Gann Circle Swing LevelsThis indicator is based on W. D. Gann's Square of 9 Chart and can be interpreted as the Gann Circle / Gann Wheel / 360 Degree Circle Chart or Square of the Circle Chart.
Spiral arrangement of numbers on the Square of 9 chart creates a very unique square root relationship amongst the numbers on the chart. If you take any number on the Square of 9 chart, take the square root of the number, then add 2 to the root and re-square it, resulting in one full 360 degree cycle (i.e. a 360 degree Circle) out from the center of the chart.
For example,
the square root of 121 = 11,
11 + 2 = 13,
and the square of 13 = 169
The number 169 is one full 360 degree cycle out (with reference to 121) from the center of the Square of 9 chart.
Similarly, if you take any number on the Square of 9 chart, take the square root of the number, then subtract 2 from the root and re-square it, resulting in one full 360 degree inward rotation towards the center of the chart.
For example,
the square root of 565 = 23.77,
23.77 - 2 = 21.77,
and the square of 21.77 = 473.93 (approximately equal to 474, which is directly below 565 on the Square of 9 chart)
The number 474 is one full 360 degree inward rotation (with reference to 565) towards the center of the chart.
How to Use this Indicator ?
This indicator is useful for finding coordinate squares on the Gann Circle that are making hard aspects to a previous position (such as a significant top or bottom) on the circle.
Input :
Swing Point (Significant price point, such as a top or a bottom)
Low / High ? (Is it a bottom or a top)
Number of Gann Levels (Number of Gann Cycles to be projected)
Output :
Gann Support or Resistance Levels (color coded as follows) :
Swing High or Swing Low (BLUE)
Support levels calculated with reference to the Swing High (RED)
Resistance levels calculated with reference to the Swing Low (LIME)
In den Scripts nach "one一季度财报" suchen
Peak Reversal v2This is a brand new version of my Peak Reversal indicator. As with the older version, the idea behind this indicator is simple: identify potential price reversal areas, and identifying markets which are trending. In this new version I focused on improving on the old concept, but introduced a bunch of features heavily inspired by Adam Grimes' ideas from The Art and Science of Trading. (I also blatantly stole the way he colors candles outside of the bands. Sorry.)
As you can see below this indicator gives traders a plethora of tools to judge whether a market is trending, and might be mean reverting soon.
Follow me, join my group, like the script. You know the drill.
Basic functions:
You have a triplet of Keltner (ATR-based) bands in Peak Reversal. They are defined by a multiplier and an EMA, which is referred to as "the mean". There's a tight, normal, and an extreme band. The multiplier defines how far apart your bands are. By default the indicator uses 1.125, 2.25, and 3.375. The tight band is off by default, but you can turn it on in the options. The mean is also off by default. This is more a personal preference thing for me, because I happen to use a different indicator to show a couple of moving averages.
Band crosses:
Peak Reversal can indicate whenever price crosses one of the bands. This can help traders identify points where a mean reversal play could be an option. Triangles indicate these crosses. New in version 2 is the ability to choose which of the bands to use to show these crosses. If you are more of an aggressive trader, you might find it better to show tight band crosses. If you are looking for more extreme market conditions, then choose extreme. The default is "normal".
Free bars:
Indicating free bars is also a concept from the book. A "free bar" is one which stands "freely" above the bands, which means its low price is completely outside of the bands. It can be argued that a freely standing bar is an even more extreme mean deviation, than just a band cross. Traders can gain an additional advantage studying the markets this way. Free bars are not shown by default, when on, a star shape on the candles indicates free bars. Both band crosses and free bars can be shown at the same time, but there might be overlap.
Deviations:
Also based on a concept from The Art and Science of Trading, is an indication of price "deviations". You will notice that when a candle "touches" a band (high and close above band), its colored. The idea here is to show traders when a market is in motion, but also when a mean reversal might be coming next. To accomplish this, the more colors deviate, the darker the color is. The idea here is also simple, the more price deviates off the mean, the likelier it is to return to it. This uses three different shades to show these deviations. 1-2 is one shade, 3-4 another, and upwards of 5 there's only the darkest shade. I didn't make extensive studies, which color for how many candles would be appropriate to use, but I do believe it doesn't matter that much in usage. It's clear what traders gain from using this information: more deviation, the likelier a snapback becomes.
