Combo 2/20 EMA & Absolute Price Oscillator (APO) This is combo strategies for get a cumulative signal.
First strategy
This indicator plots 2/20 exponential moving average. For the Mov
Avg X 2/20 Indicator, the EMA bar will be painted when the Alert criteria is met.
Second strategy
The Absolute Price Oscillator displays the difference between two exponential
moving averages of a security's price and is expressed as an absolute value.
How this indicator works
APO crossing above zero is considered bullish, while crossing below zero is bearish.
A positive indicator value indicates an upward movement, while negative readings
signal a downward trend.
Divergences form when a new high or low in price is not confirmed by the Absolute Price
Oscillator (APO). A bullish divergence forms when price make a lower low, but the APO
forms a higher low. This indicates less downward momentum that could foreshadow a bullish
reversal. A bearish divergence forms when price makes a higher high, but the APO forms a
lower high. This shows less upward momentum that could foreshadow a bearish reversal.
WARNING:
- For purpose educate only
- This script to change bars colors.
在腳本中搜尋"backtesting"
S&P500 VIX Volatility Warning IndicatorToday I am sharing with the community a volatility indicator that can help you or your algorithms avoid black swan events. Variance is most commonly used in statistics to derive standard deviation (with its square root). It does have another practical application, and that is to identify outliers in a sample of data. Variance in statistics is defined as the squared difference between a value and its mean. Calculating that squared difference means that the farther away the value is from the mean, the more the variance will grow (exponentially). This exponential difference makes outliers in the variance data more apparent.
Why does this matter?
There are assets or indices that exist in the stock market that might make us adjust our trading strategy if they are behaving in an unusual way. In some instances, we can use variance to identify that behavior and inform our strategy.
Is that really possible?
Let’s look at the relationship between VIX and the S&P500 as an example. If you trade an S&P500 index with a mean reversion strategy or algorithm, you know that they typically do best in times of volatility. These strategies essentially attempt to “call bottom” on a pullback. Their downside is that sometimes a pullback turns into a regime change, or a black swan event. The other downside is that there is no logical tight stop that actually increases their performance, so when they lose they tend to lose big.
So that begs the question, how might one quantitatively identify if this dip could turn into a regime change or black swan event?
The CBOE Volatility Index (VIX) uses options data to identify, on a large scale, what investors overall expect the market to do in the near future. The Volatility Index spikes in times of uncertainty and when investors expect the market to go down. However, during a black swan event, the VIX spikes a lot harder. We can use variance here to identify if a spike in the VIX exceeds our threshold for a normal market pullback, and potentially avoid entering trades for a period of time (I.e. maybe we don’t buy that dip).
Does this actually work?
In backtesting, this cut the drawdown of my index reversion strategies in half. It also cuts out some good trades (because high investor fear isn’t always indicative of a regime change or black swan event). But, I’ll happily lose out on some good trades in exchange for half the drawdown. Lets look at some examples of periods of time that trades could have been avoided using this strategy/indicator:
Example 1 – With the Volatility Warning Indicator, the mean reversion strategy could have avoided repeatedly buying this pullback that led to SPXL losing over 75% of its value:
Example 2 - June 2018 to June 2019 - With the Volatility Warning Indicator, the drawdown during this period reduces from 22% to 11%, and the overall returns increase from -8% to +3%
How do you use this indicator?
This indicator determines the variance of the VIX against a long term mean. If the variance of the VIX spikes over an input threshold, the indicator goes up. The indicator will remain up for a defined period of bars/time after the variance returns below the threshold. I have included default values I’ve found to be significant for a short-term mean-reversion strategy, but your inputs might depend on your risk tolerance and strategy time-horizon. The default values are for 1hr VIX data. It will pull in variance data for the VIX regardless of which chart the indicator is applied to.
Disclaimer : Open-source scripts I publish in the community are largely meant to spark ideas or be used as building blocks for part of a more robust trade management strategy. If you would like to implement a version of any script, I would recommend making significant additions/modifications to the strategy & risk management functions. If you don’t know how to program in Pine, then hire a Pine-coder. We can help!
