Normalized Velocity [Loxx]Velocity (which is often called a "smoother momentum" since it is much smoother than momentum without lagging at all) with an addition of ATR normalization
Since velocity is (even when normalization is applied) is not an indicator with fixed bounds, this indicator is uses floating levels for what is usually called overbought and oversold levels (+ a floating "zero" line is added). Something that would look like a "fixed levels" is easily achieved if you use long floating levels period in which case those levels are quite similar to fixed levels.
This indicator can be used like any momentum indicator (in that case recommended coloring mode is to use either slope coloring or "zero" middle level crossing coloring) or it can be used as a "trending" indicator in which case it is better to use coloring on outer level cross, and longer calculation periods are advised in that case.
Included:
Bar coloring
3 signal variations w/ alerts
Loxx's Expanded Source Types
Alerts
中心震盪指標
End-pointed SSA of Normalized Price Oscillator [Loxx]End-pointed SSA of Normalized Price Oscillator is an indicator that converts source price into a normalized oscillator and runs an SSA calculation to derived a smoother final output. This indicator also serves to introduce the concept of SSA to the Pine Coder community. The data returned from this algorithm is an array of modeled values on past X bars. We could use this data but it's not useful, so instead we use the end-pointed value which is the first value of the array at index 0.
What is Singular Spectrum Analysis (SSA)?
Singular spectrum analysis (SSA) is a technique of time series analysis and forecasting. It combines elements of classical time series analysis, multivariate statistics, multivariate geometry, dynamical systems and signal processing. SSA aims at decomposing the original series into a sum of a small number of interpretable components such as a slowly varying trend, oscillatory components and a ‘structureless’ noise. It is based on the singular value decomposition (SVD) of a specific matrix constructed upon the time series. Neither a parametric model nor stationarity-type conditions have to be assumed for the time series. This makes SSA a model-free method and hence enables SSA to have a very wide range of applicability.
For our purposes here, we are only concerned with the "Caterpillar" SSA. This methodology was developed in the former Soviet Union independently (the ‘iron curtain effect’) of the mainstream SSA. The main difference between the main-stream SSA and the "Caterpillar" SSA is not in the algorithmic details but rather in the assumptions and in the emphasis in the study of SSA properties. To apply the mainstream SSA, one often needs to assume some kind of stationarity of the time series and think in terms of the "signal plus noise" model (where the noise is often assumed to be ‘red’). In the "Caterpillar" SSA, the main methodological stress is on separability (of one component of the series from another one) and neither the assumption of stationarity nor the model in the form "signal plus noise" are required.
"Caterpillar" SSA
The basic "Caterpillar" SSA algorithm for analyzing one-dimensional time series consists of:
Transformation of the one-dimensional time series to the trajectory matrix by means of a delay procedure (this gives the name to the whole technique);
Singular Value Decomposition of the trajectory matrix;
Reconstruction of the original time series based on a number of selected eigenvectors.
This decomposition initializes forecasting procedures for both the original time series and its components. The method can be naturally extended to multidimensional time series and to image processing.
The method is a powerful and useful tool of time series analysis in meteorology, hydrology, geophysics, climatology and, according to our experience, in economics, biology, physics, medicine and other sciences; that is, where short and long, one-dimensional and multidimensional, stationary and non-stationary, almost deterministic and noisy time series are to be analyzed.
