timeframes.
Williams %R + Keltner chanells - indicator (AS)1)INDICATOR ---This indicator is a combination of Keltner channels and Williams %R.
It measures trend using these two indicators.
When Williams %R is overbought(above upper line (default=-20)) and Keltner lower line is below price indicator shows uptrend (green).
When Williams %R is oversold(below lower line (default=-80)) and Keltner upper line is above price indicator shows downtrend (red) .
Can be turned into a strategy quickly.
2) CALCULATIONS:
Keltner basis is a choosen type of moving average and upper line is basis + (ATR*multiplier). Same with lower but minus instead of plus so basiss – (ATR*multiplier)
Second indicator
Williams %R reflects the level of the close relative to the highest high for the lookback period
3)PLS-HELP-----Looking for tips, ideas, sets of parameters, markets and timeframes, rules for strategy -------OVERALL -every advice you can have
4) SIGNALS-----buy signal is when price is above upper KC and Williams %R is above OVB(-20). Short is exactly the other way around
5) CUSTOMIZATION:
-%R-------LENGTH/SMOOTHING/TYPE SMOOTHING MA
-%R-------OVS/MID/OVB -(MID-no use for now)
-KC -------LENGTH/TYPE OF MAIN MA
-KC-------MULTIPLIER,ATR LENGTH
-OTHER--LENGTH/TYPE OF MA - (for signal filters, not used for now)
-OTHER--SOURCE -src of calculations
-OTHER--OVERLAY - plots %R values for debugging etc(ON by default)
6)WARNING - do not use this indicator on its own for trading
7)ENJOY
Composite RSIOne issue with the famouse RSI indicator is that it is too sensitive in some cases and thus, might give false signals if we are eager to use those signals.
If we increase the length of the RSI, it might give too few signals which is not ideal as well.
This Composite RSI indicator was created to utilize the RSI strength, using 3 RSIs (with different length) in combination to give less signal than the original one.
You can use it like a normal RSI indicator:
- Try to find the entry when the RSI is in the overbought (RSI >= 70) and oversold (RSI <= 30) areas
- Use bullish divergence and bearish divergence on the RSI itself to signal your trade
In the example chart, I included a built-in RSI as well so you that you can compare the original one and the Composite RSI indicator.
Some extra features:
- Simple bullish and bearish divergences detection.
- Mark the RSI with green circle(s) when it is extremely overbought (over 80) and oversold (under 20)
Fib top and bottom Hunter - No Repaint "Top and bottom Hunter" indicator combines two popular technical analysis tools, Fibonacci retracement levels and the Relative Strength Index (RSI), to identify potential trading opportunities in the market.
Fibonacci retracement levels are based on the Fibonacci sequence, a mathematical series where each number is the sum of the two preceding ones. In trading, Fibonacci retracement levels are used to identify potential support and resistance levels based on the recent price action. The indicator uses two Fibonacci levels, fib_0 and fib_1, which are typically set to 0.382 and 0.618, respectively. These levels represent common retracement ratios.
To calculate the Fibonacci levels, the indicator considers the highest and lowest prices within a specified range, typically the highest and lowest of the last two bars. It calculates the fib_range, which is the difference between the highest and lowest prices. Then, fib_level_0 and fib_level_1 are determined by subtracting the Fibonacci ratios from the highest price.
The RSI is a momentum oscillator that measures the speed and change of price movements. It helps identify overbought and oversold conditions in the market. The RSI parameters used in this indicator are rsi_length (length of the RSI calculation), rsi_overbought (upper threshold indicating overbought conditions), and rsi_oversold (lower threshold indicating oversold conditions). The RSI value is calculated based on the closing prices.
The indicator generates buy and sell signals based on specific conditions:
Buy Condition: A buy signal is triggered when the RSI crosses above the oversold level (rsi_oversold) and the closing price is higher than fib_level_1. This indicates a potential reversal or bounce from the Fibonacci support level.
Sell Condition: A sell signal is triggered when the RSI crosses below the overbought level (rsi_overbought) and the closing price is lower than fib_level_0. This suggests a potential reversal or pullback from the Fibonacci resistance level.
