Stablecoin Dominance [LuxAlgo]The Stablecoin Dominance tool displays the evolution of the relative supply dominance of major stablecoins such as USDT, USDC, BUSD, DAI, and TUSD.
Users can disable supported stablecoins to only show the supply dominance relative to the ones enabled.
🔶 USAGE
The stablecoin space is subject to constant change due to new arriving stablecoins, regulation, collapse of coins...etc.
Studying the evolution in supply dominance can help see the effect that certain events can have on the stablecoin sphere.
This dominance graph is displayed over the user price chart to easily observe the correlation between stablecoin dominances and market prices. Users can still move the tool to a new pane below if having it on the price chart is not desired.
🔶 DETAILS
Supported stablecoins include:
Tether (USDT)
USD Coin (USDC)
Binance USD (BUSD)
Dai (DAI)
TrueUSD (TUSD)
Supply dominance of a stablecoin is calculated by dividing the total supply of that stablecoin by the total supply of all enabled stablecoins. That is for N stablecoins:
sd(stablecoin A) = supply(stablecoin 1) / [supply(stablecoin 1) + supply(stablecoin 2) + supply(stablecoin 3) + ... + supply(stablecoin N)
🔹 Display
Users can control the fill style of the displayed areas, with "Gradient" enabled by default. Using "Solid" will use a solid color for each area:
This can improve the performance of the script.
Selecting "None" will not display areas.
🔶 SETTINGS
Fill Style: Fill style of the areas between each returned supply dominance. "Gradient" will color the areas using a gradient, while "Solid" will use a solid color.
Stablecoins List: List of stablecoins used for the supply dominance calculation, disabling one stablecoin will exclude it from all calculations.
Cryptomarket
RSI Volatility Bands [QuantraSystems]RSI Volatility Bands
Introduction
The RSI Volatility Bands indicator introduces a unique approach to market analysis by combining the traditional Relative Strength Index (RSI) with dynamic, volatility adjusted deviation bands. It is designed to provide a highly customizable method of trend analysis, enabling investors to analyze potential entry and exit points in a new and profound way.
The deviation bands are calculated and drawn in a manner which allows investors to view them as areas of dynamic support and resistance.
Legend
Upper and Lower Bands - A dynamic plot of the volatility-adjusted range around the current price.
Signals - Generated when the RSI volatility bands indicate a trend shift.
Case Study
The chart highlights the occurrence of false signals, emphasizing the need for caution when the bands are contracted and market volatility is low.
Juxtaposing this, during volatile market phases as shown, the indicator can effectively adapt to strong trends. This keeps an investor in a position even through a minor drawdown in order to exploit the entire price movement.
Recommended Settings
The RSI Volatility Bands are highly customisable and can be adapted to many assets with diverse behaviors.
The calibrations used in the above screenshots are as follows:
Source = close
RSI Length = 8
RSI Smoothing MA = DEMA
Bandwidth Type = DEMA
Bandwidth Length = 24
Bandwidth Smooth = 25
Methodology
The indicator first calculates the RSI of the price data, and applies a custom moving average.
The deviation bands are then calculated based upon the absolute difference between the RSI and its moving average - providing a unique volatility insight.
The deviation bands are then adjusted with another smoothing function, providing clear visuals of the RSI’s trend within a volatility-adjusted context.
rsiVal = ta.rsi(close, rsiLength)
rsiEma = ma(rsiMA, rsiVal, bandLength)
bandwidth = ma(bandMA, math.abs(rsiVal - rsiEma), bandLength)
upperBand = ma(bandMA, rsiEma + bandwidth, smooth)
lowerBand = ma(bandMA, rsiEma - bandwidth, smooth)
long = upperBand > 50 and not (lowerBand < lowerBand and lowerBand < 50)
short= not (upperBand > 50 and not (lowerBand < lowerBand and lowerBand < 50))
By dynamically adjusting to market conditions, the RSI trend bands offer a unique perspective on market trends, and reversal zones.
Crypto Stablecoin Supply - Indicator [presentTrading]█ Introduction and How it is Different
The "Stablecoin Supply - Indicator" differentiates itself by focusing on the aggregate supply of major stablecoins—USDT, USDC, and DAI—rather than traditional price-based metrics. Its premise is that fluctuations in the total supply of these stablecoins can serve as leading indicators for broader market movements, offering traders a unique vantage point to anticipate shifts in market sentiment.
BTCUSD 6h for recent bull market
BTCUSD 8h
█ Strategy, How it Works: Detailed Explanation
🔶 Data Collection
The strategy begins with the collection of the closing supply for USDT, USDC, and DAI stablecoins. This data is fetched using a specified timeframe (**`tfInput`**), allowing for flexibility in analysis periods.
🔶 Supply Calculation
The individual supplies of USDT, USDC, and DAI are then aggregated to determine the total stablecoin supply within the market at any given time. This combined figure serves as the foundation for the subsequent statistical analysis.
🔶 Z-Score Computation
The heart of the indicator's strategy lies in the computation of the Z-Score, which is a statistical measure used to identify how far a data point is from the mean, relative to the standard deviation. The formula for the Z-Score is:
Z = (X - μ) / σ
Where:
- Z is the Z-Score
- X is the current total stablecoin supply (TotalStablecoinClose)
- μ (mu) is the mean of the total stablecoin supply over a specified length (len)
- σ (sigma) is the standard deviation of the total stablecoin supply over the same length
A moving average of the Z-Score (**`zScore_ma`**) is calculated over a short period (defaulted to 3) to smooth out the volatility and provide a clearer signal.
🔶 Signal Interpretation
The Z-Score itself is plotted, with its color indicating its relation to a defined threshold (0.382), serving as a direct visual cue for market sentiment. Zones are also highlighted to show when the Z-Score is within certain extreme ranges, suggesting overbought or oversold conditions.
