Premium VWAP Trendfollow Strategy [wbburgin]This is a strongly-revised version of my VWAP Trendfollow Strategy, which follows a substantial reworking to address various structural inefficiencies with the script, such as the narrowing of the standard deviation band upon anchor reset. I will continue updating the original script with planned adjustments, this is a different proof-of-concept that builds off of the original script thesis with a different calculation method and execution.
This strategy is not built for any specific asset or timeframe, and has been backtested on crypto and equities from 1 min-1 day. The previous experimental strategy was heavily-correlated with the actual movement of the asset, which added unpalatable risk to the strategy and increased drawdown. This revised form has a more stable backtesting curve, but I want to heavily emphasize that I cannot guarantee that the strategy will be profitable for your circumstances. Backtesting only goes so far and every exchange has a different fee schedule, which can substantially eat into your profits. At the bottom I will explain the parameters behind the strategy results.
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The VWAP Trendfollow Strategy begins with a simple premise: to enter long when the price breaks above the upper standard deviation of a VWAP, and to close the position when the price breaks below the lower standard deviation of the VWAP. This is more effective than initiating the same strategy for a VWMA because the VWAP resets its anchor depending on your chosen anchor period, and the act of resetting its anchor also resets its standard deviation value. As a consequence, in sustained uptrends, the standard deviation is pulled upward to meet the price when the anchor resets, instead of requiring the price to fall all the way back down, as in the lower standard deviation band of the VWMA. This essentially acts as the VWAP itself raising the stop loss at each anchor period, which works well for the overall trend-following strategy.
However, this narrowing can still have consequences for a simple breakout strategy; as the price gradually oscillates towards above or below its standard deviation band, it may cross over the other and produce false signals. This oscillation is worrisome especially when fees are taken into account.
Thus, the premium VWAP Trendfollow strategy has a variable width which detects abnormal narrowing of the band, and adjusts it until it is reasonable to close the variability period. Additionally, a filter is added to the open/close signals to soften the frequency of signals without impacting performance significantly.
This script contains an ATR stop loss and an ATR take profit (which is also a difference between it and the original experimental script), with customizable inputs. The strategy results shown below are with initial capital of $1000, qty entry of 10%, and commissions of 0.06%. It works best on 24/7 instruments, like crypto, but I have found it also works with FAANG stocks or other high volatility / high volume assets. The issue with stocks, however, is that the price can jump/plummet because of abnormal events after-hours, which the strategy cannot pick up on until pre-trading begins the next morning. For that reason I suggest it be used on crypto and, because of its low % profitable (but high average winning trade in relation to its average losing trade), be used on an exchange that has minimal fees or volume-based discounts. In the unfortunate case that you cannot find a minimal fee or volume-discounted fee exchange (such as fellow Americans following the liquidity-retreat on Binance.US), I encourage you to test out the higher anchor periods for the higher timeframes, which will reduce the number of trades and increase the average % per trade.
Additionally, this is a long-term strategy used best for accumulation. It is currently long-only; that may change based off of user input.
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Disclaimer
Copyright by wbburgin.
The information contained in my Scripts/Indicators/Algorithms does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Cryptomarket
Heikin Ashi Master Buy Signal ScannerHeikin Ashi Master Buy Signal Scanner is an algorithm consisting of smoothed Heiken Ashi candles and moving averages.Moving averages use 5 basic moving averages. I preferably use ema for smoothing.In addition, the main purpose of this indicator is the preferred stock market and its shares, trading pairs, etc. scanning on a single screen and seeing the buy signals on a single screen.The buy signal appears on the screen as green.
With Column Width from the indicator properties, the width of the column of 30 symbols is adjusted, and the position of the column on the screen is adjusted with the Column Number.
With the indicator, a maximum of 30 symbols can be listed at once. However, this number can be increased according to your tradingview membership type. Especially if you are a premium member of tradingview, you can add as many indicators as you want to the chart without any limitation, and you can add as many symbols as your screen width to the chart. Heikin Ashi Master Buy signals you can see on a single screen.
In addition, the indicator gives you the opportunity to set the time zone you want and you can see the signals according to the time zone you want. All you need to do for this is to set the time zone from the indicator properties.
