Automatic comparison of symbols depending on custom listIn the indicator settings, specify a list of tickers and the corresponding symbol for comparison. Each new list must be on a separate line. The line must begin with the symbol for comparison, then an equal sign, and then a list of tickers separated by commas. If the ticker selected in the chart window is not found in any of the lists, then the symbol from the first list will be used as the symbol for comparison. For example:
TVC:DXY = OANDA:XAUUSD, OANDA:XAGUSD
OANDA:BCOUSD = OANDA:SPX500USD
OANDA:SPX500USD = BINANCE:BTCUSDT
***
Автоматическое сравнение символов в зависимости от настраиваемого списка
В настройках индикатора укажите список тикеров и соответствующий символ для сравнения. Каждый новый список должен быть на отдельной строке. В начале строки должен быть указан символ для сравнения, затем знак равенства и после него список тикеров, разделенных запятыми. Если выбранный в окне графика тикер не будет найден ни в одном из списков, то в качестве символа для сравнения ему будет соответствовать символ из первого списка. Например:
TVC:DXY = OANDA:XAUUSD, OANDA:XAGUSD
OANDA:BCOUSD = OANDA:SPX500USD
OANDA:SPX500USD = BINANCE:BTCUSDT
Comparison
Ticker Performance ComparisonTicker Performance Comparison Indicator
With this tool you can compare how three different tickers of your choice have performed over a specific period you choose. It can be used on any timeframe.
As you can see in the image above, I am comparing Nvidia, Bitcoin and Wadzpay over a 365 day period. This shows me at glance which asset has done better and by how much.
It shows how the closing prices have changed from the start of your chosen period to now, by automatically drawing lines on the same scale.
Key Features:
Lookback Period: You decide how many bars (days, weeks, etc.) back to look from today.
Three Tickers: Enter up to three different ticker symbols to see how they stack up against each other
Percentage Change: The tool calculates how much each ticker's closing price has changed, in percentage terms, from the start of your lookback period.
Performance Labels: Labels at the end of the period show the percentage change for each ticker.
Important:
Ignore the lines that are drawn before your lookback period: The lines before your chosen lookback period might be misleading. They appear due to the way historical data is processed and should be ignored. Only consider the data and trends from the start of the lookback period you entered to the present for an accurate comparison.
Use this tool to easily compare how different assets have performed over the timeframe that matters to you.
Relative Strength Universal
Relative strength is a ratio between two assets, generally it is a stock and a market average (index). RS implementation details are explained here .
This script automatically decides benchmark index for RS calculation based on market cap input values and input benchmark indices values.
Relative strength calculation:
"To calculate the relative strength of a particular stock, divide the percentage change over some time period by the percentage change of a particular index over the same time period". This indicator value oscillates around zero. If the value is greater than zero, the investment has been relatively strong during the selected period; if the value is less than zero, the investment has been relatively weak.
In this script, You can input market cap values and all are editable fields. If company market cap value is grater than 75000(Default value) then stock value will be compared with Nifty index. If company market cap is between 75000 and 25000 then stock value will be compared with midcap 150 to calculate RS. If marketcap is greater than 5000 and less than 25000 then RS will be calculated based on smallcap250. If marketcap is less than 5000 and greater than 500 then it will be compared with NIFTY_MICROCAP250
Symbol CorrelationThe "Symbol Correlation" indicator calculates and displays the correlation between the chosen symbol's price and another selected source over a specified period. It also includes a moving average (SMA) of this correlation to provide a smoothed view of the relationship.
Why SMA and Table Display ?
The inclusion of SMA (Simple Moving Average) with adjustable length (SMA Length) enhances the indicator's utility by smoothing out short-term fluctuations in correlation, allowing for clearer trend identification. The SMA helps to visualize the underlying trend in correlation, making it easier to spot changes and patterns over time.
The table display of the correlation SMA value offers a concise summary of this trend. By showcasing the current correlation SMA alongside its historical values, traders can quickly gauge the relationship's strength relative to previous periods.
Interpreting the Indicator:
1. Correlation Values: The primary plot shows the raw correlation values between the symbol's price and the specified source. A value of 1 indicates a perfect positive correlation, -1 signifies a perfect negative correlation, and 0 suggests no linear relationship.
2. Correlation SMA: The SMA line represents the average correlation over a defined period (SMA Length). Rising SMA values indicate strengthening correlation trends, while declining values suggest weakening correlations.
