End Point Moving Average [EPMA]The End Point Moving Average was introduced in the October 95 issue of Technical Analysis of Stocks &
Commodities in the article "The End Point Moving Average", by Patrick E. Lafferty.
The Time Series Forecast takes this value and the slope of the regression line to forecast the next day and then plots this forecasted price as today's value.
For interpretation refer to Mr. Lafferty's article.
Please note
From line 10 starts my personal experemental modifications to this script, all above is original formula by Patrick E. Lafferty.
Regressions
Bitcoin Best Value CorridorHere is my interpretation of the "Best Time To Buy" Bitcoin over its lifetime using a logarithmic regression trendline. The upper and lower lines are 10% deviations from the centre line. I calculated the trendline in excel and then coded my results into pine script.
Top 40 High Low Strategy for SPY, 5minThis strategy is developed based on my High Low Index SPY Top 40 indicator
Notes:
- this strategy is only developed for SPY on the 5 min chart . It seems to work with QQQ as well, but it isn't optimized for it
- P/L shown is based on 10 SPY option contracts, call or put, with strike price closest to the entry SPY price and expiry of 0 to 1 day. This includes commissions (can be changed). This is only an estimate calculated using an arbitrary multiplier factor, this can be changed in the setting
- P/L is based on $5000 initial capital
- Works with both regular / extended trading session turned on/off. However, max drawdown is 1/2 with extended trading session ON
- there is still a bug that doesn't allow alert to be created due to calculation error, will update once fixed
This strategy combines signals from the following indicators to determine entry signals:
- High Low Index SPY Top 40
- MACD
- Linear Regression Slope
Entry signal is triggered when:
- High Low Index line crosses the EMA line
- MACD trending in the same direction
- Linear Regression slope is accelerating above a threshold in the same direction, indicating a strong trend
Profit target(PT) and stop loss(SL) are determined using ATR value, with 2:1 Reward to Risk ratio as default.
Exit signal may be triggered prior to PT or SL trigger when:
- High Low Index SPY Top 40 shows a reversal after overbought or oversold conditions (optional)
- Opposite entry signal is triggered
There are a number of optional settings:
- Turn on/off "option trading", P/L will be calculated using share price only without multiplication factor for trading option contracts
- # of options per trade, default to 10
- Reinvest with profit made
- Trade with trailing SL after PT hit
- Take profit early based on Top 40 overbought/oversold
- Trade 0/1 day expiry. This will signal exit by the end of the day on Mon/Wed/Fri, and only exits 1/2 of positions (if in profit) on Tues/Thurs
- Can reduce the SL level without impacting PT
- No entry between 10:05 - 10:20 (don't ask me why, but statistically it performs better)
Consider donating me some of your profit if you make $$$ hahaha~ ;)
Enjoy~~
Signals Pirate™ ScalperSignalsPirate™ Scalper has been created specifically for asset scalping to help improve your short term trading by accurately identifying ‘Buy’ and ‘Sell’ opportunities!
The simplicity of this package ensures traders of all levels of expertise can utilise this tool and experience its benefits to the fullest. The only variable that alters the tools performance is the ‘Scalp Length’ option, which dictates how frequently scalping signals are identified. A value of 10 will result in more selective and less frequent signals, whereas a value of 1 will print ‘Buy’ and ‘Sell’ signals more often.
This tool has been formed using a number of trend reversal indicators, such as the RSI and Stochastics to identify overbought and oversold conditions. As well as these it incorporates crucial pivot points to identify potential support & resistance levels where scalp opportunities will have the highest chance of being successful. Combining these means when price is extremely oversold across a multitude of indicators while sitting at a pivot point support level, a ‘Buy Scalp’ label is created – and vice versa for ‘Sell Scalp’ signals.
The default settings are the best settings we’ve found so far but you can change them to build your own unique trading strategy. We’d recommend experimenting with these values to find the best results for the asset you are trading, and your own personal trading style.
Direction for use:
1. Use on any asset class and time frame, preferably on a lower timeframe (15min or less).
2. Fine tune the ‘Scalp Length’.
3. Enter a long position once a ‘Buy Scalp’ label is created, and close the position once a ‘Sell Scalp’ label is created. For short positions enter once a ‘Sell Scalp’ label is created and close once a ‘Buy Scalp’ label is created.
We hope you love this package, and it takes your trading and investing to the next level. Please let us know if you have any questions or queries regarding the logic behind the bundle, or if you have any suggestions for improvements etc. We love your feedback and are constantly striving to continuously improve!