Now, if you wish, you can see examples of scans made on a single screen below.
Buy signals of 346 coins of Binance usdt trading pair on a single screen
Buy signals of 420 stocks of the Indian market on a single screen
Buy signals of 300 stocks of the NASDAQ on a single screen
Buy signals of 300 stocks of the BORSA ISTANBUL-BIST on a single screen
Buy signals on a single screen with 49 trading pairs in Forex
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.
Crypto Risk CalculatorCrypto Risk Calculator 's logical is bring the differential between Entry price and Stoploss price, your acceptable risk and your account size to calculate the loss size first then convert to the 'Amount coins' and have another feature like auto scale static target calculate by your loss size with RRR (Risk Reward Ratio). Give you to get easier to manage your orders. *** Create to use for Cryptocurrencies Future market ***
Key Features:
📈 Real-time Risk Assessment: Enter the amount you are willing to risk, and Crypto Risk Calculator will calculate the appropriate position size for your futures trade in real-time.
🎯 Target Lines and Static Target Prices based on RRR: Set your desired Risk-Reward Ratio (RRR), and let Crypto Risk Calculator auto-generate target prices according to your RRR. Additionally, place target lines to visualize the expected profit if the price hits that line.
⚙️ Customizable Parameters: Adjust risk percentage, RRR, and other parameters to tailor the tool to your trading strategy.
👁️ User-Friendly Interface: Crypto Risk Calculator features an easy-to-use and intuitive interface for both beginners and seasoned traders.
Usage:
Step 1: Place your entry price
Step 2: Place your stop loss price
Step 3: Place your target price
Step 4: Confirm your account detail
Step 5: Bring the 'Amount coins' to use
Parameter:
Initial account size
Risk percent
Leverage
Entry price
Stop price
Target price
Show your target price
Show static target prices
Number of your static target prices
Table position
Text size
Background color
Text color
Border color
Data output:
Chart
Entry price line
Stop loss price line (loss in base unit currency)
Target price line (profit in base unit currency)
Table
Account size
Risk percent
Leverage
Margin
Entry price
Stoploss price
Amounts coin
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.
Altcoin ComparatorUse this indicator to compare an altcoin's ratio compared to Bitcoin (orange), the general altcoin market (blue), and the entire cryptocurrency market cap (yellow).
Bright colors indicate the altcoin is outperforming the crypto market while dull colors in imply it is under-performing.
Likewise, staying in the green implies sustained outperformance while staying in the red implies sustained under-perfrmance.
Oversold values imply the altcoin is expensive while overbought imply it is cheap.
Be sure to use market caps: ETH, SOL, ADA, etc. not ETHUSD, SOLUSDT, etc.
CRYPTO DIVERGENCE FINDERThis indicator allows you to easily compare any ticker you're looking at with the ones I've found to work best over many years of studying the crypto market. For these reasons, the code of the script is hidden because that is exactly what makes it unique.
You can choose any cryptocurrency, but I recommend using only perpetuals on 'BINANCE' exchange.
If the comparison mode is enabled, the current ticker you are viewing is divided by the ticker selected in the indicator.
For example, if you are watching "SOLUSDT.P" you should open the settings of the indicator and write "SOLUSDT.P" in the ticker field. Then you will get the SOLUSDT.P correlation index with other crypto and currency pairs that are correlated (like I already said this is something that is product of many years of studying this market and this is exactly what is unique about the code so the source of the script have to stay protected).
If you are a beginer, you can just apply simple trend-breakout strategy after you spot the divergence.
For advanced traders, you can use this together with ICT's and SMC concepts as a confirmation upon your entry.
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)
LeafAlgo ProThis indicator utilizes signals generated from a normalized consensus of one of the four following consensus strategies: Oscillator Consensus, Moving Average Consensus, Democratic Fib Consensus, and an Ichimoku Cloud Consensus. When the values of the individual consensus are normalized, they can be utilized as an oscillator with a range of 0-100. The range of 0-100 can be broken down into zones where if the oscillator breaks through the different thresholds and meets the directional filter requirements, a signal is generated for strong buy, buy, sell, and strong sell with respect to which underlying threshold is breached.
