Adaptivity: Measures of Dominant Cycles and Price Trend [Loxx]Adaptivity: Measures of Dominant Cycles and Price Trend is an indicator that outputs adaptive lengths using various methods for dominant cycle and price trend timeframe adaptivity. While the information output from this indicator might be useful for the average trader in one off circumstances, this indicator is really meant for those need a quick comparison of dynamic length outputs who wish to fine turn algorithms and/or create adaptive indicators.
This indicator compares adaptive output lengths of all publicly known adaptive measures. Additional adaptive measures will be added as they are discovered and made public.
The first released of this indicator includes 6 measures. An additional three measures will be added with updates. Please check back regularly for new measures.
Ehers:
Autocorrelation Periodogram
Band-pass
Instantaneous Cycle
Hilbert Transformer
Dual Differentiator
Phase Accumulation (future release)
Homodyne (future release)
Jurik:
Composite Fractal Behavior (CFB)
Adam White:
Veritical Horizontal Filter (VHF) (future release)
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman's adaptive moving average (KAMA) and Tushar Chande's variable index dynamic average (VIDYA) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index (RSI), commodity channel index (CCI), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
What is this Hilbert Transformer?
An analytic signal allows for time-variable parameters and is a generalization of the phasor concept, which is restricted to time-invariant amplitude, phase, and frequency. The analytic representation of a real-valued function or signal facilitates many mathematical manipulations of the signal. For example, computing the phase of a signal or the power in the wave is much simpler using analytic signals.
The Hilbert transformer is the technique to create an analytic signal from a real one. The conventional Hilbert transformer is theoretically an infinite-length FIR filter. Even when the filter length is truncated to a useful but finite length, the induced lag is far too large to make the transformer useful for trading.
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, pages 186-187:
"I want to emphasize that the only reason for including this section is for completeness. Unless you are interested in research, I suggest you skip this section entirely. To further emphasize my point, do not use the code for trading. A vastly superior approach to compute the dominant cycle in the price data is the autocorrelation periodogram. The code is included because the reader may be able to capitalize on the algorithms in a way that I do not see. All the algorithms encapsulated in the code operate reasonably well on theoretical waveforms that have no noise component. My conjecture at this time is that the sample-to-sample noise simply swamps the computation of the rate change of phase, and therefore the resulting calculations to find the dominant cycle are basically worthless.The imaginary component of the Hilbert transformer cannot be smoothed as was done in the Hilbert transformer indicator because the smoothing destroys the orthogonality of the imaginary component."
What is the Dual Differentiator, a subset of Hilbert Transformer?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 187:
"The first algorithm to compute the dominant cycle is called the dual differentiator. In this case, the phase angle is computed from the analytic signal as the arctangent of the ratio of the imaginary component to the real component. Further, the angular frequency is defined as the rate change of phase. We can use these facts to derive the cycle period."
What is the Phase Accumulation, a subset of Hilbert Transformer?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 189:
"The next algorithm to compute the dominant cycle is the phase accumulation method. The phase accumulation method of computing the dominant cycle is perhaps the easiest to comprehend. In this technique, we measure the phase at each sample by taking the arctangent of the ratio of the quadrature component to the in-phase component. A delta phase is generated by taking the difference of the phase between successive samples. At each sample we can then look backwards, adding up the delta phases.When the sum of the delta phases reaches 360 degrees, we must have passed through one full cycle, on average.The process is repeated for each new sample.
The phase accumulation method of cycle measurement always uses one full cycle's worth of historical data.This is both an advantage and a disadvantage.The advantage is the lag in obtaining the answer scales directly with the cycle period.That is, the measurement of a short cycle period has less lag than the measurement of a longer cycle period. However, the number of samples used in making the measurement means the averaging period is variable with cycle period. longer averaging reduces the noise level compared to the signal.Therefore, shorter cycle periods necessarily have a higher out- put signal-to-noise ratio."
What is the Homodyne, a subset of Hilbert Transformer?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 192:
"The third algorithm for computing the dominant cycle is the homodyne approach. Homodyne means the signal is multiplied by itself. More precisely, we want to multiply the signal of the current bar with the complex value of the signal one bar ago. The complex conjugate is, by definition, a complex number whose sign of the imaginary component has been reversed."
What is the Instantaneous Cycle?
The Instantaneous Cycle Period Measurement was authored by John Ehlers; it is built upon his Hilbert Transform Indicator.
From his Ehlers' book Cybernetic Analysis for Stocks and Futures: Cutting-Edge DSP Technology to Improve Your Trading by John F. Ehlers, 2004, page 107:
"It is obvious that cycles exist in the market. They can be found on any chart by the most casual observer. What is not so clear is how to identify those cycles in real time and how to take advantage of their existence. When Welles Wilder first introduced the relative strength index (rsi), I was curious as to why he selected 14 bars as the basis of his calculations. I reasoned that if i knew the correct market conditions, then i could make indicators such as the rsi adaptive to those conditions. Cycles were the answer. I knew cycles could be measured. Once i had the cyclic measurement, a host of automatically adaptive indicators could follow.
Measurement of market cycles is not easy. The signal-to-noise ratio is often very low, making measurement difficult even using a good measurement technique. Additionally, the measurements theoretically involve simultaneously solving a triple infinity of parameter values. The parameters required for the general solutions were frequency, amplitude, and phase. Some standard engineering tools, like fast fourier transforms (ffs), are simply not appropriate for measuring market cycles because ffts cannot simultaneously meet the stationarity constraints and produce results with reasonable resolution. Therefore i introduced maximum entropy spectral analysis (mesa) for the measurement of market cycles. This approach, originally developed to interpret seismographic information for oil exploration, produces high-resolution outputs with an exceptionally short amount of information. A short data length improves the probability of having nearly stationary data. Stationary data means that frequency and amplitude are constant over the length of the data. I noticed over the years that the cycles were ephemeral. Their periods would be continuously increasing and decreasing. Their amplitudes also were changing, giving variable signal-to-noise ratio conditions. Although all this is going on with the cyclic components, the enduring characteristic is that generally only one tradable cycle at a time is present for the data set being used. I prefer the term dominant cycle to denote that one component. The assumption that there is only one cycle in the data collapses the difficulty of the measurement process dramatically."
What is the Band-pass Cycle?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 47:
"Perhaps the least appreciated and most underutilized filter in technical analysis is the band-pass filter. The band-pass filter simultaneously diminishes the amplitude at low frequencies, qualifying it as a detrender, and diminishes the amplitude at high frequencies, qualifying it as a data smoother. It passes only those frequency components from input to output in which the trader is interested. The filtering produced by a band-pass filter is superior because the rejection in the stop bands is related to its bandwidth. The degree of rejection of undesired frequency components is called selectivity. The band-stop filter is the dual of the band-pass filter. It rejects a band of frequency components as a notch at the output and passes all other frequency components virtually unattenuated. Since the bandwidth of the deep rejection in the notch is relatively narrow and since the spectrum of market cycles is relatively broad due to systemic noise, the band-stop filter has little application in trading."
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 59:
"The band-pass filter can be used as a relatively simple measurement of the dominant cycle. A cycle is complete when the waveform crosses zero two times from the last zero crossing. Therefore, each successive zero crossing of the indicator marks a half cycle period. We can establish the dominant cycle period as twice the spacing between successive zero crossings."
What is Composite Fractal Behavior (CFB)?
All around you mechanisms adjust themselves to their environment. From simple thermostats that react to air temperature to computer chips in modern cars that respond to changes in engine temperature, r.p.m.'s, torque, and throttle position. It was only a matter of time before fast desktop computers applied the mathematics of self-adjustment to systems that trade the financial markets.
Unlike basic systems with fixed formulas, an adaptive system adjusts its own equations. For example, start with a basic channel breakout system that uses the highest closing price of the last N bars as a threshold for detecting breakouts on the up side. An adaptive and improved version of this system would adjust N according to market conditions, such as momentum, price volatility or acceleration.
Since many systems are based directly or indirectly on cycles, another useful measure of market condition is the periodic length of a price chart's dominant cycle, (DC), that cycle with the greatest influence on price action.
The utility of this new DC measure was noted by author Murray Ruggiero in the January '96 issue of Futures Magazine. In it. Mr. Ruggiero used it to adaptive adjust the value of N in a channel breakout system. He then simulated trading 15 years of D-Mark futures in order to compare its performance to a similar system that had a fixed optimal value of N. The adaptive version produced 20% more profit!
This DC index utilized the popular MESA algorithm (a formulation by John Ehlers adapted from Burg's maximum entropy algorithm, MEM). Unfortunately, the DC approach is problematic when the market has no real dominant cycle momentum, because the mathematics will produce a value whether or not one actually exists! Therefore, we developed a proprietary indicator that does not presuppose the presence of market cycles. It's called CFB (Composite Fractal Behavior) and it works well whether or not the market is cyclic.
CFB examines price action for a particular fractal pattern, categorizes them by size, and then outputs a composite fractal size index. This index is smooth, timely and accurate
Essentially, CFB reveals the length of the market's trending action time frame. Long trending activity produces a large CFB index and short choppy action produces a small index value. Investors have found many applications for CFB which involve scaling other existing technical indicators adaptively, on a bar-to-bar basis.
What is VHF Adaptive Cycle?
Vertical Horizontal Filter (VHF) was created by Adam White to identify trending and ranging markets. VHF measures the level of trend activity, similar to ADX DI. Vertical Horizontal Filter does not, itself, generate trading signals, but determines whether signals are taken from trend or momentum indicators. Using this trend information, one is then able to derive an average cycle length.
חפש סקריפטים עבור "ha溢价率"
ATRvsDTR + ADR Zone + SSS50%This Script is to be used for intra day as far as the adr zones. The adr zones are used as support and resistance but also can be used to determine whether the stock is breaking out or not. Also being that the adr zones are calculated using a 5 or 10 day period unless you change the settings, and are set when price opens. It does really help you know whether a stock is moving more than it does on average to me it just signifies its directional. So I added the atr vs dtr so you can see what a stock moves on average versus what it has moved today.
The atr period is calculated based on the daily period unless you change the settings. I added to the original script 3 more percentages the atr vs dtr will change as it goes higher so that you can be aware when the stock is getting closer to moving 100% of its atr. Even though a stock breaks above or below the adr that doesn't mean it has moved more than it normally moves.
I also have the weekly open on the script as I trade the strat and I want to know, at what price the the week will change from bearish to bullish and vice versa. So that I can understand the trend when I am trading intraday.
The 50% lines were added for Sara strat snipers 50% rule and you can change the timeframes on them. This is used to know whether a candle will go 3. This also can help with retracements vs reversals, because in traditional technical analysis 50% is around where people start think its a reversal more so than a retracement.
I believe the script will be very help as it can show you price being directional but can also let you know when the stock is getting close to moving more than it normally has or if it has moved more than it normally has. As well as being able to see if something is a retracement vs a reversal. I trade TheStrat strategy so this can be very helpful in that regard
The 50% retracement levels are default 1h and daily. You can change them and whether or not they show
In the example chart you can see we are below weekly open which is bearish and you can also see where price reverses out of the upper adr zone. As well as how much of the atr we have moved on this day in time.
RouterOrdersIronLibrary "RouterOrdersIron"
Library for routing orders to the Binance exchange.
MsgDoLongMKT(id, symbol, balance)
Returns json for Iron to buy a symbol for the amount of the balance with market order.
Parameters:
id : ID of your Iron router.
symbol : Symbol for a trade, BTC example
balance : The amount for which to carry out the transaction.
Returns: true
MsgDoShortMKT(id, symbol, balance)
Returns json for Iron to sell a symbol for the amount of the balance with market order.
Parameters:
id : ID of your Iron router.
symbol : Symbol for a trade, BTC example
balance : The amount for which to carry out the transaction.
Returns: true
MsgDoLongLR(id, symbol, balance)
Returns json for Iron to buy a symbol for the amount of the balance. It is set at the best price and is re-set each time if a new price has risen before the application.