Included:
Bar coloring
Alerts
Signals
Loxx's Expanded Source Types
[blackcat] L3 RMI Trading StrategyLevel 3
Background
My view of correct usage of RSI and the relationship between RMI and RSI. A proposed RMI indicator with features is introduced
Descriptions
The Relative Strength Index (RSI) is a technical indicator that many people use. Its focus indicates the strength or weakness of a stock. In the traditional usage of this point, when the RSI is above 50, it is strong, otherwise it is weak. Above 80 is overbought, below 20 is oversold. This is what the textbook says. However, if you follow the principles in this textbook and enter the actual trading, you would lose a lot and win a little! What is the reason for this? When the RSI is greater than 50, that is, a stock enters the strong zone. At this time, the emotions of market may just be brewing, and as a result, you run away and watch others win profit. On the contrary, when RSI<20, that is, a stock enters the weak zone, you buy it. At this time, the effect of losing money is spreading. You just took over the chips that were dumped by the whales. Later, you thought that you had bought at the bottom, but found that you were in half mountainside. According to this cycle, there is a high probability that a phenomenon will occur: if you sell, price will rise, and if you buy, price will fall, who have similar experiences should quickly recall whether their RSI is used in this way. Technical indicators are weapons. It can be either a tool of bull or a sharp blade of bear. Don't learn from dogma and give it away. Trading is a game of people. There is an old saying called “people’s hearts are unpredictable”. Do you really think that there is a tool that can detect the true intentions of people’s hearts 100% of the time?
For the above problems, I suggest that improvements can be made in two aspects (in other words, once the strategy is widely spread, it is only a matter of time before it fails. The market is an adaptive and complex system, as long as it can be fully utilized under the conditions that can be used, it is not easy to use. throw or evolve):
1. RSI usage is the opposite. When a stock has undergone a deep adjustment from a high level, and the RSI has fallen from a high of more than 80 to below 50, it has turned from strong to weak, and cannot be bought in the short term. But when the RSI first moved from a low to a high of 80, it just proved that the stock was in a strong zone. There are funds in the activity, put into the stock pool.
Just wait for RSI to intervene in time when it shrinks and pulls back (before it rises when the main force washes the market). It is emphasized here that the use of RSI should be combined with trading volume, rising volume, and falling volume are all healthy performances. A callback that does not break an important moving average is a confirmed buying point or a second step back on an important moving average is a more certain buying point.
2. The RSI is changed to a more stable and adjustable RMI (Relative Momentum Indicator), which is characterized by an additional momentum parameter, which can not only be very close to the RSI performance, but also adjust the momentum parameter m when the market environment changes to ensure more A good fit for a changing market.
The Relative Momentum Index (RMI) was developed by Roger Altman and described its principles in his article in the February 1993 issue of the journal Technical Analysis of Stocks and Commodities. He developed RMI based on the RSI principle. For example, RSI is calculated from the close to yesterday's close in a period of time compared to the ups and downs, while the RMI is compared from the close to the close of m days ago. Therefore, in principle, when m=1, RSI should be equal to RMI. But it is precisely because of the addition of this m parameter that the RMI result may be smoother than the RSI.
Not much more to say, the below picture: when m=1, RMI and RSI overlap, and the result is the same.
The Shanghai 50 Index is from TradingView (m=1)
The Shanghai 50 Index is from TradingView (m=3)
The Shanghai 50 Index is from TradingView (m=5)
For this indicator function, I also make a brief introduction:
1. 50 is the strength line (white), do not operate offline, pay attention online. 80 is the warning line (yellow), indicating that the stock has entered a strong area; 90 is the lightening line (orange), once it is greater than 90 and a sell K-line pattern appears, the position will be lightened; the 95 clearing line (red) means that selling is at a climax. This is seen from the daily and weekly cycles, and small cycles may not be suitable.
2. The purple band indicates that the momentum is sufficient to hold a position, and the green band indicates that the momentum is insufficient and the position is short.
3. Divide the RMI into 7, 14, and 21 cycles. When the golden fork appears in the two resonances, a golden fork will appear to prompt you to buy, and when the two periods of resonance have a dead fork, a purple fork will appear to prompt you to sell.
4. Add top-bottom divergence judgment algorithm. Top_Div red label indicates top divergence; Bot_Div green label indicates bottom divergence. These signals are only for auxiliary judgment and are not 100% accurate.
5. This indicator needs to be combined with VOL energy, K-line shape and moving average for comprehensive judgment. It is still in its infancy, and open source is published in the TradingView community. A more complete advanced version is also considered for subsequent release (because the K-line pattern recognition algorithm is still being perfected).
