Extended Recursive Bands StrategyThe original indicator was created by alexgrover .
All credit goes to alexgrover for creating the indicator that this strategy uses.
This strategy was posted because there were multiple requests for it, and no strategy based on this indicator exists yet.
The Recursive Bands Indicator, an indicator specially created to be extremely efficient, I think you already know that calculation time is extra important in algorithmic trading, and this is the principal motivation for the creation of the proposed indicator. Originally described in Alex's paper "Pierrefeu, Alex (2019): Recursive Bands - A New Indicator For Technical Analysis", the indicator framework has been widely used in his previous uploaded indicators, however it would have been a shame to not upload it, however user experience being a major concern for me, I decided to add extra options, which explain the term "extended".
The Indicator
The indicator displays one upper and one lower band, every common usages applied to bands indicators such as support/resistance , breakout, trailing stop, etc, can also be applied to this one. Length controls how reactive the bands are, higher values will make the bands cross the price less often.
In order to provide more flexibility for the user alexgrover added the option to use various methods for the calculation of the indicator, therefore the indicator can use the average true range , standard deviation, average high-low range, and one totally exclusive method specially designed for this indicator.
Added logic:
We have implemented a logic that checks whether the bands have been following in the same direction for a set amount of bars. This logic must be true before it can enter trades. This is completely new code that was written by us entirely, and it makes a huge difference on strategy performance.
Strategy Long conditions:
1 — Price low is below the the lower band.
2 — The lower band keeps increasing in value until the 'lookback' setting amount of bars is reached.
Strategy Short conditions:
1 — Price high is above the upper band.
2 — The upper band keeps decreasing in value until the 'lookback' setting amount of bars is reached.
Strategy Properties:
We have set a default commission of 0.06% because these are Bybit's fees. The strategy uses an order size of 10% of equity, since drawdown is very low like this. We also use a 10 tick slippage to keep results realistic and account for this. All other settings were left as default apart from initial capital, just to decrease the size of the numbers.
Trend-analysis
Relative Bi-Directional Volatility RangeThe basic math behind this Indicator is very similar to the math behind the Relative Strength Index without using a standard deviation as used for the Relative Volatility Index. The Volatility Range is calculated by utilizing the highs and lows. However not in the same way as in the Relative Volatility Index. This approach leads to different values, but the overall result clearly reveals the intrinsic Volatility of the chart, so the user can be aware, when something fundamentally is going on behind the scenes. If the Volatility rises on positive and negative range (-100 to 100) it implies that something fundamental is changing.
An advantage of using this kind of calculation is the possibility of separating the data into positive (buy pressure) and negative (sell pressure) components. The bi-directional character shows a slightly overhang in one of the directions, which can be used to detect a trend. A Moving Average of the users choice shell smoothen the overhang of the Relative Bi-Directional Volatility and show a trend direction. Similar to the math of the Relative Strength Index as standard a Relative Moving Average is preferred. If the Moving Average is in the positive range (0 to 100) it indicates a bullish trend, else if the Moving Average is in the negative range (0 to -100) it indicates a bearish trend. External Indicators can use a provided Trend Shift Signal which switches from 0 to 1, if the trend becomes bullish or from 0 to -1, if the trend becomes bearish.
The user should know, that in this Indicator the starting point of the Moving Averages always begins at the first bar, because the starting progress is approximated appropriately. Most Moving Averages require a minimum number of bars to be calculated, which is chosen with the Moving Average Length. In this cases the length used will be automatically reduced in the background until the number of bars is sufficient to match the chosen length. So if data history is very short, the Indicator can be used never the less as good as possible.
It is feasible to switch the Indicator on a higher timeframe, while staying in a lower timeframe on the chart. This can be useful for making the indication cleaner, if the Moving Average is to choppy and shows too many false signals. On the other hand the benefit of a higher timeframe (or a higher Moving Average Length) is paid with higher latency of the signaling. So the user has to decide what the best setting in his case is.
This Indicator can be used with all kinds of charts. Even charts with percentage or negative values should work fine.
