Open Interest All ExchangesThe indicator collects data from available exchanges based on open interest. The indicators are calculated in the amount of Bitcoin.
Below are the tickers of the exchanges that provide the data:
- BITFINEX:BTCUSD
- BITFINEX:BTCUST
- KRAKEN:BTCUSDPERP
- BITMEX:XBTUSD
- BITMEX:XBTUSDT
- BINANCE:BTCUSDTPERP
- BINANCE:BTCUSDPERP (due to low volumes and limitations of 40 requests of the request.security function, the code contains data without using the calculation)
For me, Open Interest indicators play an important role in the trading system, for this reason I share with you. I am not a financial advisor.
**Open for cooperation**
Cerca negli script per "bitcoin"
MVRV Z ScoreIndicator Overview
MVRV Z-Score is a bitcoin chart that uses blockchain analysis to identify periods where Bitcoin is extremely over or undervalued relative to its 'fair value'.
It uses three metrics:
1. Market Value: The current price of Bitcoin multiplied by the number of coins in circulation. This is like market cap in traditional markets i.e. share price multiplied by number of shares.
2. Realised Value: Rather than taking the current price of Bitcoin, Realised Value takes the price of each Bitcoin when it was last moved i.e. the last time it was sent from one wallet to another wallet. It then adds up all those individual prices and takes an average of them. It then multiplies that average price by the total number of coins in circulation.
In doing so, it strips out the short term market sentiment that we have within the Market Value metric. It can therefore be seen as a more 'true' long term measure of Bitcoin value which Market Value moves above and below depending on the market sentiment at the time.
3. Z-score (Orange): A standard deviation test that pulls out the extremes in the data between market value and realised value.
How It Can Be Used
The MVRV Z-score has historically been very effective in identifying periods where market value is moving unusually high above realised value. These periods are highlighted by the z-score (red line) entering the pink box and indicates the top of market cycles. It has been able to pick the market high of each cycle to within two weeks.
It also shows when market value is far below realised value, highlighted by z-score entering the green box. Buying Bitcoin during these periods has historically produced outsized returns.
(Bar colors shows when market is trending down or a top - strong red or trending up and bottom - strong green. Added allerts for values)
Bitcoin Price Prediction Using This Tool
MVRV Z-Score bitcoin chart is useful for predicting Bitcoin price at the extremes of market conditions. It is able to forecast where Bitcoin price may need to pull back when MVRV Z-score enters the upper red band, and also when CRYPTOCAP:BTC price may rally after spending time in the lower green band.
Historically it has picked major Bitcoin price highs to within 2 weeks.
Created By
@aweandwonder who has unfortunately since deleted the original article and his online profile.
He built on the initial work to create MVRV by Murad Mahmudov and David Puell
Active AddressesIndicator Overview
By comparing the 28 day change in price (%) with the 28 day change in active addresses (%) for Bitcoin we are able to create a short-term sentiment indicator called AASI (Active Address Sentiment Indicator).
Grey lines on the chart show the change in active addresses.
On the outer boundaries of those grey lines are standard deviation bands.
Dotted red line = upper boundary
Dotted green line = lower boundary
Orange line is the 28 day price change (%).
When the orange line reaches the upper boundary (red dotted line) it is indicating that short term market sentiment is overheated. Because the rate of increase in price is outstripping the rate of increase in active addresses.
Zooming in on the chart (left click and drag) we can see that this often corresponds with CRYPTOCAP:BTC price (blue line) stalling and/or retracing.
The opposite is true when the 28 day price change hits the lower boundary (green dotted line). Here market sentiment is overly bearish and we often see CRYPTOCAP:BTC price then increasing thereafter.
In extreme market conditions the 28 day price change (orange line) aggressively breaks out beyond the dotted red and green bands. This is typically in a major market crash or in the latter stages of a bull market. I may add additional standard deviation bands to catch these moves but for now have left them off to keep the chart clean.
Pre 2015 data is quite volatile and messy so this charts starts at 01 January 2015.
Bitcoin Price Prediction Using This Tool
Unlike many of the other Bitcoin live charts, this live chart examines lower time frames and attempts to provide a Bitcoin price prediction in terms of directional moves on weekly timeframes. So it tries to do a Bitcoin price forecast by highlighting where price may pullback or where it may bounce using price and active address data.
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.