3. Choosing SMA Length: Traders can adjust the SMA Length parameter to tailor the moving average to their specific analysis horizon. Shorter SMA lengths react quickly to price changes but may be more volatile, while longer SMA lengths smooth out noise but respond slower to recent changes.
In summary, the "Symbol Correlation" indicator is a valuable tool for assessing the evolving relationship between a symbol's price and an external source. Its use of SMA and tabular presentation facilitates a nuanced understanding of correlation trends, aiding traders in making informed decisions based on market dynamics.
PPN - Token compare to USDT/BTCThis simple indicator allows you to easily view the price of a selected cryptocurrency token in either USDT or BTC on TradingView charts. By adding this indicator to your chart, you can quickly compare the price of the token to either USDT (Tether) or BTC (Bitcoin).
**Features:**
- Choose between displaying the token price in USDT or BTC.
- Automatically detects the current trading pair and adjusts the display accordingly.
- Uses data from the BINANCE exchange to fetch real-time prices.
**How to Use:**
1. Add the indicator to your TradingView chart.
2. Select the desired ticker ending (USDT or BTC) in the indicator settings.
3. Pin the indicator to a new scale (More -> Pin to Scale -> New scale or no scale (fullscreen).
**Note:** This indicator is intended for informational purposes only and should not be used as the sole basis for making trading decisions. Always conduct your own research and consult with a financial advisor before making any investment decisions.
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Feel free to use and modify! <3
Message me on TradingView if you have any suggestions!
Time Based Comparison Tool [TFO]The goal of this indicator is to show how multiple assets are trading relative to their Previous Highs and Lows. Many traders have probably seen charts resembling this that may plot how asset prices are trading as a percent change over time, or something similar.
The key difference with this indicator is that all prices are normalized to reflect how they are trading with respect to the previous range of a user-defined timeframe. Without the normalization process, we would simply be observing some percent change from a given point in time; but this does not provide enough information to describe where price is trading relative to our desired frame of reference.
For example, if the timeframe setting was chosen to be 1 day, the indicator would plot the Previous High (PH) and Previous Low (PL) of the current symbol on the daily timeframe, denoted here by the black lines and labels. Then, the adjusted price of all selected symbols would be shown to visualize how each one is moving with respect its own PH and PL, using the current symbol's PH and PL as reference points.
In the above chart, we can see that CL was trading below its PDL from about 10:00-11:00 am EST, then broke above and retested it at around 11:20 am EST, before trading higher. To verify that this comparison works as intended, we can check to see that CL did in fact retest its PDL at this time before trading higher. Note that we are using the close price for this evaluation.
Since limiting the output to close prices can leave out some vital information, we can change the Plot Type setting from "Close" to "High to Low," which will instead show the range of prices from high to low instead of just the close.
We can expand on this by detecting when PH's and PL's have been raided (traded through), by displaying the text PHR (Previous High Raid) or PLR (Previous Low Raid) next to the symbol's label on the right. In this case below, where we're using the 1 week timeframe, we can observe that NQ1! (purple) traded through the PL level and thus its label (right) is updated to indicate a PLR.
Similarly, YM1! traded through its PH level and was updated to indicate a PHR; and ES1! raided both levels, with its label reflecting just that.
Due to the native limitation of output series in a single pine script, alerts have been consolidated to "Any PHR" or "Any PLR," meaning these alerts would fire if any of the selected symbols raided a PH or PL, respectively. If one wanted to be alerted for just a specific symbol, this could be achieved by deselecting all symbols except that which is desired, then setting an alert and adjusting its title for easier user recognition.
Divergence AnalyzerUnlock the potential of your trading strategy with the Divergence Analyzer, a sophisticated indicator designed to identify divergence patterns between two financial instruments. Whether you're a seasoned trader or just starting, this tool provides valuable insights into market trends and potential trading opportunities.
Key Features:
1. Versatility in Symbol Selection:
- Choose from a wide range of symbols for comparison, including popular indices like XAUUSD and SPX.
- Seamlessly toggle between symbols to analyze divergences and make informed trading decisions.
2. Flexible Calculation Options:
- Customizable options allow you to use a different symbol for calculation instead of the chart symbol.
- Fine-tune your analysis by selecting specific symbols for comparison based on your trading preferences.
3. Logarithmic Scale Analysis:
- Utilizes logarithmic scales for accurate representation of price movements.