Parameters:
id : ID of your Iron router.
symbol : Symbol for a trade, BTC example
balance : The amount for which to carry out the transaction.
Returns: true
MsgDoShortLR(id, symbol, balance)
Returns json for Iron to sell a symbol for the amount of the balance. It is set at the best price and is re-set each time if a new price has risen before the application.
Parameters:
id : ID of your Iron router.
symbol : Symbol for a trade, BTC example
balance : The amount for which to carry out the transaction.
Returns: true
DoLongMKT(id, symbol, balance)
Buy a symbol for the amount of the balance. It is send market order to Iron.
Parameters:
id : ID of your Iron router.
symbol : Symbol for a trade, BTC example
balance : The amount for which to carry out the transaction.
Returns: true
DoShortMKT(id, symbol, balance)
Sell a symbol for the amount of the balance. It is send market order to Iron.
Parameters:
id : ID of your Iron router.
symbol : Symbol for a trade, BTC example
balance : The amount for which to carry out the transaction.
Returns: true
DoLongLR(id, symbol, balance)
Buy a symbol for the amount of the balance. It is set at the best price and is re-set each time if a new price has risen before the application.
Parameters:
id : ID of your Iron router.
symbol : Symbol for a trade, BTC example
balance : The amount for which to carry out the transaction.
Returns: true
DoShortLR(id, symbol, balance)
Sell a symbol for the amount of the balance. It is set at the best price and is re-set each time if a new price has risen before the application.
Parameters:
id : ID of your Iron router.
symbol : Symbol for a trade, BTC example
balance : The amount for which to carry out the transaction.
Returns: true
GetQty(price, balance)
Get Qty for strategy on balance
Parameters:
price : Order price
balance : The amount for which to carry out the transaction.
Returns: Qty for strategy order TV
CANDLE FILTER Todays scripts is based on my Pullback And Rally Candles with other meaningful candles such as Hammers and Dojis.
You can choose which Candles to show on the cart and if you want to candles to appear above or below a moving average.
If you follow my work, you may recognise some of these candles which I'm about to show you however these candles are 1) more refined and 2) has moving average filters.
Ive included a D,6H,1H Candle in this script as on different timeframes - each swing low on average has a different amount of bars within the swing low / swing high so the DPB and RD will only work on the Daily
//Pullback candle
This candle is very powerful when used with simple Price Action such as Market Structure//Demand zones and support zones. (((((WORKS BEST IN UPTRENDS AND BOTTOM OF RANGES)))))
Ive included a D,6H,1H Pullback Candle in this script as on different timeframes - each swing low on average has a different amount of bars within the swing low so the DPB will only work on the Daily
//DAILY PULLBACK (Swing Traders)
snapshot
//4H PULLBACK (Swing Traders)
snapshot
- this signal will produce more signals due to the swing low filter on the 4H
//1H PULLBACK
snapshot
- this signal has been refined due to too many candle displaying in weak areas
!!!IF YOU DONT WANT TO USE PULLBACKS DURING DOWNTRENDS THEN USE THE EMA FILTER TO TURN OFF THE PULLBACKS WHEN PRICE IS BELOW THE MOVING AVERAGE!!!
//Rally candle (My personal Favourite) (((((WORKS BEST IN DOWNTRENDS AND TOP OF RANGES)))))
This candle is very powerful when used with simple Price Action such as Market Structure//Supply zones and Resistance zones.
//DAILY RALLY(Swing Traders)
snapshot
//4H RALLY(Swing Traders)
snapshot
- this signal will produce more signals due to the swing high filter on the 4H
!!!IF YOU DONT WANT TO USE RALLIES DURING UPTRENDSTHEN USE THE EMA FILTER TO TURN OFF THE RALLIES WHEN PRICE IS ABOVE THE MOVING AVERAGE!!!
//POWERFUL DOJIS (INDECISION)
snapshot
We look for indecision in key areas to see if momentum is shifting. When combined with Pullbacks or Rallys - this will enhance the odds of a probably area.
//HAMMERS
snapshot
//MOVING AVERAGES
snapshot
Short EMA = 50
Long EMA = 200
This filter can be used when the market is trending - look out for rejections off the moving averages
Also you can chance the Short And Long EMA to choose which MA cross you want to use
snapshot
ALSO ALL THE CANDLES HAVE A ALERT CONDITIONS WHICH YOU CAN ACCESS - THIS WILL ALERT ANY CANDLE YOU CHOOSE
Please leave a like/comment on this post as this is much appreciated....
Time█ OVERVIEW
This library is a Pine Script™ programmer’s tool containing a variety of time related functions to calculate or measure time, or format time into string variables.
█ CONCEPTS
`formattedTime()`, `formattedDate()` and `formattedDay()`
Pine Script™, like many other programming languages, uses timestamps in UNIX format, expressed as the number of milliseconds elapsed since 00:00:00 UTC, 1 January 1970. These three functions convert a UNIX timestamp to a formatted string for human consumption.
These are examples of ways you can call the functions, and the ensuing results:
CODE RESULT
formattedTime(timenow) >>> "00:40:35"
formattedTime(timenow, "short") >>> "12:40 AM"
formattedTime(timenow, "full") >>> "12:40:35 AM UTC"
formattedTime(1000 * 60 * 60 * 3.5, "HH:mm") >>> "03:30"
formattedDate(timenow, "short") >>> "4/30/22"
formattedDate(timenow, "medium") >>> "Apr 30, 2022"
formattedDate(timenow, "full") >>> "Saturday, April 30, 2022"
formattedDay(timenow, "E") >>> "Sat"
formattedDay(timenow, "dd.MM.yy") >>> "30.04.22"
formattedDay(timenow, "yyyy.MM.dd G 'at' hh:mm:ss z") >>> "2022.04.30 AD at 12:40:35 UTC"
These functions use str.format() and some of the special formatting codes it allows for. Pine Script™ documentation does not yet contain complete specifications on these codes, but in the meantime you can find some information in the The Java™ Tutorials and in Java documentation of its MessageFormat class . Note that str.format() implements only a subset of the MessageFormat features in Java.
`secondsSince()`
The introduction of varip variables in Pine Script™ has made it possible to track the time for which a condition is true when a script is executing on a realtime bar. One obvious use case that comes to mind is to enable trades to exit only when the exit condition has been true for a period of time, whether that period is shorter that the chart's timeframe, or spans across multiple realtime bars.
For more information on this function and varip please see our Using `varip` variables publication.
`timeFrom( )`
When plotting lines , boxes , and labels one often needs to calculate an offset for past or future end points relative to the time a condition or point occurs in history. Using xloc.bar_index is often the easiest solution, but some situations require the use of xloc.bar_time . We introduce `timeFrom()` to assist in calculating time-based offsets. The function calculates a timestamp using a negative (into the past) or positive (into the future) offset from the current bar's starting or closing time, or from the current time of day. The offset can be expressed in units of chart timeframe, or in seconds, minutes, hours, days, months or years. This function was ported from our Time Offset Calculation Framework .
`formattedNoOfPeriods()` and `secondsToTfString()`
Our final two offerings aim to confront two remaining issues:
How much time is represented in a given timestamp?
How can I produce a "simple string" timeframe usable with request.security() from a timeframe expressed in seconds?
`formattedNoOfPeriods()` converts a time value in ms to a quantity of time units. This is useful for calculating a difference in time between 2 points and converting to a desired number of units of time. If no unit is supplied, the function automatically chooses a unit based on a predetermined time step.
`secondsToTfString()` converts an input time in seconds to a target timeframe string in timeframe.period string format. This is useful for implementing stepped timeframes relative to the chart time, or calculating multiples of a given chart timeframe. Results from this function are in simple form, which means they are useable as `timeframe` arguments in functions like request.security() .
█ NOTES
Although the example code is commented in detail, the size of the library justifies some further explanation as many concepts are demonstrated. Key points are as follows:
• Pivot points are used to draw lines from. `timeFrom( )` calculates the length of the lines in the specified unit of time.
By default the script uses 20 units of the charts timeframe. Example: a 1hr chart has arrows 20 hours in length.
• At the point of the arrows `formattedNoOfPeriods()` calculates the line length in the specified unit of time from the input menu.
If “Use Input Time” is disabled, a unit of time is automatically assigned.
• At each pivot point a label with a formatted date or time is placed with one of the three formatting helper functions to display the time or date the pivot occurred.
• A label on the last bar showcases `secondsSince()` . The label goes through three stages of detection for a timed alert.
If the difference between the high and the open in ticks exceeds the input value, a timer starts and will turn the label red once the input time is exceeded to simulate a time-delayed alert.
• In the bottom right of the screen `secondsToTfString()` posts the chart timeframe in a table. This can be multiplied from the input menu.
Look first. Then leap.
█ FUNCTIONS
formattedTime(timeInMs, format)
Converts a UNIX timestamp (in milliseconds) to a formatted time string.
Parameters:
timeInMs : (series float) Timestamp to be formatted.
format : (series string) Format for the time. Optional. The default value is "HH:mm:ss".
Returns: (string) A string containing the formatted time.
formattedDate(timeInMs, format)
Converts a UNIX timestamp (in milliseconds) to a formatted date string.
Parameters:
timeInMs : (series float) Timestamp to be formatted.
format : (series string) Format for the date. Optional. The default value is "yyyy-MM-dd".
Returns: (string) A string containing the formatted date.
formattedDay(timeInMs, format)
Converts a UNIX timestamp (in milliseconds) to the name of the day of the week.
Parameters:
timeInMs : (series float) Timestamp to be formatted.
format : (series string) Format for the day of the week. Optional. The default value is "EEEE" (complete day name).
Returns: (string) A string containing the day of the week.
secondsSince(cond, resetCond)
The duration in milliseconds that a condition has been true.
Parameters:
cond : (series bool) Condition to time.
resetCond : (series bool) When `true`, the duration resets.
Returns: The duration in seconds for which `cond` is continuously true.
timeFrom(from, qty, units)
Calculates a +/- time offset in variable units from the current bar's time or from the current time.
Parameters:
from : (series string) Starting time from where the offset is calculated: "bar" to start from the bar's starting time, "close" to start from the bar's closing time, "now" to start from the current time.
qty : (series int) The +/- qty of units of offset required. A "series float" can be used but it will be cast to a "series int".
units : (series string) String containing one of the seven allowed time units: "chart" (chart's timeframe), "seconds", "minutes", "hours", "days", "months", "years".
Returns: (int) The resultant time offset `from` the `qty` of time in the specified `units`.
formattedNoOfPeriods(ms, unit)
Converts a time value in ms to a quantity of time units.
Parameters:
ms : (series int) Value of time to be formatted.
unit : (series string) The target unit of time measurement. Options are "seconds", "minutes", "hours", "days", "weeks", "months". If not used one will be automatically assigned.
Returns: (string) A formatted string from the number of `ms` in the specified `unit` of time measurement
secondsToTfString(tfInSeconds, mult)
Convert an input time in seconds to target string TF in `timeframe.period` string format.
Parameters:
tfInSeconds : (simple int) a timeframe in seconds to convert to a string.
mult : (simple float) Multiple of `tfInSeconds` to be calculated. Optional. 1 (no multiplier) is default.
Returns: (string) The `tfInSeconds` in `timeframe.period` format usable with `request.security()`.
EMA bands + leledc + bollinger bands trend following strategy v2The basics:
In its simplest form, this strategy is a positional trend following strategy which enters long when price breaks out above "middle" EMA bands and closes or flips short when price breaks down below "middle" EMA bands. The top and bottom of the middle EMA bands are calculated from the EMA of candle highs and lows, respectively.
The idea is that entering trades on breakouts of the high EMAs and low EMAs rather than the typical EMA based on candle closes gives a bit more confirmation of trend strength and minimizes getting chopped up. To further reduce getting chopped up, the strategy defaults to close on crossing the opposite EMA band (ie. long on break above high EMA middle band and close below low EMA middle band).