Remarks
Feedbacks are appreciated.
eswaran ab//@version=5
strategy("MACD Strategy", overlay=true)
fastLength = input(12)
slowlength = input(26)
MACDLength = input(9)
MACD = ta.ema(close, fastLength) - ta.ema(close, slowlength)
aMACD = ta.ema(MACD, MACDLength)
delta = MACD - aMACD
if (ta.crossover(delta, 0))
strategy.entry("MacdLE", strategy.long, comment="MacdLE")
if (ta.crossunder(delta, 0))
strategy.entry("MacdSE", strategy.short, comment="MacdSE")
//plot(strategy.equity, title="equity", color=color.red, linewidth=2, style=plot.style_areabr)
Williams %R (v.4)This is an upgrade and an update of my Williams %R indicator modification.
As before this implementation is enhanced with CCI in the form of background colors. These colors can be used as a confirmation signal and indication of a current trend. Thee also can be employed in deciding when to enter/exit the market.
Besides, added is a scaling function and Lower/Upper Bound inputs.
DB CCI Breakout MTFDB CCI Breakout MTF
What does the indicator do?
The indicator will display crypto breakout and fallouts based on 4 timeframe CCI values. By default the current chart timeframe is used and the user may chose 3 other timeframes in the settings. Additionally, the symbol may be configured in the indicator settings. Default is Coinbase:ETHUSD.
The indicator will monitor the CCI levels on 4 timeframes and will alert to any CCI activity over 100 or under -100 which would indicate a breakout or fallout is present.
A green diamond is displayed when a breakout is detected on one or more of the timeframes for the selected symbol.
How should this indicator be used?
The indicator is a secondary alert system for the presence of breakouts or fallout conditions as under those scenarios position exit or entry strategies may be different.
Does the indicator include any alerts?
Not in this version. But I could add some if desired.
Use at your own risk and do your own diligence.
Enjoy!
Trend Surfers - Momentum + ADX + EMAThis script mixes the Lazybear Momentum indicator, ADX indicator, and EMA.
Histogram meaning:
Green = The momentum is growing and the ADX is growing or above your set value
Red = The momentum is growing on the downside and the ADX is growing or above your set value
Orange = The market doesn't have enough momentum or the ADX is not growing or above your value (no trend)
Background meaning:
Blue = The price is above the EMA
Purple = The price is under the EMA
Cross color on 0 line:
Dark = The market might be sideway still
Light = The market is in a bigger move
BB%Bx4This is just a script that combines 4 BB%B oscillators in one. It is useful for seeing multiple divergences on one graphic.
The default setting is the 1m time frame but, you can change it to 5m time frame and it will still work. You can see it on any CHART time frame and that was my goal when I made it. So, I don't have to switch back and forth.
I made this tool for my trading style and it may not work for you.
MACD x SuperTrend with trailing stoplossThis trading strategy is based on MACD crossover and crossunder. It uses the supertrend to identify the trend it is trading on and takes trades accordingly. You can use the built in risk to reward ratio parameter through the settings of the indicator for your desired R/R
My goal in creating this indicator was to learn about risk management. This indicator will put up a stop-loss and take profit target according to the entry point it shows.
This indicator showed me the best results on BTC at 5min price chart. I'm new to trading so, do your own due diligence
DCA After Downtrend v2 (by BHD_Trade_Bot)The purpose of the strategy is to identify the end of a short-term downtrend . So that you can easily to DCA certain amount of money for each month.
ENTRY
The buy orders are placed on a monthly basis for assets at the end of a short-term downtrend:
- Each month condition: In 1-hour time frame, each month has 24 * 30 candles
- The end of short-term downtrend condition: use MACD for less delay
CLOSE
The sell orders are placed when:
- Is last bar
The strategy use $1000 and trading fee is 1.1% for each order.
Pro tip: The 1-hour time frame has the best results on average:
- Total spent: $1000 x 33 = $33,000
- Total profit: $65,578
BTC Miner Netflows with smoothingBTC Miner Netflows with smoothing - shows the difference between Miner Inflow and Miner Outflow.