In summary, this indicator combines the power of Fibonacci retracement levels and the RSI to identify potential trading opportunities. It helps traders find confluence between the Fibonacci support or resistance levels and the RSI readings, indicating potential trend reversals or bounces. Traders can use this information to make informed decisions about entering or exiting positions in the market.
Feel free to change the settings for what works best for you and use this with other confluences. I personally use RSI overbought and oversold values as 80 and 20
TTP OI + LS signal filterThis oscillator helps filtering specific conditions in the market based on open interest (OI) and the ratio of longs and shorts (LS) for crypto assets.
Currently it works with BINANCE:BTCUSDT.P but soon I'll be adding support for more assets.
It flags areas of interest like:
- Too many longs, too many shorts in the market
- Open interest too high or too low
It accepts an external signal as a source in which case filters can be applied to the original signal. For example the external signal might trigger and plot a 1 when RSI break below 70. By connecting such signal with this oscillator you'll be able to only pass-through the ones that occur when any of the areas of interest mentioned above are also valid.
If both filter are applied it acts as an OR. For example, if too many longs and too many shorts are active, it will pass through the signal in either condition.
The results of the original signal filtered is printed to be able to later use it in any external backtester strategy that accepts external sources too.
If external source signal is disabled it will trigger any time the combined filters are returning true.
Open interest and the ratio of longs/shorts is considered too high whenever the stochastic RSI calculation of the OI or ratio LS reaches a level above 80 and too low when below 20
The ratio of long/shorts is calculated by dividing the ratio of longs vs shorts from BITFINEX:BTCUSDLONGS and BITFINEX:BTCUSDSHORTS
RSI, SRSI, MACD and DMI cross - Open source codeHello,
I'm a passionate trader who has spent years studying technical analysis and exploring different trading strategies. Through my research, I've come to realize that certain indicators are essential tools for conducting accurate market analysis and identifying profitable trading opportunities. In particular, I've found that the RSI, SRSI, MACD cross, and Di cross indicators are crucial for my trading success.
Detailed explanation:
The RSI is a momentum indicator that measures the strength of price movements. It is calculated by comparing the average of gains and losses over a certain period of time. In this indicator, the RSI is calculated based on the close price with a length of 14 periods.
The Stochastic RSI is a combination of the Stochastic Oscillator and the RSI. It is used to identify overbought and oversold conditions of the market. In this indicator, the Stochastic RSI is calculated based on the RSI with a length of 14 periods.
The MACD is a trend-following momentum indicator that shows the relationship between two moving averages of prices. It consists of two lines, the MACD line and the signal line, which are used to generate buy and sell signals. In this indicator, the MACD is calculated based on the close price with fast and slow lengths of 12 and 26 periods, respectively, and a signal length of 9 periods.
The DMI is a trend-following indicator that measures the strength of directional movement in the market. It consists of three lines, the Positive Directional Indicator (+DI), the Negative Directional Indicator (-DI), and the Average Directional Index (ADX), which are used to generate buy and sell signals. In this indicator, the DMI is calculated with a length of 14 periods and an ADX smoothing of 14 periods.
The indicator generates buy signals when certain conditions are met for each of these indicators.
1) For the RSI, a buy signal is generated when the RSI is below or equal to 35 and the Stochastic RSI %K is below or equal to 15, or when the RSI is below or equal to 28 the Stochastic RSI %K is below or equal to 15 or when the RSI is below or equal to 25 and the Stochastic RSI %K is below or equal to 10 or when the RSI is below or equal to 28.
2) For the MACD, a buy signal is generated when the MACD line is below 0, there is a change in the histogram from negative to positive, the MACD line and histogram are negative in the previous period, and the current histogram value is greater than 0.
3) For the DMI, a buy signal is generated when the Positive Directional Indicator (+DI) crosses above the Negative Directional Indicator (-DI), and the -DI is less than the +DI.