This strategy works on all markets on all timeframes, but as a trend following strategy it works best on markets prone to trending such as crypto and tech stocks. On lower timeframes, longer EMAs tend to work best (I've found good results on EMA lengths even has high up to 1000), while 4H charts and above tend to work better with EMA lengths 21 and below.
As an added filter to confirm the trend, a second EMA can be used. Inputting a slower EMA filter can ensure trades are entered in accordance with longer term trends, inputting a faster EMA filter can act as confirmation of breakout strength.
Bar coloring can be enabled to quickly visually identify a trend's direction for confluence with other indicators or strategies.
The goods:
Waiting for the trend to flip before closing a trade (especially when a longer base EMA is used) often leaves money on the table. This script combines a number of ways to identify when a trend is exhausted for backtesting the best early exits.
"Delayed bars inside middle bands" - When a number of candle's in a row open and close between the middle EMA bands, it could be a sign the trend is weak, or that the breakout was not the start of a new trend. Selecting this will close out positions after a number of bars has passed
"Leledc bars" - Originally introduced by glaz, this is a price action indicator that highlights a candle after a number of bars in a row close the same direction and result in greatest high/low over a period. It often triggers when a strong trend has paused before further continuation, or it marks the end of a trend. To mitigate closing on false Leledc signals, this strategy has two options: 1. Introducing requirement for increased volume on the Leledc bars can help filter out Leledc signals that happen mid trend. 2. Closing after a number of Leledc bars appear after position opens. These two options work great in isolation but don't perform well together in my testing.
"Bollinger Bands exhaustion bars" - These bars are highlighted when price closes back inside the Bollinger Bands and RSI is within specified overbought/sold zones. The idea is that a trend is overextended when price trades beyond the Bollinger Bands. When price closes back inside the bands it's likely due for mean reversion back to the base EMA in which this strategy will ideally re-enter a position. Since the added RSI requirements often make this indicator too strict to trigger a large enough sample size to backtest, I've found it best to use "non-standard" settings for both the bands and the RSI as seen in the default settings.
"Buy/Sell zones" - Similar to the idea behind using Bollinger Bands exhaustion bars as a closing signal. Instead of calculating off of standard deviations, the Buy/Sell zones are calculated off multiples of the middle EMA bands. When trading beyond these zones and subsequently failing back inside, price may be due for mean reversion back to the base EMA. No RSI filter is used for Buy/Sell zones.
If any early close conditions are selected, it's often worth enabling trade re-entry on "middle EMA band bounce". Instead of waiting for a candle to close back inside the middle EMA bands, this feature will re-enter position on only a wick back into the middle bands as will sometimes happen when the trend is strong.
Any and all of the early close conditions can be combined. Experimenting with these, I've found can result in less net profit but higher win-rates and sharpe ratios as less time is spent in trades.
The deadly:
The trend is your friend. But wouldn't it be nice to catch the trends early? In ranging markets (or when using slower base EMAs in this strategy), waiting for confirmation of a breakout of the EMA bands at best will cause you to miss half the move, at worst will result in getting consistently chopped up. Enabling "counter-trend" trades on this strategy will allow the strategy to enter positions on the opposite side of the EMA bands on either a Leledc bar or Bollinger Bands exhaustion bar. There is a filter requiring either a high/low (for Leledc) or open (for BB bars) outside the selected inner or outer Buy/Sell zone. There are also a number of different close conditions for the counter-trend trades to experiment with and backtest.
There are two ways I've found best to use counter-trend trades
1. Mean reverting scalp trades when a trend is clearly overextended. Selecting from the first 5 counter-trend closing conditions on the dropdown list will usually close the trades out quickly, with less profit but less risk.
2. Trying to catch trends early. Selecting any of the close conditions below the first 5 can cause the strategy to behave as if it's entering into a new trend (from the wrong side).
This feature can be deadly effective in profiting from every move price makes, or deadly to the strategy's PnL if not set correctly. Since counter-trend trades open opposite the middle bands, a stop-loss is recommended to reduce risk. If stop-losses for counter-trend trades are disabled, the strategy will hold a position open often until liquidation in a trending market if th trade is offsides. Note that using a slower base EMA makes counter-trend stop-losses even more necessary as it can reduce the effectiveness of the Buy/Sell zone filter for opening the trades as price can spend a long time trending outside the zones. If faster EMAs (34 and below) are used with "Inner" Buy/Zone filter selected, the first few closing conditions will often trigger almost immediately closing the trade at a loss.
The niche:
I've added a feature to default into longs or shorts. Enabling these with other features (aside from the basic long/short on EMA middle band breakout) tends to break the strategy one way or another. Enabling default long works to simulate trying to acquire more of the asset rather than the base currency. Enabling default short can have positive results for those high FDV, high inflation coins that go down-only for months at a time. Otherwise, I use default short as a hedge for coins that I hold and stake spot. I gain the utility and APR of staking while reducing the risk of holding the underlying asset by maintaining a net neutral position *most* of the time.
Disclaimer:
This script is intended for experimenting and backtesting different strategies around EMA bands. Use this script for your live trading at your own risk. I am a rookie coder, as such there may be errors in the code that cause the strategy to behave not as intended. As far as I can tell it doesn't repaint, but I cannot guarantee that it does not. That being said if there's any question, improvements, or errors you've found, drop a comment below!
Estrategia Larry Connors [JoseMetal]============
ENGLISH
============
- Description:
This strategy is based on the original Larry Connors strategy, using 2 SMAs and RSI.
The strategy has been optimized for better total profit and works better on 4H (tested on BTCUSDT).
LONG:
Price must be ABOVE the slow SMA.
When a candle closes in RSI oversold area, the next candle closes out of the oversold area and the closing price is BELOW the fast SMA = open LONG.
LONG is closed when a candle closes ABOVE the fast SMA.
SHORT:
Price must be BELOW the slow SMA.
When a candle closes in RSI overbought area, the next candle closes out of the overbought area and the closing price is ABOVE the fast SMA = open SHORT.
SHORT is closed when a candle closes BELOW the fast SMA.
*Larry Connor's strategy does NOT use a fixed Stop Loss or Take Profit, as he said, that reduces performance significantly.
- Visual:
Both SMAs (fast and slow) are shown in the chart.
By default, the fast SMA is aqua color, the slow changes between green and red depending on the "trend" (price over slow SMA = bullish, below = bearish).
RSI can't be shown because TradingView doesn't allow to show both overlay and panel indicators, so candles get a RED color when RSI is in OVERBOUGHT area and GREEN when they're on OVERSOLD area to help with that.
Background is colored when conditions are met and a position is going to be open, green for LONGs red for SHORTs.
- Usage and recommendations:
As this is a coded strategy, you don't even have to check for indicators, just open and close trades as the strategy shows.
The original strategy uses a 5 period SMA instead of the 10, and 10/90 for oversold/overbought levels, this has been optimized after the testings and results but feel free to change settings and test by yourself.
Also, the original strategy was developed for daily, but seems to work better en 4H.
- Customization:
As usual I like to make as many aspects of my indicators/strategies customizable, indicators, colors etc., feel free to ask if you feel that something that should be configurable is missing or if you have any ideas to optimize the strategy.
============
ESPAÑOL
============
- Descripción:
Esta estrategia está basada en la estrategia original de Larry Connors, utilizando 2 SMAs y RSI.
La estrategia ha sido optimizada para un mejor beneficio total y funciona mejor en 4H (probado en BTCUSDT).
LONG:
El precio debe estar por encima de la SMA lenta.
Cuando una vela cierra en la zona de sobreventa del RSI, la siguiente vela cierra fuera de la zona de sobreventa y el precio de cierre está POR DEBAJO de la SMA rápida = abre LONG.
Se cierra cuando una vela cierra POR ENCIMA de la SMA rápida.
SHORT:
El precio debe estar POR DEBAJO de la SMA lenta.
Cuando una vela cierra en la zona de sobrecompra del RSI, la siguiente vela cierra fuera de la zona de sobrecompra y el precio de cierre está POR ENCIMA de la SMA rápida = abre SHORT.
Se cierra cuando una vela cierra POR DEBAJO de la SMA rápida.
*La estrategia de Larry Connor NO utiliza un Stop Loss o Take Profit fijo, como él dijo, eso reduce el rendimiento significativamente.
- Visual:
Ambas SMAs (rápida y lenta) se muestran en el gráfico.
Por defecto, la SMA rápida es de color aqua, la lenta cambia entre verde y rojo dependiendo de la "tendencia" (precio por encima de la SMA lenta = alcista, por debajo = bajista).
El RSI no puede mostrarse porque TradingView no permite mostrar tanto los indicadores superpuestos como los del panel, así que las velas obtienen un color ROJO cuando el RSI está en el área de SOBRECOMPRA y VERDE cuando están en el área de VENTA para ayudar a ello.
El fondo se colorea cuando se cumplen las condiciones y se va a abrir una posición, verde para LONGs rojo para SHORTs.
- Uso y recomendaciones:
Como se trata de una estrategia ya programada, ni siquiera hay que comprobar los indicadores, sólo hay que abrir y cerrar las operaciones tal y como muestra la estrategia en el gráfico.
La estrategia original utiliza una SMA de 5 periodos en lugar de 10, y 10/90 para los niveles de sobreventa/sobrecompra, esto ha sido optimizado después de las pruebas y los resultados, pero sé libre de cambiar la configuración y probarla por sí mismo.
Además, la estrategia original fue desarrollada para diario, pero parece funcionar mejor en 4H.
- Personalización:
Como siempre me gusta hacer personalizables todos los aspectos de mis indicadores/estrategias, indicadores, colores, etc., preguntar si notas que falta algo que debería ser configurable o si tienes alguna idea para optimizar la estrategia.
HighTimeframeSamplingLibrary "HighTimeframeSampling"
Library for sampling high timeframe (HTF) data. Returns an array of historical values, an arbitrary historical value, or the highest/lowest value in a range, spending a single security() call.
An optional pass-through for the chart timeframe is included. Other than that case, the data is fixed and does not alter over the course of the HTF bar. It behaves consistently on historical and elapsed realtime bars.
The first version returns floating-point numbers only. I might extend it if there's interest.
🙏 Credits: This library is (yet another) attempt at a solution of the problems in using HTF data that were laid out by Pinecoders - to whom, especially to Luc F, many thanks are due - in "security() revisited" - which I recommend you consult first. Go ahead, I'll wait.
All code is my own.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
WHAT'S THE PROBLEM? OR, WHY NOT JUST USE SECURITY()
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
There are many difficulties with using HTF data, and many potential solutions. It's not really possible to convey it only in words: you need to see it on a chart.
Before using this library, please refer to my other HTF library, HighTimeframeTiming: which explains it extensively, compares many different solutions, and demonstrates (what I think are) the advantages of using this very library, namely, that it's stable, accurate, versatile and inexpensive. Then if you agree, come back here and choose your function.
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MOAR EXPLANATION
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🧹 Housekeeping: To see which plot is which, turn line labels on: Settings > Scales > Indicator Name Label. Vertical lines at the top of the chart show the open of a HTF bar: grey for historical and white for real-time bars.
‼ LIMITATIONS: To avoid strange behaviour, use this library on liquid assets and at chart timeframes high enough to reliably produce updates at least once per bar period.
A more conventional and universal limitation is that the library does not offer an unlimited view of historical bars. You need to define upfront how many HTF bars you want to store. Very large numbers might conceivably run into data or performance issues.
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BRING ON THE FUNCTIONS
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@function f_HTF_Value(string _HTF, float _source, int _arrayLength, int _HTF_Offset, bool _useLiveDataOnChartTF=false)
Returns a floating-point number from a higher timeframe, with a historical operator within an abitrary (but limited) number of bars.
@param string _HTF is the string that represents the higher timeframe. It must be in a format that the request.security() function recognises. The input timeframe cannot be lower than the chart timeframe or an error is thrown.
@param float _source is the source value that you want to sample, e.g. close, open, etc., or you can use any floating-point number.