BTCUSD Price prediction based on central bank liquidityIn recent months the idea that Bitcoin prices are increasingly linked to liquidity provided by central banks has gained strength. Multiple opinion leaders in the bitcoin space have shared their thoughts to explain why this is happening and why it makes sense. Some of these people I'm talking about are Preston Pysh, Dr. Jeff Ross, Steven McClurg, Lynn Alden among others.
The reality is that the correlation between market liquidity, measured as Assets held by the Federal Reserve, Bank of Japan and European Central bank, and Bitcoin prices is high. This made me wonder whether a regression between "market liquidity" and BTCUSD prices made sense in order to understand where Bitcoin prices are in relation to the liquidity in the market. After several trials I ended up fitting a polynomial regression of degree 5 between Market Liquidity and BTCUSD prices since 2013. This regression resulted in r-squared value of 90.93%. I initially visualized the results in python notebooks but then I thought it would be cool to be able to see them in real-time in tradingview.
That's where this script comes handy...
This script takes the coefficients and intercept from the polynomial regression I built and applies them to the "market_liquidity" index. In addition, it adds upper and lower bound lines to the prediction based on a 95% confidence interval. As you will see, particularly since 2020, the price of bitcoin has rarely been above or below the lines representing the 95% confidence interval. When price has actually crossed these lines it's been in moments where Bitcoin was highly overbought or oversold. Therefore this indicator could be used to understand when it's a good moment to enter or exit the market based on central bank fundamentals.
Here's the detailed step-by-step description of what the script does
1) It defines the coefficients obtained from running the regression betweeen "market liquidity" and BTCUSD. Market liquidity is defined as:
Market liquidity = FRED:WALCL + FX_IDX:JPYUSD*FRED:JPNASSETS + FX:EURUSD*FRED:ECBASSETSW - FRED:RRPONTSYD - FRED:WTREGEN
2) It defines a scale factor. The reason for this is that coefficients from the regression are very small numbers, given the huge numbers of the value of assets held by central banks. Pinescript doesn't support numbers with many decimals and rounds them to 0, so the coefficients had to be scaled up in order to be able to calculate the regression results.
3) It calculates market liquity with the formula defined above. Market liquidity is calculated in US Dollars.
4) It calculates the predicted BTCUSD price based on the coefficients and the market liquidity values.
5) It scales down the values by the same factor used to scale the coefficients up
6) It defines the standard deviation of the "potential_btcusd_price_scaled" and the actual BTCUSD prices.
7) It defines upper and lower bounds to the BTCUSD price prediction using a z-score of 1.96, which is equivalent to 95% confidence interval.
8) Lastly it plots the BTCUSD price prediction (orange) and the upper (red) and lower(green) confidence intervals.
The script can be updated as the correlation of BTCUSD to central bank assets changes (the slope values can be updated).
How to use it:
When actual BTCUSD price (blue line in the chart) crosses over the red line (upper bound) or crosses under the green line (lower bound) it should be taken as a sign that the price of BTCUSD may be overvalued or undervalued based on the value of assets held by major central banks.
Correlation prix [SP500, TESLA, BTCBefore you see this post I want to thank all the TradingView team. Every day that passes I learn better and better to use Pine script and I owe this to all those who publish and to the philosophy of TradingView. Thanks from Amos
This trading indicator compares the prices of the S&P 500 Index (SP500), Tesla (TSLA), and Bitcoin (BTC) to find correlations between them. To make the prices of SP500 and Tesla comparable to the price of Bitcoin, the indicator multiplies the closing price of Tesla by 114 and the closing price of the S&P 500 Index by 5.6.
In this way we can superimpose the prices on the BTC chart and see what happens.
Average BTC price/ tesla price = 114, so if we multiply the tesla price by 114 times we can superimpose it on the BTC price
At average BTC/SPX price = 5.6, also in this case we multiply the price of SPX by 5.6 to overlay the graph and see any correlations.
The indicator then calculates the average price between SP500 and Tesla, using the formula (SP500 + Tesla) / 2. This calculation creates a new line on the chart that represents the average price between these two assets.
The BTC_SP_TE variable is then calculated as the average of the closing price of Bitcoin and the previously calculated average price of SP500 and Tesla, using the formula (Btc + SP_TE) / 2. This calculation creates another line on the chart that represents the average price between Bitcoin and the previously calculated average between SP500 and Tesla.
The idea behind calculating these averages is to find correlations and patterns between the prices of these assets, which can help identify potential trading opportunities. By comparing the average prices of different assets, the trader can look for trends and patterns that might not be apparent when looking at each asset individually.