Trend IdentifierTrend Identifier for 1D BTC.USD
It smoothens a closely following moving average into a polynomial like plot.
And assumes 4 stage cycles based on the first and second derivatives.
Green: Bull / Exponential Rise
Yellow: Distribution
Red: Bear / Exponential Drop
Blue: Accumulation
Red --> Blue --> Green: indicates the start of a bull market
Green --> Yellow --> Red: indicates the start of a bear market
Green --> Yellow: Start of a distribution phase, take profits
Red --> Blue: Start of a accumulation phase, DCA
Bitcoin Movement vs. Coin's Movement MTFThis script tracks the percent change of Bitcoin vs. the percent change of the coin on the chart. Crypto markets are usually affected greatly by Bitcoin swings so being able to see if the given coin is trending above or below Bitcoin is useful market data. All choices made with this script are your own! Thanks.
Supertrend LSMA long StrategyThis is a long strategy which combines Super trend indicator with LSMA moving average.
In general it tends to works better with long trending markets such as stocks and cryptos using a big timeframe.
The rules are simple
Long entry:
Supertrend is telling us to go long and close of a candle is above moving average
Long exit:
Supertrend is telling us to go short
IF you have any questions, let me know !
Statistical and Financial MetricsGood morning traders!
This time I want to share with you a little script that, thanks to the use of arrays, allows you to have interesting statistical and financial insights taken from the symbol on chart and compared to those of another symbol you desire (in this case the metrics taken from the perpetual future ETHUSDT are compared to those taken from the perpetual future BTCUSDT, used as a proxy for the direction of cryptocurrency market)
By enabling "prevent repainting", the data retrieved from the compared symbol won't be on real time but they will static since they will belong to the previous closed candle
Here are the metrics you can have by storing data from a variable period of candles (by default 51):
✓ Variance (of the symbol on chart in GREEN; of the compared symbol in WHITE)
✓ Standard Deviation (of the symbol on chart in OLIVE; of the compared symbol in SILVER)
✓ Yelds (of the symbol on chart in LIME; of the compared symbol in GRAY) → yelds are referred to the previous close, so they would be calculated as the the difference between the current close and the previous one all divided by the previous close
✓ Covariance of the two datasets (in BLUE)
✓ Correlation coefficient of the two datasets (in AQUA)
✓ β (in RED) → this insight is calculated in three alternative ways for educational purpose (don't worry, the output would be the same).
WHAT IS BETA (β)?
The BETA of an asset can be interpretated as the representation (in relative terms) of the systematic risk of an asset: in other terms, it allows you to understand how big is the risk (not eliminable with portfolio diversification) of an asset based on the volatilty of its yelds.
We say that this representation is made in relative terms since it is expressed according to the market portfolio: this portfolio is hypothetically the portfolio which maximizes the diversification effects in order to kill all the specific risk of that portfolio; in this way the standard deviation calculated from the yelds of this portfolio will represent just the not-eliminable risk (the systematic risk), without including the eliminable risk (the specific risk).
The BETA of an asset is calculated as the volatilty of this asset around the volatilty of the market portfolio: being more precise, it is the covariance between the yelds of the current asset and those of the market portfolio all divided by the variance of the yelds of market portfolio.
Covariance is calculated as the product between correlation coefficient, standard deviation of the first dataset and standard deviation of the second asset.
So, as the correlation coefficient and the standard deviation of the yelds of our asset increase (it means that the yelds of our asset are very similiar to those of th market portfolio in terms of sign and intensity and that the volatility of these yelds is quite high), the value of BETA increases as well
According to the Capital Asset Pricing Model (CAPM) promoted by William Sharpe (the guy of the "Sharpe Ratio") and Harry Markowitz, in efficient markets the yeld of an asset can be calculated as the sum between the risk-free interest rate and the risk premium. The risk premium of the specific asset would be the risk premium of the market portfolio multiplied with the value of beta. It is simple: if the volatility of the yelds of an asset around the yelds of market protfolio are particularly high, investors would ask for a higher risk premium that would be translated in a higher yeld.