@param int _arrayLength is the number of HTF bars you want to store and must be greater than zero. You can't go back further in history than this number of bars (minus one, because the current/most recent available bar is also stored).
@param int _HTF_Offset is the historical operator for the value you want to return. E.g., if you want the most recent fixed close, _source=close and _HTF_Offset = 0. If you want the one before that, _HTF_Offset=1, etc.
The number of HTF bars to look back must be zero or more, and must be one less than the number of bars stored.
@param bool _useLiveDataOnChartTF uses live data on the chart timeframe.
If the higher timeframe is the same as the chart timeframe, store the live value (i.e., from this very bar). For all truly higher timeframes, store the fixed value (i.e., from the previous bar).
The default is to use live data for the chart timeframe, so that this function works intuitively, that is, it does not fix data unless it has to (i.e., because the data is from a higher timeframe).
This means that on default settings, on the chart timeframe, it matches the raw source values from security(){0}.
You can override this behaviour by passing _useLiveDataOnChartTF as false. Then it will fix all data for all timeframes.
@returns a floating-point value that you requested from the higher timeframe.
@function f_HTF_Array(string _HTF, float _source, int _arrayLength, bool _useLiveDataOnChartTF=false, int _startIn, int _endIn)
Returns an array of historical values from a higher timeframe, starting with the current bar. Optionally, returns a slice of the array. The array is in reverse chronological order, i.e., index 0 contains the most recent value.
@param string _HTF is the string that represents the higher timeframe. It must be in a format that the request.security() function recognises. The input timeframe cannot be lower than the chart timeframe or an error is thrown.
@param float _source is the source value that you want to sample, e.g. close, open, etc., or you can use any floating-point number.
@param int _arrayLength is the number of HTF bars you want to keep in the array.
@param bool _useLiveDataOnChartTF uses live data on the chart timeframe.
If the higher timeframe is the same as the chart timeframe, store the live value (i.e., from this very bar). For all truly higher timeframes, store the fixed value (i.e., from the previous bar).
The default is to use live data for the chart timeframe, so that this function works intuitively, that is, it does not fix data unless it has to (i.e., because the data is from a higher timeframe).
This means that on default settings, on the chart timeframe, it matches raw source values from security().
You can override this behaviour by passing _useLiveDataOnChartTF as false. Then it will fix all data for all timeframes.
@param int _startIn is the array index to begin taking a slice. Must be at least one less than the length of the array; if out of bounds it is corrected to 0.
@param int _endIn is the array index BEFORE WHICH to end the slice. If the ending index of the array slice would take the slice past the end of the array, it is corrected to the end of the array. The ending index of the array slice must be greater than or equal to the starting index. If the end is less than the start, the whole array is returned. If the starting index is the same as the ending index, an empty array is returned. If either the starting or ending index is negative, the entire array is returned (which is the default behaviour; this is effectively a switch to bypass the slicing without taking up an extra parameter).
@returns an array of HTF values.
@function f_HTF_Highest(string _HTF="", float _source, int _arrayLength, bool _useLiveDataOnChartTF=true, int _rangeIn)
Returns the highest value within a range consisting of a given number of bars back from the most recent bar.
@param string _HTF is the string that represents the higher timeframe. It must be in a format that the request.security() function recognises. The input timeframe cannot be lower than the chart timeframe or an error is thrown.
@param float _source is the source value that you want to sample, e.g. close, open, etc., or you can use any floating-point number.
@param int _arrayLength is the number of HTF bars you want to store and must be greater than zero. You can't have a range greater than this number.
@param bool _useLiveDataOnChartTF uses live data on the chart timeframe.
If the higher timeframe is the same as the chart timeframe, store the live value (i.e., from this very bar). For all truly higher timeframes, store the fixed value (i.e., from the previous bar).
The default is to use live data for the chart timeframe, so that this function works intuitively, that is, it does not fix data unless it has to (i.e., because the data is from a higher timeframe).
This means that on default settings, on the chart timeframe, it matches raw source values from security().
You can override this behaviour by passing _useLiveDataOnChartTF as false. Then it will fix all data for all timeframes.
@param _rangeIn is the number of bars to include in the range of bars from which we want to find the highest value. It is NOT the historical operator of the last bar in the range. The range always starts at the current bar. A value of 1 doesn't make much sense but the function will generously return the only value it can anyway. A value less than 1 doesn't make sense and will return an error. A value that is higher than the number of stored values will be corrected to equal the number of stored values.
@returns a floating-point number representing the highest value in the range.
@function f_HTF_Lowest(string _HTF="", float _source, int _arrayLength, bool _useLiveDataOnChartTF=true, int _rangeIn)
Returns the lowest value within a range consisting of a given number of bars back from the most recent bar.
@param string _HTF is the string that represents the higher timeframe. It must be in a format that the request.security() function recognises. The input timeframe cannot be lower than the chart timeframe or an error is thrown.
@param float _source is the source value that you want to sample, e.g. close, open, etc., or you can use any floating-point number.
@param int _arrayLength is the number of HTF bars you want to store and must be greater than zero. You can't go back further in history than this number of bars (minus one, because the current/most recent available bar is also stored).
@param bool _useLiveDataOnChartTF uses live data on the chart timeframe.
If the higher timeframe is the same as the chart timeframe, store the live value (i.e., from this very bar). For all truly higher timeframes, store the fixed value (i.e., from the previous bar).
The default is to use live data for the chart timeframe, so that this function works intuitively, that is, it does not fix data unless it has to (i.e., because the data is from a higher timeframe).
This means that on default settings, on the chart timeframe, it matches raw source values from security().
You can override this behaviour by passing _useLiveDataOnChartTF as false. Then it will fix all data for all timeframes.
@param _rangeIn is the number of bars to include in the range of bars from which we want to find the highest value. It is NOT the historical operator of the last bar in the range. The range always starts at the current bar. A value of 1 doesn't make much sense but the function will generously return the only value it can anyway. A value less than 1 doesn't make sense and will return an error. A value that is higher than the number of stored values will be corrected to equal the number of stored values.
@returns a floating-point number representing the lowest value in the range.
Rainbow Oscillator The Rainbow Oscillator is a technical indicator that shows prices in overbought or oversold areas. That allows you to catch the price reversal point.
---------------
FEATURES
---------------
.:: Dynamic levels ::.
The indicator levels are divided into several zones, which have a fibonacci ratio. Zones determine the overbought/oversold level. Blue and green level zones are better for buying, red and orange for selling. Dynamic levels are used as replacements for classic levels such as -100 and 100 for the CCI indicator or 30 and 70 for the RSI indicator. Dynamic levels work much better than static levels, as they are more adaptive to the current market situation.
.:: Composite oscillator (3 in 1) ::.
The main signal line of the indicator includes all three oscillators RSI, CCI, Stoch in different ratios. In the settings, you can change the proportions or completely remove one of the oscillators by setting its weight to 0
.:: CCI + RSI + Stoch ratio setting ::.
Each of the oscillators has its own weight in the calculation formula: w2 * cci ( + w1 * ( rsi - 50) + (1 - w2 - w1) * ( stoch - 50), this allows you to create the resulting oscillator from all indicators, depending on the weight of each of them. Each weight value must be between 0 and 1 so that the sum of all weights does not exceed 1.
.:: Smoothing levels and lines of the oscillator ::.
Smoothing the oscillator readings allows you to filter out the noise and get more accurate data. Level offset allows you to customize the support for inputs.
.:: Market Flat ::.
Dynamic creation of levels allows you to find in the price reversal zone, even when the price is in a flat
.:: Sources ::.
You can change the data source for the indicator to the number of longs and shorts for the selected asset. For example, BTCUSDLONGS / BTCUSDSHORTS is perfect for Bitcoin, then the oscillator will work on this data and will not use the quote price.
.:: Trend Detection ::.
The main line of the oscillator has 2 colors - green and red. Red means downtrend, green means uptrend. Trend reversal points are most often found in overbought and oversold zones.
.:: Alerts ::.
Alerts inside for next events: Buy (blue point) Sell (red point) and TrendReversal (change line color)
----------------
TRADING
—-------------
There are several possible entry points for the indicator, let's consider them all.
1) Trend reversal.
Long entry: The indicator line is in the green zone below 0 (oversold), while the line changes color from red (downward) to green (upward)
Short entry: The indicator line is in the red zone above the 0 (overbought) mark, while the line changes color from green to red.
2) Red and blue dots.
Long entry: Blue dot
Short Entry: Red Dot
I prefer to use the first trading method.
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SETTINGS
----------------
.:: Trend Filter (checkbox) ::.
Use trend confirmation for red/blue dots. When enabled, the blue dot requires an uptrend, red dot requires downtrend confirmation before appearing.
.:: Use long/shorts (checkbox) ::.
Change formula to use longs and shorts positions as data source (instead of quote price)
.:: RSI weight / CCI weight / Stoch weight ::.
Weight control coefficients for RSI and CCI indicators, respectively. When you set RSI Weight = 0, equalize the combo of CCI and Stoch , when RSI Weight is zero and CCI Weight is equal to the oscillator value will be plotted
only from Stoch . Intermediate values have a high degree of measurement of each of the three oscillators in percentage terms from 0 to 100. The calculation uses the formula: w2 * cci ( + w1 * ( rsi - 50) + (1 - w2 - w1) * ( stoch - 50),
where w1 is RSI Weight and w2 is CCI Weight, Stoch weight is calculated on the fly as (1 - w2 - w1), so the sum of w1 + w2 should not exceed 1, in this case Stoch will work as opposed to CCI and RSI .
.:: Oscillograph fast and slow periods ::.
The fast period is the period for the moving average used to smooth CCI, RSI and Stoch. The slow period is the same. The fast period must always be less than the slow period.
.:: Oscillograph samples period::.
The period of smoothing the total values of indicators - creates a fast and slow main lines of the oscillator.
.:: Oscillograph samples count::.
How many times smoothing applied to source data.
.:: Oscillator samples type ::.
Smoothing line type e.g. EMA, SMA, RMA …
.:: Level period ::.
Periodically moving averages used to form the levels (zone) of the Rainbow Oscillator indicator
.:: Level offset ::.
Additional setting for shifting levels from zero points. Can be useful for absorbing levels and filtering input signals. The default is 0.
.:: Level redundant ::.
It characterizes the severity of the state at each iteration of the level of the disease. If set to 1 - the levels will not decrease when the oscillator values fall. If it has a value of 0.99 - the levels are reduced by 0.01
each has an oscillator in 1% of cases and is pressed to 0 by more aggressive ones.
.:: Level smooth samples ::.
setting allows you to set the number of strokes per level. Measuring the number of averages with the definition of the type of moving averages
.:: Level MA Type ::.
Type of moving average, average for the formation of a smoothing overbought and oversold zone
Ichimoku Cloud MasterIchimoku Cloud Master aims to provide the ichimoku trader with easy alert functionality to not miss out on valuable trade setups. The key purpose of this script is to better visualise crucial moments in Ichimoku trading. These alerts should not be used for botting in my opinion as they always need a human to confirm the ichimoku market structure. For example, is the Kijun-Sen flat and too far away from price? A good ichimoku trader will not enter at such a point in time.
Explanation of script:
Chikou(lagging span): pink line, this is price plotted 26 bars ago. People ignore the power of this it is crucial to see how chikou behaves towards past price action as seen in the chart below where we got an entry at red arrow because chikou bounced from past fractal bottom.
Kijun-Sen(base line): Black line or color coded line. This is the equilibrium of last 26 candles. To me this is the most important line in the system as it attracts price.
Kijun = (Highest high of 26 periods + Lowest low of 26 periods) ÷ 2
Tenkan-Sen(conversion line): Blue line. This is the equilibrium of last 9 candles. In a strong uptrend price stays above this line.
Tenkan = (Highest high of 9 periods + Lowest low of 9 periods) ÷ 2
Senkou A (Leading span A)= Pink cloud line, this is the average of the 2 components projected 26 bars in the future.
Senkou A = (Tenkan + Kijun) ÷ 2
Senkou B (Leading span B) = Green cloud line, this is the 52 day equilibrium projected 26 bars in the future.