Bull -> Bear
█ Trade Direction
- **Entry Threshold**: A Z-Score crossing above 0.382 suggests an increase in stablecoin supply relative to its historical average, potentially indicating bullish market sentiment or incoming capital flow into cryptocurrencies.
- **Exit Threshold**: Conversely, a Z-Score dropping below -0.382 may signal a reduction in stablecoin supply, hinting at bearish sentiment or capital withdrawal.
█ Usage
Traders can leverage the "Stablecoin Supply - Indicator" to gain insights into the underlying market dynamics that are not immediately apparent through price analysis alone. It is particularly useful for identifying potential shifts in market sentiment before they are reflected in price movements. By integrating this indicator with other technical analysis tools, traders can develop a more rounded and informed trading strategy.
█ Default Settings
- Timeframe Input (`tfInput`): Allows users to specify the timeframe for data collection, adding flexibility to the analysis.
- Z-Score Length (`len`): Set to 252 by default, representing the period over which the mean and standard deviation of the stablecoin supply are calculated.
- Color Coding: Uses distinct colors (green for bullish, red for bearish) to indicate the Z-Score's position relative to its thresholds, enhancing visual clarity.
- Extreme Range Fill: Highlights areas between defined high and low Z-Score thresholds with distinct colors to indicate potential overbought or oversold conditions.
By integrating considerations of stablecoin supply into the analytical framework, the "Stablecoin Supply - Indicator" offers a novel perspective on cryptocurrency market dynamics, enabling traders to make more nuanced and informed decisions.
Trend Change IndicatorThe Trend Change Indicator is an all-in-one, user-friendly trend-following tool designed to identify bullish and bearish trends in asset prices. It features adjustable input values and a built-in alert system that promptly notifies investors of potential shifts in both short-term and long-term price trends. This alert system is crucial for helping less active investors correctly position themselves ahead of major trend shifts and assists in risk management after a trend is established. It's important to note that this indicator is most effective with assets that historically exhibit strong trends.
At the heart of this tool is the interaction between the 30-day and 60-day Exponential Moving Averages (EMA). A bullish trend is indicated in green when the 30-day EMA is above the 60-day EMA, while a bearish trend is signaled in red when the 30-day EMA is below the 60-day EMA. The appearance of gray alerts users to potential shifts in the current trend as the EMAs converge, falling below the Average True Range (ATR) safety margin. This analysis is conducted across both hourly and daily timeframes, with the 4-hour timeframe providing early signals for daily trend changes. The band visually represents the interaction between the daily EMAs and is also displayed in the second row of the table, with the first row showing the same EMA interaction on the 4-hour timeframe.
This indicator also includes a 140-day (20-week) Simple Moving Average (SMA), visually represented by a line with predictive dots. This feature significantly enhances the investor's ability to understand long-term trends in asset prices, offering forward-looking insights by projecting the SMA value 10 days into the future. The value of this forecast lies in interpreting the slope of the dots; upward trending dots suggest a bullish underlying trend, while downward trending dots indicate a bearish trend. Generally, prices above the SMA signal bullishness, and prices below indicate bearishness.
In summary, the Trend Change Indicator is a comprehensive solution for identifying price trends and managing risk. Its intuitive, color-coded design makes it an indispensable tool for traders and investors who aim to be well-positioned ahead of trend shifts and manage risk once a trend has been established. While it has proven historically valuable in trending markets such as cryptocurrencies, tech stocks, and commodities, it is advisable to use this indicator in conjunction with other technical analysis tools for a more comprehensive and well-rounded decision-making process.
Liquidation Level ScreenerThe Liquidation Level Screener is an analytical tool designed for traders who seek a comprehensive view of potential liquidation zones in the market. This script, adaptable to almost any timeframe from 1 minute to 3 days, offers a unique perspective by mapping out key liquidation levels where significant market actions could occur.
Key Features:
Multi-Exchange Data Aggregation: Unlike many other indicators, the Liquidation Levels Indicator compiles data from multiple leading exchanges including Binance, Bitmex, Kraken, and Bitfinex. This approach ensures a more holistic and accurate representation of market sentiment, providing insights into potential liquidation points across various platforms.
Customizable Timeframes and Modes: The script is versatile, working effectively across various timeframes. It operates in two distinct modes:
Actual Levels Display: Visually represents potential liquidation levels.
Settings Mode: Showcases an open interest (OI) oscillator. When OI is exceptionally high, indicating a surge in opened positions at a specific candle, it signals traders to be vigilant about upcoming liquidation levels.
Three-Tier Liquidation System: The indicator categorizes liquidation levels into three distinct tiers based on open interest levels—1, 2, and 3—with Level 3 representing the highest concentration of open positions. This tiered approach allows traders to gauge the significance of each level and adjust their strategies accordingly.
Histogram Visualization: A novel feature of this script is the histogram on the chart's right side, representing the concentration of liquidation levels in specific market zones. This visual aid helps traders identify crucial areas that warrant close attention, enhancing decision-making.
Customizable Options:
Moving Averages: Choose from a wide range of moving average types, including VWMA, SMA, EMA, and more, to tailor the indicator to your analysis style.
Histogram Settings: Adjust the number of histograms, lookback bars, and their proximity to the latest candle, allowing for a personalized density and range of visualization.
Liquidation Level Sensitivity: Set thresholds for different liquidation levels, fine-tuning the indicator to detect varying degrees of market leverage.
Color Coding: Customize the color scheme for different leverage levels, enhancing visual clarity and ease of interpretation.
The Liquidation Level Screener offers a unique edge by highlighting potential zones where significant market movements can occur due to liquidations. By consolidating data from multiple exchanges, it provides a more rounded view of market behavior, which is essential in today’s interconnected trading environment. The tiered liquidation system and histogram feature equip traders with the ability to identify and focus on key market segments where high activity is expected. This tool is particularly valuable for traders who base their strategies on market liquidity and leverage dynamics.