Advanced mode:
Last but not least, I decided to add an advanced mode for advanced traders. This does nothing more than flip all colors and shapes upside down. Everything that is red, becomes green. The idea is where some traders say "buy low, sell high" (standard mode), other traders might say "buy high, sell higher" (advanced mode). See for yourself, which one you like better.
3SMA + Ichimoku 2leadlineThis indicator simultaneously displays two lines, which are the leading spans of the Ichimoku Kinko Hyo, and three simple moving averages.
To make it easier to distinguish between the simple moving average line and the line of the Ichimoku Kinko Hyo, the simple moving average line is set to level 2 thickness by default.
Also, the color of Reading Span 1 in the Ichimoku Kinko Hyo has been changed from green to lime to improve color visibility.
I (author of this indicator) use this indicator especially as a simple perspective on the cryptocurrency BTC / USD(USDT).
If this indicator is a problem, moderators don't know about tradingview beginners.
" Visibility " should be a high-priority item not only for indicators but also for graph requirements.
Visibility is one of the most important factors for investors who have to make instant decisions in one minute and one second.
The purpose of this indicator is to display two leading spans that are easily noticed in the Ichimoku cloud and three simple moving averages whose set values can be changed.
This is because chart analysis often uses a combination of a simple moving average of three periods and two lead spans of the Ichimoku cloud.
Also, in chart analysis, green is often displayed with the same thickness on both the moving average line and the Ichimoku cloud.
Therefore, if the moving average line and the Ichimoku cloud often use the same green color, the visibility will drop. Therefore, the green color of Ichimoku cloud was changed to lime color by default.
Tradingview beginners often refer only to the two lines of the leading span of Ichimoku Cloud. Therefore, we decided not to draw lines that are difficult to use.
Many Tradingview beginners don't know that you can change the thickness of the indicator .
Therefore, this indicator shows by DEFAULT the three commonly used simple moving averages that are thickened by one step at the same time.
Also, since the same green color is often used for the Ichimoku cloud and the moving average line, the green color of the preceding span of the Ichimoku cloud is changed to lime color by default.
The originality of this indicator is that it enhances " visibility " so that novice tradingview users will not be confused on the chart screen.
The lines other than the preceding span of the Ichimoku cloud are not displayed, and the moving average line is level 2 thick so that the user can easily see it.
This indicator not only combines a simple moving average and Ichimoku cloud, but also improves "visibility" by not incorporating lines that are difficult to see from the beginning and making it only the minimum display, making it easy for beginners to understand. The purpose is to do.
If any of the other TradingView indicators already meet the following, acknowledge that this indicator is not original.
・Display 3 simple moving averages at the same time
・For visibility, the thickness of the simple moving average line is set to level 2 from the beginning.
・A setting that does not dare to draw lines other than the lead span of Ichimoku cloud.
・Make the moving average line and the Ichimoku cloud line different colors and thicknesses from the beginning.
Flawless Victory Strategy - 15min BTC Machine Learning StrategyHello everyone, I am a heavy Python programmer bringing machine learning to TradingView. This 15 minute Bitcoin Long strategy was created using a machine learning library and 1 year of historical data in Python. Every parameter is hyper optimized to bring you the most profitable buy and sell signals for Bitcoin on the 15min chart. The historical Bitcoin data was gathered from Binance API, in case you want to know the best exchange to use this long strategy. It is a simple Bollinger Band and RSI strategy with two versions included in the tradingview settings. The first version has a Sharpe Ratio of 7.5 which is amazing, and the second version includes the best stop loss and take profit positions with a Sharpe Ratio of 2.5 . Let me talk a little bit more about how the strategy works. The buy signal is triggered when close price is less than lower Bollinger Band at Std Dev 1, and the RSI is greater than a certain value. The sell signal is triggered when close price is greater than upper Bollinger Band at Std Dev 1, and the RSI is greater than a certain value. What makes this strategy interesting is the parameters the Machine Learning library found when backtesting for the best Sharpe Ratio. I left my computer on for about 28 hours to fully backtest 5000 EPOCHS and get the results. I was able to create a great strategy that might be one of TradingView's best strategies out on the website today. I will continue to apply machine learning to all my strategies from here on forward. Please Let me know if you have any questions or certain strategies you would like me to hyper optimize for you. I'm always willing to create profitable strategies!