Senkou B = (Highest high of prior 52 periods + Lowest low of prior 52 periods) ÷ 2
Notice how the distance between Chikou and the cloud is also 52 bars. This is all part of Hosoda's numbers which I am not going to explain here.
Fractals: These are the black triangles you find at key turning point. If you want to know how they work reseach williams fractals. I've used fractals with a period of 9 as it is an ichimoku number. These fractals are useful when working with ichimoku wave theory. Again I will not explain that here but in further education
Fractal Support: Ability to extend lines from the fractals which can be used as an entry/exit mechanism in your trading. For example wait for tenkan to cross kijun and then enter on fractal breakout.
Signals:
Crossing of Chikou (lagging span) with past Kijun-Sen: this will color code the Bars / Kijun-Sen (you can turn this off in options)
The script also has a signal for this, this will be the green and purple diamonds. Where green is bullish and purple is bearish.
wy is this important?
When current price plotted 26 candles back (chikou) crosses over the past equilibrium (kijun-sen) this usualy means price has moved past resistance levels where sellers come in. This indicates a switch in market structure and price is bullish from this point, this is the same in the other direction.
Kumo Twist: when the kumo cloud (future) has a crossover from for example green to red (bull to bear). The script plots these using the colored cross symbols as seen in the picture above. A chikou cross + a Kumo twist at same bar of next to eachother below the cloud can be a great entry sign: this would be an entry after cross in the chart above.
Kijun Bounce: when in an uptrend the price retraces back to Kijun-Sen and starts to go back up. These are marked by the yellow circles as seen in chart below:
low below Kijun-Sen and close above it
Strong Trend: when Tenkan is above Kijun, price above cloud, future cloud green, chikou above close, chikou above Kijun we establish a strong bullish trend. For bearish the exact opposite. The script has a function to send an alert at the start of such trends and to plot them with small colored circles above the bars.
Customisation:
I've added options to disable specific aspects of the indicator for those traders who do not want to use all aspects of the indicator. In the customisation tab I've given each part a clear title so you can use your own colors/shapes.
The perfect entry?
Further info:
Look into my education pane, I will be adding education in the future. The chance of me making a more advanced version of the script including line forecasting etc is rather high so watch out for that.
For those who want to master this system I recommend reading the book:
How to make money with the ichimoku system by Balkrishna M. Sadekar
Or the originals books by Hosoda the inventor of Ichimoku if you can get your hands on them and can read Japanese.
Almost all info about the ichimoku system you find on the internet will lose you money because they reduce the system to simple signals that do not generate money.
I will be providing educational material on tradingview using this indicator.
AbdulLibraryLibrary "AbdulLibrary"
The library consists of three sections:
Technical Analysis Functions - A collection of tools commonly used by day traders
Trading Setup Filters Functions - A number of filters that help day traders to screen trading signals
Candlestick Pattern Detection Functions - To detect different candlestick patterns that are used in day trading setups
Note that this would have been possible without the help of @ZenAndTheArtOfTrading as I build-up this library after completing his pine script mastery course so big thanks to him
The content of the library are:-
fibLevels(preDayClose, preDayHigh, preDayLow) Calculates Daily Pivot Point and Fibonacci Key Levels
Parameters:
preDayClose : The previous day candle close
preDayHigh : The previous day candle high
preDayLow : The previous day candle low
Returns: Returns Daily Pivot Point and Fibonacci Key Levels as a tuple
bullishFib(canHigh, canLow, fibLevel) Calculates Fibonacci Levels in Bullish move
Parameters:
canHigh : The high of the move
canLow : The low of the move
fibLevel : The Fib level as % you want to calculate
Returns: Returns The Fib level for the Bullish move
bearishFib(canHigh, canLow, fibLevel) Calculates Fibonacci Levels in Bearish move
Parameters:
canHigh : The high of the move
canLow : The low of the move
fibLevel : The Fib level as % you want to calculate
Returns: Returns The Fib level for the Bearish move
getCandleSize() Calculates the size of candle (high - low) in points
Returns: Returns candle size in points
getCandleBodySize() Calculates the size of candle (close - open) in points
Returns: Returns candle body size in points
getHighWickSize() Calculates the high wick size of candle in points
Returns: Returns The high wick size of candle in points
getLowWickSize() Calculates the low wick size of candle in points
Returns: Returns The low wick size of candle in points
getBodyPercentage() Calculates the candle body size as % of overall candle size
Returns: Returns The candle body size as % of overall candle size
isSwingHigh(period) Checks if the price has created new swing high over a period of time
Parameters:
period : The lookback time we want to check for swing high
Returns: Returns True if the current candle or the previous candle is a swing high
isSwingLow(period) Checks if the price has created new swing low over a period of time
Parameters:
period : The lookback time we want to check for swing low
Returns: Returns True if the current candle or the previous candle is a swing low
isDojiSwingHigh(period) Checks if a doji is a swing high over a period of time
Parameters:
period : The lookback time we want to check for swing high
Returns: Returns True if the doji is a swing high
isDojiSwingLow(period) Checks if a doji is a swing low over a period of time
Parameters:
period : The lookback time we want to check for swing low
Returns: Returns True if the doji is a swing low
isBigBody(atrFilter, atr, candleBodySize, multiplier) Checks if a candle has big body compared to ATR
Parameters:
atrFilter : Check if user wants to use ATR to filter candle-setup signals
atr : The ATR value to be used to compare candle body size
candleBodySize : The candle body size
multiplier : The multiplier to be used to compare candle body size
Returns: Returns Boolean true if the candle setup is big
isSmallBody(atrFilter, atr, candleBodySize, multiplier) Checks if a candle has small body compared to ATR
Parameters:
atrFilter : Check if user wants to use ATR to filter candle-setup signals
atr : The ATR value to be used to compare candle body size
candleBodySize : The candle body size
multiplier : The multiplier to be used to compare candle body size
Returns: Returns Boolean true if the candle setup is small
isHammer(fibLevel, colorMatch) Checks if a candle is a hammer based on user input parameters and candle conditions
Parameters:
fibLevel : Fib level to base candle body on
colorMatch : Checks if user needs for the candel to be green
Returns: Returns Boolean - True if the candle setup is hammer
isShootingStar(fibLevel, colorMatch) Checks if a candle is a shooting star based on user input parameters and candle conditions
Parameters:
fibLevel : Fib level to base candle body on
colorMatch : Checks if user needs for the candel to be red
Returns: Returns Boolean - True if the candle setup is star
isBullEngCan(allowance, period) Check if a candle is a bullish engulfing candle
Parameters:
allowance : How many points the candle open is allowed to be off (To allow for gaps)
period : The lookback period for swing low check
Returns: Boolean - True only if the candle is a bullish engulfing candle
isBearEngCan(allowance, period) Check if a candle is a bearish engulfing candle
Parameters:
allowance : How many points the candle open is allowed to be off (To allow for gaps)
period : The lookback period for swing high check
Returns: Boolean - True only if the candle is a bearish engulfing candle
isBullDoji(maxSize, wickLimit, colorFilter) Check if a candle is a bullish doji candle
Parameters:
maxSize : Maximum candle body size as % of total candle size to be considered as doji
wickLimit : Maximum wick size of one wick compared to the other wick
colorFilter : Checks if the doji is green
Returns: Boolean - True if the candle is a bullish doji
isBearDoji(maxSize, wickLimit, colorFilter) Check if a candle is a bearish doji candle
Parameters:
maxSize : Maximum candle body size as % of total candle size to be considered as doji
wickLimit : Maximum wick size of one wick compared to the other wick
colorFilter : Checks if the doji is red
Returns: Boolean - True if the candle is a bearish doji
isBullOutBar() Check if a candle is a bullish outside bar
Returns: Boolean - True if the candle is a bullish outside bar
isInsideBar() Check if a candle is an inside bar
Returns: Returns Boolean - True if a candle is an inside bar
Triple ThreatThis indicator provides buy and sell signals for Bitcoin based on confluence from well-known momentum, volatility, and trend indicators. It has successfully captured the major directional trends on Bitcoin's daily chart since 2018, and the settings are currently optimized for this chart in particular. This indicator implements RSI to gauge momentum, BBWP to gauge volatility, and an EMA to gauge trend. Maximum confluence signals are represented by horizontal bars in the indicator's pane, where the tallest green bar is a confirmed buy signal, and the tallest red bar is a confirmed sell signal. The shortest bar represents a momentum-only signal, and the second-shortest bar represents a volatility signal in confluence with the previously given momentum signal.
To track momentum, the RSI is plotted to the indicator plane against a moving average of the RSI. A momentum signal is generated when the RSI crosses over its moving average, retests/approaches the moving average, and then continues in the crossover direction (i.e., it fails to cross the moving average to the opposite side, creating a successful retest). The settings that affect this trigger are the "Crossover Threshold," which specifies how much the RSI should exceed the moving average to be considered a crossover, and the "Retest threshold," which specifies how closely the RSI should approach the moving average to be considered a retest. A momentum signal is ALSO generated if the RSI or its moving average exceed their counterpart by a certain threshold. For example, if the threshold was set at 10, a BUY signal would be generated when the RSI exceeds the moving average by 10, or a SELL signal would be generated when the moving average exceeds the RSI by 10. This threshold can be set using the "Instant Signal Threshold" setting. Either type of momentum signal will be plotted on the pane as the shortest horizontal bar, with its color indicating the signal's direction.
Volatility is primarily measured using the Bollinger Band Width Percentile (BBWP) indicator, which was created by The_Caretaker. BBWP plots the volatility of the asset's price, given by Bollinger Band width, relative to past volatility by assigning the volatility readings into percentiles. The indicator also includes a moving average of the BBWP itself, where a crossover to the upside represents expanding volatility and a crossover to the downside represents contracting volatility. This indicator is used to confirm a signal given by the momentum indicators - a momentum signal that is given during a period of expanding volatility has a greater likelihood of success. Therefore, when the BBWP crosses above its moving average by a given threshold, a previously triggered momentum signal is considered to be "confirmed." The threshold for this crossover can be set using the "BBWP Confirmation Threshold" setting. However, it is also relevant that periods of extreme volatility often accompany an extremity in price action (a "top" or "bottom"), in which case the BBWP is likely to contract after price reaches such an extremity. This phenomenon is captured by also using "extreme reads" on the momentum indicator to signal that there has already been enough volatility to confirm a momentum signal. If the RSI gives an "extreme read" before triggering a signal, the momentum signal is also considered to be confirmed. For example, if the RSI is above 80, breaks below 80, and then gives a SELL signal, this sell signal is considered to be confirmed without requiring the BBWP to crossover its moving average to the upside. The threshold that would confirm a SELL signal can be set with the "Overbought" setting, and the threshold that would confirm a BUY signal can be set with the "Oversold" setting. Whenever a volatility signal confirms a momentum signal, a medium-sized horizontal bar will be plotted on the pane in the same directional color as the momentum signal. Note that a momentum signal may trigger at the exact same time as the volatility signal which confirms it; in this case, only the medium-sized bar will be visible on the pane, but its direction can still be identified by its color.
Lastly, to reduce the likelihood of "false signals," a trend indicator is used to confirm the direction of the signal. This is typically an exponential moving average. If a confirmed volatility SELL signal is given, and the closing price is below the moving average, then the SELL signal is also confirmed by the trend. Likewise, if a confirmed volatility BUY signal is given, and the closing price is above the moving average, then the BUY signal is confirmed by the trend. The type and length of the moving average used to verify the trend can be set using the "Moving Average Type" and "Moving Average Length" settings found below the momentum/volatility settings. A trend signal is plotted on the pane as a tall horizontal bar, and is more deeply colored than the momentum and volatility signals.
For maximum confluence, it is recommended that the trend signal, given by the tallest bar, is the one that forms the basis of trades executed while using the Triple Threat indicator. It is possible to enter more aggressive trades with better entries by using only the volatility signal, given by the medium-sized bar, however this entails greater risk and should only be done in confluence with an additional trading strategy of your own discretion. Backtesting has shown that using the volatility signal alone underperforms using the volatility signal in confluence with the trend signal.