[Suitable Hope] Crypto Marketcap Dominance OverviewThe Crypto Marketcap Dominance Overview indicator is a simple yet very useful indicator that aims at helping traders identify where the crypto liquidity is flowing. The indicator uses Cryptocap's real time crypto marketcap dominance data (in %) between several key categories:
- Bitcoin
- True total 2 (altcoins and Ethereum excluding the top 3 biggest stablecoins)
- True total 3 (altcoins excl. Ethereum and the top 3 biggest stablecoins)
- Ethereum
- Stablecoins
- Defi.
The indicator works across all timeframes but is best used on the default daily timeframe to identify changes in liquidity trends between the different categories. More categories can be expected to be added in the future; depending on Cryptocap's available data.
Traders or users of this indicator have a selections of options:
- Choose a dedicated timeframe
- Turn on/off the individual categories they wish to use
- Turn on/off labels
- Change global colour coding of each category and label
- Activate or deactive the 0 to 100% bands
Although there are a couple of similar indicators trying to do something similar, I tend to find them lacking clarity. I coded this indicator to provide a more simple and clearer view of the crypto marketcap dominance. I hope you find this indicator helpful.
Happy trading and good luck!
Open Interest OscillatorIn the middle of a bustling cryptocurrency market, with Bitcoin navigating a critical phase and the community hype over potential ETF approvals, current funding rates, and market leverage, the timing is optimal to harness the capabilities of sophisticated trading tools.
Meet the Open Interest Oscillator – special indicator tailored for the volatile arena of cryptocurrency trading. This powerful instrument is adept at consolidating open interest data from a multitude of exchanges, delivering an in-depth snapshot of market sentiment across all timeframes, be it a 1-minute sprint or a weekly timeframe.
This versatile indicator is compatible with nearly all cryptocurrency pairs, offering an expansive lens through which traders can gauge the market's pulse.
Key Features:
-- Multi-exchange Data Aggregation: This feature taps into the heart of the crypto market by aggregating open interest data from premier exchanges such as BINANCE, BITMEX, BITFINEX, and KRAKEN. It goes a step further by integrating data from various pairs and stablecoins, thus providing traders with a rich, multi-dimensional view of market activities.
-- Open Interest Bars: Witness the flow of market dynamics through bars that depict the volume of positions being opened or closed, offering a clear visual cue of trading behavior. In this mode, If bars are going into negative zone, then traders are closing their positions. If they go into positive territory - leveraged positions are being opened.
-- Bollinger Band Integration: Incorporate a layer of statistical analysis with standard deviation calculations, which frame the open interest changes, giving traders a quantified edge to evaluate the market's volatility and momentum.
-- Oscillator with Customizable Thresholds: Personalize your trading signals by setting thresholds that resonate with your unique trading tactics. This customization brings the power of tailored analytics to your strategic arsenal.
-- Max OI Ceiling Setting: In the fast-paced crypto environment where data can surge to overwhelming levels, the Max OI Ceiling ensures you maintain a clear view by capping the open interest data, thus preserving the readability and interpretability of information, even when market activity reaches feverish heights.
Triple Confirmation Kernel Regression Overlay [QuantraSystems]Kernel Regression Oscillator - Overlay
Introduction
The Kernel Regression Oscillator (ᏦᏒᎧ) represents an advanced tool for traders looking to capitalize on market trends.
This Indicator is valuable in identifying and confirming trend directions, as well as probabilistic and dynamic oversold and overbought zones.
It achieves this through a unique composite approach using three distinct Kernel Regressions combined in an Oscillator.
The additional Chart Overlay Indicator adds confidence to the signal.
Which is this Indicator.
This methodology helps the trader to significantly reduce false signals and offers a more reliable indication of market movements than more widely used indicators can.
Legend
The upper section is the Overlay. It features the Signal Wave to display the current trend.
Its Overbought and Oversold zones start at 50% and end at 100% of the selected Standard Deviation (default σ = 3), which can indicate extremely rare situations which can lead to either a softening momentum in the trend or even a mean reversion situation.
The lower one is the Base Chart.
The Indicator is linked here
It features the Kernel Regression Oscillator to display a composite of three distinct regressions, also displaying current trend.
Its Overbought and Oversold zones start at 50% and end at 100% of the selected Standard Deviation (default σ = 2), which can indicate extremely rare situations.
Case Study
To effectively utilize the ᏦᏒᎧ, traders should use both the additional Overlay and the Base
Chart at the same time. Then focus on capturing the confluence in signals, for example:
If the 𝓢𝓲𝓰𝓷𝓪𝓵 𝓦𝓪𝓿𝓮 on the Overlay and the ᏦᏒᎧ on the Base Chart both reside near the extreme of an Oversold zone the probability is higher than normal that momentum in trend may soften or the token may even experience a reversion soon.
If a bar is characterized by an Oversold Shading in both the Overlay and the Base Chart, then the probability is very high to experience a reversion soon.
In this case the trader may want to look for appropriate entries into a long position, as displayed here.
If a bar is characterized by an Overbought Shading in either Overlay or Base Chart, then the probability is high for momentum weakening or a mean reversion.
In this case the trade may have taken profit and closed his long position, as displayed here.
Please note that we always advise to find more confluence by additional indicators.
Recommended Settings
Swing Trading (1D chart)
Overlay
Bandwith: 45
Width: 2
SD Lookback: 150
SD Multiplier: 2
Base Chart
Bandwith: 45
SD Lookback: 150
SD Multiplier: 2
Fast-paced, Scalping (4min chart)
Overlay
Bandwith: 75
Width: 2
SD Lookback: 150
SD Multiplier: 3
Base Chart
Bandwith: 45
SD Lookback: 150
SD Multiplier: 2
Notes
The Kernel Regression Oscillator on the Base Chart is also sensitive to divergences if that is something you are keen on using.
For maximum confluence, it is recommended to use the indicator both as a chart overlay and in its Base Chart.
Please pay attention to shaded areas with Standard Deviation settings of 2 or 3 at their outer borders, and consider action only with high confidence when both parts of the indicator align on the same signal.
