Degen Dominator - (Crypto Dominance Tool) - [mutantdog]A fairly simple one this time. Another crypto dominance tool, consider it a sequel to Dominion if you will. Ready to go out-of-the-box with a selection of presets at hand.
The premise is straightforward, rather than viewing the various marketcap dominance indexes as their standard percentage values, here we have them represented as basic oscillators. This allows for multiple indexes to be viewed in one pane and gives a decent overview of their relative changes and thus the flow of capital within the overall crypto market. As a general rule-of-thumb, when a plot is above zero then the dominance is climbing, thus capital is likely flowing in that direction. The inverse applies when below zero. When the market is quiet, all will be close to zero. Basic overbought/oversold conditions can also be inferred too.
Active as default are:
Bitcoin (0range): CRYPTOCAP:BTC.D
Ethereum (Blue): CRYPTOCAP:ETH.D
Stablecoins (Red): CRYPTOCAP:USDT.D + CRYPTOCAP:USDC.D
Altcoins (Green): 100 - (all of the above)
These are plotted according to the selected oscillator preset and it's length parameter. The default is set to 'EMA Centre'. An optional RMA(3) smoothing filter is also included and active as default. Each index plot has its own colour and opacity settings available on the main page.
Additionally, the following are also available (deactivated as default):
Total DeFi : CRYPTOCAP:TOTALDEFI.D
Current Symbol : Will try to match corresponding dominance index for the chart symbol if available.
Custom Input : Manual text input, will try to match if available.
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The included presets determine the oscillator type used, all are fairly simple and easy to interpret:
EMA Centre
SMA Centre
Median Centre
Midrange Centre
The first 4 are all variations on the same theme, simply calculated as the difference between the actual value and its respective average. EMA is the default and is my personal preference, if you generally favour using an SMA then perhaps that would be your better choice. Like the two MAs, median and midrange are also dependant on the length parameter. Midrange is calculated from the difference between highest and lowest values within the length period, with a little extra smoothing from an RMA(3).
Simple Delta
Weighted Delta
Running Delta
Often referred to as momentum, delta is just change over time. 'Simple' is the most basic of these, the difference between the current value and the value (length) bars prior. A more long-winded way of calculating this would be to take the difference between each bar and its previous then average them with an SMA which results in the same value. 'Weighted' adopts that principle but instead uses a WMA, likewise 'Running' is the same but using an RMA. The latter is actually the basis of RSI calculations before any normalisation is applied, as you can see in the next preset.
RSI
CMO
RSI really should not need explaining, it is however applied a little differently here to the usual, in this case centred around 0. The x100 multiplication factor has been dropped too for the sake of consistency. The same principle applies with CMO, which is basically a 'Simple Delta' version of RSI.
Hard Floor
Soft Floor
These last two are a little different but both can provide useful interpretations. The floor here is simply the lowest value within the chosen length period. 'Hard' plots the difference between the current value and the floor, thus giving a value that is always above 0. In this case, focus should be given to the relative heights of each with a simple interpretation that capital is flowing into those that are climbing and out of those descending. 'Soft' is essentially the same except that the floor is smoothed with an RMA(3), the result being that when new lows are made, the plot will break below 0 before the floor corrects a few bars later. This soft break provides additional information to that given by 'Hard' so is probably the more useful of the two.
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To finish it off, a bunch of preset alerts are included for the various 0 crossings.
So that just about covers everything then, all quite straightforward really. Future updates may include some extra stuff, the composition of the stablecoin index may change if necessary too. While this is not really a tweaker's tool like some of my other projects, there's still some room for experimentation here. The 'current' and 'custom' indexes can provide some useful data for compatible altcoins and the possibility to compare inter-related tokens (eg: Doge vs Shib). While i introduced this as a sort of sequel to Dominion, it is not intended as a replacement but more of a companion. This initially started as a feature intended for that one but it quickly grew into its own thing. Both the oscillator view here and the more traditional view have merits, i personally use this one primarily now but frequently refer to Dominion for confirmations etc.