- Linear regression coefficients are calculated on the logarithmic scale, providing a comprehensive view of trend strength.
4. Dynamic Length and Smoothing:
- Adjust the length parameter to adapt the indicator to different market conditions.
- Smoothed linear regression with exponential moving averages enhances clarity and reduces noise.
5. Standard Deviation Normalization:
- Normalizes standard deviations over 200 periods, offering a standardized view of price volatility.
- Easily compare volatility levels across different symbols for effective divergence analysis.
6. Color-Coded Divergence Visualization:
- Clearly distinguish positive and negative divergences with customizable color options.
- Visualize divergence deltas with an intuitive color scheme for quick and effective interpretation.
7. Symbol Information Table:
- An included table provides at-a-glance information about the selected symbols.
- Identify Symbol 1 and Symbol 2, along with their corresponding positive and negative divergence colors.
How to Use:
1. Select symbols for analysis using the user-friendly inputs.
2. Customize calculation options based on your preferences.
3. Analyze the divergence delta plot for clear visual indications.
4. Refer to the symbol information table for a quick overview of selected instruments.
Empower your trading strategy with the Divergence Analyzer and gain a competitive edge in the dynamic world of financial markets. Start making more informed decisions today!
Sector relative strength and correlation by KaschkoThis script provides a quick overview of the relative strength and correlation of the symbols in a sector by showing a line chart of the close prices on a percent scale with all symbols starting at zero at the left side of the chart. It allows a great deal of flexibility in the configuration of the sectors and symbols in it. The standard preset sectors cover the most important futures markets and their symbols.
However, up to ten sectors with up to ten symbols each can be freely configured. Each sector is defined by a single line that has the following format:
Sector name:Symbol suffix:List of comma separated symbols
For example, the first predefined sector is defined as follows.
Energies:1!:CL,HO,NG,RB
1. The name of the sector is "Energies"
2. The suffix is "1!", i.e., to each symbol in the list "1!" is appended to get the continous future for the given symbol root. When using stock, forex or other symbols, simply leave the suffix empty.
3. The list of comma separated symbols is "CL,HO,NG,RB", i.e. crude oil, heating oil, natural gas and gasoline. As the suffix is "1!", the actual symbols whose prices are shown are "CL1!","HO1!","NG1!" and "RB1!"
You can choose to use settlement-as-close and back-adjusted contracts. The sector can also be determined automatically ("Auto-select"). In this case, it is determined to which sector the symbol currently displayed in the main chart belongs and the script displays it in the context of the other symbols in the sector.
By selecting a suitable chart time frame and time range, you can quickly determine which symbols in the sector are stronger or weaker and which are more or less strongly correlated.
The following symbols are best suited for a quick trial, as the sectors are preset for these:
CL1!,ES1!,6A1!,6B1!,6c1!,6E1!,6J1!,6M1!,6N1!,6S1!,GC1!,GF1!,HE1!,HG1!,HO1!,LBR1!,LE1!,NG1!,NQ1!,PA1!,PL1!,RB1!,SI1!,YM1!,ZB1!,ZC1!,ZF1!,ZL1!,ZM1!,ZN1!,ZO1!,ZR1!,ZS1!,ZT1!,ZW1!,CC1!,CT1!,DX1!,KC1!,OJ1!,SB1!,RTY1!
You can also use the script to compare any symbols (e.g. different shares) with each other. Preferably use the "Custom" sector for this.
Easy To Trade indicatorAbstract
This script evaluates how easy for traders to trade.
This script computes the level that the gains were distributed in many trading days.
We can use this indicator to decide the instruments and the time we trade.
Introduction
Why we think the trading markets are boring?
It is because most of the gains were concentrated in a few trading days.
We look for instruments we can buy at support and sell at resistance frequently and repeatedly.
However, it does not happen usually because it is difficult to find sellers sell at support and buyers buy at resistance.
This script is a method to measure if an instrument is difficult to trade.
If most of the gains were concentrated in a few trading days, this script says it is difficult to trade.
If gains were distributed in many trading days and we can buy low and sell high repeatedly, this script says it is easy to trade.
Therefore, this script measure how difficult for us to trade by the ratio between the area of value and the total gain.
How it works
1. Determine the instruments and time frames we are interested in.
2. Determine how many days this script evaluate the result. This number may depend on how many days from you buy in to you sell out.