This tool shows its best performance on timeframes lower than 4 hours.
Traders are encouraged to test and determine the most suitable settings for their specific trading strategies and timeframes.
The trend following functionality is indicated through the "𝓢𝓲𝓰𝓷𝓪𝓵 𝓦𝓪𝓿𝓮" Line, with optional "Up" and "Down" arrows to denote trend directions only (toggle “Show Trend Signals”).
Methodology
The Kernel Regression Oscillator takes three distinct kernel regression functions,
used at similar weight, in order to calculate a balanced and smooth composite of the regressions. Part of it are:
The Epanechnikov Kernel Regression: Known for its efficiency in smoothing data by assigning less weight to data points further away from the target point than closer data points, effectively reducing variance.
The Wave Kernel Regression: Similarly assigning weight to the data points based on distance, it captures repetitive and thus wave-like patterns within the data to smoothen out and reduce the effect of underlying cyclical trends.
The Logistic Kernel Regression: This uses the logistic function in order to assign weights by probability distribution on the distance between data points and target points. It thus avoids both bias and variance to a certain level.
kernel(source, bandwidth, kernel_type) =>
switch kernel_type
"Epanechnikov" => math.abs(source) <= 1 ? 0.75 * (1 - math.pow(source, 2)) : 0.0
"Logistic" => 1/math.exp(source + 2 + math.exp(-source))
"Wave" => math.abs(source) <= 1 ? (1 - math.abs(source)) * math.cos(math.pi * source) : 0.
kernelRegression(src, bandwidth, kernel_type) =>
sumWeightedY = 0.
sumKernels = 0.
for i = 0 to bandwidth - 1
base = i*i/math.pow(bandwidth, 2)
kernel = kernel(base, 1, kernel_type)
sumWeightedY += kernel * src
sumKernels += kernel
(src - sumWeightedY/sumKernels)/src
// Triple Confirmations
Ep = kernelRegression(source, bandwidth, 'Epanechnikov' )
Lo = kernelRegression(source, bandwidth, 'Logistic' )
Wa = kernelRegression(source, bandwidth, 'Wave' )
By combining these regressions in an unbiased average, we follow our principle of achieving confluence for a signal or a decision, by stacking several edges to increase the probability that we are correct.
// Average
AV = math.avg(Ep, Lo, Wa)
The Standard Deviation bands take defined parameters from the user, in this case sigma of ideally between 2 to 3,
to help the indicator detect extremely improbable conditions and thus take an inversely probable signal from it to forward to the user.
The parameter settings and also the visualizations allow for ample customizations by the trader. The indicator comes with default and recommended settings.
For questions or recommendations, please feel free to seek contact in the comments.
Kimchi Premium / Korean Premium ALL TICKERSKimchi Premium
Due to the isolated nature of Korean crypto markets, Koreans pay a hefty premium on most cryptos. (Usually ranging from 3% to 5%). This is colloquially known as the " Kimchi Premium ".
Uses
The extend of this premium can be used to gauge Korean sentiment towards certain tickers. Most of the insane alt coin rallies that are started by Korean degens are missed by foreign traders entirely. This script seeks to fix that.
Notes
This script automatically detects your current ticker and compares the USDT pair to the KRW pair after adjusting for exchange rate.
Works on all USDT, USDC, BUSD, FDUSD, USD, USDT.P, USDC.P or KRW pairs. Will obviously throw an error if your ticker has no KRW pairing.
Blockunity Stablecoin Liquidity (BSL)Monitor the liquidity of the crypto market by tracking the capitalizations of the major Stablecoins.
Stablecoin Liquidity (BSL) is an ideal tool for visualizing data on major Stablecoins. The number of Stablecoins in circulation is one of the best indices of liquidity within the crypto market. It’s an important metric to keep an eye on, as an increase in the number of Stablecoins in circulation offers a great opportunity to see cryptoasset prices rise. The tool’s multiple on-board display modes enable analysis of its data in the best possible conditions.
The Idea
The goal is to provide the community with the ideal tool to visualize the liquidity of the crypto market, via the state of the market capitalizations of the major Stablecoins.
How to Use
The tool is very easy to use and interpret. First of all, let's distinguish two main elements:
The chart as 3 distinct display modes to let you observe data in the best possible conditions.
There is a panel that summarizes the market capitalizations of the main Stablecoins.
Display Mode: Cumulative
In Cumulative mode (default), the different capitalizations are displayed one on top of the other with colored bands.
You can see that when the number of Stablecoins in circulation increases, crypto asset prices enter an uptrend. And if the liquidity of Stablecoins dries up, the trend will become bearish.
Display Mode: Aggregated
Aggregated mode displays a single line, which is the sum of the different capitalizations, varying between green and red depending on the state of this data according to its moving average declared in the 'Aggregated MA Lengh' field.
You can thus easily see trend changes and therefore opportunities to enter or exit the crypto market.
Display Mode: Independent
The Independent mode also displays the different capitalizations, but detached from each other with labels.
This display mode is particularly interesting for studying transfers from one Stablecoin to another, as can be seen below.
Other Settings
You can choose whether or not to include each of the Stablecoins data, and configure their display color. Note that in 'Cumulative' display mode, the data is taken into account even if the box is unchecked.
How it Works
The tool works in a simple way: We take the market capitalization data of the Stablecoins that interest us, then we process them according to the different display modes.
Let us know if you would like other ways of visualizing this data!
Crypto Daily WatchList And Screener [M]
Hi, this is a watchlist and screener indicator designed for traders in the field of cryptocurrencies who want to monitor developments in other currency pairs and indices.
The indicator consists of two tables. One of them is the table containing indices such as BTC dominance, total, total2, which allows you to track market developments and changes. In this table, you will find price information, daily change, stochastic, and trend information.
The other table includes cryptocurrencies like BTC/USDT, ETH/USDT, DOT/USDT, and more. In this table, you will see real-time prices, daily volume, daily change, stochastic, the correlation coefficient between the pair and Bitcoin, and the trend value calculated based on MACD.