P.S. You can always pyramid this strategy for more gains! I just don't add pyramiding when creating my strategies because I want to show you the true win/loss ratio based buying one time and one selling one time. I feel like when creating a strategy that includes pyramiding right off the bat falsifies the win rate. This is my way of being transparent with you all. Have fun trading!
Monte Carlo Range Forecast [DW]This is an experimental study designed to forecast the range of price movement from a specified starting point using a Monte Carlo simulation.
Monte Carlo experiments are a broad class of computational algorithms that utilize random sampling to derive real world numerical results.
These types of algorithms have a number of applications in numerous fields of study including physics, engineering, behavioral sciences, climate forecasting, computer graphics, gaming AI, mathematics, and finance.
Although the applications vary, there is a typical process behind the majority of Monte Carlo methods:
-> First, a distribution of possible inputs is defined.
-> Next, values are generated randomly from the distribution.
-> The values are then fed through some form of deterministic algorithm.
-> And lastly, the results are aggregated over some number of iterations.
In this study, the Monte Carlo process used generates a distribution of aggregate pseudorandom linear price returns summed over a user defined period, then plots standard deviations of the outcomes from the mean outcome generate forecast regions.
The pseudorandom process used in this script relies on a modified Wichmann-Hill pseudorandom number generator (PRNG) algorithm.
Wichmann-Hill is a hybrid generator that uses three linear congruential generators (LCGs) with different prime moduli.
Each LCG within the generator produces an independent, uniformly distributed number between 0 and 1.
The three generated values are then summed and modulo 1 is taken to deliver the final uniformly distributed output.
Because of its long cycle length, Wichmann-Hill is a fantastic generator to use on TV since it's extremely unlikely that you'll ever see a cycle repeat.
The resulting pseudorandom output from this generator has a minimum repetition cycle length of 6,953,607,871,644.
Fun fact: Wichmann-Hill is a widely used PRNG in various software applications. For example, Excel 2003 and later uses this algorithm in its RAND function, and it was the default generator in Python up to v2.2.
The generation algorithm in this script takes the Wichmann-Hill algorithm, and uses a multi-stage transformation process to generate the results.
First, a parent seed is selected. This can either be a fixed value, or a dynamic value.
The dynamic parent value is produced by taking advantage of Pine's timenow variable behavior. It produces a variable parent seed by using a frozen ratio of timenow/time.
Because timenow always reflects the current real time when frozen and the time variable reflects the chart's beginning time when frozen, the ratio of these values produces a new number every time the cache updates.
After a parent seed is selected, its value is then fed through a uniformly distributed seed array generator, which generates multiple arrays of pseudorandom "children" seeds.
The seeds produced in this step are then fed through the main generators to produce arrays of pseudorandom simulated outcomes, and a pseudorandom series to compare with the real series.
The main generators within this script are designed to (at least somewhat) model the stochastic nature of financial time series data.
The first step in this process is to transform the uniform outputs of the Wichmann-Hill into outputs that are normally distributed.
In this script, the transformation is done using an estimate of the normal distribution quantile function.
Quantile functions, otherwise known as percent-point or inverse cumulative distribution functions, specify the value of a random variable such that the probability of the variable being within the value's boundary equals the input probability.
The quantile equation for a normal probability distribution is μ + σ(√2)erf^-1(2(p - 0.5)) where μ is the mean of the distribution, σ is the standard deviation, erf^-1 is the inverse Gauss error function, and p is the probability.
