[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!
Cryptomarket
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.
Crypto Correlation MatrixA crypto correlation matrix or table is a tool that displays the correlation between different cryptocurrencies and other financial assets. The matrix provides an overview of the degree to which various cryptocurrencies move in tandem or independently of each other. Each cell represents the correlation between the row and column assets respectively.
The correlation matrix can be useful for traders and investors in several ways:
First, it allows them to identify trends and patterns in the behavior of different cryptocurrencies. By looking at the correlations between different assets, traders can gain insight into the intra-relationships of the crypto market and make more informed trading decisions. For example, if two cryptocurrencies have a high positive correlation, meaning that they tend to move in the same direction, a trader may want to diversify their portfolio by choosing to invest in only one of the two assets.
Additionally, the correlation matrix can help traders and investors to manage risk. By analyzing the correlations between different assets, traders can identify opportunities to hedge their positions or limit their exposure to particular risks. For example, if a trader holds a portfolio of cryptocurrencies that are highly correlated with each other, they may be at greater risk of losses if the market moves against them. By diversifying their portfolio with assets that are less correlated with each other, they can reduce their overall risk.
Some of the unique properties for this specific script are the correlation strength levels in conjunction with the color gradient of cells, intended for clearer readability.
Features:
Supports up to 64 different crypto assets.
Dark/Light mode.
Correlation strength levels and cell coloring.
Adjustable positioning on the chart.
Alerts at the close of a bar. (Daily timeframe or higher recommended)
Grid Spot Trading Algorithm V2 - The Quant ScienceGrid Spot Trading Algorithm V2 is the last grid trading algorithm made by our developer team.
Grid Spot Trading Algorithm V2 is a fixed 10-level grid trading algorithm. The grid is divided into an accumulation area (red) and a selling area (green).
In the accumulation area, the algorithm will place new buy orders, selling the long positions on the top of the grid.
BUYING AND SELLING LOGIC
The algorithm places up to 5 limit orders on the accumulation section of the grid, each time the price cross through the middle grid. Each single order uses 20% of the equity.
Positions are closed at the top of the grid by default, with the algorithm closing all orders at the first sell level. The exit level can be adjusted using the user interface, from the first level up to the fifth level above.
CONFIGURING THE ALGORITHM
1) Add it to the chart: Add the script to the current chart that you want to analyze.
2) Select the top of the grid: Confirm a price level with the mouse on which to fix the top of the grid.
3) Select the bottom of the grid: Confirm a price level with the mouse on which to fix the bottom of the grid.
4) Wait for the automatic creation of the grid.
USING THE ALGORITHM
Once the grid configuration process is completed, the algorithm will generate automatic backtesting.
You can add a stop loss that destroys the grid by setting the destruction price and activating the feature from the user interface. When the stop loss is activated, you can view it on the chart.
USDT Inflow TrackerUSDT INFLOW TRACKER
What does this script do? It looks for important inflow from USDT and write it below or above your chart.
Does it matter? Yes because Tether with planned USDT inflow highly manipulate the crypto market.
With this simple script you can study what and when something strange is going to happen on your favourite token.
HOW IT WORKS?
Pretty simple. It just continuosly check USDT (and USDC) Market Cap and verify if the last candle is way higher than last one. If it was way higher than expected it plot a green square and write a note with the total Inflow of USDT in the crypto market (not specifcially for your token)
Now you can see when an important inflow is done and start to plan your entry and exit strategy in the crypto market.
AUTOSET
With Autoset you can rely on standard values
5min TF : Inflow greater than of 15 mln (in 1 candle)
30min TF : Inflow greater than of 150 mln (in 1 candle)
60min TF : Inflow greater than of 300 mln (in 1 candle)
1Day TF : Inflow greater than of 900 mln (in 1 candle)
So you can check your favourite coin in no time looking for a good trading position
MANUAL SETTINGS
Otherwise you can set directly your Inflow to track based on your needs.
In the example below I've set to check everytime an Inflow of 25mln USDT or greater was done.
As you can see it highly influence the relative token.
Crypto Uptrend Script + Pullback//Volume CandlesDescription: his is an adaption of my Pullback candle - This works on all timeframes and Markets (Forex//Stocks//)
Crypto Uptrend Script with Pullback Candle allows traders to get into a trend when the price is at end of a pullback and entering a balance phase in the market (works on all markets). The use of Moving averages to help identify a Trends and the use of Key levels to help traders be aware of where strong areas are in the market.
This script can work really well in Crypto Bull Runs when used on HTF and with confluences
The script has key support and resistance zones which are made up of quarterly data. Price reacts to these areas but patience is required as price will take time to come into these areas
I have updated the Pullback Candle with the use of Volume to filter out the weak Pullback Candles -
There are new candles to the script.
The First candle is the Bullish Volume Candle - This candle is set to a multiplier of 2x with a crossover of 50/100 on Volume - this then will paint a purple candle.
Uses of the Bullish Volume Candle:
Breakthrough of key areas // special chart patterns
Rejection of key areas
End of a impulse wave (Profit Takers)
The second candle is a Hammer - I prefer using the Hammers on Higher Timeframes however they do work on all timeframes. .
The third candle is a Exhaustion of impulse downward move.
Uses of this candle - can denote a new trend but has to be with confluence to a demand area // support area or with any use of technical analysis - using this alone is not advised
The fourth candle is a indecision candle in the shape of a Doji - this candle can help identify if the trend is in a continuation or a reversal
This script can work really well in Crypto Bull Runs
Disclaimer: There will be Pullbacks with High Volume (Breakouts) and not go the way as intended but this script is to allow traders to get into trends at good price levels. The script can paint signals in areas where price is too expensive so please do your own due diligence on the markets as this script is to help get into good areas of price
Please leave a thumbs up if you like this script and message me for information on how to use the script.
MVRV Z Score and MVRV Free Float Z-ScoreIMPORTANT: This script needs as much historic data as possible. Please run it on INDEX:BTCUSD , BNC:BLX or another chart of sufficient length.
MVRV
The MVRV (Market Value to Realised Value Ratio) simply divides bitcoins market cap by bitcoins realized market cap. This was previously impossible on Tradingview but has now been made possible thanks to Coinmetrics providing us with the realized market cap data.
In the free float version, the free float market cap is used instead of the regular market cap.
Z-Score
The MVRV Z-score divides the difference between Market cap and realized market cap by the historic standard deviation of the market cap.
Historically, this has been insanely accurate at detecting bitcoin tops and bottoms:
A Z-Score above 7 means bitcoin is vastly overpriced and at a local top.
A Z-Score below 0.1 means bitcoin is underpriced and at a local bottom.
In the free float version, the free float market cap is used instead of the regular market cap.
The Z-Score, also known as the standard score is hugely popular in a wide range of mathematical and statistical fields and is usually used to measure the number of standard deviations by which the value of a raw score is above or below the mean value of what is being observed or measured.
Credits
MVRV Z Score initially created by aweandwonder
MVRV initially created by Murad Mahmudov and David Puell