Sessions with High/Low DiffThe main purpose of this indicator is to facilitate backtesting, but it may also be useful for traders to easily identify the current
active/open trading sessions on lower-timeframe charts.
This indicator also tracks the session high/low difference and plots it as a label on the last candle of the session once the last
bar of that session has finished printing and a new candle opened. The position and direction of the label is based on the
session open and close - if the session open is greater than the session close (which would equate to the equivalent of a red candle),
the label will be printed UNDER the last candle, and vice versa if the session close is above the session open.
The number printed inside the label is the difference between the session high and the session low, scaled to the minimum tick value of the chart.
Note #1: There is a Pinescript maximum of 500 labels allowed on any chart. While I could have gotten fancy and done some wizardry with label arrays,
I didn't really see a point to it. If labels are enabled for all 4 sessions at the same time, that would still have them available for the past 125
sessions, which would be about 6 months (approx 252 trading days per year, and this would cover 125 of them). If you limit to 2 sessions, you double
your potential look-back to almost a year (250 days out of the 252 average trading days each year), and for a single session, you double it yet again
to just under 2 years.
Note #2: As this indicator tracks open, high, low, and close for each session, it can potentially be enhanced (or forked) to construct "session candles".
I'm not sure what use this would be to anyone, but the pieces are there should someone find a use for it.
While it would be easy to add alerts on sessions opening/closing, I didn't see a purpose or value in that as it would be little more than a
glorified alarm clock. If I get enough demand to add them, I will gladly consider it.
200DMA last DOM - ajhImplements and backtests a simple 200 day moving average trend following rules based on last day of month to limits trades to 12 per year.
From the book : 5 BEST Moving Average Strategies (That beat buy and hold) by Steve Burns and Holly Burns
Click on the cog to set the input date range eg; 2000-01-01 to 2016-12-31
The book back tested SP500 returns from 2000-2016 317% using this method vs 125% buy and hold only with less drawdown.
Simple 200 day moving average test and trading on last day of month.
(you may find it trades on next available day close to end of month as not all dates can be traded weekends etc..)
Rules are ;
1. if last day of month and stock over 200 day moving average, then go long 100%
2. if last day of month and stock under 200 day moving average, then close long 100% and goto cash.
Aims to miss market declines and keep you long for upside.
Note: Have found doesn't work well in choppy markets moving sideways like the FTSE100 for same period 2000-2016 and causes losses. Also for many stocks.
ETF 3-Day Reversion StrategyIntroduction: This strategy is a modification of the “3-day Mean Reversion Strategy” from the book "High Probability ETF Trading" by Larry Connors and Cesar Alvarez. In the book, the authors discuss a high-probability ETF mean reversion strategy for a 1-day time-frame with these simple rules:
The price must be above the 200 day SMA and below the 5 day SMA.
The low of today must be lower than the low of yesterday (must be true for 3 consecutive days)
The high of today must be lower than the high of yesterday (must be true for 3 consecutive days)
If the 3 rules above are true, then buy on the close of the current day.
Exit when the closing price crosses above the 5 day SMA.
In practice and in backtesting, I’ve found that the strategy consistently works better when using an EMA for the trend-line instead of an SMA. So, this script uses an EMA for the trend-line. I’ve also made the length of the exit EMA adjustable.
How it works:
The Strategy will buy when the buy conditions above are true. The strategy will sell when the closing price crosses over the Exit Moving Average
Plots:
Green line = Exit Moving Average (Default 5 Day EMA)
Blue line = 5 Day EMA (Used as Entry Criteria)
Disclaimer: Open-source scripts I publish in the community are largely meant to spark ideas that can be used as building blocks for part of a more robust trade management strategy. If you would like to implement a version of any script, I would recommend making significant additions/modifications to the strategy & risk management functions. If you don’t know how to program in Pine, then hire a Pine-coder. We can help!