Please also be advised that the default setting are optimized for Bitcoin's daily chart only. The indicator is still applicable to other timeframes and asset classes, but the settings may need to be modified. I have a list of settings for other Bitcoin timeframes, and I would be happy to share them upon request.
I hope you can find this indicator to be of some use to your trading strategies. I'd be happy to hear any feedback from the community, so please don't hesitate to reach out. Stay safe, and happy trading.
MACD-X Overlay, More Than MACD by DGTMoving Average Convergence Divergence – MACD
The most popular indicator used in technical analysis , the moving average convergence divergence ( MACD ), created by Gerald Appel. MACD is a trend-following momentum indicator , designed to reveal changes in the strength, direction, momentum, and duration of a trend in a financial instrument’s price
Historical evolution of MACD ,
- Gerald Appel created the MACD line,
- Thomas Aspray added the histogram feature to MACD
- Giorgos E. Siligardos created a leader of MACD
MACD employs two Moving Averages of varying lengths (which are lagging indicators) to identify trend direction and duration. Then, MACD takes the difference in values between those two Moving Averages (MACD Line) and an EMA of those Moving Averages (Signal Line) and plots that difference between the two lines as a histogram which oscillates above and below a center Zero Line. The histogram is used as a good indication of a security's momentum.
The MACD indicator is typically good for identifying three types of basic signals;
Signal Line Crossovers
A Signal Line Crossover is the most common signal produced by the MACD . On the occasions where the MACD Line crosses above or below the Signal Line, that can signify a potentially strong move. The standard interpretation of such an event is a recommendation to buy if the MACD line crosses up through the Signal Line (a "bullish" crossover), or to sell if it crosses down through the Signal Line (a "bearish" crossover). These events are taken as indications that the trend in the financial instrument is about to accelerate in the direction of the crossover.
Zero Line Crossovers
Zero Line Crossovers occur when the MACD Line crossed the Zero Line and either becomes positive (above 0) or negative (below 0). A change from positive to negative MACD is interpreted as "bearish", and from negative to positive as "bullish". Zero crossovers provide evidence of a change in the direction of a trend but less confirmation of its momentum than a signal line crossover
Divergence
Divergence is another signal created by the MACD . Simply, divergence occurs when the MACD and actual price are not in agreement. A "positive divergence" or "bullish divergence" occurs when the price makes a new low but the MACD does not confirm with a new low of its own. A "negative divergence" or "bearish divergence" occurs when the price makes a new high but the MACD does not confirm with a new high of its own. A divergence with respect to price may occur on the MACD line and/or the MACD Histogram
Moving Average Crossovers , another hidden signal that MACD Indicator identifies
Many traders will watch for a short-term moving average to cross above a longer-term moving average and use this to signal increasing upward momentum. This bullish crossover suggests that the price has recently been rising at a faster rate than it has in the past, so it is a common technical buy sign. Conversely, a short-term moving average crossing below a longer-term average is used to illustrate that the asset's price has been moving downward at a faster rate and that it may be a good time to sell.
Moving Average Crossovers in reality is Zero Line Crossovers, the value of the MACD indicator is equal to zero each time the two moving averages cross over each other. For easy interpretation by trades, Zero Line Crossovers are simply described as positive or negative MACD
False signals
Like any forecasting algorithm, the MACD can generate false signals. A false positive, for example, would be a bullish crossover followed by a sudden decline in a financial instrument. A false negative would be a situation where there is bearish crossover, yet the financial instrument accelerated suddenly upwards
What is “MACD-X” and Why it is “More Than MACD”
In its simples form, MACD-X implements variety of different calculation techniques applied to obtain MACD Line. Different calculation techniques lead to different values for MACD Line, as will further discuss below, and as a consequence the signal line and the histogram values will differentiate accordingly.
Main features of MACD-X ;
1- Plotting of the Oscillator presented on top of the price chart (main chart) and applicable on both log and linear scale. Maximum plotting length is limited to 250 bars
2- Introduces different proven techniques applied on MACD calculation, such as MACD-AS (Histogram), MACD-Leader and MACD-Source, besides the traditional MACD (MACD-TRADITIONAL)
• MACD-Traditional, by Gerald Appel
It is the MACD that we know, stated as traditional just to avoid confusion with other techniques used with this study
• MACD-Histogram, by Thomas Aspray
The MACD-Histogram measures the distance between MACD and its signal line (the 9-day EMA of MACD ). Aspray developed the MACD-Histogram to anticipate signal line crossovers in MACD . Because MACD uses moving averages and moving averages lag price, signal line crossovers can come late and affect the reward-to-risk ratio of a trade. Bullish or bearish divergences in the MACD-Histogram can alert chartists to an imminent signal line crossover in MACD
Aspray's contribution served as a way to anticipate (and therefore cut down on lag) possible MACD crossovers which are a fundamental part of the indicator.
• MACD-Leader, by Giorgos E. Siligardos, PhD
MACD Leader has the ability to lead MACD at critical situations. Almost all smoothing methods encounter in technical analysis are based on a relative-weighted sum of past prices, and the Leader is no exception. The concealed weights of MACD Leader are such that more relative weight is used in the more recent prices than the respective weights used by the components of MACD . In effect, the Leader expresses more changes in average price dynamics for the recent price movement than MACD , thus eventually leading MACD , especially when significant trend changes are about to take place.
• MACD-Source, a custom experimental interpretation of mine,
MACD Source, presents an application of MACD that evaluates Source/MA Ratio, relatively with less lag, as a basis for MACD Line, also can be expressed as source convergence/divergence to its moving average. Among the various techniques for removing the lag between price and moving average (MA) of the price, one in particular stands out: the addition to the moving average of a portion of the difference between the price and MA. MACD Source, is based on signal length mean of the difference between Source and average value of shot length and long length moving average of the source (Source/MA Ratio), where the source is actual value and hence no lag and relatively less lag with the average value of moving average of the source .
MACD Source provides relatively early crossovers comparing to MACD and better momentum direction indications, assuming the lengths are set to same values
3- Alerts presented for MACD and Signal Line Crosses both for Early Warning and Confirmed Crossovers
For more, You are kindly invited to have a look to other MACD or similar studies presented on separate pane
MACD-X, More Than MACD by DGT , P-MACD by DGT and Price Distance to its MA by DGT
Disclaimer : Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely
The script is for informational and educational purposes only. Use of the script does not constitutes professional and/or financial advice. You alone the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script
Smoothed Heiken AshiIt is a Heiken Ashi candle overlay. It has a selectable moving average before HA calculation and another after HA calculation, to smooth original Heiken Ashi candles.
It can be used:
Detecting Short/Long term trend direction
Dynamic support/resistance, not just a line, but it has a height
Trailing stop
Trend reversal detection, when price cross above/below Heiken Ashi candle
A lot of moving averages can be selected to adjust it to the selected market.
It uses my TAExt library, so you can use it in your strategies as well.
_Auto Pivot PointsOne of the main drawbacks to displaying Pivot Points on a chart is that many times the more extreme pivots (R/S3, R/S4, R/S5) aren't anywhere close to the price action during a timeframe. These extreme pivot points clutter up your chart and make it hard to use the "auto" zoom feature of TradingView.
The " _Auto Pivot Points " indicator solves these problems by automatically only displaying the pivot points if the price has crossed the pivot during the timeframe or it is the next closest pivot . For example, on monthly pivots if the price has only crossed the R1 Pivot then this indicator will display the R2 Pivot and any pivots below but it won't display the R3, R4, R5 pivots . The R3, R4, & R5 pivots are not very useful to the trader because the price hasn't even crossed the R2 Pivot . But as soon as the price crosses the R2 Pivot then this indicator will display the R3 Pivot because it is the next closest. And the same logic applies to the S Pivots .
If you need to see all the Pivots then there is a convenient toggle to display all the pivots by turning off the intelligent auto pivots . But as soon as you don't need to display all the pivots the toggle will turn on the automatic pivots .
This indicator has many style and logic options. This script allows you to control:
Number of past timeframes to display
Displaying Pivot labels
Label position (left/right)
Line color
Line width
Note: TradingView has a limit of 40 security calls per script. Due to this limitation this indicator can only display pivots a max of 7 time periods back.
Note 2: This indicator uses the Traditional pivot calculations.
Session Levels - Ultimate Range IndicatorSession Levels - Ultimate Range Indicator
Primarily developed for trading the E-MINI Futures Markets like NQ or ES from the CME Group,
but also more than suitable for Crypto or other instruments.
This indicator highlights the chosen session, which can be Globex, Asian, London and New York.
It plots the important levels and also renders the Opening Range as it forms (a.k.a. Initial Balance).
After the 1st hour Opening Range is finished, it can plot the Standard Deviations / Projections.
See below for a complete feature list.
All Opening Ranges on chart and for the New York session the Range Projections are turned on:
s3.tradingview.com
How to use (example):
If you are trading the Nasdaq Futures (NQ!)
Enable the Globex Overnight session. Basically in the Futures Market, the Globex session is everything outside of US trading hours of Stocks. This draws the important overnight levels, like the Low, 25%, 50%, 75% and the High.
Enable the New York Session with Levels and Opening Range. Generally, 70% of the time the 1st hour will put a Low or High of the day.
If the price is trading above the Globex Low, most likely the Low of the Day is formed and the price target for the day will be 1.5x Standard Deviation and 2x Standard Deviation.
[*} Deviation of the Initial Balance depends on the volume ad overall market structure.
** This is not financial advice or any guarantee **
Features:
Show each Session Highlighted on Intraday chart in it's own color (each session can be turned off and has customizable times and color)
Show Line Levels of each session: Low, 25%, 50%, 75% and the High (customizable color)
Show the Opening Range (Initial Balance) of the Asian, London and New York session. Note: NY has more options.
Opening Range is displayed as a box with level lines (customizable color)
Levels are drawn to the end of the NY Cash session (customizable time)
Show IB Standard Deviations 0.5 - 3.0. Calculated from the Opening Range (Initial Balance)
Option to display Higher Timeframe levels: Previous Day Open/Close and Previous Week Open/Close
All level lines and OR boxes size dynamically as the session progresses
Built in Alerts for when price hits key levels. e.g. Alert when price crosses the NY Opening Range High. Or an Alert when the first STDEV is hit.
Option to toggle display of drawings for Today's trading session only, or Show all recent session levels. This keeps the chart clean or not.
Extras:
The NY Opening Range also has a 50% level line
The NY Opening Bar can be highlighted separately
The Level Lines can have small labels turned on/off. Values are only shown on mouse over to keep a clean chart
Keep in mind:
1) This indicator works on all instruments, but on instruments with limited market hours, your chart setting
has to be set to "Extended Hours" otherwise. For example TSLA on NASDAQ.
2) The Exchange Time Zone for the CME Group is Chicago UTC-6. So the session times you configure in the settings menu are based on that timezone too.
3) Globex opens at 5pm CST and closes when the US session starts 8:30CST.
4) When enabling the Alerts in the Indicator settings, be sure to also create an alarm for this indicator using the Alarm function of Tradingview.
Period Dollar Cost Average BacktesterHere is a simple script to calculate the profits and other dollar cost average strategy statistics. This strategy was created to avoid asset price volatility, so the pump and dump scheme does not affect the portfolio. By dividing the investment amount into periods, the investor doesn’t need to analyze the market, fundamental analysis, or anything. The goal is to increase the asset holdings and avoid fast and robust price movements.
This indicator has some configurations.
Amount to buy: the amount to buy at each time
Broker fee %: the fee percentage that the broker has for spot trade
Frequency: the frequency of the investments. Example: 1 Day means that every day, it will buy an amount of the asset
Starting Date: when the indicator will start the investment simulation
Ending Date: when the indicator will end the investment simulation
InfoCell With/Height: it relates to the panel for view purposes. Change the values to fit better on your screen.