The "Customize" section in the settings enables you to personalize the appearance of the tables according to your preferences.
Crypto Spot/Futures Dominance Indicator with AlertsFutures/Spot Dominance Indicator:
Overview:
The futures/spot dominance indicator is a versatile tool used by traders and analysts to assess the relative strength or dominance of the futures market in relation to the spot (or cash) market for a specific asset. It offers insights into market sentiment, potential arbitrage opportunities, and risk management while incorporating the VWAP indicator for added context.
How It Works:
This indicator automatically detects and adapts to the futures symbol applied to the chart, simplifying the setup for traders. However, it still necessitates manual input of the corresponding spot pair to ensure accuracy.
Automatic Futures Symbol Detection: The indicator starts by automatically detecting the futures symbol on the trading chart, eliminating the need for manual configuration. This ensures that the indicator is applied to the correct futures contract.
Manual Spot Pair Entry: To provide a reliable reference point for the comparison, traders must manually input the corresponding spot symbol via the indicator's inputs. For instance, if the indicator detects the BTCUSDT.P futures symbol, traders would manually enter the BTCUSDT spot symbol.
Gathering Data: The indicator collects historical price data for both the detected futures contract and the manually specified spot symbol. This data includes open, high, low, and close prices, as well as trading volume.
VWAP Calculation: To gain a deeper understanding of price trends and market dynamics, the indicator calculates the VWAP (Volume Weighted Average Price) for both the futures and spot markets. The VWAP places more weight on prices with higher trading volume, offering a weighted average that reflects market consensus.
Premium/Discount Calculation: By subtracting the VWAP of the spot market from the VWAP of the futures market, the indicator quantifies the premium or discount of the futures price concerning the spot price. A positive value indicates a premium, while a negative value suggests a discount.
Plotting: The premium/discount value is displayed as a line on the chart, often alongside moving averages or other smoothing techniques for improved trend analysis.
Alerts: In addition to its analysis capabilities, this indicator now includes alerts to enhance your trading experience. It alerts you in the following scenarios:
Premium Above Average: Notifies you when the premium crosses above the average line.
Premium Below Average: Alerts you when the premium crosses below the average line.
Premium Above Zero: Provides an alert when the premium crosses above the zero line.
Premium Below Zero: Generates an alert when the premium crosses below the zero line.
Benefits of the Futures/Spot Dominance Indicator:
Sentiment Analysis: Traders use the indicator to assess market sentiment. A futures premium might signify bullish sentiment, while a discount could indicate bearish sentiment.
Arbitrage Opportunities: Identifying price discrepancies between futures and spot markets can help traders spot arbitrage opportunities, where they can profit from price differentials.
Risk Management: The indicator assists in evaluating risks associated with futures positions, helping traders manage their exposure effectively.
Trend Confirmation: When used in conjunction with other technical indicators, futures/spot dominance, along with VWAP, can provide additional confirmation of price trends.
Hedging: Investors and corporations use this tool to gauge the effectiveness of hedging strategies based on futures contracts.
Speculative Trading: Traders and investors use the indicator to inform speculative positions, aligning their trades with perceived market strength or weakness.
Insightful Analysis: Futures/spot dominance analysis, enriched by VWAP data, offers insights into market behavior during specific events or changes in economic conditions.
In summary, the futures/spot dominance indicator, with its integration of VWAP and automatic futures symbol detection, provides traders and investors with a comprehensive tool to assess market dynamics. It aids in sentiment analysis, risk management, and trend confirmation while offering potential arbitrage opportunities. The newly added alerts enhance the indicator's functionality, providing timely notifications of key market events. However, it relies on manual input of the corresponding spot pair to ensure precise comparisons between futures and spot markets. It should be used alongside other analysis techniques for a well-rounded view of the market.
MAX_MIN_V1
Another simple indicator, maximum, minimum and average values. The point of imbalance in the price of an asset is sought.
It is used for any temporality and in almost any asset.
You can configure the visibility of the different elements.
All Candlestick Patterns on Backtest [By MUQWISHI]▋ INTRODUCTION :
The “All Candlestick Patterns on Backtest” indicator generates a table that offers a clear visualization of the historical return percentages for each candlestick pattern strategy over a specified time period. This table serves as an organized resource, serving as a launching point for in-depth research into candle formations. It may help to rectify any misconceptions surrounding candlestick patterns, refine trading approaches, and it could be foundation to make informed decisions in trading journey.
_______________________
▋ OVERVIEW:
_______________________
▋ CREDIT:
Credit to public technical “*All Candlestick Patterns*” indicator.
_______________________
▋ TABLE:
_______________________
▋ CHART:
_______________________
▋ INDICATOR SETTINGS:
#Section One: Table Setting
#Section Two: Backtest Setting
(1) Backtest Starting Period.
Note: If the datetime of the first candle on the chart is after the entreated datetime, the calculation will start from the first candle on the chart.
(2) Initial Equity ($).
(3) Leverage: Current Equity x Leverage Value.
(4) Entry Mode:
- “At Close”: Execute entry order as soon as the candle confirmed.
- “Breakout High (Low for Short)”: Stop limit buy order, entry order will be executed as soon as the next candle breakout the high of last pattern’s candle (low for short)
(5) Cancel Entry Within Bars: This option is applicable with {Entry Mode = Breakout High (Low for Short)}, to cancel the Entry Order if it's not executed within certain selected number of bars.
(6) Stoploss Range: the range refers to high of pattern - low of pattern.
(7) Risk:Reward: the calculation of risk:reward range start from entry price level. For example: A pattern triggered with range 10 points, and entry price is 100.
- For 1:1~risk:reward would the stoploss at 90 and takeprofit at 110.
- For 1:3~risk:reward would the stoploss at 90 and takeprofit at 130.
#Section Three: Technical & Candle Patterns
_______________________
▋ Comments:
This table was developed for research and educational purposes.