The indicator plots these prices on a chart and fills the area between them with either green or fuchsia, depending on which one is higher. The strategy suggests buying Bitcoin when the average price of SP500 and Tesla is higher than the current price of Bitcoin, and selling when it is lower.
To add visual cues to the trading strategy, the indicator uses the plotchar function to display a small triangle below the chart when it detects a potential buying opportunity. This is done with the following parameters:
Value: BTC_SP_TE < Btc and Btc > Btc1 and Btc1 > Btc , which is a logical expression that checks whether the average price of SP500 and Tesla is less than the current price of Bitcoin (BTC_SP_TE < Btc), and whether the current price of Bitcoin is higher than the price 10 bars ago (Btc > Btc1 ) and higher than the price on the previous bar (Btc1 > Btc ).
Text: "Moyen BTC_SP_Te", which is the text to display inside the marker.
Symbol: "▲", which is the symbol to use for the marker. In this case, it is a small triangle pointing upwards.
Location: location.belowbar, which specifies that the marker should be placed below the bar.
I hope this is an example of how to create an indicator on TradingView, remember that correlations do not always last, it is possible that when you see the graph this correspondence no longer exists, do your studies and get inspired.
Typical Sweeps: Pivot high/low boxes. Grade sweeps, Handles/PipsTool to show typical pip-grade/ handle-grade sweep distance above pivot highs and pivot lows
-In consolidation/ranging periods (i.e. most of the time); Highs/Lows may by swept by fairly consistent distances in typical stop raids.
-Idea is from ICT teaching on typical Pip-grade sweeps in FX (10,20,30pips). Designed to work on FX, Indices, Commodities, Bitcoin.
-Above chart shows S&P; sweeping below and then above by 5 handles.
///inputs///
~choose sweep distance handles ($) or pips: will auto-calculate depending on the asset: FX= pips; Indices/stocks/commodities = handles ($)
--(2,5,10,20,30,50,100, 500, 1000)
~choose pivot lookback: larger number for more significant swing highs/lows
~choose number of historical boxes to display
~toggle on/off Pivot high boxes and Pivot low boxes independently
~extend boxes fully to the right (default is not extend)
~toggle on/off text
~text & box formatting options
Bitcoin, hourly chart; Pivot lookback = 15; $100 sweep boxes:
Eur/Usd; 15m chart; Pivot lookback = 30; 10pip sweep boxes; Boxes extended fully to the right:
VFIBs AgreementVFIBs Agreement is a custom oscillator, using Volume Weighted Fibonacci Bands (VFIBs).
The two values in yellow and teal relate to the price action and where they fall in the Fibonacci Bands for the 50 and 200 VWMAs, respectively. These values are scaled logarithmically, making it so that the 7 period moving averages of the values tend to 'stick' to the top (just above 20) or bottom (just below -20). When the background color is deep red, this indicates that there is bullish momentum and likely a bull market. The inverse, in green, represents bearish momentum or a bear market. These colors correspond to the 200 period VFIB.
The bands of the VFIBs are broken down by fibonacci values as different channels, moving alongside the mid-line above and below. The price action will go between these values, showing where it is in the extremes. This is what VFIBs agreement represents.
In order for an uptrend to begin, the two VFIBs must 'agree'. With the 50 period VFIB trending up, it doesn't matter if it keeps getting rejected by the 200 period, as we can see with Bitcoin. When the 50 period VFIB starts to pull the 200 period up or down, it could indicate an imminent reversal.
This indicator works well with any market that you would use the VFIBs in. Mid and large cap stocks, top cryptocurrencies, and indices are my top choices.
Round NumbersThis is a variation of "Round numbers above and below" indicator by BitcoinJesus-Not-Roger-Ver. I've made it two sets of lines and round number range changeable. Defaults at 100 and 500 round numbers.
Round Numbers and Quarter LevelsThis script is based on "Round Numbers Above and Below" by BitcoinJesus-Not-Roger-Ver, but unlike this script that only shows "Round Numbers" levels, my script also shows "Quarter Number" levels like 25 and 75 that are very important for those who follow the quarters theory.
Also the original script doesn't have different colors for different levels while my script has different colors and different styles for every level, this way it will be much easyer to recognize the levels at first sight.
Finally the origianl script only works with Forex while my script also works with indexes like SP500 and others.
Round Numbers are very important psychological levels in trading but also quarters levels (25 and 75) have a huge importance, so I created this script that shows all these levels with different colors and different lines style.
You can edit the color and the style of the lines as you wish and you can add all the levels you want.