This indicator has three lines:
Total Invested (green): total amount invested at the end of the period
Total Net Profit (pink): total profit by converting the amount of the asset bought at the latest closing price
Holding Profits (yellow): the amount that would be in the portfolio if the investor had invested all the capital in a signal trade at the beginning of the period.
The statistics panel has some information to help you understand buying the asset in one or more trades. So, besides those three lines that were mentioned above, here are the other statistics:
Entry Price: The price of the asset when the first investment was made
Gross Profit: Total amount of profit, not excluding the losses
Gross Losses: Total amount of losses, not excluding the profits
Profit Factor: The Gross Profit divided by the Gross Loss. A value above 1 means it’s profitable.
Profit/Trades: Net profit per trade. This includes the broker fees.
Recovery Factor: The Net profit divided by the relative drawdown. The higher the recovery factor, the faster the recovery of a loss
Total Asset Bought: The amount of the asset that was bought at the end of the investment plan
Absolute Drawdown: The total amount of losses that made the account balance go below its initial value
Relative Drawdown: The max drawdown that occurred, no matter the account balance amount
Total Trades: number of times the investment was made in the selected period
Total Fee: total Fee that was spent on the total investment
Total Winning Trades: the total amount of winning trades. A trade is considered a winner if the net profit is up compared with the latest investment.
Total Losing Trades: the total amount of losing trades. A trade is considered a loser if the net profit is down compared to the latest investment.
Max consecutive wins: the max amount of consecutive winning trades
Max consecutive losses: the max amount of consecutive losing trades
The chart above uses the default configuration of the indicator. Placed on the BTCUSD market, taking the time range of January 1st, 2018 to January 1st, 2022, 4 years. Buying a BTC amount with 10 USDT every day in that period would generate a more than 500% profit. Compared to the profit amount by just holding the count, which was close to 350% profit, the dollar cost average by period would be much more profitable.
Market Breadth EMAs V2Second version of Market Breadth EMAs for $SPY. Getting a little more complicated than V1 but removed noise.
Key:
Green line = % of stocks above their 20-period moving average, the "twitch line"
Red line = % of stocks above their 200-period moving average, the "long term trend"
White line = weighted average of the % of stocks above the 20/50/100/200 averages, the "general trend." Captures bursts that the 200 misses, and is more trustworthy than the 20.
Background colors = limits of the red/green/white where reversals have happened historically. The darker the color, the stronger the signal.
Histogram = the change in the white line over time, for different time periods: 1/4/10/20, the "trend strength/confidence." i.e. If the white line "General Trend" has been drifting lower for a month but started increasing the past 2 days, you might have 3 red histograms and 1 green one.
Techniques:
If the green, red, or white line is above 50%, then more than half the stocks are above that average. So, if they're in the top half, bullish market. Bottom half, bearish market.
If the green line is above the red, market has rising/bullish momentum. If red is above green, market has falling/bearish momentum.
If the white line is rising, bullish momentum. If it's falling, bearish momentum.
If the histograms are all green, there is strong momentum in that direction. The % of stocks above their important averages has been increasing each day for both the short term and long term.
If the histograms go from all green to a mix of green and red, be on the lookout for a reversal from one of the background levels. Usually initiates from the 20 (green line) first.
If price dips without the histogram changing, HODL.
K's Volatility BandsVolatility bands come in all shapes and forms contrary to what is believed. Bollinger bands remain the principal indicator in the volatility bands family. K's Volatility bands is an attempt at optimizing the original bands. Below is the method of calculation:
* We must first start by calculating a rolling measure based on the average between the highest high and the lowest low in the last specified lookback window. This will give us a type of moving average that tracks the market price. The specificity here is that when the market does not make higher highs nor lower lows, the line will be flat. A flat line can also be thought of as a magnet of the price as the ranging property could hint to a further sideways movement.
* The K’s volatility bands assume the worst with volatility and thus will take the maximum volatility for a given lookback period. Unlike the Bollinger bands which will take the latest volatility calculation every single step of time, K’s volatility bands will suppose that we must be protected by the maximum of volatility for that period which will give us from time to time stable support and resistance levels.
Therefore, the difference between the Bollinger bands and K's volatility bands are as follows:
* Bollinger Bands' formula calculates a simple moving average on the closing prices while K's volatility bands' formula calculates the average of the highest highs and the lowest lows.
* Bollinger Bands' formula calculates a simple standard deviation on the closing prices while K's volatility bands' formula calculates the highest standard deviation for the lookback period.
Applying the bands is similar to applying any other volatility bands. We can list the typical strategies below:
* The range play strategy : This is the usual reversal strategy where we buy whenever the price hits the lower band and sell short whenever it hits the upper band.
* The band re-entry strategy : This strategy awaits the confirmation that the price has recognized the band and has shaped a reaction around it and has reintegrated the whole envelope. It may be slightly lagging in nature but it may filter out bad trades.
* Following the trend strategy : This is a controversial strategy that is the opposite of the first one. It assumes that whenever the upper band is surpassed, a buy signal is generated and whenever the lower band is broken, a sell signal is generated.
* Combination with other indicators : The bands can be combined with other technical indicators such as the RSI in order to have more confirmation. This is however no guarantee that the signals will improve in quality.
* Specific strategy on K’s volatility bands : This one is similar to the first range play strategy but it adds the extra filter where the trade has a higher conviction if the median line is flat. The reason for this is that a flat line means that no higher highs nor lower lows have been made and therefore, we may be in a sideways market which is a fertile ground for mean-reversion strategies.
Kelt + BBand Combination (kingthies) █ Overview
The Kelt-BBand Combo is a trading approach that I've used for multiple years now, and works on any timeframe, chart possible. There are various versions of this approach published by myself and others who find value in measuring the deviations of price and strategize market entries and exits. For an entry-level description of each component, I'll type them up below.
█ Using This Indicator
While there are various strategies to use this tool, I'll share the one that has yielded me the most success across traditional and cryptocurrency markets - first understand the different appearances of both....
IF the bbands are inside the kelts, the squeeze is on. In 90% of cases this is often a bullish leaning event
IF the bbands are pinching (regardless of slope or kelt behavior),these are your primary support and resistances, respectively
When trending up, HA candles will touch between the upper kelt and upper bband on every candle, across all timeframes
When trending down, HA candles will touch between the lower kelt and lower bband on every candle, across all timeframes
If one timeframe is not giving clear indicator of trend direction or s/r to follow, zoom out. the higher timeframe will always win and show you the true direction
█ Intro to Bollinger Bands
Bollinger Bands consists of a center line representing the moving average of a security’s price over a certain period, and two additional parallel lines (called the trading bands) one of which is just the moving average plus k-times the standard deviation over the selected time frame, and the other being the moving average minus k-times the standard deviation over that same timeframe. This technique has been developed in the 1980’s by John Bollinger, who lately registered the terms “Bollinger Bands” as a U.S. trademark in 2011. Technical analysts typically use 20 periods and k = 2 as default settings to build Bollinger Bands, while they can choose a simple or exponential moving average. Bollinger Bands provide a relative definition of high and low prices of a security. When the security is trading within the upper band, the price is considered high, while it is considered low when the security is trading within the lower band.
There is no general consensus on the use of Bollinger Bands among traders. Some traders see a buy signal when the price hits the lower Bollinger Band and close their position when the price hits the moving average. Some others buy when the price crosses over the upper band and sell when the price crosses below the lower band. We can see here two opposing interpretations based on different rationales, depending whether we are in a reversal or continuation pattern. Another interesting feature of the Bollinger Bands is that they give an indication of the volatility levels; a widening gap between the upper and lower bands indicates an increasing volatility, while a narrowing band indicates a decreasing volatility. Moreover, when the bands have an almost flat slope (parallel to the x-axis) the price will generally oscillate between the bands as if trading through a channel.
█ Intro to Keltner Channels
Keltner Channels aka Kelts were first described by a Chicago grain trader called Chester W. Keltner in his 1960 book How to Make Money in Commodities. Though Keltner claimed no ownership of the original idea and simply called it the ten-day moving average trading rule, his name was applied by those who heard of this concept through his books.
Similarly to the Bollinger Bands, Keltner channel is a technical analysis tool based on three parallel lines. In fact, the Keltner indicator consists of a central moving average in addition to channel lines spread above and below it. The central line represents a 10-day simple moving average of what Chester W. Keltner called typical price. The typical price is defined as the average of the high, low and close. The distance between the central line and the upper, or lower line, is equivalent to the simple moving average of the preceding 10 days' trading ranges.
One way to interpret the Keltner Channel would be to consider the price breakouts outside of the channel. A trader would track price movement and consider any close above the upper line as a strong buy signal. Equivalently, any close below the lower line would be considered a strong sell signal. The trader would follow the trend emphasized by the indicator while complementing his analysis with the use of other indicators as well. However, the breakout method only works well when the market moves from a range-bound setting to an established trend. In a trend-less configuration, the Keltner Channel is better used as an overbought/oversold indicator. Thus, as the price breaks out below the lower band, a trader waits for the next close inside the Keltner Channel and considers this price behavior as an oversold situation indicating a potential buy signal. Similarly, as the price breaks out above the upper band, the trader waits for the next close inside the Keltner Channel and considers this price movement as an overbought situation indicating a potential sell signal. By waiting for the price to close within the Channel, the trader avoids getting caught in a real upside or downside breakout.
Happy Trading!
Mean Reversion Strategy v2 [KL]Description :
This strategy will enter a position when the following conditions are met:
a) Main signal: When source data (ATR) diverts from its moving average value, and
b) Confirmation: If predicted direction of trend is favorable.
Assumptions :
During periods of high price volatility, ATR diverts from its moving average value. Eventually, ATR should revert. But since just knowing the magnitude of increase/decrease of ATR does not indicate a trend signal, we need to introduce a model to predict the current trend.
In short:
• Trend Prediction : This strategy calculates the expected logarithmic return of the security (the "Drift") and considers prices to be moving in uptrend if the drift curve is upward sloping.
• Assessment of ATR diversion : To determine "yes/no" regarding whether ATR at a given point in time has diverted, this script conducts a two-tailed hypothesis test at each candlestick period. The null hypothesis (H0) is that the fast moving average value should equal the slow moving average value (say, denoted as H0: atr14 == atr28; it is assumed that atr28 is more meaningful for the purpose of describing the current trend because it has a larger sample size). Investopedia has an article summarizing this topic .
Exit Condition :
When trailing stop loss hits.
Previous version :
This strategy is based on Version 1 published back in September . This older version considers +/- one standard deviation to be the critical values relative to average ATR when testing whether ATR has diverted from the mean. This does not take Standard Error ("SE") into account. As a result, the threshold is often too wide and it generates too many entry signals.
CandleEvaluationLibrary "CandleEvaluation"
Contains functions to evaluate bullish and bearish, engulfing, and outsized candles. They are different from the built-in indicators from TradingView in that these functions don't evaluate classical patterns composed of multiple candles, and they reflect my own understanding of what is "bullish" and bearish", "engulfing", and "outsized".
isBullishBearishCandle()
Determines if the current candle is bullish or bearish according to the length of the wicks and the open and close.
int _barsBack How many bars back is the candle you want to evaluate. By default this is 0, i.e., the current bar.
returns Two values, true or false, for whether it's a bullish or bearish candle respectively.
isTripleBull()
Tells you whether a candle is a "Triple Bull" - that is, one which is bullish in three ways:
It closes higher than it opens
It closes higher than the body of the previous candle
The High is above the High of the previous candle.
int _barsBack How many bars back is the candle you want to evaluate. By default this is 0, i.e., the current bar.
returns True or false.
isTripleBear()
Tells you whether a candle is a "Triple Bear" - that is, one which is bearish in three ways:
It closes lower than it opens
It closes lower than the body of the previous candle
The Low is below the Low of the previous candle.
int _barsBack How many bars back is the candle you want to evaluate. By default this is 0, i.e., the current bar.
returns True or false.
isBigBody()
Tells you if the current candle has a larger than average body size.
int _length - The length of the sma to calculate the average
float _percent - The percentage of the average that the candle body has to be to count as "big". E.g. 100 means it has to be just larger than the average, 200 means it has to be twice as large.
returns True or false
isBullishEngulfing()
Tells you if the current candle is a bullish engulfing candle.
int _barsBack How many bars back is the candle you want to evaluate. By default this is 0, i.e., the current bar.
int _atrFraction The denominator for the ATR fraction, which is the small amount by which the open can be different from the previous close.
returns True or false
isBearishEngulfing()
Tells you if the current candle is a bearish engulfing candle.
int _barsBack How many bars back is the candle you want to evaluate. By default this is 0, i.e., the current bar.
int _atrFraction The denominator for the ATR fraction, which is the small amount by which the open can be different from the previous close.
returns True or false
Realtime 5D Profile [LucF]█ OVERVIEW
This indicator displays a realtime profile that can be configured to visualize five dimensions: volume, price, time, activity and age. For each price level in a bar or timeframe, you can display total or delta volume or ticks. The tick count measures activity on a level. The thickness of each level's line indicates its age, which helps you identify the most recent levels.