The indicator generates sell signals when certain conditions are met for each of these indicators:
1) For the RSI, a sell signal is generated when the RSI is above or equal to 75 and the Stochastic RSI %K is above or equal to 85, or when the RSI is above or equal to 80 and the Stochastic RSI %K is above or equal to 85, or when the RSI is above or equal to 85 and the Stochastic RSI %K is above or equal to 90 or when the RSI is above or equal to 82.
2)For the MACD, a sell signal is generated when the MACD line is above 0, there is a change in the histogram from positive to negative, the MACD line and histogram are positive in the previous period, and the current histogram value is less than the previous histogram value. On the other hand, a buy signal is generated when the MACD line is below 0, there is a change in the histogram from negative to positive, the MACD line and histogram are negative in the previous period, and the current histogram value is greater than the previous histogram value.
3)For the DMI a bearish signal is generated when plusDI crosses above minusDI, indicating that bulls are losing strength and bears are taking control.
The indicator uses a combination of these four indicators to generate potential buy and sell signals. The buy signals are generated when RSI and SRSI values are in oversold conditions, while sell signals are generated when RSI and SRSI values are in overbought conditions. The indicator also uses MACD crossovers and DMI crossovers to generate additional buy and sell signals.
When a signal is strong?
The use of multiple signals within a specific timeframe can increase the accuracy and reliability of the signals generated by this indicator. It is recommended to look for at least two signals within a range of 5-8 candles in order to increase the probability of a successful trade.
Why it's original?
1) There is no indicator in the library that combine all of these indicators and give you a 360 view
2)The combination of the RSI, Stochastic RSI, MACD, and DMI indicators in a single script it's unique and not available in the libray.
3)The specific parameters and conditions used to calculate the signals may be unique and not found in other scripts or libraries.
4)The use of plotshape() to plot the signals as shapes on the chart may be unique compared to other scripts that simply plot lines or bars to indicate signals.
5)The use of alertcondition() to trigger alerts based on the signals may be unique compared to other scripts that do not have custom alert functionality.
Keep attention!
It is important to note that no trading indicator or strategy is foolproof, and there is always a risk of losses in trading. While this indicator may provide useful information for making conclusions, it should not be used as the sole basis for making trading decisions. Traders should always use proper risk management techniques and consider multiple factors when making trading decisions.
Support me:)
If you find this new indicator helpful in your trading analysis, I would greatly appreciate your support! Please consider giving it a like, leaving feedback, or sharing it with your trading network. Your engagement will not only help me improve this tool but will also help other traders discover it and benefit from its features. Thank you for your support!
hidden & regular rsi divergenceThis is a divergence indicator that draws regular and hidden divergences based on the Zigzag indicator and RSI indicator. There are two degrees of Zigzag. So, in each Zigzag degree, there are two types of regular divergences and one type of hidden divergence.
👉(The logic is written in case of a bearish regular divergence. The opposite will apply for a bullish one.)
Type 1 of regular divergence (Logic 1):
Zigzag has to form a higher high. The highest RSI within both Zigzag legs must form lower highs, but the RSI values which are exactly at the Zigzag highs should not form lower highs.
Type 2 of regular divergence (Logic 2):
Zigzag has to form a higher high. The highest RSI within both Zigzag legs must form lower highs, and the RSI values which are exactly at the Zigzag highs should form lower highs.
👉(The logic is written in case of a bearish hidden divergence. The opposite will apply for a bullish one.)
Zigzag has to form a lower high. The highest RSI within both Zigzag legs must form higher highs.
👉There is also a filter that will be applied to all the divergences. It only shows the divergences whose corresponding RSI value was above/below a level (overbought level/oversold level).
Logic for regular divergences:
Bearish regular divergence's first high's (leftmost) RSI value should be greater than or equal to 70.
Bullish regular divergence's first low's (leftmost) RSI value should be less than or equal to 30.
Logic for hidden divergences:
Bearish hidden divergence's second high's (rightmost) RSI value should be greater than or equal to 70.
Bullish hidden divergence's second low's (rightmost) RSI value should be less than or equal to 30.
👉There is another feature also. This indicator colors the background based on whether the RSI is in a bullish or bearish range.