In 1 hour chart 4 levels is usually enough but if you watch a daily chart then 8 levels is way better.
Features:
Personalize color to 00 round levels
Personalize color to 50 round levels
Personalize color to Quarters levels
Personalize line style to 00 round levels
Personalize line style to 50 round levels
Personalize line style to Quarters levels
Choose number of lines above and below price level (4 is default)
R19 STRATEGYHello again.
Let me introduce you R19 Strategy I wrote for mostly BTC long/short signals
This is an upgrated version of STRATEGY R18 F BTC strategy.
I checked this strategy on different timeframes and different assest and found it very usefull for BTC 1 Hour and 5 minutes chart.
Strategy is basically takes BTC/USDT as a main indicator, so you can apply this strategy to all cryptocurrencies as they mostly acts accordingly with BTC itself (Of course you can change main indicator to different assets if you think that there is a positive corelation with. i.e. for BTC signals you can sellect DXY index for main indicator to act for BTC long/short signals)
Default variables of the inticator is calibrated to BTC/USDT 5 minute chart. I gained above %77 success.
Strategy simply uses, ADX, MACD, SMA, Fibo, RSI combination and opens positions accordingly. Timeframe variable is very important that, strategy decides according the timeframe you've sellected but acts within the timeframe in the chart. For example, if you're on the 5 minutes chart, but you've selected 1 hour for the time frame variable, strategy looks for 1 hour MACD crossover for opening a position, but this happens in 5 minutes candle, It acts quickly and opens the position.
Strategy also uses a trailing stop loss feature. You can determine max stoploss, at which point trailing starts and at which distance trailing follows. The green and red lines will show your stoploss levels according to the position strategy enters (green for long, red for short stop loss levels). When price exceeds to the certaing levels of success, stop loss goes with the profitable price (this means, when strategy opens a position, you can put your stop loss to the green/red line in actual trading)
You can fine tune strategy to all assets.
Please write down your comments if you get more successfull about different time zones and different assets. And please tell me your fine tuning levels of this strategy as well.
See you all.
Polynomial Regression Extrapolation [LuxAlgo]This indicator fits a polynomial with a user set degree to the price using least squares and then extrapolates the result.
Settings
Length: Number of most recent price observations used to fit the model.
Extrapolate: Extrapolation horizon
Degree: Degree of the fitted polynomial
Src: Input source
Lock Fit: By default the fit and extrapolated result will readjust to any new price observation, enabling this setting allow the model to ignore new price observations, and extend the extrapolation to the most recent bar.
Usage
Polynomial regression is commonly used when a relationship between two variables can be described by a polynomial.
In technical analysis polynomial regression is commonly used to estimate underlying trends in the price as well as obtaining support/resistances. One common example being the linear regression which can be described as polynomial regression of degree 1.
Using polynomial regression for extrapolation can be considered when we assume that the underlying trend of a certain asset follows polynomial of a certain degree and that this assumption hold true for time t+1...,t+n . This is rarely the case but it can be of interest to certain users performing longer term analysis of assets such as Bitcoin.
The selection of the polynomial degree can be done considering the underlying trend of the observations we are trying to fit. In practice, it is rare to go over a degree of 3, as higher degree would tend to highlight more noisy variations.
Using a polynomial of degree 1 will return a line, and as such can be considered when the underlying trend is linear, but one could improve the fit by using an higher degree.
The chart above fits a polynomial of degree 2, this can be used to model more parabolic observations. We can see in the chart above that this improves the fit.
In the chart above a polynomial of degree 6 is used, we can see how more variations are highlighted. The extrapolation of higher degree polynomials can eventually highlight future turning points due to the nature of the polynomial, however there are no guarantee that these will reflect exact future reversals.
Details
A polynomial regression model y(t) of degree p is described by:
y(t) = β(0) + β(1)x(t) + β(2)x(t)^2 + ... + β(p)x(t)^p
The vector coefficients β are obtained such that the sum of squared error between the observations and y(t) is minimized. This can be achieved through specific iterative algorithms or directly by solving the system of equations:
β(0) + β(1)x(0) + β(2)x(0)^2 + ... + β(p)x(0)^p = y(0)
β(0) + β(1)x(1) + β(2)x(1)^2 + ... + β(p)x(1)^p = y(1)
...
β(0) + β(1)x(t-1) + β(2)x(t-1)^2 + ... + β(p)x(t-1)^p = y(t-1)
Note that solving this system of equations for higher degrees p with high x values can drastically affect the accuracy of the results. One method to circumvent this can be to subtract x by its mean.