[UPRIGHT Trading] Auto-Trendlines Pro (cc)Hello Traders -
Today I am releasing a full-featured auto-trendline indicator.
This makes it easier for beginners and professionals alike to analyze a charts trending support and resistance.
What are Trendlines and why do we use them?
In short, a trendline is a diagonal line that connects to two or more price points on a chart to show the current direction of price. These are used to identify and confirm trend direction in technical analysis and show support and resistance points.
Utilizing pivot points and different calculations for sources we're able to create the trendlines; with adjustable slopes (or just use of proprietary calculations) we are able to make these lines to line up with the current trend.
How it's different:
Accurate auto-drawn calculated trendlines.
Fully customizable - the ability to adjust the trendlines easily to exact specifications with every type of trader in mind.
Can be used to spot long trend as well as short, by adjusting length or using extend both to see previous pivots it's touched.
Then retracted, for perfect long trend.
Can show old trendlines for analysis (click image to see).
Auto-labels Higher-Highs, Higher-Lows, Lower-Highs, Lower-Lows at pivots.
Lining up trendlines with Break signals can help provide more accurate trendlines (potentially teaching) beginners how to draw them better.
Signature double trendline set.
Also notice the additional sell/buy signals (shown above).
Squeeze / Low-float mode adjusts to fit big moves.
Adjust the opacity to hide or fade a line (as seen above).
Pre-filled alerts for breakouts / breakdowns.
Please see author instructions for access.
Cheers,
Mike
(UPRIGHT Trading)
Bitcoin Power Law Bands (BTC Power Law) Indicator█ OVERVIEW
The 'Bitcoin Power Law Bands' indicator is a set of three US dollar price trendlines and two price bands for bitcoin , indicating overall long-term trend, support and resistance levels as well as oversold and overbought conditions. The magnitude and growth of the middle (Center) line is determined by double logarithmic (log-log) regression on the entire USD price history of bitcoin . The upper (Resistance) and lower (Support) lines follow the same trajectory but multiplied by respective (fixed) factors. These two lines indicate levels where the price of bitcoin is expected to meet strong long-term resistance or receive strong long-term support. The two bands between the three lines are price levels where bitcoin may be considered overbought or oversold.
All parameters and visuals may be customized by the user as needed.
█ CONCEPTS
Long-term models
Long-term price models have many challenges, the most significant of which is getting the growth curve right overall. No one can predict how a certain market, asset class, or financial instrument will unfold over several decades. In the case of bitcoin , price history is very limited and extremely volatile, and this further complicates the situation. Fortunately for us, a few smart people already had some bright ideas that seem to have stood the test of time.
Power law
The so-called power law is the only long-term bitcoin price model that has a chance of survival for the years ahead. The idea behind the power law is very simple: over time, the rapid (exponential) initial growth cannot possibly be sustained (see The seduction of the exponential curve for a fun take on this). Year-on-year returns, therefore, must decrease over time, which leads us to the concept of diminishing returns and the power law. In this context, the power law translates to linear growth on a chart with both its axes scaled logarithmically. This is called the log-log chart (as opposed to the semilog chart you see above, on which only one of the axes - price - is logarithmic).
Log-log regression
When both price and time are scaled logarithmically, the power law leads to a linear relationship between them. This in turn allows us to apply linear regression techniques, which will find the best-fitting straight line to the data points in question. The result of performing this log-log regression (i.e. linear regression on a log-log scaled dataset) is two parameters: slope (m) and intercept (b). These parameters fully describe the relationship between price and time as follows: log(P) = m * log(T) + b, where P is price and T is time. Price is measured in US dollars , and Time is counted as the number of days elapsed since bitcoin 's genesis block.
DPC model
The final piece of our puzzle is the Dynamic Power Cycle (DPC) price model of bitcoin . DPC is a long-term cyclic model that uses the power law as its foundation, to which a periodic component stemming from the block subsidy halving cycle is applied dynamically. The regression parameters of this model are re-calculated daily to ensure longevity. For the 'Bitcoin Power Law Bands' indicator, the slope and intercept parameters were calculated on publication date (March 6, 2022). The slope of the Resistance Line is the same as that of the Center Line; its intercept was determined by fitting the line onto the Nov 2021 cycle peak. The slope of the Support Line is the same as that of the Center Line; its intercept was determined by fitting the line onto the Dec 2018 trough of the previous cycle. Please see the Limitations section below on the implications of a static model.