Because erf^-1() does not have a simple, closed form interpretation, it must be approximated.
To keep things lightweight in this approximation, I used a truncated Maclaurin Series expansion for this function with precomputed coefficients and rolled out operations to avoid nested looping.
This method provides a decent approximation of the error function without completely breaking floating point limits or sucking up runtime memory.
Note that there are plenty of more robust techniques to approximate this function, but their memory needs very. I chose this method specifically because of runtime favorability.
To generate a pseudorandom approximately normally distributed variable, the uniformly distributed variable from the Wichmann-Hill algorithm is used as the input probability for the quantile estimator.
Now from here, we get a pretty decent output that could be used itself in the simulation process. Many Monte Carlo simulations and random price generators utilize a normal variable.
However, if you compare the outputs of this normal variable with the actual returns of the real time series, you'll find that the variability in shocks (random changes) doesn't quite behave like it does in real data.
This is because most real financial time series data is more complex. Its distribution may be approximately normal at times, but the variability of its distribution changes over time due to various underlying factors.
In light of this, I believe that returns behave more like a convoluted product distribution rather than just a raw normal.
So the next step to get our procedurally generated returns to more closely emulate the behavior of real returns is to introduce more complexity into our model.
Through experimentation, I've found that a return series more closely emulating real returns can be generated in a three step process:
-> First, generate multiple independent, normally distributed variables simultaneously.
-> Next, apply pseudorandom weighting to each variable ranging from -1 to 1, or some limits within those bounds. This modulates each series to provide more variability in the shocks by producing product distributions.
-> Lastly, add the results together to generate the final pseudorandom output with a convoluted distribution. This adds variable amounts of constructive and destructive interference to produce a more "natural" looking output.
In this script, I use three independent normally distributed variables multiplied by uniform product distributed variables.
The first variable is generated by multiplying a normal variable by one uniformly distributed variable. This produces a bit more tailedness (kurtosis) than a normal distribution, but nothing too extreme.
The second variable is generated by multiplying a normal variable by two uniformly distributed variables. This produces moderately greater tails in the distribution.
The third variable is generated by multiplying a normal variable by three uniformly distributed variables. This produces a distribution with heavier tails.
For additional control of the output distributions, the uniform product distributions are given optional limits.
These limits control the boundaries for the absolute value of the uniform product variables, which affects the tails. In other words, they limit the weighting applied to the normally distributed variables in this transformation.
All three sets are then multiplied by user defined amplitude factors to adjust presence, then added together to produce our final pseudorandom return series with a convoluted product distribution.
Once we have the final, more "natural" looking pseudorandom series, the values are recursively summed over the forecast period to generate a simulated result.
This process of generation, weighting, addition, and summation is repeated over the user defined number of simulations with different seeds generated from the parent to produce our array of initial simulated outcomes.
After the initial simulation array is generated, the max, min, mean and standard deviation of this array are calculated, and the values are stored in holding arrays on each iteration to be called upon later.
Reference difference series and price values are also stored in holding arrays to be used in our comparison plots.
In this script, I use a linear model with simple returns rather than compounding log returns to generate the output.
The reason for this is that in generating outputs this way, we're able to run our simulations recursively from the beginning of the chart, then apply scaling and anchoring post-process.
This allows a greater conservation of runtime memory than the alternative, making it more suitable for doing longer forecasts with heavier amounts of simulations in TV's runtime environment.
From our starting time, the previous bar's price, volatility, and optional drift (expected return) are factored into our holding arrays to generate the final forecast parameters.
After these parameters are computed, the range forecast is produced.
The basis value for the ranges is the mean outcome of the simulations that were run.
Then, quarter standard deviations of the simulated outcomes are added to and subtracted from the basis up to 3σ to generate the forecast ranges.
All of these values are plotted and colorized based on their theoretical probability density. The most likely areas are the warmest colors, and least likely areas are the coolest colors.