That's it for now anyway. As always, feedback is welcome below. Enjoy!
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BTC Performance Table / BTC Seasonality Visualization
This script visualizes Bitcoins "seasonality", in form of a colored table (based on the idea from "BigBangTheory")
The history table shows you which months do statistically perform better/worse in comparison to other months.
How to use this script:
Choose ticker "BLX" ("BraveNewCoin Liquid Index for Bitcoin").
Set the charts time frame to weekly or daily. Tables position on the screen and its colors are configurable.
Table explanation:
Cells show whether a gain or a loss occured from month to month, since BTC came out in 2010.
The price difference, between monthly open and monthly close, determines the cell color (negative -> red, positive -> green).
The year column shows total gain (green) or loss (red) for that particular year.
Each value is presented as a rounded percentage number.
How this script works:
The script calculates the price difference between each monthly and yearly open and close, storing those numbers inside arrays.
Then it populates the table, by using those numbers and doing the cell coloring (there will be a yellow cell, in case no change should occur).
German Short-Description
Prozentuale Übersicht in Tabellenform, der monatlichen, sowie jährlichen, Performance des Bitcoin (basierend auf der Idee von "BigBangTheory").
Hierdurch wird die "Saisonalität" des Bitcoin sichtbar. D.h. welche Monate des Jahres, im Vergleich zu anderen Monaten, statistisch gesehen öfter positiv/negativ schließen.
Zwecks vollständiger Darstellung muss der Ticker "BLX" ("BraveNewCoin Liquid Index for Bitcoin") im weekly oder daily time frame aktiv sein. Indicator
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VWMA/SMA 3Commas BotThis strategy utilizes two pairs of different Moving Averages, two Volume-Weighted Moving Averages (VWMA) and two Simple Moving Averages (SMA).
There is a FAST and SLOW version of each VWMA and SMA.
The concept behind this strategy is that volume is not taken into account when calculating a Simple Moving Average.
Simple Moving Averages are often used to determine the dominant direction of price movement and to help a trader look past any short-term volatility or 'noise' from price movement, and instead determine the OVERALL direction of price movement so that one can trade in that direction (trend-following) or look for opportunities to trade AGAINST that direction (fading).
By comparing the different movements of a Volume-Weighted Moving Average against a Simple Moving Average of the same length, a trader can get a better picture of what price movements are actually significant, helping to reduce false signals that might occur from only using Simple Moving Averages.
The practical applications of this strategy are identifying dominant directional trends. These can be found when the Volume Weighted Moving Average is moving in the same direction as the Simple Moving Average, and ideally, tracking above it.
This would indicate that there is sufficient volume supporting an uptrend or downtrend, and thus gives traders additional confirmation to potentially look for a trade in that direction.
One can initially look for the Fast VWMA to track above the Fast SMA as your initial sign of bullish confirmation (reversed for downtrending markets). Then, when the Fast VWMA crosses over the Slow SMA, one can determine additional trend strength. Finally, when the Slow VWMA crosses over the Slow SMA, one can determine that the trend is truly strong.
Traders can choose to look for trade entries at either of those triggers, depending on risk tolerance and risk appetite.
Furthermore, this strategy can be used to identify divergence or weakness in trending movements. This is very helpful for identifying potential areas to exit one's trade or even look for counter-trend trades (reversals).
These moments occur when the Volume-Weighted Moving Average, either fast or slow, begins to trade in the opposite direction as their Simple Moving Average counterpart.
For instance, if price has been trending upwards for awhile, and the Fast VWMA begins to trade underneath the Fast SMA, this is an indication that volume is beginning to falter. Uptrends need appropriate volume to continue moving with momentum, so when we see volume begin to falter, it can be a potential sign of an upcoming reversal in trend.
Depending on how quickly one wants to enter into a movement, one could look for crosses of the Fast VWMA under/over the Fast SMA, crosses of the Fast VWMA over/under the Slow SMA, or crosses over/under of the Slow VWMA and the Slow SMA.