Miner income, sales as well as holdings, are generally considered to have a huge market impact, by analyzing miner Netflows, users can gauge if overall miners are accumulating or selling; high positive values point to accumulation, while negative numbers indicate net selling.
Data queried from IntoTheBlock.
Step-MA Filtered CCI [Loxx]Step-MA Filtered CCI is a CCI indicator that is filtered using a stepping moving average function. This produces a CCI that is much cleaner due to noise reduction.
What is CCI?
The Commodity Channel Index ( CCI ) measures the current price level relative to an average price level over a given period of time. CCI is relatively high when prices are far above their average. CCI is relatively low when prices are far below their average. Using this method, CCI can be used to identify overbought and oversold levels.
Included:
Bar coloring
3 signal variations w/ alerts
Loxx's Expanded Source Types
mess JBI have made an all in one powerful script. It contains all meme lines(Moving average, Ema, Dema, Vwma, Hma)
In general, orange color means negative and white means positive. But you can very easily customize the colors according to your need and enable and disable any meme line.
Dots represent change of price action, although it works on every time frame but I have got best results on 15minute and 4hour Time Frame.
Cross represent change in volume. Now that's the most powerful thing, I have picked time segmented oscillator and changed the cod to represent Volume change. To take a better note of market, Start from Bigger Time frames. This indicator predicted every move Perfectly.
Enjoy
Heiken Ashi & Super TrendThis is one of my open source 1h strategies
It works on Binance: BTCUSDTPERP charts
This strategy involves two indicators
1. Heiken Ashi - a typical technical indicator to help highlight and clarify the current trend. This somehow allows the chart to ignore unnecessary fluctuations and make the trend more visible.
2.Super Trend - - One of the most common ATR-based indicators, the SuperTrend indicator is useful to help you catch big trends.
Buy entry conditions are as follows.
1. The Super Trend indicator running on the Heiken Ashi chart gives a buy signal.
2. Buy at the current market price and take profit at 1% of the normal k-line at this time.
Take profit
TP - 1%
Stop Loss
None
Sharpe Ratio v4I'm publishing this indicator freely, because I'd like to get it reviewed by other people. This indicator was written whilst reading the book Systematic Trading by Robert Carver. In this book Carver describes trading rules that use a "dynamic" position size based on something like an evolving Sharpe Ratio . There are only a few other Sharpe indicators on TradingView, but they are either undocumented or use closed source code. You can use the following code as you wish for your own projects.
I'd like to let other people see this work, and let me know where they think this script is wrong, so that I can improve it.
Here's a basic rundown of Sharpe Ratio and its calculation.
SR is defined as: (excess) return minus the risk free rate divided by standard deviation of those returns. (This is where we're uncertain. Is the standard deviation of the returns, or just the closes?) But anyway the calculation itself is pretty simple:
SR = (r – b) ÷ s
Where r is the return of the asset over a certain period.
b is the interest rate of the risk-free asset.
s is the standard deviation of the returns over the same period.
For this indicator to "work" correctly, we're assuming the risk-free rate is 0. In fact, I did not include b at all in the indicator because it would make things too complicated, and go beyond the aim of this work.
To calculate the returns over a certain period, I'm using Rate of Change. Then calculating the standard deviation of those returns is pretty easy because we can use the same lookback period we used for ROC for the StDev calculation, thus:
averageReturn = ta.roc(close, lookbackLength)
stdev = ta.stdev(averageReturn, lookbackLength)
sharpe = (averageReturn / stdev)
Please leave a comment below if you believe this is incorrect. The chart shows a normal ROC indicator for comparison. I've also created a "bands" version of this indicator, which I'm planning to also release. The Keltner channel is just for comparing it with the StDev bands.
TARVIS Labs - Alts Macro Bottom/Top SignalsSCRIPT DESCRIPTION
PLEASE READ THROUGH THIS CAREFULLY.