Supertrend StrategyThis Supertrend strategy will allow you to enter a long or short from a supertrend trend change. Both ATR period and ATR multiplier are adjustable. If you check off "Change ATR Calculation Method" it will base the calculation off the sma and give you slightly different results, which may work better depending on the asset. Be sure to enter slippage and commission into the properties to give you realistic results.
I've also built in backtesting date ranges and the ability to trade only within certain times of day and have it close all trades at the end of that time frame. This is especially useful for day trading stocks. If you check off "Enter First Trade ASAP" then when using the time frame option it will enter the current trade. If however you uncheck that box and instead check off "Wait To Enter First Trade" it will wait for the trend to change and then enter.
You can also specify a % based take profit and stop loss. In most cases the stop loss is not needed because of the atr based stop that supertrend provides so you could check only take profit and see if it works best to take profit or to let supertrend trend change get you out. Also keep in mind that if you have "Enter First Trade ASAP" checked off and use the stop loss and/or take profit then it will re-enter the current trend again.
Finally there's custom alert fields so you can send custom alert messages for strategy entry and exit for use with automated trading services. Simply enter your messages in the fields within the strategy properties and then put {{strategy.order.alert_message}} in your alert message body and it will dynamically pull in the appropriate message.
US Sector CorrelationsA new and interesting way to look at Breadth. As for the usefulness of it, one would have to do some proper backtesting to get a full grasp of the capabilities. This is just a concept currently. But in general, SPX holding near ATHs with very low sector correlations can be a topping indicator. SPX selling off with Correlations all very positive across each sector...can be a sign of an impending bottom. But, needs the "full bake" of proper testing and analysis versus just guessing. I like the concept and want to explore it further, and I will. This is just the start.
Combo 2/20 EMA & 3 Day Pattern This is combo strategies for get a cumulative signal.
First strategy
This indicator plots 2/20 exponential moving average. For the Mov
Avg X 2/20 Indicator, the EMA bar will be painted when the Alert criteria is met.
Second strategy
This startegy based on 3-day pattern reversal described in "Are Three-Bar
Patterns Reliable For Stocks" article by Thomas Bulkowski, presented in
January,2000 issue of Stocks&Commodities magazine.
That pattern conforms to the following rules:
- It uses daily prices, not intraday or weekly prices;
- The middle day of the three-day pattern has the lowest low of the three days, with no ties allowed;
- The last day must have a close above the prior day's high, with no ties allowed;
- Each day must have a nonzero trading range.
WARNING:
- For purpose educate only
- This script to change bars colors.
Swing EMAWhat is Swing EMA?
Swing EMA is an exponential moving average crossover-based indicator used for low-risk directional trading.
it's used for different types of Ema 20,50,100 and 200, 3 of them are plotted on chat 20,100,200.
100 and 200 Ema is used for showing support and resistance and it contains highlights area between them and its change color according to market crossover condition.
20 moving average is used for knowing Market Behaviour and changing its color according to crossover conditions of 50 and 20 Ema.
How does it work?
It contains 4 different types of moving averages 20,50,100, 200 out of 3 are plotted on the chart.
20 Ema is used for knowing current market behavior. Its changes its color based on the crossover of 50 Ema and 20 Ema, if 20 Ema is higher than 50 Ema then it changes its color to green, and its opposites are changed their color to red when 20 Ema is lower than 50 Ema.
100 and 200 Ema used as a support and resistance and is also contain highlighted areas between them its change their color based on the crossover if 100 Ema is higher than 200 Ema a then both of them are going to change color to Green and as an opposite, if 200 Ema is higher then 100 Ema is going to change its color to red.
So in simple word 100 and 200 Ema is used as support and resistance zone and 20 Ema is used to know current market behavior.
How to use it?
It is very easy to understand by looking at the example I gave where are the two different types of phrases. phrase bull phrase and bear phrase so 100 and 200 Ema is used as a support and resistance and to tell you which phrase is currently on the market on example there is a bull phrase on the left side and bear phrase on the right side by using your technical analysis you can find out a really good spot to buy your stocks on a bull phrase and too short on the bear phrase. 20 Ema is used as a knowing the current market behavior it doesn't make any difference on buying or selling as much as 100 Ema and 200 Ema.