3. If the instrument you choose is easy to trade, this script reports higher values.
4. If the instrument is long term bullish, the number "easy to invest" is usually higher than the number "easy to short" .
5. We can consider trade instruments which are easier to trade than others.
6. We can consider wait until the period that it is difficult to trade has past or keep believing that some instruments are easier to trade than others.
Parameters
x_src = The price for each trading day this script use. It may be open , high , low , close or their combination.
x_is_exp = Whether this script evaluate the price movement in exponential or logarithm. You are advised to answer yes if the price changes drastically.
x_period = How many days this script evaluate the result.
Conclusion
With this indicator , we have data to explain how easy or difficult an instrument is for traders . In other words , if we hear some people say the trading markets are boring or difficult for traders , we can use this indicator to verify how accurate their comments are.
With this explainable analysis , we have more knowledge about which instruments and which sessions are relative easy for us to buy low and sell high repeatedly and frequently , we can have better proceeding than buy and hold simply.
Relative Daily Change% by SUMIT
"Relative Daily Change%" Indicator (RDC)
The "Relative Daily Change%" indicator compares a stock's average daily price change percentage over the last 200 days with a chosen index.
It plots a colored curve. If the stock's change% is higher than the index, the curve is green, indicating it's doing better. Red means the stock is under-performing.
This indicator is designed to compare the performance of a stock with specific index (as selected) for last 200 candles.
I use this during a breakout to see whether the stock is performing well with comparison to it`s index. As I marked in the chart there was a range zone (red box), we got a breakout with good volume and it is also sustaining above 50 and 200 EMA, the RDC color is also in green so as per my indicator it is performing well. This is how I do fine-tuning of my analysis for a breakout strategy.
You can select Index from the list available in input
**Line Color Green = Avg Change% per day of the stock is more than the Selected Index
**Line Color White = Avg Change% per day of the stock is less than the Selected Index
If you want details of stocks for all index you can ask for it.
Disclaimer : **This is for educational purpose only. It is not any kind of trade recommendation/tips.
Strength Comparison @joshuuuexample:
if you want to find the stronger/weaker pair between eurusd and gbpusd, what you can do is check the eurgbp charts. if eurgbp is bullish, that means, that longs longs on eurusd are better than on gbpusd.
Unfortunately, there is no such thing to compare for example usoil with ukoil, or us100 with us500.
That's where this indicator comes in handy. You can choose whatever two symbols you want, that are supported by tradingview and you will get a chart, which shows symbol1/symbol2.
Now you can use normal market structure, or the ema option, to find out the stronger symbol.
This can also help predicting the so called SMT Divergences, taught by ICT.
⚠️ Open Source ⚠️
Coders and TV users are authorized to copy this code base, but a paid distribution is prohibited. A mention to the original author is expected, and appreciated.
⚠️ Terms and Conditions ⚠️
This financial tool is for educational purposes only and not financial advice. Users assume responsibility for decisions made based on the tool's information. Past performance doesn't guarantee future results. By using this tool, users agree to these terms.
Smoothing R-Squared ComparisonIntroduction
Heyo guys, here I made a comparison between my favorised smoothing algorithms.
I chose the R-Squared value as rating factor to accomplish the comparison.
The indicator is non-repainting.
Description
In technical analysis, traders often use moving averages to smooth out the noise in price data and identify trends. While moving averages are a useful tool, they can also obscure important information about the underlying relationship between the price and the smoothed price.
One way to evaluate this relationship is by calculating the R-squared value, which represents the proportion of the variance in the price that can be explained by the smoothed price in a linear regression model.
This PineScript code implements a smoothing R-squared comparison indicator.
It provides a comparison of different smoothing techniques such as Kalman filter, T3, JMA, EMA, SMA, Super Smoother and some special combinations of them.
The Kalman filter is a mathematical algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more accurate than those based on a single measurement.
The input parameters for the Kalman filter include the process noise covariance and the measurement noise covariance, which help to adjust the sensitivity of the filter to changes in the input data.
The T3 smoothing technique is a popular method used in technical analysis to remove noise from a signal.
The input parameters for the T3 smoothing method include the length of the window used for smoothing, the type of smoothing used (Normal or New), and the smoothing factor used to adjust the sensitivity to changes in the input data.
The JMA smoothing technique is another popular method used in technical analysis to remove noise from a signal.
The input parameters for the JMA smoothing method include the length of the window used for smoothing, the phase used to shift the input data before applying the smoothing algorithm, and the power used to adjust the sensitivity of the JMA to changes in the input data.