█ FEATURES
Inputs
• Parameters
• Center Intercept (b) and Slope (m): These log-log regression parameters control the behavior of the grey line in the middle
• Resistance Intercept (b) and Slope (m): These log-log regression parameters control the behavior of the red line at the top
• Support Intercept (b) and Slope (m): These log-log regression parameters control the behavior of the green line at the bottom
• Controls
• Plot Line Fill: N/A
• Plot Opportunity Label: Controls the display of current price level relative to the Center, Resistance and Support Lines
Style
• Visuals
• Center: Control, color, opacity, thickness, price line control and line style of the Center Line
• Resistance: Control, color, opacity, thickness, price line control and line style of the Resistance Line
• Support: Control, color, opacity, thickness, price line control and line style of the Support Line
• Plots Background: Control, color and opacity of the Upper Band
• Plots Background: Control, color and opacity of the Lower Band
• Labels: N/A
• Output
• Labels on price scale: Controls the display of current Center, Resistance and Support Line values on the price scale
• Values in status line: Controls the display of current Center, Resistance and Support Line values in the indicator's status line
█ HOW TO USE
The indicator includes three price lines:
• The grey Center Line in the middle shows the overall long-term bitcoin USD price trend
• The red Resistance Line at the top is an indication of where the bitcoin USD price is expected to meet strong long-term resistance
• The green Support Line at the bottom is an indication of where the bitcoin USD price is expected to receive strong long-term support
These lines envelope two price bands:
• The red Upper Band between the Center and Resistance Lines is an area where bitcoin is considered overbought (i.e. too expensive)
• The green Lower Band between the Support and Center Lines is an area where bitcoin is considered oversold (i.e. too cheap)
The power law model assumes that the price of bitcoin will fluctuate around the Center Line, by meeting resistance at the Resistance Line and finding support at the Support Line. When the current price is well below the Center Line (i.e. well into the green Lower Band), bitcoin is considered too cheap (oversold). When the current price is well above the Center Line (i.e. well into the red Upper Band), bitcoin is considered too expensive (overbought). This idea alone is not sufficient for profitable trading, but, when combined with other factors, it could guide the user's decision-making process in the right direction.
█ LIMITATIONS
The indicator is based on a static model, and for this reason it will gradually lose its usefulness. The Center Line is the most durable of the three lines since the long-term growth trend of bitcoin seems to deviate little from the power law. However, how far price extends above and below this line will change with every halving cycle (as can be seen for past cycles). Periodic updates will be needed to keep the indicator relevant. The user is invited to adjust the slope and intercept parameters manually between two updates of the indicator.
█ RAMBLINGS
The 'Bitcoin Power Law Bands' indicator is a useful tool for users wishing to place bitcoin in a macro context. As described above, the price level relative to the three lines is a rough indication of whether bitcoin is over- or undervalued. Users wishing to gain more insight into bitcoin price trends may follow the author's periodic updates of the DPC model (contact information below).
█ NOTES
The author regularly posts on Twitter using the @DeFi_initiate handle.
█ THANKS
Many thanks to the following individuals, who - one way or another - made the 'Bitcoin Power Law Bands' indicator possible:
• TradingView user 'capriole_charles', whose open-source 'Bitcoin Power Law Corridor' script was the basis for this indicator
• Harold Christopher Burger, whose Bitcoin’s natural long-term power-law corridor of growth article (2019) was the basis for the 'Bitcoin Power Law Corridor' script
• Bitcoin Forum user "Trololo", who posted the original power law model at Logarithmic (non-linear) regression - Bitcoin estimated value (2014)
MM Chop Filter Range BoxesMatch with the MM Chop Filter
This draw Non repainting range boxes when the oscillator see a range.
-Breakout Buy/Sell Signals and Exit signals when prices enters a range just in case you did get into a trade. .
-Alarms to match the signals
How to use
Match with the oscillator and always trade the trend with your strategy confirmation and the breakout this indicator provides
iCryptoScalperHi everyone!
In this post I would like to present my personal indicator for short-term strategies on cryptocurrencies called iCryptoScalper , but let me first introduce myself:
I am a theoretical physicist with a deep passion for trading and mathematical modelling of the financial markets.
I started trading cryptocurrencies more than 4 years ago and, throughout this period, I got more and more involved in trying to describe the mechanisms governing
the price action at lower timeframes like 1, 5 and 15 minutes.
As a beginner, I started with the usual "buy and hold" strategy, the safest but also boring option. Afterthat, I tried to get more involved on speed trading
and scalping and, as it happens to all the beginners, I went through many mistakes.