Tips
Don't trade against the market.
Try trade on trending stocks rather than sideways stock.
The higher the area between 100 Ema and 200 Ema is the stronger the phrase.
Do Backtesting before real trading.
Enjoy Trading.
Zendog V3 backtest DCA bot 3commasMAJOR UPDATE:
- Update to Pinescript v5
- MAJOR refactor for the logic of how orders are placed. BO order is placed when the condition is first encountered and we are not in a deal.
The extra SO orders (if based on price movement) are all placed on the next candle after BO order, instead of each being placed one after another.
Take profit (if percentage) and Stop loss are placed on the first candle after BO order because if BO and TP are on the same candle TV does not execute properly.
These changes should improve strategy accuracy when multiple prices are hit by the same candle.
- NEW FEATURE: Support to Stop deal using an external indicator (i.e. stop long deal when RSI > 80)
- NEW FEATURE: Support to trigger Safety orders using an external indicator (i.e. trigger each additional SO when RSI < 10, regardless of price movement)
The price movement logic may be implemented in the indicator that plots start / end signals. The SO size is calculated using the configuration of steps.
- NEW FEATURE: Safety order command for 3commas bot. This is implemented using Add funds in the quote currency (for pair BTCUSDT the quote currency is USDT)
The SO size is calculated using the configuration of steps, for exact order size (and price) use the built-in Steps table.
- NEW FEATURE: Addition of extra columns to the steps table: Required price for TP, Required % change for TP, Required % change for BEP (Breakeven point)
- Update to steps table to remove prices when Safety orders are not based on % price change
- The code is opensource. I will not be able to sustain merges for the script, but feel free to use and develop your own version and ping me on discord to review them
and maybe include in the original script
Moving Average Multitool CrossoverAs per request, this is a moving average crossover version of my original moving average multitool script .
It allows you to easily access and switch between different types of moving averages, without having to continuously add and remove different moving averages from your chart. This should make backtesting moving average crossovers much, much more easier. It also has the option to show buy and sell signals for the crossovers of the chosen moving averages.
It contains the following moving averages:
Exponential Moving Average (EMA)
Simple Moving Average (SMA)
Weighted Moving Average (WMA)
Double Exponential Moving Average (DEMA)
Triple Exponential Moving Average (TEMA)
Triangular Moving Average (TMA)
Volume-Weighted Moving Average (VWMA)
Smoothed Moving Average (SMMA)
Hull Moving Average (HMA)
Least Squares Moving Average (LSMA)
Kijun-Sen line from the Ichimoku Kinko-Hyo system (Kijun)
McGinley Dynamic (MD)
Rolling Moving Average (RMA)
Jurik Moving Average (JMA)
Arnaud Legoux Moving Average (ALMA)
Vector Autoregression Moving Average (VAR)
Welles Wilder Moving Average (WWMA)
Sine Weighted Moving Average (SWMA)
Leo Moving Average (LMA)
Variable Index Dynamic Average (VIDYA)
Fractal Adaptive Moving Average (FRAMA)
Variable Moving Average (VAR)
Geometric Mean Moving Average (GMMA)
Corrective Moving Average (CMA)
Moving Median (MM)
Quick Moving Average (QMA)
Kaufman's Adaptive Moving Average (KAMA)
Volatility-Adjusted Moving Average (VAMA)
Modular Filter (MF)
RSI %b Signal [H1 Backtesting]-----------------------------------------------------------------
This simple strategy base on RSI, EMA, Bollinger Bands to get Buy and Sell Signal with detail as below:
-----------------------------------------------------------------
1.Define Oscillator Line
+ Oscillator Line is smoothed by ema(28) of RSI(14) on H1 Timeframe
2.Define Overbought and Oversold
+ Apply Bollinger Bands BB(80,3) on Oscillator Line and calculate %b
+ Overbought Zone marked above level 0.8
+ Oversold Zone marked below level 0.2
3.Buy Signal
+ Entry Long Position when %b crossover Point of Entry Long
+ Deafault Point of Entry Long is 0.2
+ Buy signal marked by Green dot
4.Sell Signal