Oscillator:
The Oscillator setting consists of the Average Directional Index (ADX) set as a value instead of +/- and is not used in the scoring to gather consensus. Rather, a value of 25 or above is used to confirm the trend regardless of positive or negative. The Chande Momentum Oscillator (CMO), Detrended Price Oscillator (DPO), Momentum, Rate of Change (ROC), Relative Strength Index (RSI), True Strength Index (TSI), and Volume Oscillator are used in the Oscillator table for a consensus value and given a + or - depending on the condition being met. The conditions and weighting are as follows:
-- CMO > or < 0, given a weight of +/- 2
-- DPO > or < 0, given a weight of +/- 2
-- Momentum > or < 0, given a weight of +/- 2
-- ROC > or < 0, given a weight of +/- 2
-- RSI > or < 50, given a weight of +/- 1
-- TSI Value Line > or < 0, given a weight of +/- 1
-- TSI Signal Line > or < 0, given a weight of +/- 1
-- Volume Osc. > or < 0, given a weight of +/- 2
Moving Average:
For the Moving Average Ribbon/Multi-MA setting the user is able to determine the type of MA for 11 moving averages. The type selection consists of EMA, DEMA, TEMA, SMA, RMA, VWMA, WMA, SMMA, and a Hull MA. The preset values for the 11 moving averages are 5, 7, 10, 14, 21, 26, 50, 75, 100, 150, and 200. The consensus conditions and weighting are as follows:
-- If MA(1 through 10) < or > the price source, given a weight of +/- 1
-- If MA(11) < or > the price source, given a weight of +/- 2
DFMA:
The Democratic Fibonacci Moving Average setting is derived from our indicator of the same name. The source for the DFMA can be chosen by the user, but the SMA lengths are predetermined in Fibonacci intervals from 3 to 233. The DFMA line itself is determined by finding the average value of these 10 Fibonacci MA lengths. The consensus conditions and weighting are as follows:
-- If Fib. MA (3-233) < or > the source, given a weight of +/- 1
-- If DFMA value < or > the source, given a weight of +/- 2.
Ichimoku:
The Ichimoku setting values a handful of conditions using the Tenkan-sen/Conversion Line, Kijun-sen/Base Line, Senkou-span A and B, and the Chikou-span, each of which are given their standard values of 9, 26, 52, and 26, respectively, but can be changed in the user settings if desired. As opposed to the other tables, there are fewer conditions to be met and given values to. All of the conditions are given the same weighting (+/- 1). The conditions are as follows:
-- Kijun-sen < or > the source
-- Tenkan-sen < or > the source
-- Kijun-sen > or < the Chikou-span
-- Tenkan-sen > or < the Kijou-sen
-- Senkou Span A > or < Senkou Span B
Dynamic Bar Coloring
The bar coloring is based on the values of the underlying consensus oscillator.
-- If the consensus value >= 75 coloring= "Lime"
-- If the consensus value is between 55 and 70, coloring= "Green"
-- If the consensus value is between 45 and 55, coloring= "Yellow"
-- If the consensus value is between 30 and 45, coloring= "Orange"
-- If consensus value is <= 30, coloring= "Red"
Regression Channels
The visible channel utilizes a basis line of a quadratic regression line. The quadratic regression is well suited for determining (and predicting) trends. Calculating the regression involves five summation equations that utilize the bar index (x1), the price source (defaulted to ohlc4), the desired length, and the square of x1. Determining the coefficient values requires an additional step that factors in the simple moving average of the source, bar index, and squared bar index. The envelopes that are formed around the regression line are a multiple of that regression line using the high/low range of the price. This envelope can be used to determine points of interest where the price may break through, consolidate at, or reverse from. The channels should be used in conjunction with the signals generated to determine if the signal is valid.
Note past performance is not indicative of future results. This is meant to be used as a tool, and the signals generated by this script should be confirmed with other technical analysis.
DG RSIhello crypto community,
i made combine two rsi between dominance and current chart.
mostly it has negative co relation.
1. purple which is stable coin rsi
2. dark green which is your current chart rsi.
back test its easy to understand.
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.
iGapFinderHi everybody!