This is a script specifically written to help provide indicators from a macro view for ALTS. This script needs to be run on the 1 day. It helps indicate when to accumulate alts, and when its in a bull run when this a bull run top beginning to form with warnings, and a indicator that a top is in. This is described further below.
NOTE - in order to accomodate most alts the script had to be broad enough in its indicators to cover many different scenarios. If you are trading a smaller altcoin I suggest taking a more conservative approach to accumulation.
FAQs:
1. Why is there no accumulation zone showing up before an uptrend?
This could be because the trend has been so strong for this coin that there hasn't been a strong enough signal to accumulate or this could be that the chart doesnt have enough historical data (needs over 2 years) for the indicators to flash green.
2. Why is there no tops shown for a chart Im looking at?
This is either because there isn't enough historical data (needs over 2 years) for the indicators to build or because the altcoin didnt perform as well as the rest of the market. The altcoin has to perform as well as the market over the length of the bull run in order for the signals to show. Typically an altcoin that shows sharp increases and sharp drops shortly after will not have signals show up.
3. The "Potential End of Bull Run Top Indicator" showed up but we weren't near the top yet, why is that?
The alts indicator has to work across many altcoins, and their trends are not all the same. This can lead to the indicator showing but not necessarily being the exact top. The data from the alts macro bottom/top signals should be paired with the "TARVIS Labs bitcoin macro bottom/top signals" indicator for BTC. The reasoning is because if the top is not showing that its in for Bitcoin its likely that the altcoin's top is also not in. You should use the two in tandem to know if the bull run top is very likely in.
ACCUMULATION ZONE INDICATOR - LIGHT GREEN
Description
When we look at the general crypto landscape, the 200d & 300d EMAs are extremely useful. We can use their cross and momentum in order to determine a bottom forming. If the price has fallen over 40% below the 200 day EMA and the 200 day EMA has crossed below the 300d EMA, its a downtrend with a steep fall, which could indicate a good time to accumulate. When we see the 200 day EMA's slope drop drastically (over 5% w/w) it is also a good signal to accumulate.
Strategy for Usage
For alts, the strategy can vary drastically. You need to take into account:
1. the market cap of the altcoin, is it a smaller market cap altcoin or a larger one?
2. historical trend, does it typically trend strongly with a smaller accumulation zone?
Once you've taken these into account you can form a strategy. For example, if the altcoin has had smaller accumulation zones historically you'll want to take advantage of the accumulation zones when they pop up and be more aggressive (say a 30 day accumulation). If the altcoin has historically had longer accumulation zones then you'll want to be more conservative with your strategy and potentially have a 100 day (or even longer) accumulation period. If the altcoin is a smaller market cap alt, you will want to also take that into account. You'll want to likely be more conservative,
STRONG BUY IN ACCUMULATION ZONE INDICATOR - DARK GREEN
Description
We can add to the bottoming signal by looking for strong downtrends inside the bottoming signal. We do this by seeing when the 36 day EMA has a slope decreasing by 2% day/day.
Strategy for Usage
These strong downtrend days can be used to add more to our accumulation strategy. We can add more on these days (ex. double what you were planning to on a typical accumulation day).
LOCAL TOP NEAR BULL RUN TOP INDICATOR - RED
Description
When the 100 week EMA is in a strong uptrend (4% increase w/w) we can look for significant loss of momentum in order to determine if a local top is in near a bull run top. This strategy uses a MACD with 9/36/9 config for the daily chart. We look for the signals momentum loss, when the slope becomes negative.
Strategy for Usage
Ideally the right strategy to use here is to exit the market when this indicator starts. When the indicator ends if the "Potential End of Bull Run Top Indicator" is not showing on the chart you can buy back into the market.
POTENTIAL END OF BULL RUN TOP INDICATOR - DARK RED
Description
When the 100 week EMA is in a strong uptrend (3% increase w/w), and a MACD config of 108/234/9 has a negative signal slope signifying a very large momentum loss, but the 1d 18 EMA is still above the 1d 63 EMA we show this signal.