+ Entry Short Position when %b crossunder Point of Entry Short
+ Deafault Point of Entry Short is 0.8
+ Sell signal marked by Red dot
5.Exit Signal
+ Exit Position (both Long and Short) when %b go into Overbought Zone or Oversold Zone
+ Exit signal marked by Yellow dot
-----------------------------------------------------------------
MA MTF Cross StrategyStrategy Introduction
This multi-timeframe strategy generates buy and sell entries based on two Moving Averages’ cross with an option to turn on trend direction confirmation through 3rd Moving Average selection. While all three moving averages can be selected from the following list:
SMA
EMA
DEMA
TEMA
LRC
WMA
MF
VAMA
TMA
HMA
JMA
Kijun v2
EDSMA
McGinley
Only long trades are enabled currently
Default Settings
I've set the default selection to the perfect options for 1D timeframe. You can modify all MAs selections and their lengths according to your selected timeframes.
Following default settings are used:
Heiken Ashi Candles are selected by default as source
1st Moving Average selection is set to LRC (Linear Regression Curve)
Length of 1st Moving Average is set to 50
2nd Moving Average is set to EDSMA (Ehlers Deviation-Scaled Moving Average)
Length of 2nd Moving Average is set to 30
3rd Moving Average is set to HMA (Hull Moving Average)
Length of 3rd Moving Average is set to 200
Uptrend direction confirmation through 3rd Moving Average is set to false by default
Start date is set to start from 2013
Backtesting can also be done selecting %age of equity
Suggestions for Usage
Mostly winning trades by set defaults have no prominent drawdown so losing trades can be abolished with Stoploss. Would soon add Stoploss and Takeprofit options in next version. Also, if you want an alerts version of it then just comment below and would publish it later. I’ve found this strategy useful on 1D timeframe with described default settings but multiple Mas selections can be explored further.
Moving Average MultitoolI made this script as a personal tool while backtesting multiple moving averages. It allows you to easily access and switch between different types of moving averages, without having to continuously add and remove different moving averages from your chart.
It also has the option to show the a 14 period average distance between the closing price of an asset and the selected moving average, as a multiple of ATR. This number can be shown by enabling the "Show ATR Between MA and Close" setting. The intention of this value is to quantify and compare the speed of different moving averages across any instrument and any timeframe. The higher the value, the slower the moving average. The lower the value, the faster the moving average.
MZ SRSI Strategy V1.0Strategy Introduction
This strategy starts from selection of 1st Moving Average from one of following:
SMA
EMA
DEMA
TEMA
LRC
WMA
MF
VAMA
TMA
HMA
JMA
Kijun v2
EDSMA
McGinley
Then it calculates the RSI of selected 1st Moving Average
In the end it calculates Moving Average of previously calculated RSI and for this purpose 2nd Moving Average is also selected from above list.
Cross of RSI and its Moving Average generates Strategy Alerts
Only long trades are enabled currently
Default Settings
I've set the default selection to the perfect options for 1D and 4h timeframes. You can modify both MAs selection and their length according to your selected timeframe.
Following default settings are used:
Heiken Ashi Candles are selected by default as source
1st Moving Average selection is set to LRC (Linear Regression Curve)
Length of 1st Moving Average is set to 50
RSI length is set to 2 because it is supposed to be fast
2nd Moving Average of RSI is set to TMA (Triangular Moving Average)
Length of 1st Moving Average is set to 5
Start date is set to 2011
Backtesting can also be done selecting %age of equity
Suggestions for Usage
Mostly winning trades have no prominent drawdown so losing trades can be abolished with Stoploss. Would soon add Stoploss, MTF and Takeprofit options in next version. Also if you want an alerts version of it then just comment below and would publish it later. I’ve found this strategy useful on 1D and 4h timeframes with described default settings.