This concept was originally published here on PulseWire by ProfitProgrammers.
Here is a link to his original indicator script:
I have added onto this concept by:
converting the original indicator into a strategy tester for backtesting
adding the ability to conveniently test long or short strategies, or both
adding the ability to calculate dynamic position sizes
adding the ability to calculate dynamic stop losses and take profit levels using the Average True Range
adding the ability to exit trades based on overbought/oversold crosses of the Stochastic RSI
conveniently switch between different thresholds or speeds of the Moving Average crosses to test different strategies on different asset classes
easily hook this strategy up to 3Commas for automation via their DCA bot feature
Full credit to ProfitProgrammers for the original concept and idea.
Any feedback or suggestions are greatly appreciated.
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Trend Following based on Trend ConfidenceThis is a Trend Following strategy based on the Trend Confidence indicator.
The goal of this strategy is to be a simple Trend Following strategy, but also to be as precise as possible when it comes to the question 'how confident are we that a linear trend is ongoing?'. For this we calculate the 'confidence' of a linear trend in the past number of closing prices. The idea of this strategy is that past a certain confidence, the ongoing linear trend is more likely to continue than not.
Trend Confidence:
The Trend Confidence shows us how strong of a linear trend the price has made in the past number (given by Length parameter) of closing prices. The steepness of the price change makes the Trend Confidence more extreme (more positive for an uptrend or more negative for a downtrend), and the deviation from a straight line makes the Trend Confidence less extreme (brings the confidence closer to 0). This way we can filter out signals by wild/sudden price moves that don't follow a clear linear trend.
Math behind the Trend Confidence:
A linear fit is made on the past number of closing prices, using Ordinary Linear Regression. We have the steepness of the linear fit: b in y=a+bx . And we have the standard deviation of the distances from the closing prices to the linear fit: sd . The Trend Confidence is the ratio b/sd .
Entries and Exits:
For entry and exit points we look at how extreme the Trend Confidence is. The strategy is based on the assumption that past a certain confidence level, the ongoing linear trend is more likely to continue than not.
So when the Trend Confidence passes above the 'Long entry" threshold, we go Long. After that when the Trend Confidence passes under the 'Long exit' threshold, we exit. The Long entry should be a positive value so that we go Long once a linear uptrend with enough confidence has been detected.
When the Trend Confidence passes below the 'Short entry' threshold, we go Short. After that when the Trend Confidence passes above the 'Short exit' threshold, we exit. The Short entry should be a negative value so that we go Short once a linear downtrend with enough confidence has been detected.
Default Parameters:
The strategy is intended for BTC-USD market, 4 hour timeframe. The strategy also works on ETH-USD with similar parameters.
The Length is arbitrarily set at 30, this means we look at the past 30 closing prices to determine a linear trend. Note that changing the length will change the range of Trend Confidence values encountered.
The default entry and exit thresholds for Longs and Shorts do not mirror each other. This is because the BTC-USD market goes up more heavily and more often than it goes down. So the ideal parameters for Longs and Shorts are not the same.
The positive results of the strategy remain when the parameters are slightly changed (robustness check).
The strategy uses 100% equity per trade, but has a 10% stop loss so that a maximum of 10% is risked per trade.
Commission is set at 0.1% as is the highest commission for most crypto exchanges.
Slippage is set at 5 ticks, source for this is theblock.co.
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Bitcoin Miner Extreme SellingThis script is for identifying extreme selling. Judging by the chart, Bitcoin miners often (not always) sell hard for two reasons: to take profit into parabolic price rises, or to stay solvent when the price is very low.
Extreme selling thus often coincides with long-term tops and bottoms in Bitcoin price. This can be a useful EXTRA data point when trying to time long-term Bitcoin spot or crypto equity investment (NOT advice, you remain responsible, etc). The difference between selling measured in BTC and in USD gives a reasonable idea of whether miners are selling to make a profit or to stay solvent.