Strategy for Usage
This is a strong indicator that the top is in, and it potentially being the bull run top. Because alts can vary strongly in their charts, this should be a strong warning but not necessarily a certainty that the bull run is over.
STD-Filtered, N-Pole Gaussian Filter [Loxx]This is a Gaussian Filter with Standard Deviation Filtering that works for orders (poles) higher than the usual 4 poles that was originally available in Ehlers Gaussian Filter formulas. Because of that, it is a sort of generalized Gaussian filter that can calculate arbitrary (order) pole Gaussian Filter and which makes it a sort of a unique indicator. For this implementation, the practical mathematical maximum is 15 poles after which the precision of calculation is useless--the coefficients for levels above 15 poles are so high that the precision loss actually means very little. Despite this maximal precision utility, I've left the upper bound of poles open-ended so you can try poles of order 15 and above yourself. The default is set to 5 poles which is 1 pole greater than the normal maximum of 4 poles.
The purpose of the standard deviation filter is to filter out noise by and by default it will filter 1 standard deviation. Adjust this number and the filter selections (price, both, GMA, none) to reduce the signal noise.
What is Ehlers Gaussian filter?
This filter can be used for smoothing. It rejects high frequencies (fast movements) better than an EMA and has lower lag. published by John F. Ehlers in "Rocket Science For Traders".
A Gaussian filter is one whose transfer response is described by the familiar Gaussian bell-shaped curve. In the case of low-pass filters, only the upper half of the curve describes the filter. The use of gaussian filters is a move toward achieving the dual goal of reducing lag and reducing the lag of high-frequency components relative to the lag of lower-frequency components.
A gaussian filter with...
One Pole: f = alpha*g + (1-alpha)f
Two Poles: f = alpha*2g + 2(1-alpha)f - (1-alpha)2f
Three Poles: f = alpha*3g + 3(1-alpha)f - 3(1-alpha)2f + (1-alpha)3f
Four Poles: f = alpha*4g + 4(1-alpha)f - 6(1-alpha)2f + 4(1-alpha)3f - (1-alpha)4f
and so on...
For an equivalent number of poles the lag of a Gaussian is about half the lag of a Butterworth filters: Lag = N*P / pi^2, where,
N is the number of poles, and
P is the critical period
Special initialization of filter stages ensures proper working in scans with as few bars as possible.
From Ehlers Book: "The first objective of using smoothers is to eliminate or reduce the undesired high-frequency components in the eprice data. Therefore these smoothers are called low-pass filters, and they all work by some form of averaging. Butterworth low-pass filters can do this job, but nothing comes for free. A higher degree of filtering is necessarily accompanied by a larger amount of lag. We have come to see that is a fact of life."
References John F. Ehlers: "Rocket Science For Traders, Digital Signal Processing Applications", Chapter 15: "Infinite Impulse Response Filters"
Included
Loxx's Expanded Source Types
Signals
Alerts
Bar coloring
Related indicators
STD-Filtered, Gaussian Moving Average (GMA)
STD-Filtered, Gaussian-Kernel-Weighted Moving Average
One-Sided Gaussian Filter w/ Channels
Fisher Transform w/ Dynamic Zones
R-sqrd Adapt. Fisher Transform w/ D. Zones & Divs .
Gaussian Filter MACD [Loxx]Gaussian Filter MACD is a MACD that uses an 1-4 Pole Ehlers Gaussian Filter for its calculations. Compare this with Ehlers Fisher Transform.
What is Ehlers Gaussian filter?
This filter can be used for smoothing. It rejects high frequencies (fast movements) better than an EMA and has lower lag. published by John F. Ehlers in "Rocket Science For Traders". First implemented in Wealth-Lab by Dr René Koch.
A Gaussian filter is one whose transfer response is described by the familiar Gaussian bell-shaped curve. In the case of low-pass filters, only the upper half of the curve describes the filter. The use of gaussian filters is a move toward achieving the dual goal of reducing lag and reducing the lag of high-frequency components relative to the lag of lower-frequency components.