An information panel is also displayed at the starting time which shows the starting time and price, forecast type, parent seed value, simulations run, forecast bars, total drift, mean, standard deviation, max outcome, min outcome, and bars remaining.
The interesting thing about simulated outcomes is that although the probability distribution of each simulation is not normal, the distribution of different outcomes converges to a normal one with enough steps.
In light of this, the probability density of outcomes is highest near the initial value + total drift, and decreases the further away from this point you go.
This makes logical sense since the central path is the easiest one to travel.
Given the ever changing state of markets, I find this tool to be best suited for shorter term forecasts.
However, if the movements of price are expected to remain relatively stable, longer term forecasts may be equally as valid.
There are many possible ways for users to apply this tool to their analysis setups. For example, the forecast ranges may be used as a guide to help users set risk targets.
Or, the generated levels could be used in conjunction with other indicators for meaningful confluence signals.
More advanced users could even extrapolate the functions used within this script for various purposes, such as generating pseudorandom data to test systems on, perform integration and approximations, etc.
These are just a few examples of potential uses of this script. How you choose to use it to benefit your trading, analysis, and coding is entirely up to you.
If nothing else, I think this is a pretty neat script simply for the novelty of it.
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How To Use:
When you first add the script to your chart, you will be prompted to confirm the starting date and time, number of bars to forecast, number of simulations to run, and whether to include drift assumption.
You will also be prompted to confirm the forecast type. There are two types to choose from:
-> End Result - This uses the values from the end of the simulation throughout the forecast interval.
-> Developing - This uses the values that develop from bar to bar, providing a real-time outlook.
You can always update these settings after confirmation as well.
Once these inputs are confirmed, the script will boot up and automatically generate the forecast in a separate pane.
Note that if there is no bar of data at the time you wish to start the forecast, the script will automatically detect use the next available bar after the specified start time.
From here, you can now control the rest of the settings.
The "Seeding Settings" section controls the initial seed value used to generate the children that produce the simulations.
In this section, you can control whether the seed is a fixed value, or a dynamic one.
Since selecting the dynamic parent option will change the seed value every time you change the settings or refresh your chart, there is a "Regenerate" input built into the script.
This input is a dummy input that isn't connected to any of the calculations. The purpose of this input is to force an update of the dynamic parent without affecting the generator or forecast settings.
Note that because we're running a limited number of simulations, different parent seeds will typically yield slightly different forecast ranges.
When using a small number of simulations, you will likely see a higher amount of variance between differently seeded results because smaller numbers of sampled simulations yield a heavier bias.
The more simulations you run, the smaller this variance will become since the outcomes become more convergent toward the same distribution, so the differences between differently seeded forecasts will become more marginal.
When using a dynamic parent, pay attention to the dispersion of ranges.
When you find a set of ranges that is dispersed how you like with your configuration, set your fixed parent value to the parent seed that shows in the info panel.
This will allow you to replicate that dispersion behavior again in the future.
An important thing to note when settings alerts on the plotted levels, or using them as components for signals in other scripts, is to decide on a fixed value for your parent seed to avoid minor repainting due to seed changes.
When the parent seed is fixed, no repainting occurs.
The "Amplitude Settings" section controls the amplitude coefficients for the three differently tailed generators.
These amplitude factors will change the difference series output for each simulation by controlling how aggressively each series moves.
When "Adjust Amplitude Coefficients" is disabled, all three coefficients are set to 1.
Note that if you expect volatility to significantly diverge from its historical values over the forecast interval, try experimenting with these factors to match your anticipation.
The "Weighting Settings" section controls the weighting boundaries for the three generators.
These weighting limits affect how tailed the distributions in each generator are, which in turn affects the final series outputs.
The maximum absolute value range for the weights is . When "Limit Generator Weights" is disabled, this is the range that is automatically used.
The last set of inputs is the "Display Settings", where you can control the visual outputs.
From here, you can select to display either "Forecast" or "Difference Comparison" via the "Output Display Type" dropdown tab.
"Forecast" is the type displayed by default. This plots the end result or developing forecast ranges.
