Cabal Dev IndicatorThis is a TradingView Pine Script (version 6) that creates a technical analysis indicator called the "Cabal Dev Indicator." Here's what it does:
1. Core Functionality:
- It calculates a modified version of the Stochastic Momentum Index (SMI), which is a momentum indicator that shows where the current close is relative to the high/low range over a period
- The indicator combines elements of stochastic oscillator calculations with exponential moving averages (EMA)
2. Key Components:
- Uses configurable input parameters for:
- Percent K Length (default 15)
- Percent D Length (default 3)
- EMA Signal Length (default 15)
- Smoothing Period (default 5)
- Overbought level (default 40)
- Oversold level (default -40)
3. Calculation Method:
- Calculates the highest high and lowest low over the specified period
- Finds the difference between current close and the midpoint of the high-low range
- Applies EMA smoothing to both the range and relative differences
- Generates an SMI value and further smooths it using a simple moving average (SMA)
- Creates an EMA signal line based on the smoothed SMI
4. Visual Output:
- Plots the smoothed SMI line in green
- Plots an EMA signal line in red
- Shows overbought and oversold levels as gray horizontal lines
- Fills the areas above the overbought level with light red
- Fills the areas below the oversold level with light green
This indicator appears designed to help traders identify potential overbought and oversold conditions in the market, as well as momentum shifts, which could be used for trading decisions.
Would you like me to explain any specific part of the indicator in more detail?
Solana
Lockin Strength Indicator (LSI)How It Works:
RSI Calculation: The standard RSI is calculated using a 14-period by default.
Volume Weighting: If enabled, the LSI modifies the RSI by weighting it based on the volume relative to its moving average. This emphasizes periods of high or low volume, which can be particularly useful for Solana-based assets that might have unique volume profiles.
Plotting: The LSI is plotted with standard overbought and oversold levels, and background highlighting makes these areas visually distinct.
Customization:
RSI Length: You can adjust the length of the RSI period.
Overbought/Oversold Levels: You can modify the levels for overbought and oversold signals.
Volume Weighting: You can toggle volume weighting on or off.
This indicator is designed to give you a more nuanced view of Solana cryptocurrencies by combining RSI with volume dynamics.
Grayscale GSOL Solana Financials [NeoButane]This script shows Grayscale's GSOL financials based on the information from their website. Investors and traders like to use financials when making the decision to buy, sell, or hold.
►Usage
This script is specific to GSOL. Investors and traders use financials when making the decision to buy, sell, or hold. How one interprets financials is up to the individual. For example, investors who believe a Solana ETF is coming soon can view the "% Discount / Premium to NAV", which is currently over 600%, and decide not to buy because the premium would collapse if an ETF began trading.
►Configuration
Data select the data you'd like to display.
Show Highest label show the highest value of the entire data set.
Line Color an expression of self.
Extrapolate Data Using Average or Last Known Value Shows a line beyond the dataset, using the average of all past data or the last data point to predict newer data. % Discount / Premium to NAV, Share Premium, and SOL Per Share are supported.
→Data retrieved from Grayscale
AUM assets under management.
NAV net asset value.
Market Price market price of GSOL.
Shares Outstanding number of shares held in the open market.
→Data retrieved from Grayscale, modified by me
% Discount / Premium to NAV the % away NAV is from the market price of GSOL.
Formula: (GSOL - NAV) / NAV
Share Premium the actual $ premium of GSOL to its NAV.
Formula: GSOL - NAV
SOL Per Share the amount of SOL 1 share of GSOL can redeem. This is derived using Kraken's SOLUSD daily close prices.
Formula: Kraken's SOLUSD / NAV
SOL Price Using Market Price Premium the price of SOL if GSOL's market price was "correct" and the SOL Per Share ratio remained the same.
Formula: GSOL / SOL Per Share
►How this works
Grayscale has a spreadsheet of historical data available on their GSOL page. Since financials are not available for OTC:GSOL, I placed all the data into arrays to emulate a symbol's price (y) coordinates. UNIX time for each day, also in an array, is used as the time (x) coordinates. The UNIX arrays and data arrays are then looped to plot as lines, with data y2 being the next data point, making it appear as a continuous line.
Grayscale's GSOL was downloaded spreadsheet and opened in Excel. SOLUSD prices were exported using TradingView export function. The output of information was pasted into Pine Script. For matching up Kraken's SOLUSD prices to each Grayscale's data since GSOL does not trade daily, dates were converted to UNIX and matched with xlookup(). A library or seed will be used in the future for updating.
References
Data retrieved from Grayscale's website 2024/08/04.
www.grayscale.com
Quantity of Solana held by the trust can be seen in their filings. Ctrl + F "Quantity of
SOL "
www.grayscale.com
Q1 2024: www.grayscale.com
The high premium can partly be explained by private placement currently being closed. This means private sales can't dilute share value.
www.etf.com
SOLANA Performance & Volatility Analysis BB%Overview:
The script provides an in-depth analysis of Solana's performance and volatility. It showcases Solana's price, its inverse relationship, its own volatility, and even juxtaposes it against Bitcoin's 24-hour historical volatility. All of these are presented using the Bollinger Bands Percentage (BB%) methodology to normalise the price and volatility values between 0 and 1.
Key Components:
Inputs:
SOLANA PRICE (SOLUSD): The price of Solana.
SOLANA INVERSE (SOLUSDT.3S): The inverse of Solana's price.
SOLANA VOLATILITY (SOLUSDSHORTS): Volatility for Solana.