At the beginning, trying to find the best scalping strategy, was a very difficult task and I barely managed to perform well, mostly because every trade were overwhelmed
by my emotional approach and the fear of missing the right entry point and/or exit point. However, thanks to these difficulties, I understood that I needed
an algorithmic procedure to improve my performances and overtake the emotional approach, with a more technical approach: a mathematical guide that precisely tells me how to behave in the best way possible to be profitable.
To achieve this goal, I put all my efforts in trying to write a consistent mathematical model able to give me all the statistical informations I needed to reach
the best performances and, of course, the best possible profits.
The iCryptoScalper is an explicit mathematical tool to be used for scalping strategies and optimized for different cryptocurrency pairs on 15/30 min timeframes.
The script gives you many useful informations and details regarding the current and subsequent trade, accompanied with a detailed overview on both the last 20 short
and long trade results.
Let us have a look to all the detailed informations the script shows to you:
CHART
- Lines: The script plots for you the Entry price (yellow line), the Stop Loss price (red line) and a series of 8 Take Profit levels (green lines).
- Background: The green background color indicates that the script is in a long position, viceversa, the red background color indicates that the script is in a short position.
- Labels: The blue labels indicate the maximum achieved profit for each trade.
- Alerts: The script shows two types of alerts, the "prepare to #" one and the true entry one. The prepare alert is very useful to understand when the strategy is going
to enter a specific trade, thus giving you the possibility to set up all the necessary Entry/SL/TP levels on your favorite trading platform.
- Crosses: The green and red crosses are precisely located at the corresponding long and short entry price for the next trade, thus giving you a preview on the target price
that has to be reached for the indicator to enter. They are computed thanks to a mathematical model I set up and optimized for each cryptocurrency pair.
PANEL
- Overview: This part shows you two probability tables for the last 20 long and short trades each. The first table indicates the set of probabilities of reaching the corresponding TP level, whereas the second table shows the conditional probability , namely the probability of reaching a certain profit level once the previous one has been achieved.
Below the tables you can find three quantities again referring to the last 20 long and short trades: the Average Maximum Profit , the Average Maximum Drawdown and the Average Risk/Reward Ratio .
Last but not least, the correlation between the current asset and BTC is displayed together with the current BTC status.
- Active Trade: This part collects all the data related to the current trade status.
- Next Trade: This part collects all the data related to the next trade status.
ATTENTION!
Please notice that the equity line you see in the "Strategy Tester" section of TradingView is unreliable compared to the real performances of the script. This is due to the
fact that the TradingView engine is designed for backtesting automatic trading strategies and not real-time trading bots.
An example is the following: Bob buys 1 BTC-PERP contract at 10000$, setting the Stop Loss at 9000$. The price of the perpetual then goes to 12000$ and then go back hitting the Stop Loss. For the TradingView Engine this is a
trade with a permanent loss of 1000$. However, for the iCryptoScalper users, the trade is perfectly fine thanks to the numerous TP levels (and corresponding probabilities) given by the script within the trade window.
Сatching knivesThis strategy is based on the regression line and volume
The Linear Regression Channel is a three-line technical indicator that displays the high, low and midpoint of the current trend.
How does it work in strategy?
If there is a deviation by a given percentage, the entry occurs
//LOGIC ENTRY
-Length-сhannel length
-Deviation-deviation of the boundaries, the higher , the rarer the entries
-% low for regression-deviation directly from the boundaries, the higher the number, the less frequent the entries
-Required % down bar-additional condition for entry (the candle on which the entry takes place from the logic must necessarily fall by a given percentage)
-Volume-the volume, which must be larger by the number of times you specify ( you can set the volume lower, but for better entries, you need to set the deviation percentages higher!)
//EXIT SETTING
Take profit and stop loss when a certain percentage is reached
//SETTINGS NEXT ENTRY AND GRID
Allow signal lower than,% - the next entry into a trade from logic occurs only when a decrease by a certain percentage
Allow grid,% - when the price drops by the percentage specified in the settings, the entry will take place, but only on the next bar.
//DATA RANGE
-Testing results for any period of time
//
Default settings for infrequent but relatively accurate entries for TF 1 hour.
It costs pyramiding 5 and take profit 5%. Choose the flavors of your choice!
Good luck!
Weighted Least Squares Moving AverageLinearly Weighted Ordinary Least Squares Moving Regression
aka Weighted Least Squares Moving Average -> WLSMA
^^ called it this way just to for... damn, forgot the word
Totally pwns LSMA for some purposes here's why (just look up):
- 'realistically' the same smoothness;
- less lag;
- less overshoot;
- more or less same computationally intensive.