There is an option with this display type to show the developing extremes of the simulations. This option is enabled by default.
There's also an option with this display type to show one of the simulated price series from the set alongside actual prices.
This allows you to visually compare simulated prices alongside the real prices.
"Difference Comparison" allows you to visually compare a synthetic difference series from the set alongside the actual difference series.
This display method is primarily useful for visually tuning the amplitude and weighting settings of the generators.
There are also info panel settings on the bottom, which allow you to control size, colors, and date format for the panel.
It's all pretty simple to use once you get the hang of it. So play around with the settings and see what kinds of forecasts you can generate!
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ADDITIONAL NOTES & DISCLAIMERS
Although I've done a number of things within this script to keep runtime demands as low as possible, the fact remains that this script is fairly computationally heavy.
Because of this, you may get random timeouts when using this script.
This could be due to either random drops in available runtime on the server, using too many simulations, or running the simulations over too many bars.
If it's just a random drop in runtime on the server, hide and unhide the script, re-add it to the chart, or simply refresh the page.
If the timeout persists after trying this, then you'll need to adjust your settings to a less demanding configuration.
Please note that no specific claims are being made in regards to this script's predictive accuracy.
It must be understood that this model is based on randomized price generation with assumed constant drift and dispersion from historical data before the starting point.
Models like these not consider the real world factors that may influence price movement (economic changes, seasonality, macro-trends, instrument hype, etc.), nor the changes in sample distribution that may occur.
In light of this, it's perfectly possible for price data to exceed even the most extreme simulated outcomes.
The future is uncertain, and becomes increasingly uncertain with each passing point in time.
Predictive models of any type can vary significantly in performance at any point in time, and nobody can guarantee any specific type of future performance.
When using forecasts in making decisions, DO NOT treat them as any form of guarantee that values will fall within the predicted range.
When basing your trading decisions on any trading methodology or utility, predictive or not, you do so at your own risk.
No guarantee is being issued regarding the accuracy of this forecast model.
Forecasting is very far from an exact science, and the results from any forecast are designed to be interpreted as potential outcomes rather than anything concrete.
With that being said, when applied prudently and treated as "general case scenarios", forecast models like these may very well be potentially beneficial tools to have in the arsenal.
Sharktank - Pi Cycle PredictionThe Pi Cycle indicator has called tops in Bitcoin quite accurately. Assuming history repeats itself, knowledge about when it might happen again could benefit you.
The indicator is fairly simple:
- A daily moving average of 350 ("long_ma" in script)
- A daily moving average of 111 ("short_ma" in script)
The value of the long moving average is multiplied by two. This way the longer moving average appears above the shorter one.
When the shorter one (orange colored) crosses above the longer (green colored) one, it could mean the top is in.
These moving averages rise at a certain rate. Using these rates we could try to estimate a possible crossover moment. That's exactly what this indicator does! It gives the user a prediction of when a crossover might happen.
Special thanks to:
- Ninorigo, for making his indicator public. This one uses his as a starting point.
- The_Caretaker, for coming up with this idea about calling a top. Yet, his is more price-based, this one is more time-based.
Price Action - Support & Resistance by DGTSᴜᴘᴘᴏʀᴛ ᴀɴᴅ Rᴇꜱɪꜱᴛᴀɴᴄᴇ , is undoubtedly one of the key concepts of technical analysis
█ Sᴜᴘᴘᴏʀᴛ ᴀɴᴅ Rᴇꜱɪꜱᴛᴀɴᴄᴇ Dᴇꜰɪɴɪᴛɪᴏɴ
Support and Resistance terms are used by traders to refer to price levels on charts that tend to act as barriers, preventing the price of an financial instrument from getting pushed in a certain direction.
A support level is a price level where buyers are more aggressive than sellers. This means that the price is more likely to "bounce" off this level rather than break through it. However, once the price has breached this level it is likely to continue falling until meeting another support level.