Candlestick patterns are almost similar as seen in “*All Candlestick Patterns*” indicator.
The table results should not be taken as a major concept to build a trading decision.
Personally, I see candlestick patterns as a means to comprehend the psychology of the market, and help to follow the price action.
Please let me know if you have any questions.
Thank you.
Daily Network Value to Transactions Signal (NVTS)
Quote of GlassNode ...
The NVT Signal (NVTS) is a modified version of the original NVT Ratio.
It uses a 90 day moving average of the daily transaction volume in the denominator instead of the raw daily transaction volume.
This moving average improves the ratio to better function as a leading indicator.
The Network Value to Transactions (NVT) Ratio is calculated by dividing the market cap by the transferred on-chain volume measured in USD.
GlassNode says the NVT Ratio was created by Willy Woo.
I have peaked into Glassnode and took their idea.
I also added a few more Moving Averages to select from, and the length can also be changed.
This script does not depend on Glassnode alone, instead I pulls data of several services...
CoinMarketCap
CoinMetrics
GlassNode
IntoTheBlock
Therefor we have more Tokens to select from.
I have also blocked some faulty data of each service.
If you get a study error of any kind then there is no data available,
or you on a wrong timeframe.
Best to use this script in a daily chart.
And keep in mind it pulls data of yesterday.
Therefor the plot is offset by 1 to the left.
The script will check each service if the data for the chart is available.
Market Cap is taken in the following order ...
CainMarketCap
GlassNode
CoinMetrics
Transaction volume as USD is taken in the following order ...
IntoTheBlock
CoinMetrics
GlassNode
Happy Trading!
kyle algo v1
Integration of multiple technical indicators: The strategy mainly combines two technical indicators - Keltner Channels and Supertrend, to generate trading signals. It also calculates fifteen exponential moving averages (EMAs) for the high price with different periods ranging from 9 to 51.
Unique combination of indicators: The traditional Supertrend typically uses Average True Range (ATR) to calculate its upper and lower bands. In contrast, this script modifies the approach to use Keltner Channels instead.
Flexible sensitivity adjustment: This strategy provides a "sensitivity" input parameter for users to adjust, which controls the multiplier for the range in the Supertrend calculation. This can make the signals more or less sensitive to price changes, allowing users to tailor the strategy to their own risk tolerance and trading style.
EMA Energy Representation: The code offers a visualization of "EMA Energy", which color-codes the EMA lines based on whether the closing price is above or below the EMA line. This can provide an intuitive understanding of market trends.
Clear visual signals: The strategy generates clear "BUY" and "SELL" signals, represented as labels on the chart. This makes it easy to identify potential entry and exit points in the market.
Customizable: The script provides several user inputs, making it possible to fine-tune the strategy according to different market conditions and individual trading preferences.
EMA (Exponential Moving Average) Principle:
The EMA is a type of moving average that assigns more weight to the most recent data.
It responds more quickly to recent price changes and is used to capture short-term price trends.
Principle of Color Change :
In this trading strategy, the color of the EMA line changes based on whether the closing price is above or below the EMA. If the closing price is above the EMA, the EMA line turns green,
indicating an upward price trend. Conversely, if the closing price is below the EMA, the EMA line turns red,
indicating a downward price trend. These color changes help traders to more intuitively identify price trends
In short, our team provides a lot of practical space
That is your development space
Buy&Sell Bullish Engulfing - The Quant Science🇺🇸
GENERAL OVERVIEW
Buy&Sell Bullish Engulfing - The Quant Science It is a Buy&Sell strategy based on the 'Bullish Engulfing' candlestick pattern. The main goal of the strategy is to achieve a consistent and sustainable return over time, with a manageable level of risk.
Bullish Engulfing
The template was developed at the top of the Indicator provided by TradingView called 'Engulfing - Bullish'.
ENTRY AND EXIT CRITERIA
Entry: A single long order is opened when the candlestick pattern is formed, and the percentage size of the order (%) is fixed by the trader through the user interface.
Exit: The long trade is closed on a percentage equity take profit-stop loss.
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PANORAMICA GENERALE
Buy&Sell Bullish Engulfing - The Quant Science è una strategia Buy&Sell basata sul candlestick pattern 'Bullish Engulfing'. L'obiettivo principale della strategia è ottenere un ritorno costante e sostenibile nel tempo, con un livello gestibile di rischio.
Bullish Engulfing
Il template è stato sviluppato al top dell' Indicatore fornito da Trading View chiamato 'Engulfing - Bullish'.
CRITERI DI ENTRATA E USCITA
Entrata: viene aperto un singolo ordine long quando si forma il candlestick pattern, la size percentuale dell'ordine (%) viene selezionato tramite l'interfaccia utente dal trader.
Uscita: la chiusura della posizione avviene unicamente tramite un take profit-stop loss percentuale calcolato sul capitale.
Bitcoin Limited Growth ModelThe Bitcoin Limeted Growth is a model proposed by QuantMario that offers an alternative approach to estimating Bitcoin's price based on the Stock-to-Flow (S2F) ratio. This model takes into account the limitations of the traditional S2F model and introduces refinements to enhance its analysis.
The S2F model is commonly used to analyze Bitcoin's price by considering the scarcity of the asset, measured by the stock (existing supply) relative to the flow (new supply). However, the LGS-S2F Bitcoin Price Formula recognizes the need for improvements and presents an updated perspective on Bitcoin's price dynamics.
Invalidation of the Normal S2F Model:
The normal S2F model has faced criticisms and challenges. One of the limitations is its assumption of a linear relationship between the S2F ratio and Bitcoin's price, overlooking potential nonlinearities and other market dynamics. Additionally, the normal S2F model does not account for external influences, such as market sentiment, regulatory developments, and technological advancements, which can significantly impact Bitcoin's price.