CREDITS
The idea for using the ratio of miner outflows to reserves comes from the "Bitcoin Miner Sell Pressure" script by the pioneering capriole_charles.
The two request.security calls are identical. Another similarity is that you have to sum the outflows to make it make sense. But it doesn't make much difference, it turns out from testing, to use an average of the reserves, so I didn't. All other code is different.
The script from capriole_charles uses Bollinger bands to highlight periods when sell pressure is high, uses a rolling 30-day sum, and only uses the BTC metrics.
My script uses a configurable 2-6 week rolling sum (there's nothing magical about one month), uses different calculations, and uses BTC, USD, and composite metrics.
INPUTS
Rolling Time Basis : Determines how much data is rolled up. At the lowest level, daily data is too volatile. If you choose, e.g., 1 week, then the indicator displays the relative selling on a weekly basis. Longer time periods, obviously, are smoother but delayed, while shorter time periods are more reactive. There is no "real" time period, only an explicit interpretation.
Show Data > Outflows : Displays the relative selling data, along with a long-term moving average. You might use this option if you want to compare the "real" heights of peaks across history.
Show Data > Delta (the default): Only the difference between the relative selling and the long-term moving average is displayed, along with an average of *that*. This is more signal and less noise.
Base Currency : Configure whether the calculations use BTC or USD as the metric. This setting doesn't use the BTC price at all; it switches the data requested from INTOTHEBLOCK.
If you choose Composite (the default), the script combines BTC and USD together in a relative way (you can't simply add them, as USD is a much bigger absolute value).
In Composite mode, the peaks are coloured red if BTC selling is higher than USD, which usually indicates forced selling, and green if USD is higher, which usually indicates profit-taking. This categorisation is not perfectly accurate but it is interesting insomuch as it is derived from block data and not Bitcoin price.
In BTC or USD mode, a gradient is used to give a rough visual idea of how far from the average the current value is, and to make it look pretty.
USAGE NOTES
Because of the long-term moving averages, the length of the chart does make a difference. I recommend running the script on the longest Bitcoin chart, ticker BLX.
To use it to compare selling with pivots in crypto equities, use a split chart: one BLX with the indicator applied, and one with the equity of your choice. Sync Interval, Crosshair, Time, and Date Range, but not Symbol.
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Cheat Code's RedemptionWELCOME TO THE CHEAT CODE REDEMPTION PACK!!!!
I want to take a deep dive into what this indicator consists of and how you can use it to improve your trading strategy.
-What does the CCR consist of?
The Oscillator:
The oscillator is a combination of a true strength index sampled from on-balance volume and a regular RSI at default settings. The reason I added the on-balance volume is that it does not tend to remain at overbought or oversold conditions as traditional momentum oscillators do.
The Histogram:
The histogram is copied to a tee from the MACD histogram, the only difference here is that I extended the moving averages to depict a special pairing; the ema55 slow and ema21 fast. I then converted it into another true strength index, as the calculations fit all time frames.
The Divergences:
The divergences of an indicator can be extremely useful in catching scalp opportunities, a DARK RED/GREEN represents a REGULAR divergence, while a SALMON/LIGHT GREEN color represents a HIDDEN divergence.
The moving average:
The moving average built into this indicator is depicted as an aqua or yellow line, when the oscillator is moving in an uptrend, the moving average will appear aqua, when the oscillator is in a downtrend it will appear yellow. Use this as confirmation bias or as the third derivative of market position.
Oscillator Colors:
The Oscillator color is an important thesis of this indicator. When the line is green, it means the market is effectively in an uptrend, when it is red, it means the market is in a downtrend. Use this to prevent longing in a serious downtrend and vice versa.
If you have any questions regarding the indicator(s), feel free to reach out to me in the comments or through Direct Message!!!
Safe Trading, Don't get Rekt
- CheatCode1 <3 Indicator
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