I decided to release this script to help traders keeping track of market gaps on the CME.
The script works in general for any market and at any timeframe.
The script allows the user to:
- Identify price gaps of a customized amplitude (Gap Width)
- Compute the probabilities of filling them (specific for bullish and bearish gaps or cumulative)
- Visualize gaps on the chart through red and green price areas.
- Visualize the last N unfilled bullish and bearish gaps together with their time of creation.
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.
Correlation Trading StrategyEnglish description:
Title: Correlation Trading Strategy (CTS)
The Correlation Trading Strategy (CTS) is a unique approach that uses the Pearson correlation coefficient to identify potential trading opportunities between two cryptocurrency pairs. The strategy compares historical price data of two selected cryptocurrencies and calculates the degree of correlation between them.
Inputs:
Lookback Period: The time interval for calculating correlation (e.g., 30, 60, 90 days).
Timeframe Period: The timeframe for the historical price data (e.g., '5').
First Symbol: The first cryptocurrency symbol to compare (e.g., BTCUSD).
Second Symbol: The second cryptocurrency symbol to compare (e.g., ETHUSD).
Enter Long Threshold: The correlation threshold for entering a long position.
Exit Long Threshold: The correlation threshold for exiting a long position.
The strategy enters a long position when the correlation coefficient is equal to or higher than the Enter Long Threshold and exits the position when the correlation coefficient falls below the Exit Long Threshold. The Pearson correlation coefficient ranges from -1 (perfectly negatively correlated) to 1 (perfectly positively correlated), with 0 indicating no correlation. By adjusting the thresholds, traders can customize the strategy to suit their risk appetite and trading style.
Russian description:
Заголовок: Торговая стратегия на основе корреляции (CTS)
Торговая стратегия на основе корреляции (CTS) представляет собой уникальный подход, использующий коэффициент корреляции Пирсона для выявления потенциальных торговых возможностей между двумя парными криптовалютами. Стратегия сравнивает исторические данные о ценах двух выбранных криптовалют и рассчитывает степень корреляции между ними.
Входные параметры:
Период анализа: временной интервал для расчета корреляции (например, 30, 60, 90 дней).
Временной период: временной период для исторических данных о ценах (например, '5').
Первый символ: первый символ криптовалюты для сравнения (например, BTCUSD).
Второй символ: второй символ криптовалюты для сравнения (например, ETHUSD).
Порог для открытия длинной позиции: порог корреляции для открытия длинной позиции.
Порог для закрытия длинной позиции: порог корреляции для закрытия длинной позиции.
Стратегия открывает длинную позицию, когда коэффициент корреляции равен или выше порога для открытия длинной позиции, и закрывает позицию, когда коэффициент корреляции опускается ниже порога для закрытия длинной позиции
Degen IndicatorThis indicator uses candle patterns I have identified by studying cryptocurrency charts. The main goal is to help you tune out noise and price swings so you are better able to trade with the trend. If you can trade with the trend you will be profitable. Don’t fight the trend.
Signals:
Orange T with Orange Bar - Top
Grey T - Weak Top
Orange P - Pause (Minimal pullback expected before additional upside)
Grey B - Weak Bottom
Green B - Possible Bottom
Blue B with Blue Bar - Likely Bottom
Grey D - Weak Dump
Pink D - Possible Dump
Red D - Likely Dump
Bar Colors:
Grey Green #699969 (Slightly Bullish)
Green #2ca02c (Bullish)
Bright Green #00ff00 (Strong Bullish)
Light Pink #cf6666 (Slightly Bearish)
Red #d62728 (Bearish)
Bright Red #ff0000 (Strong Bearish)
Orange Top #ff9800 (Local price maximum)
Blue Bottom #0066ff (Local price minimum)
Recommended Settings:
Change the Body and the Wick to be Grey. Deselect Border.
Purpose:
Making the default bar colors Grey will help you tune into the trend. Look for clusters of candles where only one non Grey color is present. If there are 3 - 5 or more of the same color also pay attention to the size of the candles. You can see the strength of the moves if they are growing or shrinking in size. Oftentimes a trend will end with an Engulfing Candle after a cluster of candles with the other color. Use this as a sign to exit your position and/or enter a new position.