A gaussian filter with...
one pole is equivalent to an EMA filter.
two poles is equivalent to EMA ( EMA ())
three poles is equivalent to EMA ( EMA ( EMA ()))
and so on...
For an equivalent number of poles the lag of a Gaussian is about half the lag of a Butterworth filters: Lag = N * P / (2 * ¶2), where,
N is the number of poles, and
P is the critical period
Special initialization of filter stages ensures proper working in scans with as few bars as possible.
From Ehlers Book: "The first objective of using smoothers is to eliminate or reduce the undesired high-frequency components in the eprice data. Therefore these smoothers are called low-pass filters, and they all work by some form of averaging. Butterworth low-pass filtters can do this job, but nothing comes for free. A higher degree of filtering is necessarily accompanied by a larger amount of lag. We have come to see that is a fact of life."
References John F. Ehlers: "Rocket Science For Traders, Digital Signal Processing Applications", Chapter 15: "Infinite Impulse Response Filters"
Included
Loxx's Expanded Source Types
Signals, zero or signal crossing, signal crossing is very noisy
Alerts
Bar coloring
STD-Filtered, Gaussian Moving Average (GMA) [Loxx]STD-Filtered, Gaussian Moving Average (GMA) is a 1-4 pole Ehlers Gaussian Filter with standard deviation filtering. This indicator should perform similar to Ehlers Fisher Transform.
The purpose of the standard deviation filter is to filter out noise by and by default it will filter 1 standard deviation. Adjust this number and the filter selections (price, both, GMA, none) to reduce the signal noise.
What is Ehlers Gaussian filter?
This filter can be used for smoothing. It rejects high frequencies (fast movements) better than an EMA and has lower lag. published by John F. Ehlers in "Rocket Science For Traders". First implemented in Wealth-Lab by Dr René Koch.
A Gaussian filter is one whose transfer response is described by the familiar Gaussian bell-shaped curve. In the case of low-pass filters, only the upper half of the curve describes the filter. The use of gaussian filters is a move toward achieving the dual goal of reducing lag and reducing the lag of high-frequency components relative to the lag of lower-frequency components.
A gaussian filter with...
one pole is equivalent to an EMA filter.
two poles is equivalent to EMA(EMA())
three poles is equivalent to EMA(EMA(EMA()))
and so on...
For an equivalent number of poles the lag of a Gaussian is about half the lag of a Butterworth filters: Lag = N * P / (2 * ¶2), where,
N is the number of poles, and
P is the critical period
Special initialization of filter stages ensures proper working in scans with as few bars as possible.
From Ehlers Book: "The first objective of using smoothers is to eliminate or reduce the undesired high-frequency components in the eprice data. Therefore these smoothers are called low-pass filters, and they all work by some form of averaging. Butterworth low-pass filtters can do this job, but nothing comes for free. A higher degree of filtering is necessarily accompanied by a larger amount of lag. We have come to see that is a fact of life."
References John F. Ehlers: "Rocket Science For Traders, Digital Signal Processing Applications", Chapter 15: "Infinite Impulse Response Filters"
Included
Loxx's Expanded Source Types
Signals
Alerts
Bar coloring
Related indicators
STD-Filtered, Gaussian-Kernel-Weighted Moving Average
One-Sided Gaussian Filter w/ Channels
Fisher Transform w/ Dynamic Zones
R-sqrd Adapt. Fisher Transform w/ D. Zones & Divs.
Wolfpack Divergences [multigrain]█ OVERVIEW
A fast and improved divergence finding algorithm that aims to be better than the built-in TradingView divergence algorithm.
█ CONCEPTS
Wolfpack
Wolfpack is an oscillator made popular by darrellfischer1 all the way back in 2017. Since then the Wolfpack oscillator has been utilized by a number of notable strategy/indicator creators. At some point it was realized that the oscillator was simply the Moving Average Crossover Divergence oscillator with the fast and slow length of 3 and 8, respectively. The true significance and reasoning behind these lengths are unknown, however one may surmise that they are chosen due to their relevance as Fibonacci numbers.