Addressing the Issues:
The LGS-S2F Bitcoin Price Formula introduces refinements to address the limitations of the traditional S2F model. These refinements aim to provide a more comprehensive analysis of Bitcoin's price dynamics:
Nonlinearity: The LGS-S2F model recognizes that the relationship between the S2F ratio and Bitcoin's price may not be linear. It incorporates a logistic growth function that considers the diminishing returns of scarcity and the saturation of market demand.
Data Analysis: The LGS-S2F model employs statistical analysis and data-driven techniques to validate its predictions. It leverages historical data and econometric modeling to support its analysis of Bitcoin's price.
Utility:
The LGS-S2F Bitcoin Price Formula offers insights for traders and investors in the cryptocurrency market. By incorporating a more refined approach to analyzing Bitcoin's price, this model provides an alternative perspective. It allows market participants to consider various factors beyond the S2F ratio alone, potentially aiding in their decision-making processes.
Key Features:
Adjustable Coefficients
Sigma calculation methods: Normal or Stdev
Credit:
The LGS-S2F Bitcoin Price Formula was developed by QuantMario, who has contributed to the field of cryptocurrency analysis through their research and modeling efforts.
The Z-score The Z-score, also known as the standard score, is a statistical measurement that describes a value's relationship to the mean of a group of values. It's measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean.
The concept of Z-score was introduced by statistician Carl Friedrich Gauss as part of his "method of the least squares," which was an important step in the development of the normal distribution and Z-score tables. It's a key concept in statistics and is used in various statistical tests.
In financial analysis, Z-scores are used to determine whether a data point is usual or unusual. You can think of it as a measure of how many standard deviations an element is from the mean. For instance, a Z-score of 1.0 would denote a value that is one standard deviation from the mean. Z-scores are also used to predict probabilities, with Z-scores having a distribution that is expected to be normal.
In trading, a Z-score is used to determine how often a trading system may produce a string of winners or losers. It can help a trader to understand whether the losses or profits they see are something that the system would most likely produce, or if it's a once in a blue moon situation. This helps traders make decisions about when to start or stop a system.
I just wanted to play a bit with the Z-score I guess.
Feel free to share your findings if you discover additional applications for this strategy or identify timeframes where it appears to perform more optimally.
How it works:
This strategy is based on a statistical concept called Z-score, which measures the number of standard deviations a data point is from the mean. In other words, it helps determine how unusual or usual a data point is.
In the context of this strategy, Z-score is applied to a 10-period EMA (Exponential Moving Average) of Heikin-Ashi candlestick close prices. The Z-score is calculated over a look-back period of 25 bars.
The EMA of the Z-score is then calculated over a 20-bar period, and the upper and lower thresholds (bounds for buy and sell signals) are defined using the 90th and 10th percentiles of this EMA score.
Long positions are taken when the Z-score crosses above the lower threshold or crosses above the mid-line (50th percentile). An additional long entry is made when the Z-score crosses above the highest value the EMA has been in the past 100 periods.
Short positions are initiated when the EMA crosses below the upper threshold, lower threshold or the highest value the EMA has been in the past 100 periods.
Positions are closed when opposing entry conditions are met, for example, a long position is closed when the short entry condition is true, and vice versa.
Set your desired start date for the strategy. This can be modified in the timestamp("YYYY MM DD") function at the top of the script.
VWAP Trendfollow Strategy [wbburgin]This is an experimental strategy that enters long when the instrument crosses over the upper standard deviation band of a VWAP and enters short when the instrument crosses below the bottom standard deviation band of the VWAP. I have added a trend filter as well, which stops entries that are opposite to the current trend of the VWAP. The trend filter will reduce total false breakouts, thus improving the % profitable while maintaining the overall returns of the strategy. Because this is a trend-following breakout strategy, the % profitable will typically be low but the average % return will be higher. As a rule, be sure to look at the average winning trade % compared to the average losing trade %, and compare that to the % profitable to judge the effectiveness of a strategy. Factor in fees and slippage as well.
This strategy appears to work better with the lower timeframes, and I was impressed with its results. It also appears to work on a wide range of asset classes. There isn't a stop loss or take profit built-in (other than the reversal signals, which close the current trade), so I would encourage you to expand on the strategy based on your own trading parameters.
You can toggle off the bar colors and the trend filter if you so desire.
Future updates to this script (or ideas of improving on it) might include a take profit level set at one standard deviation past the current level and a stop loss level set at one standard deviation closer to the vwap from the current level - or applying a multiple to the two based off of your reward/risk ratio.
About the strategy results below: this is with commissions of 0.5 % per trade.
Cobra's CryptoMarket VisualizerCobra's Crypto Market Screener is designed to provide a comprehensive overview of the top 40 marketcap cryptocurrencies in a table\heatmap format. This indicator incorporates essential metrics such as Beta, Alpha, Sharpe Ratio, Sortino Ratio, Omega Ratio, Z-Score, and Average Daily Range (ADR). The table utilizes cell coloring resembling a heatmap, allowing for quick visual analysis and comparison of multiple cryptocurrencies.
The indicator also includes a shortened explanation tooltip of each metric when hovering over it's respected cell. I shall elaborate on each here for anyone interested.
Metric Descriptions:
1. Beta: measures the sensitivity of an asset's returns to the overall market returns. It indicates how much the asset's price is likely to move in relation to a benchmark index. A beta of 1 suggests the asset moves in line with the market, while a beta greater than 1 implies the asset is more volatile, and a beta less than 1 suggests lower volatility.
2. Alpha: is a measure of the excess return generated by an investment compared to its expected return, given its risk (as indicated by its beta). It assesses the performance of an investment after adjusting for market risk. Positive alpha indicates outperformance, while negative alpha suggests underperformance.
3. Sharpe Ratio: measures the risk-adjusted return of an investment or portfolio. It evaluates the excess return earned per unit of risk taken. A higher Sharpe ratio indicates better risk-adjusted performance, as it reflects a higher return for each unit of volatility or risk.