A resistance level is the opposite of a support level. It is where the price tends to find resistance as it rises. Again, this means that the price is more likely to "bounce" off this level rather than break through it. However, once the price has breached this level it is likely to continue rising until meeting another resistance level.
A previous support level will sometimes become a resistance level when the price attempts to move back up, and conversely, a resistance level will become a support level as the price temporarily falls back.
█ Iᴅᴇɴᴛɪꜰʏɪɴɢ Sᴜᴘᴘᴏʀᴛ ᴀɴᴅ Rᴇꜱɪꜱᴛᴀɴᴄᴇ
Support and resistance can come in various forms, and the concept is more difficult to master than it first appears. Identification of key support and resistance levels is an essential ingredient to successful technical analysis.
If the price stalls and reverses in the same price area on minimum of two different occasions, then a horizontal line is drawn to show that the market is struggling to move past that area. Those areas are static barriers, one of the most popular forms of support/resistance and are highlighted with horizontal lines.
Repeated test , the more often a support/resistance level is "tested" over an extended period of time (touched and bounced off by price), the more significance is given to that specific level
High volume , the more buying and selling that has occurred at a particular price level, the stronger the support or resistance level is likely to be
Market psychology , plays a major role as traders and investors remember the past and react to changing conditions to anticipate future market movement.
Psychological levels , is a price level that significantly affects the price of an underlying financial instrument. Typically, near round numbers often serve as support and resistance
The following support and resistance related topics are beyond the scope of this study, so they will be mentioned roughly only as a reference for support and resistance concept
Trendlines , Support and resistance levels in trends are dynamic. Throughout an uptrend, levels of support tend to look like a trendline, usually clustering around higher lows. As the price rises, the price where buyers consider the stock to be “too cheap” also changes, which creates new support levels on the way up. The same is also true for resistance levels. In an uptrend, a stock is continuously breaking through perceived resistance levels and making new highs
Moving Averages , is a constantly changing line that smooths out past price data while also allowing the trader to identify support and resistance. In the example Notice how the price of the asset finds support at the moving average when the trend is up, and how it acts as resistance when the trend is down
The Fibonacci Retracement/Extension tool , is a favorite among many short-term traders because it clearly identifies levels of potential support and resistance
Pivot Point Calculations , is another common technical analysis technique, where pivot point is calculated based on the high, low, and closing prices of previous trading session/day and support & resistance levels are projected based on the pivot point, different calculation techniques are available, as presented in this example of an pivot point indicator : PVTvX by DGT
█ Tʀᴀᴅɪɴɢ Bᴀꜱᴇᴅ ᴏɴ Sᴜᴘᴘᴏʀᴛ ᴀɴᴅ Rᴇꜱɪꜱᴛᴀɴᴄᴇ
Once an area or "zone" of support or resistance has been identified, those price levels can serve as potential entry or exit points because, as a price reaches a point of support or resistance, it will do one of two things—bounce back away from the support or resistance level (trading ranges), or violate the price level and continue in its direction (trading breakouts) —until it hits the next support or resistance level
The basic trading method for using support and resistance is to buy near support in uptrends or the parts of ranges or chart patterns where prices are moving up and to sell/sell short near resistance in downtrends or the parts of ranges and chart patterns where prices are moving down. Buying near support or selling near resistance can pay off, but there is no assurance that the support or resistance will hold. Therefore, consider waiting for some confirmation that the market is still respecting that area
Trading breakouts, a breakout is a potential trading opportunity that occurs when an asset's price moves above a resistance level or moves below a support level on increasing volume. The first step in trading breakouts is to identify current price trend patterns along with support and resistance levels in order to plan possible entry and exit points. Once the asset trades beyond the price barrier, volatility tends to increase and prices usually trend in the breakout's direction. Breakouts are such an important trading strategy since these setups are the starting point for future volatility increases, large price swings and, in many circumstances, major price trends. When trading breakouts, it is important to consider the underlying asset's support and resistance levels. The more times an asset price has touched these areas, the more valid these levels are and the more important they become. At the same time, the longer these support and resistance levels have been in play, the better the outcome when the asset price finally breaks out. Asset prices will often move slightly further than we expect them to. This doesn't happen all the time, but when it does it is called a false breakout. Therefore it is important to consider waiting for some confirmation while trading breakouts. It’s also popular for traders to sell 50% of their positions at the resistance level, and hold the rest in anticipation of a breakout above resistance
█ Pʀɪᴄᴇ Aᴄᴛɪᴏɴ - Sᴜᴘᴘᴏʀᴛ & Rᴇꜱɪꜱᴛᴀɴᴄᴇ ʙʏ DGT Sᴛᴜᴅʏ
This experimental study attempts to identify the support and resistance levels. Assumes a simple logic to discover moments where the price is rising or falling consecutively for minimum 3 bars with the condition volume increases on each bar and the last bar’s volume should be bigger than the long term volume moving average. A line will be drawn at the end of the move (highest or lowest, depending on the move direction), the line will be drawn at minimum on the 3rd bar and if condition holds for other consecutive bars the line will switch to 4th, 5th etc bar.