Divergences
Divergence is when the price of an asset is moving in the opposite direction of a technical indicator, such as an oscillator, or is moving contrary to other data. Divergence warns that the current price trend may be weakening, and in some cases may lead to the price changing direction.
█ USAGE
Wolfpack
Similar to many other oscillators, when the Wolfpack oscillator reports a value above the zero-line, this indicates a bullish trend in the price. Subsequently, a value below the zero-line indicate a bearish trend in the price.
Divergences
Divergence in technical analysis may signal a major positive or negative price move. A positive divergence occurs when the price of an asset makes a new low while an indicator, such as money flow, starts to climb. Conversely, a negative divergence is when the price makes a new high but the indicator being analyzed makes a lower high.
Weighted percentile nearest rank oscillatorOriginal script
This is my attempt at making a price oscillator out of gorx1's weighted percentile nearest rank script. I centered everything to the 50th percentile and everything oscillates around that. The upper and lower bounds are 100th and 0th. Normalization normalizes the data to the top and bottom lines. The 'center line' represents the momentum of the 50th percentile in either direction. Good luck and happy hunting.
DCA After Downtrend (by BHD_Trade_Bot)The purpose of the strategy is to identify the end of a short-term downtrend . So that you can easily to DCA certain amount of money for each month.
ENTRY
The buy orders are placed on a monthly basis for assets at the end of a short-term downtrend:
- Each month condition: In 1-hour time frame, each month has 240 candles
- The end of short-term downtrend condition: use MACD for less delay
CLOSE
The sell orders are placed when:
- Is last bar
The strategy use $1000 and trading fee is 0.1% for each order.
Pro tip: The 1-hour time frame for TSLA has the best results on average:
- Total spent: $1000 x 85 = $85,000
- Total profit: $790,556
Nasdaq 100 ScreenerNasdaq 100 screener is comprehensive table displaying the following parameters :
Op = Open Price of the Day.
LaP = Last Price.
O-L = Open Price of the Day - Last Price.
ROC = Rate of Change .
SMA20 = Simple Moving Average 20 period.
S20d = Last Price - SMA 20.
SMA50 = Simple Moving Average 50 period.
S50d = Last Price - SMA 50.
SMA200 = Simple Moving Average 200 period.
S200d = Last Price - SMA 200.
ADX(14) = Average Directional Index.
RSI(14) = Relative Strength Index.
CCI(20) = Commodity Channel Index.
ATR(14) = Average True Range.
MOM(10) = Momentum.
AcDis(K) = Accumulation/Distribution.
CMF(20) = Chaikin Money Flow.
MACD = Moving Average Convergence Divergence.
Sig = MACD signal.
Nasdaq 100 stocks are divided into following alphabetical grouping for input access purpose under “Options” in “Settings” menu.
A to B 21 stocks “Input symbols” are listed under the “Options” in “Input A to B”
C to E 18 stocks “Input symbols” are listed under the head “Options” in “Input C to E”
F to L 19 stocks “Input symbols” are listed under the head “Options” in “Input F to L”
M to P 22 stocks “Input symbols” are listed under the head “Options” in “Input M to P”
R to Z 20 stocks “Input symbols” are listed under the head “Options” in “Input R to Z”
A to Z 100 stocks “Input symbols” are listed under the head “Options” in “Input A to Z”
User after visiting the “Settings” menu simply is required to select the “input symbol” from the stock listed under respective alphabetical Input lists to which the particular stock belongs. The resultant data is tabulated under respective row in Table .At a time User can see 5 different stocks i.e one each in different alphabetical lists in respective alphabetical order rows stated in the Table. User can scroll in each list to access and shift to any other stock in the list. In addition a Master list of all 100 stocks is given under “ Input A to Z “ at the last row of table.
Nasdaq 100 screener is a simple table , which facilitate to view 6 different stocks at a time (inclusive one from Master list of “Input A to Z” with a display of 19 parameters.