█ WARNING
The indicator only works in real time. Contrary to TradingView's line of volume profile indicators , it does not show anything on historical bars or closed markets, and it cannot display volume information if none exists for the data feed the chart is using. A realtime indicator such as this one only displays information accumulated while it is running on a chart. The information it calculates cannot be saved on charts, nor can it be recalculated from historical bars. If you refresh the chart, or the script must re-execute for some reason, as when you change inputs, the accumulated information will be lost.
Because "Realtime 5D Profile" requires time to accumulate information on the chart, it will be most useful to traders working on small timeframes who trade only one instrument and do not frequently change their chart's symbol or timeframe. Traders working on higher timeframes or constantly changing charts will be better served by TradingView's volume profiles. Before using this indicator, please see the "Limitations" section further down for other important information.
█ HOW TO USE IT
Load the indicator on an active chart (see here if you don't know how).
The default configuration displays:
• A double-sided volume profile showing at what price levels activity has occurred.
• The left side shows "down" volume, the right side shows "up" volume.
• The value corresponding to each level is displayed.
• The width of lines reflects their relative value.
• The thickness of lines reflects their age. Four thicknesses are used, with the thicker lines being the most recent.
• The total value of down/up values for the profile appears at the top.
To understand how to use profiles in your trading, please research the subject. Searches on "volume profile" or "market profile" will yield many useful results. I provide you with tools — I do not teach trading. To understand more about this indicator, read on. If you choose not to do so, please don't ask me to answer questions that are already answered here, nor to make videos; I don't.
█ CONCEPTS
Delta calculations
Volume is slotted in up or down slots depending on whether the price of each new chart update is higher or lower than the previous update's price. When price does not move between chart updates, the last known direction is used. In a perfect world, Pine scripts would have access to bid and ask levels, as this would allow us to know for sure if market orders are being filled on upticks (at the ask) or downticks (at the bid). Comparing the price of successive chart updates provides the most precise way to calculate volume delta on TradingView, but it is still a compromise. Order books are in constant movement; in some cases, order cancellations can cause sudden movements of both the bid and ask levels such that the next chart update can occur on an uptick at a lower price than the previous one (or vice versa). While this update's volume should be slotted in the up slot because a buy market order was filled, it will erroneously be slotted in the down slot because the price of the chart's update is lower than that of the previous one. Luckily, these conditions are relatively rare, so they should not adversely affect calculations.
Levels
A profile is a tool that displays information organized by price levels. You can select the maximum quantity of levels this indicator displays by using the script's "Levels" input. If the profile's height is small enough for level increments to be less than the symbol's tick size, a smaller quantity of levels is used until the profile's height grows sufficiently to allow your specified quantity of levels to be displayed. The exact position of levels is not tethered to the symbol's tick increments. Activity for one level is that which happens on either side of the level, halfway between its higher or lower levels. The lowest/highest levels in the profile thus appear higher/lower than the profile's low/high limits, which are determined by the lowest/highest points reached by price during the profile's life.
Level Values and Length
The profile's vertical structure is dynamic. As the profile's height changes with the price range, it is rebalanced and the price points of its levels may be recalculated. When this happens, past updates will be redistributed among the new profile's levels, and the level values may thus change. The new levels where updates are slotted will of course always be near past ones, but keep this fluidity in mind when watching level values evolve.
The profile's horizontal structure is also dynamic. The maximum length of level lines is controlled by the "Maximum line length" input value. This maximum length is always used for the largest level value in the profile, and the length of other levels is determined by their value relative to that maximum.
Updates vs Ticks
Strictly speaking, a tick is the record of a transaction between two parties. On TradingView, these are detected on seconds charts. On other charts, ticks are aggregated to form a chart update . I use the broader "update" term when it names both events. Note that, confusingly, tick is also used to name an instrument's minimal price increment.
Volume Quality
If you use volume, it's important to understand its nature and quality, as it varies with sectors and instruments. My Volume X-ray indicator is one way you can appraise the quality of an instrument's intraday volume.
█ FEATURES
Double-Sided Profiles
When you choose one of the first two configuration selections in the "Configuration" field's dropdown menu, you are asking the indicator to display a double-sided profile, i.e., where the down values appear on the left and the up ones on the right. In this mode, the formatting options in the top section of inputs apply to both sides of the profile.
Single-Sided Profiles
The six other selections down the "Configuration" field's dropdown menu select single-sided profiles, where one side aggregates the up/down values for either volume or ticks. In this mode, the formatting options in the top section of inputs apply to the left profile. The ones in the following "Right format" section apply to the right profile.
Calculation Mode
The "Calculation" input field allows the selection of one of two modes which applies to single-sided profiles only. Values can represent the simple total of volume or ticks at each level, or their delta. The mode has no effect when a double-sided profile is used because then, the total is represented by the sum of the left and right sides. Note that when totals are selected, all levels appear in the up color.
Age
The age of each level is always displayed as one of four line thicknesses. Thicker lines are used for the youngest levels. The age of levels is determined by averaging the times of the updates composing that level. When viewing double-sided profiles, the age of each side is calculated independently, which entails you can have a down level on the left side of the profile appear thinner than its corresponding up side level line on the right side because the updates composing the up side are more recent. When calculating the age of single-sided profiles, the age of the up/down values aggregated to calculate the side are averaged. Since they may be different, the averaged level ages will not be as responsive as when using a double-sided profile configuration, where the age of levels on each side is calculated independently and follows price action more closely. Moreover, when displaying two single-sided profiles (volume on one side and ticks on the other), the age of both sides will match because they are calculated from the same realtime updates.
Profile Resets
The profile can reset on timeframes or trend changes. The usual timeframe selections are available, including the chart's, in which case the profile will reset on each new chart bar. One of two trend detection logics can be used: Supertrend or the one used by LazyBear in his Weis Wave indicator . Settings for the trend logics are in the bottommost section of the inputs, where you can also control the display of trend changes and states. Note that the "Timeframe" field's setting also applies to the trend detection mechanism. Whatever the timeframe used for trend detection, its logic will not repaint.
Format
Formatting a profile for charts is often a challenge for traders, and this one is no exception. Varying zoom factors on your chart and the frequency of profile resets will require different profile formats. You can achieve a reasonable variety of effects by playing with the following input fields:
• "Resets on" controls how frequently new profiles are drawn. Spacing out profiles between bars can help make them more usable.
• "Levels" determines the maximum quantity of levels displayed.
• "Offset" allows you to shift the profile horizontally.
• "Profile size" affects the global size of the profile.
• Another "Size" field provides control over the size of the totals displayed above the profile.
• "Maximum line length" controls how far away from the center of the bar the lines will stretch left and right.
Colors
The color and brightness of levels and totals always allows you to determine the winning side between up and down values. On double-sided profiles, each side is always of one color, since the left side is down values and the right side, up values. However, the losing side is colored with half its brightness, so the emphasis is put on the winning side. When there is no winner, the toned-down version of each color is used for both sides. Single-sided profiles use the up and down colors in full brightness on the same side. Which one is used reflects the winning side.
Candles
The indicator can color candle bodies and borders independently. If you choose to do so, you may want to disable the chart's bars by using the eye icon near the symbol's name.
Tooltips
A tooltip showing the value of each level is available. If they do not appear when hovering over levels, select the indicator by clicking on its chart name. This should get the tooltips working.
Data Window
As usual, I provide key values in the Data Window, so you can track them. If you compare total realtime volumes for the profile and the built-in "Volume" indicator, you may see variations at some points. They are due to the different mechanisms running each program. In my experience, the values from the built-in don't always update as often as those of the profile, but they eventually catch up.
█ LIMITATIONS
• The levels do not appear exactly at the position they are calculated. They are positioned slightly lower than their actual price levels.
• Drawing a 20-level double-sided profile with totals requires 42 labels. The script will only display the last 500 labels,
so the number of levels you choose affects how many past profiles will remain visible.
• The script is quite taxing, which will sometimes make the chart's tab less responsive.
• When you first load the indicator on a chart, it will begin calculating from that moment; it will not take into account prior chart activity.
• If you let the script run long enough when using profile reset criteria that make profiles last for a long time, the script will eventually run out of memory,
as it will be tracking unmanageable amounts of chart updates. I don't know the exact quantity of updates that will cause this,
but the script can handle upwards of 60K updates per profile, which should last 1D except on the most active markets. You can follow the number of updates in the Data Window.
• The indicator's nature makes it more useful at very small timeframes, typically in the sub 15min realm.
• The Weis Wave trend detection used here has nothing to do with how David Weis detects trend changes.
LazyBear's version was a port of a port, so we are a few generations removed from the Weis technique, which uses reversals by a price unit.
I believe the version used here is useful nonetheless because it complements Supertrend rather well.
█ NOTES
The aggregated view that volume and tick profiles calculate for traders is a good example of one of the most useful things software can do for traders: look at things from a methodical, mathematical perspective, and present results in a meaningful way. Profiles are powerful because, if the volume data they use is of good enough quality, they tell us what levels are important for traders, regardless of the nature or rationality of the methods traders have used to determine those levels. Profiles don't care whether traders use the news, fundamentals, Fib numbers, pivots, or the phases of the moon to find "their" levels. They don't attempt to forecast or explain markets. They show us real stuff containing zero uncertainty, i.e., what HAS happened. I like this.
The indicator's "VPAA" chart name represents four of the five dimensions the indicator displays: volume, price, activity and age. The time dimension is implied by the fact it's a profile — and I couldn't find a proper place for a "T" in there )
I have not included alerts in the script. I may do so in the future.
For the moment, I have no plans to write a profile indicator that works on historical bars. TradingView's volume profiles already do that, and they run much faster than Pine versions could, so I don't see the point in spending efforts on a poor ersatz.
For Pine Coders
• The script uses labels that draw varying quantities of characters to break the limitation constraining other Pine plots/lines to bar boundaries.
• The code's structure was optimized for performance. When it was feasible, global arrays, "input" and other variables were used from functions,
sacrificing function readability and portability for speed. Code was also repeated in some places, to avoid the overhead of frequent function calls in high-traffic areas.
• I wrote my script using the revised recommendations in the Style Guide from the Pine v5 User Manual.
█ THANKS
• To Duyck for his function that sorts an array while keeping it in synch with another array.
The `sortTwoArrays()` function in my script is derived from the Pine Wizard 's code.
• To the one and only Maestro, RicardoSantos , the creative volcano who worked hard to write a function to produce fixed-width, figure space-padded numeric values.
A change in design made the function unnecessary in this script, but I am grateful to you nonetheless.
• To midtownskr8guy , another Pine Wizard who is also a wizard with colors. I use the colors from his Pine Color Magic and Chart Theme Simulator constantly.
• Finally, thanks to users of my earlier "Delta Volume" scripts. Comments and discussions with them encouraged me to persist in figuring out how to achieve what this indicator does.