If it's within 80-60, the background will be colored green (this means that RSI is in a bullish range).
If it's within 40-20, the background will be colored red (this means that RSI is in a bearish range).
Stochastic Chebyshev Smoothed With Zero Lag SmoothingFast and Smooth Stochastic Oscillator with Zero Lag
Introduction
In this post, we will discuss a custom implementation of a Stochastic Oscillator that not only smooths the signal but also does so without introducing any noticeable lag. This is a remarkable achievement, as it allows for a fast Stochastic Oscillator that is less prone to false signals without being slow and sluggish.
We will go through the code step by step, explaining the various functions and the overall structure of the code.
First, let's start with a brief overview of the Stochastic Oscillator and the problem it addresses.
Background
The Stochastic Oscillator is a momentum indicator used in technical analysis to determine potential overbought or oversold conditions in an asset's price. It compares the closing price of an asset to its price range over a specified period. However, the Stochastic Oscillator is susceptible to false signals due to its sensitivity to price movements. This is where our custom implementation comes in, offering a smoother signal without noticeable lag, thus reducing the number of false signals.
Despite its popularity and widespread use in technical analysis, the Stochastic Oscillator has its share of drawbacks. While it is a price scaler that allows for easier comparisons across different assets and timeframes, it is also known for generating false signals, which can lead to poor trading decisions. In this section, we will delve deeper into the limitations of the Stochastic Oscillator and discuss the challenges associated with smoothing to mitigate its drawbacks.
Limitations of the Stochastic Oscillator
False Signals: The primary issue with the Stochastic Oscillator is its tendency to produce false signals. Since it is a momentum indicator, it reacts to short-term price movements, which can lead to frequent overbought and oversold signals that do not necessarily indicate a trend reversal. This can result in traders entering or exiting positions prematurely, incurring losses or missing out on potential gains.
Sensitivity to Market Noise: The Stochastic Oscillator is highly sensitive to market noise, which can create erratic signals in volatile markets. This sensitivity can make it difficult for traders to discern between genuine trend reversals and temporary fluctuations.
Lack of Predictive Power: Although the Stochastic Oscillator can help identify potential overbought and oversold conditions, it does not provide any information about the future direction or strength of a trend. As a result, it is often used in conjunction with other technical analysis tools to improve its predictive power.
Challenges of Smoothing the Stochastic Oscillator
To address the limitations of the Stochastic Oscillator, many traders attempt to smooth the indicator by applying various techniques. However, these approaches are not without their own set of challenges:
Trade-off between Smoothing and Responsiveness: The process of smoothing the Stochastic Oscillator inherently involves reducing its sensitivity to price movements. While this can help eliminate false signals, it can also result in a less responsive indicator, which may not react quickly enough to genuine trend reversals. This trade-off can make it challenging to find the optimal balance between smoothing and responsiveness.
Increased Complexity: Smoothing techniques often involve the use of additional mathematical functions and algorithms, which can increase the complexity of the indicator. This can make it more difficult for traders to understand and interpret the signals generated by the smoothed Stochastic Oscillator.
Lagging Signals: Some smoothing methods, such as moving averages, can introduce a time lag into the Stochastic Oscillator's signals. This can result in late entry or exit points, potentially reducing the profitability of a trading strategy based on the smoothed indicator.
Overfitting: In an attempt to eliminate false signals, traders may over-optimize their smoothing parameters, resulting in a Stochastic Oscillator that is overfitted to historical data. This can lead to poor performance in real-time trading, as the overfitted indicator may not accurately reflect the dynamics of the current market.
In our custom implementation of the Stochastic Oscillator, we used a combination of Chebyshev Type I Moving Average and zero-lag Gaussian-weighted moving average filters to address the indicator's limitations while preserving its responsiveness. In this section, we will discuss the reasons behind selecting these specific filters and the advantages of using the Chebyshev filter for our purpose.