Combo Backtest 123 Reversal & TEMA1This is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
This study plots the TEMA1 indicator. TEMA1 ia s triple MA (Moving Average),
and is calculated as 3*MA - (3*MA(MA)) + (MA(MA(MA)))
WARNING:
- For purpose educate only
- This script to change bars colors.
GenericTradingLibrary "GenericTrading"
This library aims to collect rare but useful operations for
get_most_recent_long_or_short_position_closed_index() : returns most recent long/short closed bar index.
get_most_recent_long_or_short_position_open_index() : returns most recent long/short closed bar index.
These two functions designed to help to speed up the coding for strategies that contains "re-enter" logic.
These two functions also could applies in the situations where time-count is needed in your condition.
Jake Bernstein - Moving Average ChannelWe all know that moving averages, in particular, moving averages of closing prices tend to be highly inaccurate indicators and frequently miss major tops and bottoms. In backtesting, they tend to be accurate some 30 to 40% of the time which is to my way of thinking unacceptable. On the contrary moving averages of opens versus closes for highs versus lows, when used properly avoid the drawbacks of closing moving averages, particularly when combined with a trigger. Shown above is my moving average channel method which uses the 57 SMA of Williams accumulation distribution as a setup or trigger. As shown by the arrows two consecutive price bars completely below the MA channel low and triggered by Williams below SMA constitutes a sell signal. Conversely, two consecutive price bars or more above the moving average channel high accompanied by Williams above its moving average constitutes a sell trigger. The moving average channel high, the red line is a 10 period Moving average of highs. The Moving average channel low, the green line is an 8 period Moving average of the low. There are at least a dozen applications of this methodology including its ability to spot trend changes, support, resistance, swing trades, market strength, market weakness, and more. I will post some of these additional uses of the moving average channel as they present themselves. Do note that in this chart there were two instances above the moving average channel high but these were not triggered by Williams AD and therefore the trend remains down for the duration of this chart. The methodology associated with my MAC is completely rules-based and works in any timeframe. Thank you my friend Larry Williams for developing your excellent version of accumulation-distribution
LPB MicroCycles StrategyWhat it is:
We use the Hodrick-Prescott filter applied to the closing price, and then take the outputted trendline and apply a custom vwap, the time frame of which is based on user input, not the default 1 day vwap . Then we go long if the value 2 bars ago is greater then one bar ago. We sell and color the bars and lines when the if the value of 2 bars ago is less than one bar ago.
Also included:
GUI for backtesting
ATR Based Stop Loss
How to use:
Go long when the indicators suggest it, and use the stop losses to reduce risk.
Best if paired with a volatility measurement (inside candles, average true range , bollingerband%B)
Argo I (alerts for 3commas single bots)This script lets users create BUY/SELL alerts for 3commas single bots in a simple way, based on a built in set of indicators that can be tweaked to work together or separately through the study settings. Indicators include Bollinger Bands, Williams %R, RSI, EMA, SMA , Market Cipher, Inverse Fisher Transform.
If the user choses to create both BUY and SELL signals from the study settings, the alert created will send both BUY and SELL signals for the selected pair. Note the script will only send alerts for the pair selected in the study settings, not for the current chart (if different).
How to use:
- Add the script to the current chart
- Open the study settings , insert bot details. Pairs MUST be in capital letters or 3commas will not recognize them.
- Still in the study settings, tweak the deal start/close conditions from various indicators until happy. The study will plot the entry / exit points below the current chart (1 = buy, 2 = sell)
- Ideally, test the settings with a backtesting script. The present script is compatible with the Trading Parrot's backtester.
- When happy, right click on the "..." next to the study name, then "Add alert'".
- Under "Condition", on the second line, chose "Any alert () function call". Add the webhook from 3commas, give it a name, and "create".
Happy tweaking!
Relative Volume (rVol), Better Volume, Average Volume ComparisonThis is the best version of relative volume you can find a claim which is based on the logical soundness of its calculation.