BITCOIN 24 HOUR HISTORICAL VOLATILITY (BVOL24H): Bitcoin's volatility over the past 24 hours.
BB Calculations:
The script uses the Bollinger Bands methodology to calculate the mean (SMA) and the standard deviation of the prices and volatilities over a certain period (default is 20 periods). The calculated upper and lower bands help in normalising the values to the range of 0 to 1.
Normalised Metrics Plotting:
For better visualisation and comparative analysis, the normalised values for:
Solana Price
Solana Inverse
Solana Volatility
Bitcoin 24hr Volatility
are plotted with steplines.
Band Plotting:
Bands are plotted at 20%, 40%, 60%, and 80% levels to serve as reference points. The area between the 40% and 60% bands is shaded to highlight the median region.
Colour Coding:
Different colours are used for easy differentiation:
Solana Price: Blue
Solana Inverse: Red
Solana Volatility: Green
Bitcoin 24hr Volatility: White
Licence & Creator:
The script adheres to the Mozilla Public Licence 2.0 and is credited to the author, "Volatility_Vibes".
Works well with Breaks and Retests with Volatility Stop
Ichimoku Cloud and Bollinger Bands (by Coinrule)The Ichimoku Cloud is a collection of technical indicators that show support and resistance levels, as well as momentum and trend direction. It does this by taking multiple averages and plotting them on a chart. It also uses these figures to compute a “cloud” that attempts to forecast where the price may find support or resistance in the future.
The Ichimoku Cloud was developed by Goichi Hosoda, a Japanese journalist, and published in the late 1960s. It provides more data points than the standard candlestick chart. While it seems complicated at first glance, those familiar with how to read the charts often find it easy to understand with well-defined trading signals.
The Ichimoku Cloud is composed of five lines or calculations, two of which comprise a cloud where the difference between the two lines is shaded in.
The lines include a nine-period average, a 26-period average, an average of those two averages, a 52-period average, and a lagging closing price line.
The cloud is a key part of the indicator. When the price is below the cloud, the trend is down. When the price is above the cloud, the trend is up.
The above trend signals are strengthened if the cloud is moving in the same direction as the price. For example, during an uptrend, the top of the cloud is moving up, or during a downtrend, the bottom of the cloud is moving down.
The Bollinger Bands are among the most famous and widely used indicators. A Bollinger Band is a technical analysis tool defined by a set of trendlines plotted two standard deviations (positively and negatively) away from a simple moving average ( SMA ) of a security's price, but which can be adjusted to user preferences. They can suggest when an asset is oversold or overbought in the short term, thus providing the best time for buying and selling it.
This strategy combines the Ichimoku Cloud with Bollinger Bands to better enter trades.
Long orders are placed when these basic signals are triggered.
Long Position:
Tenkan-Sen is above the Kijun-Sen
Chikou-Span is above the close of 26 bars ago
Close is above the Kumo Cloud
The closing price is greater than the upper standard deviation of the Bollinger Bands
Short Position:
Tenkan-Sen is below the Kijun-Sen
Chikou-Span is below the close of 26 bars ago
Close is below the Kumo Cloud
The upper standard deviation of the Bollinger Band is greater than the closing price
The script is backtested from 1 January 2022 and provides good returns.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
This script also works well on BTC 30m/1h, ETH 2h, MATIC 2h/30m, AVAX 1h/2h, SOL 45m timeframes
Dap's Oscillator- Short Term Momentum and Trend. BINANCE:BTCUSDT BYBIT:BTCUSDT BYBIT:ETHUSDT BINANCE:ETHUSDT
DAP's OSCILLATOR:
WHAT IS IT?
This Oscillator was created to inspire confidence in the short-term trend of traders. This will work very well with a volatility metric (I recommend BBWP by @The_Caretaker)
WHAT IS IT MADE OF?
1. Consists of a series of equations (mainly the difference between simple to exponential moving averages) and Standard deviations of these moving average differences (length equivalent to the length of sampled ma's)
2. These equations are then boiled down through an averaging process array, after averaging the covariants are equated against the variants of the positive side of the array. This is what is presented as the aqua line.
3. The RC average (yellow) is the sma following the DAP'S Oscillator at a specified length
4. The most important part of this indicator is simply the momentum oscillator represented as a green or red line based on the value relative to the Oscillators.
HOW DO I USE THIS?
As I mentioned before mixed with a volatility metric, it should set you up for a good decision based on short-term trends. I would say to be careful for periods of consolidation, with the consolidation the momentum often meets hands with DAP's Oscillator and can cause fake-outs. You want to spot divergences from the price to the momentum difference, as well as room to work down or upward to secure a good entry on a position.
CHEAT CODE'S NOTES:
I appreciate everyone who has boosted my previous scripts, it means a lot. If you want to translate words to pine script onto a chart, feel free to PM me. I would be happy to help bring an indicator to life. I may take a quick break but will be back shortly to help create more cheat codes for yall. Thanks!
-Cheat Code
Price DEFI Categories against BTC & ETH/* Work in progress. The indicator is not finished. *\
The indicator shows the pricing of 3 DEFI categories against 2 possible baselines, BTC and ETH.
To do:
* Make a simple array in the source code to enter and remove new projects to the category. -> Maybe can also make it so that the source code does not have to be altered (projects can be added through input etc.)
* Adjust weightings depending on project data but this is not as important since weightings are being priced in by the market.
* Try to find a way to update input to string instead of booleans. As of currently, I could not seem to use input strings into plot functions because of an error.
* and more. Leave some feedback, that would be highly appreciated!