Filter Selection
Chebyshev Type I Moving Average: The Chebyshev filter was chosen for its ability to provide a smoother signal without sacrificing much responsiveness. This filter is designed to minimize the maximum error between the original and the filtered signal within a specific frequency range, effectively reducing noise while preserving the overall shape of the signal. The Chebyshev Type I Moving Average achieves this by allowing a specified amount of ripple in the passband, resulting in a more aggressive filter roll-off and better noise reduction compared to other filters, such as the Butterworth filter.
Zero-lag Gaussian-weighted Moving Average: To further improve the Stochastic Oscillator's performance without introducing noticeable lag, we used the zero-lag Gaussian-weighted moving average (GWMA) filter. This filter combines the benefits of a Gaussian-weighted moving average, which prioritizes recent data points by assigning them higher weights, with a zero-lag approach that minimizes the time delay in the filtered signal. The result is a smoother signal that is less prone to false signals and is more responsive than traditional moving average filters.
Advantages of the Chebyshev Filter
Effective Noise Reduction: The primary advantage of the Chebyshev filter is its ability to effectively reduce noise in the Stochastic Oscillator signal. By minimizing the maximum error within a specified frequency range, the Chebyshev filter suppresses short-term fluctuations that can lead to false signals while preserving the overall trend.
Customizable Ripple Factor: The Chebyshev Type I Moving Average allows for a customizable ripple factor, enabling traders to fine-tune the filter's aggressiveness in reducing noise. This flexibility allows for better adaptability to different market conditions and trading styles.
Responsiveness: Despite its effective noise reduction, the Chebyshev filter remains relatively responsive compared to other smoothing filters. This responsiveness allows for more accurate detection of genuine trend reversals, making it a suitable choice for our custom Stochastic Oscillator implementation.
Compatibility with Zero-lag Techniques: The Chebyshev filter can be effectively combined with zero-lag techniques, such as the Gaussian-weighted moving average filter used in our custom implementation. This combination results in a Stochastic Oscillator that is both smooth and responsive, with minimal lag.
Code Overview
The code begins with defining custom mathematical functions for hyperbolic sine, cosine, and their inverse functions. These functions will be used later in the code for smoothing purposes.
Next, the gaussian_weight function is defined, which calculates the Gaussian weight for a given 'k' and 'smooth_per'. The zero_lag_gwma function calculates the zero-lag moving average with Gaussian weights. This function is used to create a Gaussian-weighted moving average with minimal lag.
The chebyshevI function is an implementation of the Chebyshev Type I Moving Average, which is used for smoothing the Stochastic Oscillator. This function takes the source value (src), length of the moving average (len), and the ripple factor (ripple) as input parameters.
The main part of the code starts by defining input parameters for K and D smoothing and ripple values. The Stochastic Oscillator is calculated using the ta.stoch function with Chebyshev smoothed inputs for close, high, and low. The result is further smoothed using the zero-lag Gaussian-weighted moving average function (zero_lag_gwma).
Finally, the lag variable is calculated using the Chebyshev Type I Moving Average for the Stochastic Oscillator. The Stochastic Oscillator and the lag variable are plotted on the chart, along with upper and lower bands at 80 and 20 levels, respectively. A fill is added between the upper and lower bands for better visualization.
Conclusion
The custom Stochastic Oscillator presented in this blog post combines the Chebyshev Type I Moving Average and zero-lag Gaussian-weighted moving average filters to provide a smooth and responsive signal without introducing noticeable lag. This innovative implementation results in a fast Stochastic Oscillator that is less prone to false signals, making it a valuable tool for technical analysts and traders alike.
However, it is crucial to recognize that the Stochastic Oscillator, despite being a price scaler, has its limitations, primarily due to its propensity for generating false signals. While smoothing techniques, like the ones used in our custom implementation, can help mitigate these issues, they often introduce new challenges, such as reduced responsiveness, increased complexity, lagging signals, and the risk of overfitting.
The selection of the Chebyshev Type I Moving Average and zero-lag Gaussian-weighted moving average filters was driven by their combined ability to provide a smooth and responsive signal while minimizing false signals. The advantages of the Chebyshev filter, such as effective noise reduction, customizable ripple factor, and responsiveness, make it an excellent fit for addressing the limitations of the Stochastic Oscillator.