I have amalgamated various volume analysis into one synergistic script. I wasn't going to opensource it. But, as one of the lucky few winners of TradingClue 2. I felt obligated to give something back to the community.
Relative volume traditionally compares current volume to prior bar volume or SMA of volume. This has drawbacks. The question of relative volume is "Volume relative to what?" In the traditional scripts you'll find it displays current volume relative to the last number of bars. But, is that the best way to compare volume. On a daily chart, possibly. On a daily chart this can work because your units of time are uniform. Each day represents a full cycle of volume. However, on an intraday chart? Not so much.
Example: If you have a lookback of 9 on an hourly chart in a 24 hour market, you are then comparing the average volume from Midnight - 9 AM to the 9 AM volume. What do you think you'll find? Well at 9:30 when NY exchanges open the volume should be consistently and predictably higher. But though rVol is high relative to the lookback period, its actually just average or maybe even below average compared to prior NY session opens. But prior NY session opens are not included in the lookback and thus ignored.
This problem is the most visibly noticed when looking at the volume on a CME futures chart or some equivalent. In a 24 hour market, such as crypto, there are website's like skew can show you the volume disparity from time of day. This led me to believe that the traditional rVol calculation was insufficient. A better way to calculate it would be to compare the 9:30 am 30m bar today to the last week's worth of 9:30 am 30m bars. Then I could know whether today's volume at 9:30 am today is high or low based on prior 9:30 am bars. This seems to be a superior method on an intraday basis and is clearly superior in markets with irregular volume
This led me to other problems, such as markets that are open for less than 24 hours and holiday hours on traditional market exchanges. How can I know that the script is accurately looking at the correct prior relevant bars. I've created and/or adapted solutions to all those problems and these calculations and code snippets thus have value that extend beyond this rVol script for other pinecoders.
The Script
This rVol script looks back at the bars of the same time period on the viewing timeframe. So, as we said, the last 9:30 bars. Averages those, then divides the: . The result is a percentage expressed as x.xxx. Thus 1.0 mean current volume is equal to average volume. Below 1.0 is below the average and above 1.0 is above the average.
This information can be viewed on its own. But there are more levels of analysis added to it.
Above the bars are signals that correlate to the "Better Volume Indicator" developed by, I believe, the folks at emini-watch and originally adapted to pinescript by LazyBear. The interpretation of these symbols are in a table on the right of the indicator.
The volume bars can also be colored. The color is defined by the relationship between the average of the rVol outputs and the current volume. The "Average rVol" so to speak. The color coding is also defined by a legend in the table on the right.
These can be researched by you to determine how to best interpret these signals. I originally got these ideas and solid details on how to use the analysis from a fellow out there, PlanTheTrade.
I hope you find some value in the code and in the information that the indicator presents. And I'd like to thank the TradingView team for producing the most innovative and user friendly charting package on the market.
(p.s. Better Volume is provides better information with a longer lookback value than the default imo)
Credit for certain code sections and ideas is due to:
LazyBear - Better Volume
Grimmolf (From GitHub) - Logic for Loop rVol
R4Rocket - The idea for my rVol 1 calculation
And I can't find the guy who had the idea for the multiples of volume to the average. Tag him if you know him
Final Note: I'd like to leave a couple of clues of my own for fellow seekers of trading infamy.
Indicators: indicators are like anemometers (The things that measure windspeed). People talk bad about them all the time because they're "lagging." Well, you can't tell what the windspeed is unless the wind is blowing. anemometers are lagging indicators of wind. But forecasters still rely on them. You would use an indicator, which I would define as a instrument of measure, to tell you the windspeed of the markets. Conversely, when people talk positively about indicators they say "This one is great and this one is terrible." This is like a farmer saying "Shovels are great, but rakes are horrible." There are certain tools that have certain functions and every good tool has a purpose for a specific job. So the next time someone shares their opinion with you about indicators. Just smile and nod, realizing one day they'll learn... hopefully before they go broke.