In this way the expected yeld of an asset would be calculated from the linear expression of the "Security Market Line": r_i = r_f + β*(r_m-r_f)
where:
r_i = expected yeld of the asset
r_f = risk free interest rate
β = beta
r_m = yeld of market portfolio
I know that considering Bitcoin as a proxy of the market portfolio involved in the calculation of Beta would be an inaccuracy since it doesn't have the property of maximum diversification (since it is a single asset), but there's no doubt that it's tying the prices of altcoins (upward and downward) thanks to the relevance of its dominance in the capitalization of cryptocurrency market. So, in the lack of a good index of cryptocurrencies (as the FTSE MIB for the italian stock market), and as long the dominance of Bitcoin will persist with this intensity, we can use Bitcoin as a proxy of the market portfolio
Consolidation Ranges [kingthies] Consolidation Range Analysis
Published by Eric Thies, January 2021
█ Indicator Summary
This tool calculates, analyzes and plots the visualization of a relative range over a given period of time
By adding to charts, users are enabled to see the impulsive nature of market cycles, along with their efforts to consolidate thereafter
The default period is 30, and should be adjusted to users preference
The default input is the current close price, on the chosen timeframe of the chart
█ Script Source
//
//@version=4
//© kingthies || This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
study("Consolidation Ranges ", shorttitle="CR ", overlay=true)
// !<------ User Inputs ----->
src = input(close, title='Range Input (Default set to Close'), lengthEMA=input(30,title='Length'),zoneToggle = input(true, title="Toggle Zone Highlights"), iCol = color.new(#FFFFFF, 100),
// !<---- Declarations & Calculations ---- >
trndUp = float(na),trndDwn = float(na), mid = float(na), e = ema(src, lengthEMA)
trndUp := src < nz(trndUp ) and src > trndDwn ? nz(trndUp ) : high, trndDwn := src < nz(trndUp ) and src > trndDwn ? nz(trndDwn ) : low, mid := avg(trndUp, trndDwn)
// !< ---- Plotting ----->
highRange = plot(trndUp == nz(trndUp ) ? trndUp : na, color=color.white, linewidth=2, style=plot.style_linebr, title="Top of Period Range")
lowRange = plot(trndDwn == nz(trndDwn ) ? trndDwn : na, color=color.white, linewidth=2, style=plot.style_linebr, title="Bottom of Period Range")
xzone = plot(zoneToggle ? src > e ? trndDwn : trndUp : na, color=iCol, style=plot.style_circles, linewidth=0, editable=false)
fill(highRange, xzone, color=color.lime,transp=70), fill(xzone, lowRange, color=color.red,transp=70)
//
Colored VolumeThe height represents total volume, the ratio of red to green represents the bullish/bearish volume. AKA buyers or sellers.
Krowns 10 PACK Combo (5 EMAs, 5 SMAs) - v2Version 2 - Krowns Crypto 10 pack moving average set - written by "Kick Back Time" also known as Mr.Scrogers Neighborhood
...after receiving a lot of likes from the first version I thought I would go ahead and put out the updated version that I've been using
There's a few things I've changed to make it easier to adapt to.
This set is very similar to what Krown uses - I rarely look at the 100 SMA, but I do like the 128 SMA, so I made it default over the 100...
It's all adjustable in values, colors, line thicknesses, etc... it's all good
Tweeks/Improvements:
1) now has a shorter overlay title so it takes up less space on the chart and is less distractive
2) the 30, 50 and 128 SMA's are now default pink which stand out well and are easier to associate as SMA's
The Block IndicatorThis indicator finds Mondays and Wednesdays and draws a vertical line, so you can easy do your bias or trend analysis.
Options
You can turn off/on the Wednesday's line.
[RS]Moving Average Trend Expansion Analysis V0experimental: analyzing the differences between price closure and multiple moving averages to discern movement and direction of market.
upper signal is the long trend, while the lower signal symbolizes faster movements within the trend.