When using the Stochastic Oscillator, traders should be aware of these limitations and challenges, and consider incorporating other technical analysis tools and techniques to supplement the indicator's signals. This can help improve the overall accuracy and effectiveness of their trading strategies, reducing the risk of losses due to false signals and other limitations associated with the Stochastic Oscillator.
Feel free to use, modify, or improve upon this custom Stochastic Oscillator code in your trading strategies. We hope this detailed walkthrough of the custom Stochastic Oscillator, its limitations, challenges, and filter selection has provided you with valuable insights and a better understanding of how it works. Happy trading!
Spider VisionSpider Vision is an indicator that I created for trading view, which consists of a spider chart with 7 indicators built into it. This chart provides a visual representation of how these indicators are behaving, allowing traders to quickly assess the current market conditions.
The chart displays the following indicators:
RSI (Relative Strength Index): This is a momentum indicator that measures the strength of a security's price action. When the RSI is above 70, it is considered overbought, and when it is below 30, it is considered oversold.
Stochastic: This is another momentum indicator that compares the closing price of a security to its price range over a given time period. When the stochastic is above 80, it is considered overbought, and when it is below 20, it is considered oversold.
Momentum: This is a simple indicator that measures the change in a security's price over a given time period. When the momentum is positive, it indicates that the price is increasing, and when it is negative, it indicates that the price is decreasing.
BBW (Bollinger Bands Width): This indicator measures the width of the Bollinger Bands, which are a popular technical analysis tool used to identify potential trends and reversals. When the BBW is high, it suggests that the market is volatile, and when it is low, it suggests that the market is quiet.
DTO (Detrended Price Oscillator): This indicator measures the difference between the price of a security and its moving average. When the DTO is positive, it indicates that the price is above its moving average, and when it is negative, it indicates that the price is below its moving average.
Chop Zone: This indicator measures the choppiness of the market by comparing the average true range (ATR) to the difference between the high and low prices over a given time period. When the chop zone is high, it suggests that the market is choppy, and when it is low, it suggests that the market is trending.
Chaikin Oscillator: This is an oscillator that measures the accumulation/distribution of a security. When the Chaikin Oscillator is positive, it indicates that there is buying pressure in the market, and when it is negative, it indicates that there is selling pressure.
To use this indicator, traders can simply add it to their TradingView chart and adjust the input parameters to suit their trading style. The scale parameter can be used to adjust the size of the spider chart, while the color parameters can be used to customize the appearance of the chart. Traders can also adjust the length of each indicator to suit their preference.
Overall, the Spider Vision indicator provides a convenient way for traders to quickly assess the current market conditions and make more informed trading decisions.
SPY 4 Hour Swing TraderThe purpose of this script is to spot 4 hour pivots that indicate ~30 trading day swings. As VIX starts to drop options trading will get more boring and as we get back on the bull and can benefit from swing trading strategy. Swing trading doesn't make a whole lot of sense when VIX is above 28. Seems to get best results on 4 hour chart for this one. This indicator spots a go long opportunity when the 5 ema crosses the 13 ema on the 4 hour along with the RSI > 50 and the ADX > 20 and Stoichastic values (smoothed line < 80 or line < 90) and close > last candle close and the True Range < 6. It also spots uses a couple different means to determine when to exit the trade. Sell condition is primarily when the 13 ema crosses the 5 ema and the MACD line crosses below the signal line and the smoothed Stoichastic appears oversold (greater than 60) and slop of RSI < -.2. Stop Losses and Take Profits are configurable in Inputs along with ability to include short trades plus other MACD and Stoichastic settings. If a stop loss is encountered the trade will close. Also once twice the expected move is encountered partial profits will taken and stop losses and take profits will be re-established based on most recent close. Also a VIX above 28 will trigger any open positions to close. If trying to use this for something other than SPXL it is best to update stop losses and take profit percentages and check backtest results to ensure proper levels have been selected and the script gives satisfactory results.