The EMA and SMA techniques are also popular methods used in technical analysis to remove noise from a signal.
The input parameters for the EMA and SMA techniques include the length of the window used for smoothing.
The indicator displays a comparison of the R-squared values for each smoothing technique, which provides an indication of how well the technique is fitting the data.
Higher R-squared values indicate a better fit. By adjusting the input parameters for each smoothing technique, the user can compare the effectiveness of different techniques in removing noise from the input data.
Usage
You can use it to find the best fitting smoothing method for the timeframe you usually use.
Just apply it on your preferred timeframe and look for the highlighted table cell.
Conclusion
It seems like the T3 works best on timeframes under 4H.
There's where I am active, so I will use this one more in the future.
Thank you for checking this out. Enjoy your day and leave me a like or comment. 🧙♂️
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Credits to:
▪@loxx – T3
▪@balipour – Super Smoother
▪ChatGPT – Wrote 80 % of this article and helped with the research
Quad RSRelative Strength (RS) is an Indicator which measures a Stock's performance as compared to a Benchmark Index or another Stock.
For example: RS will tell you whether “A” is increasing more or less than “B” in any market condition. It is one of the tools which is best suited for Momentum Investing.
How RS can be used as a Momentum Indicator:
RS is used in identifying both the strongest and the weakest stock, or any asset class, within the market. Usually, the stocks which display strong or weak RS over a given time period tend to continue to move in the same direction.
How to calculate Relative Strength:
Divide change of "A" over some time period by the change of a particular index/stock "B" over the same time period.
This indicator oscillates around zero. If the value is greater than zero, "A" has been relatively strong compared to "B", during the selected period; if the value is less than zero, "A" has been relatively weak.
Configuration & Default settings:
The Relative symbol can be Input, default is Nifty50.
Time frame can be set, I recommend setting to Day. Default time frame is set to same as chart.
Four different periods can be set. Default values are 500, 250, 125 & 63. If time frame is set as 'Day', these numbers correspond to 2 years, 1 year, 1/2 year & 1 quarter.
Example chart: NiftyMidCap100 with Quad RS indicator with Nifty50 used as Relative Symbol, Four periods: 500, 250, 125 & 63
MarketronShows you how the asset on the chart is trending versus the market. You can customise the market that it uses, and there are some common markets programmed in as options.
Displays moving averages and a simple red/green bias.
You could do this yourself by typing, e.g., ADAUSDT/TOTAL into the asset box in TradingView and adding some EMAs manually and then interpreting them by eye. There's no hidden technology in this indicator. It just makes it a lot easier.
You can choose various bias options.
I'm not sure if it will work at resolutions lower than one day, depending on the level of your TradingView plan.
These are all the user-configurable settings and what they do.
Market (Auto) – Choose from various preselected markets.
Market Ticker Manual Override – You can type in the ticker for your market if it's not in the list. If you do, it overrides the Auto list.
Show Classic EMAs – Show customisable Exponential Moving Averages.
Bias Mode – Derive the red/green bias from whether price is above/below the Classic EMAs, or from a custom EMA function, or both.
Show Bias Background – Colour the background, or not, with the directional bias.
EMA 1 Length (smallest) – The length for the smallest EMA.
EMA 2 Length – Length for the second EMA.
EMA 3 Length – Length for the third EMA.
Ticker vs IndexI was exploring a simple idea how I can visualize the ticker performance against the underlying Index (or any other ticker) performance.
how it works:
When the line is moving up (blue zone), the ticker is performing better than the underlying index (e.g. SPX)(configurable).
When the line is moving down (red zone), the ticker is performing worse than the underlying index.
How to use it:
Use as confirmation always in conjunction with other (main) indicators, avoid "buy" when indicator is in the red zone
Also, crossing over the zero line is often an indication for an upcoming upward move
Try to different SMA length - default is 20 but 10 was often showing better results
(No financial advise, for testing purposes only)
FunctionDynamicTimeWarpingLibrary "FunctionDynamicTimeWarping"
"In time series analysis, dynamic time warping (DTW) is an algorithm for
measuring similarity between two temporal sequences, which may vary in
speed. For instance, similarities in walking could be detected using DTW,
even if one person was walking faster than the other, or if there were
accelerations and decelerations during the course of an observation.