"Pretty cool, huh?", Bucky Roberts©, thenewboston
Now, would you please (just look down) and see the comparison of impulse & step responses:
Impulse responses
Step responses
Ain't it beautiful?
"Motivation behind the concept & rationale", by gorx1
Many been trippin' applying stats methods that require normally distributed data to time series, hence all these B*ll**** Bands and stuff don't really work as it should, while people blame themselves and buy snake oil seminars bout trading psychology, instead of using proper tools. Price... Neither population nor the samples are neither normally nor log-normally distributed. So we can't use all the stuff if we wanna get better results. I'm not talking bout passing each rolling window to a stat test in order to get the proper descriptor, that's the whole different story.
Instead we can leverage the fact that our data is time-series hence we can apply linear weighting, basically we extract another info component from the data and use it to get better results. Volume, range weighting don't make much sense (saying that based on both common sense and test results). Tick count per bar, that would be nice tho... this is the way to measure "intensity". But we don't have it on TV unfortunately.
Anyways, I'm both unhappy that no1 dropped it before me during all these years so I gotta do it myself, and happy that I can give smth cool to every1
Here is it, for you.
P.S.: the script contains standalone functions to calculate linearly weighted variance, linearly weighted standard deviation, linearly weighted covariance and linearly weighted correlation.
Good hunting
Logarithmic Trend ChannelThis indicator automatically draws a regression channel plotted on logarithmic scale from the first quotation.
This model is useful for the long term series data (such as 10 or 20 years time span).
The Pearson correlation measures the strength of the linear relationship between two variables. It has a value between to 1, with a value of 0 meaning no correlation, and + 1 meaning a total positive correlation.
Logarithmic price scales are a type of scale used on a chart, plotted such that two equivalent price changes are represented by the same vertical changes on the scale.
They differ from linear price scales because they display percentage points and not dollar price increases for a stock.
Technical issues
*The user have to pan over the chart from the beginning to the end of the study range (such as 10 years of bars) so the pine script could generate those lines on the chart.
*If on the chart the number of bar is less than the lookback period, it won't generate any lines as well.
Linear Regression Channel Breakout StrategyThis strategy is based on LonesomeTheBlue's Linear Regression Channel Indicator. First of all, I would like to thank LonesomeTheBlue. Breaking the Linear Regression Channel to close the candle triggers a Long or Short signal. If the slope of the Linear Regression Channel is positive, it is Short when it breaks out the lower line, and when the slope is negative, it is Long when it breaks out the upper line. The default is optimized for 8-hour candles, and for other hour candles, find the optimal value yourself. Below is a description of LonesomeTheBlue's Linear Regression Channel.
이 전략은 LonesomeTheBlue의 Linear Regression Channel Indicator를 기반으로 만들어졌습니다. 우선 LonesomeTheBlue님께 감사의 말씀을 드립니다. Linear Regression Channel을 돌파하여 봉 마감하면 Long 또는 Short 신호를 트리거합니다. Linear Regression Channel의 기울기가 양인 경우 하단 라인을 돌파하면 Short이고 그 기울기가 음인 경우 상단 라인을 돌파하면 Long입니다. 기본값은 8시간봉에 최적화 되어 있으며, 다른 시간봉은 직접 최적값을 찾아보십시오. 아래는 LonesomeTheBlue의 Linear Regression Channel에 대한 설명을 퍼왔습니다.
________________________________________________
There are several nice Linear Regression Channel scripts in the Public Library. and I tried to make one with some extra features too. This one can check if the Price breaks the channel and it shows where is was broken. Also it checks the momentum of the channel and shows it's increasing/decreasing/equal in a label, shape of the label also changes. The line colors change according to direction.
using the options, you can;
- Set the Source (Close, HL2 etc)
- Set the Channel length
- Set Deviation
- Change Up/Down Line colors
- Show/hide broken channels
- Change line width
meaning of arrows:
⇑ : Uptrend and moment incresing
⇗ : Uptrend and moment decreasing
⇓ : Downtrend and moment incresing
⇘ : Downtrend and moment decreasing
⇒ : No trend
[RS]Long Term Price Range Analysis (MML)Study on Price range Regression and range (deviation multiplier needs to be accommodate manually to fit price action)
study was made for time frames above weekly
[RS]Linear Regression Bands V1experiment with linear regression, the purpose was to catch break outs early, but it creates to much visual noise
same as version 0 but with added margin filter and signal to mark entrys