Advice:
Start on HTF and find the clusters of Tops and Bottoms. Dial into lower timeframes to find the local Tops and Bottoms for entry points. Look for clusters of signals. Be ready for one candle to signify a change in the trend then look for confirmation with additional candles. Do not think about Tops or Bottoms as absolutes. A Top that gets beat with a Bullish Engulfing candle is telling you the Bullish strength is strong. Do not short Grey D’s. Do not long Grey B’s. As always, use these signals in conjunction with your other preferred methods of trading to find confluence and trade with the trend. On LTF this indicator will be very noisy. On HTF it will be more stable.
Logic:
Signals were developed by myself and subjected to extensive backtesting. Each signal uses various combinations of: candle names (Doji, Morning Star, Bearish Engulfing, Bullish Engulfing, etc), volume, price change as a percent, price change as an absolute number, length of the wick the open, close, high, and low candle values. The signals incorporate these values ranging from one candle prior to many candles prior attempting to predict the trend.
Logic not used:
Moving Averages, RSI, OBV, VPVR and Bollinger Bands.
Trendmaster - Crypto Flow IndexWhat it is:
The Trendmaster Crypto Flow Index is a unique tool designed to give you an overview of the performance of different Crypto market sectors and sub-sectors. It helps you to identify where you should be focusing your investments for maximum portfolio efficiency and profitability.
What it does:
The Crypto Flow Index presents a visual overview of the flows of retail and institutional capital into the four main market sectors: Large Caps, Alts Coins, Shit Coins, and Stable Coins as well as several other sub-sectors. Each sector is assigned a "Flow Score", which indicates its current performance, demand, and strength in percentage terms. The "Flow Score" also provides insights into the current stage of the market cycle and the typical over and underperformances of assets that correlate to it. Additionally, the index factors in the sector have a "Correlation" to the broader market, allowing you to see the best sectors for trading and investing, either for positional hedging or differential plays.
How to Use it:
To use the Trendmaster Crypto Flow Index, you can simply observe the evolving colored line within the indicator and the table overview. You can identify which sectors are outperforming or underperforming the general market and make informed decisions about where to direct your focus and funds. By monitoring the transitions of Flow between sectors, you can gain invaluable insights into the market cycle and the typical over and underperformances of assets that correlate to it. This information will help you to maximize portfolio efficiency by targeting different market sectors based on their performance to the overall cryptocurrency market. The index covers different sectors, including Large caps, Alts, Shit, Stables, AI, Defi, Dex, Exchange, Gaming, Meme, Metaverse, Nft, Privacy, Smart, and Sports.
Examples of Cryptocurrencies represented in the different market sectors:
Large caps: The biggest market cap cryptocurrencies such as BTC and ETH.
Alts: High-cap and high-volume digital assets that are smaller than large caps, such as LTC and XRP.
Shit coins: Smaller cap projects that are highly speculative and experience significant price volatility, such as BAT and HOT.
Stables: Fiat-pegged assets that provide a stable value, such as USDT and USDC.
AI: Projects that are based on artificial intelligence, such as FET and AGIX.
DeFi: Leverages high volume smart contract platforms to provide financial products in crypto, mainly ERC20 tokens such as LINK and AAVE.
DEX: Decentralized exchanges with their own utility tokens, such as UNI and SUSHI.
Exchange: Centralized exchanges with their own utility tokens, such as BNB and CRO.
Gaming: Web3/crypto gaming platforms with their own utility tokens, such as AXS and GMT.
Meme: Similar to shit coins, but with no real functionality and based purely on social media and memes, such as DOGE and SHIB.
Metaverse: Projects that aim to provide Metaverse assets such as virtual land and assets, such as MANA and SAND.
NFT: Non-fungible tokens with their own token or NFT-based platforms that have their own utility tokens, such as APE and LOOKS.
Privacy: Anonymous and privacy-focused chains, such as XMR and ZEC.
Smart: Projects that provide smart contract alternatives to ETH, such as ADA and AVAX.
Sports: Fan tokens based on real-world sports teams or platforms that support and distribute them, such as CHZ and FLOW.
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