DTW has been applied to temporal sequences of video, audio, and graphics
data — indeed, any data that can be turned into a linear sequence can be
analyzed with DTW. A well-known application has been automatic speech
recognition, to cope with different speaking speeds. Other applications
include speaker recognition and online signature recognition.
It can also be used in partial shape matching applications."
"Dynamic time warping is used in finance and econometrics to assess the
quality of the prediction versus real-world data."
~~ wikipedia
reference:
en.wikipedia.org
towardsdatascience.com
github.com
cost_matrix(a, b, w)
Dynamic Time Warping procedure.
Parameters:
a : array, data series.
b : array, data series.
w : int , minimum window size.
Returns: matrix optimum match matrix.
traceback(M)
perform a backtrace on the cost matrix and retrieve optimal paths and cost between arrays.
Parameters:
M : matrix, cost matrix.
Returns: tuple:
array aligned 1st array of indices.
array aligned 2nd array of indices.
float final cost.
reference:
github.com
report(a, b, w)
report ordered arrays, cost and cost matrix.
Parameters:
a : array, data series.
b : array, data series.
w : int , minimum window size.
Returns: string report.
Return & Drawdown
ReDraw script calculates the historical returns and drawdown for the given periods.
By default, the return of the linear regression trends is displayed (can be turned off in settings). In this mode, two linear regression trends are being computed for both long and short periods, and the percent value indicates the "return of the trend" for the corresponding period. Observing the dynamic of the linear regression trends can give a great hint if the trend is slowing down.
When the smoothing method is set to "none" or WMA3/5, the real asset return is shown for both periods, using the formula (LastPrice-FirstPrice)/FirstPrice
The script calculates the maximum drawdown for the long period using the formula (max(Price) - LastPrice) / max(Price).
The white line under the zero is the average maximum drawdown over the long period.
When the mode is set to Compare, ReDraw will display the difference in metrics between the current and selected symbol (SPY by default).
EsIstTurnt's Relative Value Comparison Multi SymbolCompare the relative valuation of up to 8 tickers. By taking a shorter term moving average and dividing by a longer term moving average(optionally with an offset) we get a value that is either above or below 1. Easy to tell what is undervalued and overvalued with this setup. Useful for comparing different asset classes or sector specific securities looking for outperformers/underperformers. Overvalued and Undervalued levels marked by Red and Green background. Recommended in conjunction with other indicators of your choosing for confirmation of trend changes but this is good for getting a broader view of the market you're interested in. Multiple timeframes, sources available however you should tinker with it to find what gives you the best view for your preferred timeframe.
Relative StrengthRelative strength is a calculation of the price trend of a stock or a financial instrument in comparison to another instrument, stock, or industry. It shall be determined by taking the price of one commodity and dividing it by another.
Relative strength is a strategy used for determining value stocks and is used in momentum investing as well. It involves investing in stocks that have done well, in relation to their index or benchmark. For example, a relative strength investor might pick technology companies that have outperformed the Nasdaq Composite Index or large-cap stocks that are lagging against the S&P 500 index(Adjustable in the settings).
This indiator will give you a plot for relative strength between the current pair with another pair (adjustable in the settings), with a plotshape for RSNHBP & RSNH
Features :
1. Relative Strength
2. Double EMA of Relative Strength
3. RSNHBP & RSNH
How to use it :
1. Adjust All the settings parameter
2. For Alerting, Just use any alert function call, it will give you an alert of RSNHBP and RSNH
Stock Rotation Model [CC]This is an original indicator so a true hidden gem in my opinion. I based this idea off of the work by Giorgos Siligardos (Stocks and Commodities Aug 2012) with his indicator called the Sector Rotation Model. This indicator is best used as a trend confirmation in combination with another indicator such as a leading indicator. This will show you how strong the current stock you are looking at is compared to the S&P 500 which almost everyone uses as a relative strength comparison. Feel free to change the default lengths if you would like as these were just the settings that I liked the best overall. Let me know if you find any good combos that works for most stocks in general. I have included strong buy and sell signals in addition to normal ones so strong signals are darker in color and normal signals are lighter in color. Buy when the line turns green and sell when it turns red.
Let me know if there are any other indicators or scripts you would like to see me publish!
Swing ComparatorHere I bring you an array of methods to compare the swings and consistency between assets.
This indicator is excellent for swing traders and scalpers looking to maximize their profits by examining which of two closely related pairs provides greater price fluctuation during given period.