Cipher B divergencies for Crypto (Finandy support)Hello Traders!
In times of high volatility, it is important to follow a market-neutral strategy to protect your hard-earned assets. The simple script employs common buy/sell and/or divergencies signals from the VuManChu Cipher B indicator with fixed stop losses and takes profits. The signals are filtered by a local trend of a coin of interest and the global trend of Bitcoin. These trends-filtered signals demonstrated better performance on most of the back- and forward- tests for USDT cryptocurrency futures. The strategy is based on my real experience, it's a diamond I want to share with you.
In terms of visualization if the background is red and the price is below the yellow line then only a short position can be opened. Conversely, if the price is above the yellow line AND the background is green only a long position can be opened.
Inputs from VuManChu you can find on the top. Frankly, I do not know how they can help you to improve the performance of the strategy. My inputs of the script you can find in "Trend Settings" and "TP/SL Settings" at the bottom.
The checkbox "Only divergencies" lets to broadcast only more reliable buy/sell signals for a cost of rare deals.
The checkbox "Cancel all positions if price crosses local sma?" makes additional trailing stop loss. Usually, this function increases the win rate by "smoothing" the risk/reward ratio, as a usual stop loss does.
You can tune SL/TP based on backtesting.
To connect the script to Finandy just edit "name" and "secret" to connect your webhook (see the bottom of the script).
The rule of thumb for the strategy is "only divergencies" - ON, high reward/risk (TP/SL) ratio, 5 min timeframe on chart help with performance.
Finally, I am looking forward to feedback from you. If you have some cool features for my script in your mind, do not hesitate to leave them in the comments.
Good luck!
Volume in Base CurrencyShows the volume in USD, EUR, etc (whatever the base currency is for the asset) instead of number of stocks, bitcoins, etc.
BTC Supply weighted channel: OnchainUse this oscillator in the weekly time frame and then draw the above linear channel
The premise of this idea is that the trend slope of the bitcoin price correlates with the bitcoin supply chart, which shows the total amount of bitcoin ever created/issued.
Therefore, Bitcoin price is weighted based on Bitcoin supply.
As a result, the above channel has been created, which is a linear channel, and it seems that it can be an oscillator to determine the bitcoin trend, as well as the tops and bottoms of the market.
Bitcoin seems to respect the bottom and top lines of this channel as well as its midline
ETH MA ChannelThe 200-week moving average for bitcoin is considered to be the most popular bitcoin support and determines the bitcoin price bottom. But examining this index in the case of bitcoin does not have the same result for Ethereum. The above moving average channel is designed according to the price action of ETH to determine its top and bottom based on the 200w moving average. This channel has a good performance on the historical chart.
BlackMEX - Production CostBitcoin's Value as determined by Joules of energy input only
Calculations per Medium article EV = (Energy-in) / (Supply Growth Rate) * (Fiat Factor)
Historic Energy Efficiency data can only be entered monthly due to processing speed constraints of below data load and should be considred an estimate only.
Energy Efficiency Data requires manual updating. Currently accurate as of 28 December 2019
Bitcoin Production Cost
Cambridge Bitcoin Electricity Consumption Index (CBECI) - Bitcoin's global electricity consumption in TwH.
NB: Uses MONTHLY averages of raw data from CBECI. TV script run-time is too slow with Daily/Weekly data here.
This requires manual updating once a month for ongoing accuracy.
Moving Average Multipliers MTF (Mescu)Includes 4 customizable Moving Average with multipliers and multi-timeframe (MTF).
Tweaks the parameters to your liking, it should be pretty simple to understand
Used here with BTC/USD (1W) to identify good sell and buy zone for Bitcoin.
Got the idea from the 2-year MA Multiplier indicator, but didn't find something of my liking on TradingView, so I made my own.
Drop me a comment if you have any questions, suggestions, improvements.
Mescu
www.tradingview.com
BTC Spot/Futures Volume RatioShows the ratio between the spot trading volume versus futures trading volume for Bitcoin. This ratio may be interpreted as how active the market currently is, and may lead to various interpretations. For example, when the price is at a high level and this ratio gradually decreases, it may imply the end of the distribution phase; when the price is low and the ratio is at the bottom, it may imply the bottom of the price.
V/T Ratio: Onchain BTC MetricThis is a New Onchain metric that is designed for bitcoin by myself Mjshahsavar (Ghoddusifar), and it is published for the first time in this trading view in this post.