4. Sortino Ratio: is a risk-adjusted measure similar to the Sharpe ratio but focuses only on downside risk. It considers the excess return per unit of downside volatility. The Sortino ratio emphasizes the risk associated with below-target returns and is particularly useful for assessing investments with asymmetric risk profiles.
5. Omega Ratio: measures the ratio of the cumulative average positive returns to the cumulative average negative returns. It assesses the reward-to-risk ratio by considering both upside and downside performance. A higher Omega ratio indicates a higher reward relative to the risk taken.
6. Z-Score: is a statistical measure that represents the number of standard deviations a data point is from the mean of a dataset. In finance, the Z-score is commonly used to assess the financial health or risk of a company. It quantifies the distance of a company's financial ratios from the average and provides insight into its relative position.
7. Average Daily Range: ADR represents the average range of price movement of an asset during a trading day. It measures the average difference between the high and low prices over a specific period. Traders use ADR to gauge the potential price range within which an asset might fluctuate during a typical trading session.
Utility:
Comprehensive Overview: The indicator allows for monitoring up to 40 cryptocurrencies simultaneously, providing a consolidated view of essential metrics in a single table.
Efficient Comparison: The heatmap-like coloring of the cells enables easy visual comparison of different cryptocurrencies, helping identify relative strengths and weaknesses.
Risk Assessment: Metrics such as Beta, Alpha, Sharpe Ratio, Sortino Ratio, and Omega Ratio offer insights into the risk associated with each cryptocurrency, aiding risk assessment and portfolio management decisions.
Performance Evaluation: The Alpha, Sharpe Ratio, and Sortino Ratio provide measures of a cryptocurrency's performance adjusted for risk. This helps assess investment performance over time and across different assets.
Market Analysis: By considering the Z-Score and Average Daily Range (ADR), traders can evaluate the financial health and potential price volatility of cryptocurrencies, aiding in trade selection and risk management.
Features:
Reference period optimization, alpha and ADR in particular
Source calculation
Table sizing and positioning options to fit the user's screen size.
Tooltips
Important Notes -
1. The Sharpe, Sortino and Omega ratios cell coloring threshold might be subjective, I did the best I can to gauge the median value of each to provide more accurate coloring sentiment, it may change in the future.
The median values are : Sharpe -1, Sortino - 1.5, Omega - 20.
2. Limitations - Some cryptos have a Z-Score value of NaN due to their short lifetime, I tried to overcome this issue as with the rest of the metrics as best I can. Moreover, it limits the time horizon for replay mode to somewhere around Q3 of 2021 and that's with using the split option of the top half, to remain with the older cryptos.
3. For the beginner Pine enthusiasts, I recommend scimming through the script as it serves as a prime example of using key features, to name a few : Arrays, User Defined Functions, User Defined Types, For loops, Switches and Tables.
4. Beta and Alpha's benchmark instrument is BTC, due to cryptos volatility I saw no reason to use SPY or any other asset for that matter.
Crypto Trend IndicatorThe Crypto Trend Indicator is a trend-following indicator specifically designed to identify bullish and bearish trends in the price of Bitcoin, and other cryptocurrencies. This indicator doesn't provide explicit instructions on when to buy or sell, but rather offers an understanding of whether the trend is bullish or bearish. It's important to note that this indicator is only useful for trend trading.
The band is a visual representation of the 30-day and 60-day Exponential Moving Average (EMA). When the 30-day EMA is above the 60-day EMA, the trend is bullish and the band is green. When the 30-day EMA is below the 60-day EMA, the trend is bearish and the band is red. When the 30-day EMA starts to converge with the 60-day EMA, the trend is neutral and the band is grey.
The line is a visual representation of the 20-week Simple Moving Average (SMA) in the daily timeframe. "Bull" and "Bear" signals are generated when the 20-day EMA is either above or below the 20-week SMA, in conjunction with a bullish or bearish trend. When the band is green and the 20-day EMA is above the 20-week SMA, a “Bull” signal emerges. When the band is red and the 20-day EMA is below the 20-week SMA, a “Bear” signal emerges. The 20-week SMA can potentially also function as a leading indicator, as substantial price deviations from the SMA typically indicate an overextended market.
While this indicator has traditionally identified bullish and bearish trends in various cryptocurrency assets, past performance does not guarantee future results. Therefore, it is advisable to supplement this indicator with other technical tools. For instance, range-bound indicators can greatly improve the decision-making process when planning for entries and exits points.
Rainbow Drift BetaRainbow Drift Beta is an indicator that detects the triggers of long and short positions at any TF.
It's based on two different type of approaches to the EMAs periods:
- Classic EMAs periods: 10 and 50
- Cycle EMAs perdios: 16, 64 and 256
The 256 period EMA (Annual Cycle) detects the trend: if the EMA 64 (Three-Weekly Cycle) is above, it shows an uptrend; while the EMA 64 is below, it means that the price action is in downtrend.
10 and 16 periods EMAs are working together as well as the 50 and the 64. The first couple reacts faster than the second one and as soon as the 10 is above the 16, the band shows the first attempt of the price action to go in the uptrend direction. The same concept is applied to the second couple (50, 64): when EMA 50 > EMA 64 it's a confirmation of the faster EMAs long direction. Viceverca happens for the downtrend but with the same concept.
As the EMA periods taken in consideration are quite often a sensitive level of reaction of the price, the indicator detects when there is trigger of a long or a short set up and plots a label on the chart. It's possibile to set up an alert as well.
Quite important, the indicator is looking for sideways patterns as the breakout of them shows a clear direction of the price.
Moreover, in order to privide the first and the best entry possibile, the indicator has a function that is triggering only one time as the trend reverted: for example, a long entry on the EMA 10-16 happens only one time since they crossover the EMA 64.
As included in the name, this is a beta version and new improvements will be added in the near future like suggested price entry, SL and TP, and the focus of the development is to avoid as much as possibile the false triggers.
Of course the best way to improve the code is to receive the users' feedbacks, so please feel free to post your comments and questions.