This indicator works against two assets, which are to be configured in settings.
This indicator has 5 particular plots for you to examine, each which can be considered for you to contemplate which pair for you to next perform a trade on.
First off, let's start with the blue.
The blue is simply a pearson correlation coefficient, thankfully now included in tradingview. This provides a value of 1 as values show to be close correlation, 0 showing no correlation, and -1 showing negative correlation - meaning an increase in one pair correlates to a decrease in another pair. This will turn green when greater than 0.975, showing a very strong relationship between the two pairs, and red when below -0.975. This is the only plot to be interpreted on a scale from -1 to +1.
Next, we have the purple and yellow background plots, followed by the white and green moving averages. Though similar, these are all slightly different.
For each of these 4 plots, a value greater than 0 indicates greater price swings for your Symbol #1, while a value less than 0 indicates greater price swings for Symbol #2.
These calculations are performed on a per bar basis, meaning you're likely going to be examining bars longer than what you'll normally be trading on. Use confluence, as well as your own judgement for this.
For example, if symbol #1 provides a bar with an open value 1% greater or less than close, providing a 1% swing on a given bar, but symbol #2 provides 2%, the indicator will fall down toward the negative, as Symbol #2 had the greater swing.
First, yellow focuses on only open/close bar values, and thus the body of the candlestick.
Purple, on the other hand, focuses on the wicks of the candle - thus, the high/low values. I've opted to make these two different values as a wick focuses on the embodiment within the time period, and body focuses on the open/close instant.
Next, the green is an extended EMA of the purple - High/Low ratio. This is important to examine trend overtime, and reduce unneeded noise.
Lastly, the white is simply difference in the standard deviation of the particular bars, between the two symbols you have selected. The tends to usually tie up with the green pretty well.
Considering this is going to by nature be very noisy datasets, I have included in settings the option to extend an EMA for everything. They have their default settings, but if you'd like to examine the trend without an EMA, feel free to set it to 1 to eliminate its effects.
I have additionally added the ability to introduce clipping, as well as scale the correlation coefficient to remain visible when examining very short term time scales. In the future, I hope to properly normalize all plots to remain within a -1 to +1 basis. Please be patient as I have multiple projects ongoing.
Suggestions and constructive criticism are very well encouraged.
Anyone is welcome to utilize this in their code, as well, i just ask you provide credit.
As you reduce to time frames less than a day, you will likely have to reduce the coefficient min/max closer to 0.025, or just hide it entirely.
TODO:
Make it look better. Sorry, folks.
Introduce latency between pairs.
Examine significance of a coefficient of determination
Remove static weights and introduce z-score and linear normalization.
Consider adding room for a 3rd pair. This could get ugly, however.
ROC vs BTCThis is a modification of my Rate of Change Percentile script, used to compare the current ticker (e.g. Altcoins) to BTC.
Essentially we are looking at (Current Ticker ROC percentile) vs (Bitcoin ROC percentile).
In other words, we are using the ROC value of both the current ticker and BTC, and ranking each based on their previous ROC.
We compare the rankings to gauge the relative overperformance or underperformance of the current ticker vs BTC.
The blue line is BTC, the columns are the current ticker.
Green columns above the blue line indicate positive ROC and current ticker has higher ROC ranking than BTC.
Red columns below the blue line indicate negative ROC and current ticker has a higher ROC ranking than BTC.
*** PLEASE LEAVE A LIKE AND FOLLOW IF YOU ENJOY THE SCRIPT ***
Any questions, comments or feedback I'd love to hear from you below!
DivergenceLibrary "Divergence"
Calculates a divergence between 2 series
bullish(_src, _low, depth) Calculates bullish divergence
Parameters:
_src : Main series
_low : Comparison series (`low` is used if no argument is supplied)
depth : Fractal Depth (`2` is used if no argument is supplied)
Returns: 2 boolean values for regular and hidden divergence
bearish(_src, _high, depth) Calculates bearish divergence
Parameters:
_src : Main series
_high : Comparison series (`high` is used if no argument is supplied)
depth : Fractal Depth (`2` is used if no argument is supplied)
Returns: 2 boolean values for regular and hidden divergence
I created this library to plug and play divergences in any code.
You can create a divergence indicator from any series you like.
Fractals are used to pinpoint the edge of the series. The higher the depth, the slower the divergence updates get.
My Plain Stochastic Divergence uses the same calculation. Watch it in action.