How to forecast: Prediction is accomplished by analyzing the behavior of instruments of measure to aggregate data (using your anemometer). The data is then assembled into a predictive model based on the measurements observed (a trading system). That predictive model is tested against reality for it's veracity (backtesting). If the model is predictive, you can optimize your decision making by creating parameter sets around the prediction that are synergistic with the implications of the prediction (risk, stop loss, target, scaling, pyramiding etc).
<3
PSAR + EMA/TEMA/RSI/OBVThe Parabolic Stop-and-Reservse (PSAR) is a trend indicator, intended to capture reversal signals and show entry and exit points. The PSAR is bullish when the PSAR is below the candle body (usually indicated by a dot) and bearish when the PSAR is above the candle body. The PSAR generally only moves in the direction of the trend, making it useful for markets with an upward or downward trend, as well as swing markets. It is weaker when the market it sideways, as it can be prone to frequent flips (bull-to-bear or vice versa) in markets where a predominant trend is not present.
In order to combat the tendency for rapid swings in the PSAR, it is commonly paired with a second indicator. Often, this is a moving average (MA) to confirm the PSAR signal. Here is a common example:
PSAR + 2 EMAs: A trade would consider entering long when the PSAR is bullish and the fast EMA is above the short EMA.
PSAR + 3 EMAs: As above, but the trader could also add a very long EMA (200, for example) and use that as an additional filter.
In addition to using EMA, other MAs can be used and may be more appropriate to certain instruments and timeframes. Using TEMA, for example, may result in less lag but introduce more noise. Likewise, the Ehler's MAMA is an option.
Some traders use other indicators as PSAR confirmation signals, such as the relative strength index (RSI) on on-balance volume (OBV). The strategy is similar:
bullish PSAR + RSI oversold = consider long entry
bullish PSAR + OBV oscillator > 0 = consider long entry
The strategy presented here is based on my PSAR + EMA + TEMA study. Any of the above strategies are supported by this script:
1. The PSAR is the primary signal.
2. Confirmation is provided by any of the following: EMA , TEMA , Ehler's MAMA , RSI , or OBV.
3. You may use a third EMA (set to 200 as the default) to filter entries -- if used, the strategy will only show signals if the price is above the third (additional) EMA .
For example, a normal long signal would be a bullish PSAR + fast EMA > slow EMA + price > ema 200.
In addition, you may use a SL, which is set to the PSAR dots shown. You may also limit the backtesting dates. (Please note in the chart above, I do not have a limit on the trading dates. I believe this exaggerates the success of the strategy, but the house rules demand I not limit the timeframe to show you a more accurate picture.)
Combo Backtest 123 Reversal & T3 Averages This is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
This indicator plots the moving average described in the January, 1998 issue
of S&C, p.57, "Smoothing Techniques for More Accurate Signals", by Tim Tillson.
This indicator plots T3 moving average presented in Figure 4 in the article.
T3 indicator is a moving average which is calculated according to formula:
T3(n) = GD(GD(GD(n))),
where GD - generalized DEMA (Double EMA) and calculating according to this:
GD(n,v) = EMA(n) * (1+v)-EMA(EMA(n)) * v,
where "v" is volume factor, which determines how hot the moving average’s response
to linear trends will be. The author advises to use v=0.7.
When v = 0, GD = EMA, and when v = 1, GD = DEMA. In between, GD is a less aggressive
version of DEMA. By using a value for v less than1, trader cure the multiple DEMA
overshoot problem but at the cost of accepting some additional phase delay.
In filter theory terminology, T3 is a six-pole nonlinear Kalman filter. Kalman
filters are ones that use the error — in this case, (time series - EMA(n)) —
to correct themselves. In the realm of technical analysis, these are called adaptive
moving averages; they track the time series more aggres-sively when it is making large
moves. Tim Tillson is a software project manager at Hewlett-Packard, with degrees in
mathematics and computer science. He has privately traded options and equities for 15 years.
WARNING:
- For purpose educate only
- This script to change bars colors.