I think this metric has a very high capability to determine the ATH and bottom of the market. This metric can solve a problem that channels are unable to solve. this could be the equivalent of what is known in the stock market as P/E
Calculations:
V/T RATIO = MA (7) of Log ((THE TOTAL VOLUME OF BITCOIN TRANSFERRED ONCHAIN IN USD)/(THE TOTAL AMOUNT OF TRANSACTIONS))
INTERPRETATION:
What is the long-term price channel of Bitcoin? Have you ever thought that maybe drawing a price channel is not right and maybe we should look for something else?
Channel drawing for the price is a subjective and interpretive subject. Look at the charts below, they are all correct in terms of drawing, but no one can say which one will happen. There is no certainty because drawing them is objective.
But who can say which one will definitely work?
We need something more objective. I think V/T Ratio does that.
Just draw the channel. There is only one channel for it. And it has worked historically well to this day.
Compare the drawn channel with the price chart. It works right. When the metric reaches the top line of the channel, it indicates the new ATH and the end of the cycle.
When it reaches the bottom line of the channel, it indicates that the price has reached the bottom.
A Market Cycle:
According to this metric, the bitcoin cycle has 5 stages:
1- Bottom Price: which V/T Ratio touches the bottom line of the channel: In this case, we expect the price to reach the bottom.
2- Semi-high price: that the metric reaches the middle line of the channel: In this case, Bitcoin creates a local top in the MID-Term and Long-Term timeframes
3- Semi-low price: which has a metric return to the lower part of the channel (but the price can still increase)
4- ATH: that Bitcoin reaches its highest historical price
5- It starts after the ATH until the metric reaches the bottom part of the channel again.
RSI Cor Bias [Moto]Hello traders,
This is a pretty simple script. It gives a background directional bias color respective to RSI levels from input thresholds in the settings. Users can choose the upper and lower thresholds and the symbol that the RSI is from.
For example, by default, the upper threshold is 52 and the lower 48. If Bitcoins RSi is above 52, the background color will be green, below 48 it's pink, between and no color will be applied.
Generally, buying should be occurring in pink to green transition or in green, and conversely selling should be occurring in green to pink transition or in pink.
Thanks,
Moto
Macro EMA Correlation
This script is useful to see correlation between macroeconomic assets, displayed in different ema line shown in percentage to compare these assets on the same basis. Percentage will depend on the time frame selection. In the higher timeframe you will see higher variation and in small timeframe smaller variation.
You can select the timeframe who suit your trading style. The 1h and 4h fit well for longer trend swing trade and the lower time frame 15m, 5m, 1m are good for scalping or daily trading.
The following asset are available:
Bitcoin
Ethereum
Gold
Crypto total market cap excluding bitcoin (total2)
United state 10-year government bond (US10Y)
Usdt dominance show the concentration of usdt hold. For example, when trader are fearful they sell their crypto position to keep more usdt in their portfolio (USDT.D)
The USD/JPY pair the dollar usd versus the Japanese Yen one of the most forex traded pair.
You can clic on parameter to select the asset you want to analyse.
The main correlation observed are:
bitcoin negatively correlated with the usdt dominance.
bitcoin negatively correlated with the usd/jpy pair
bitcoin is positively correlated to eth, total2 (altcoin)
bitcoin positively correlated with gold
bitcoin is mostly negatively correlated to us10y
The basis of correlation is that positively correlated asset goes in the same direction and that the negatively correlated goes in opposite direction.
So, the idea is to use these information to see trend reversing.
Example 1: when bitcoin and usdt dominance are extended in opposite direction we look for a possible retracement toward 1% wich is the middle base.
Example 2 : when bitcoin make a move we look for ethereum and total 2 to follow
Fusion: Big Arty CandlesAnyone who follows Arty knows about his "Big A** Candle" strategies.
I didn't like the BAC indicators that had code available so I wrote this one that has some decent flexibility and display options.
You can use this to enter a trade immediately after a BAC, probably in the opposite direction and ride the pullback that usually occurs or just use it to avoid trading until things settle down. I use it to avoid trading for a few bars on the 15 minute timeframe on bitcoin.
The settings are certainly not optimized so set them to whatever suits your needs as the defaults will probably be wrong for you.
The code is structured to easily drop into a bigger system so use it as a lone indicator or add the code to some bigger project you are creating. If you do integrate it into something else then send me a note as it would be nice to know it's being well used.
Finally, if you find value please do make a comment, give a thumbs up etc.
Enjoy and good luck!