Lines will not be deleted so the historical ones will remain and will emphasis the levels significance when they overlap in feature. Strong levels are more likely to hold and cause the price to move in the other direction, whereas the minor levels may only cause the price to pause and keep moving in the same direction. Determining future levels of support and resistance can drastically improve the returns of a short-term investing strategy
Bar colors will be painted based on the volume of the specific bar to its long term volume moving average. This will help identifying the support and resistance levels significance and emphasis the sings of breakouts
Finally, Volume spikes will be marked on top of the price chart. A high volume usually indicates more interest in the security and the presence of institutional traders. However, a rapidly rising price in an uptrend accompanied by a huge volume may be a sign of exhaustion. Traders usually look for breaks of support and resistance to enter positions. When security break critical levels without volume , you should consider the breakout suspect and prime for a reversal off the highs/lows. Volume spikes are often the result of news-driven events. Volume spike will often lead to sharp reversals since the moves are unsustainable due to the imbalance of supply and demand
A good example with many support and resistance concepts observed on a stock chart and detected by the study
Settings:
Length of volume moving average, where volume moving average is used to detect support and resistance levels, is used as reference to compare with threshold values for volume spikes and colors of the bars
Hint, to get more historical lines scrolling chart to left will enable visualization of them. Please note they may appear to much all 500 line limit is used 😉
Special thanks to @HEMANT Telegram user, for his observations and suggestions
Disclaimer:
Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely
The script is for informational and educational purposes only. Use of the script does not constitute professional and/or financial advice. You alone have the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script
Volume-based S/R Levels
█ OVERVIEW
After my last indicator "Order Block Finder" was unexpectedly popular with the TradingView community, I decided to publish another experimental indicator which again tries to identify "areas of interest"
Idea:
Often candles with long wicks represent strong buying & selling pressure, especially when they are combined with extraordinary volume. Especially interesting to me are the lower wicks on red candles and the upper wicks of green candles. These wicks can potentially indicate "areas of interest" by the bigger players in the market and price may interact with these levels again in the future.
This indicator tries to identify these "high volume / long wick" candles and paints a line of either Support or Resistance from the wick into the future.
█ CALCULATION LOGIC
Extraordinary Volume is identified by first calculating thresholds based on a volume Moving Average and Standard Deviations. Two Standard Deviation Values are entered to identify HIGH and EXTREME threshold levels. The current volume is classified by comparing the volume against these thresholds.
The following inputs can be made:
- Volume MA Length
- Standard Deviation Length
- Threshold for HIGH Volume (Number of StdDev)
- Threshold for EXTREME Volume (Number of StdDev)
Another entry parameter can be used to specify the Minimum Wick Length (in % of the candle body value) which identifies a "relevant" candle. If this value is set to 0, then there is no limit and all high volume candles are considered.
The identified Support/Resistance levels are shown as lines on the chart. The parameter "Length of lines (hours)" can be used to set the length of the lines (always in hours). Depending on the timeframe, this needs to be adjusted.
(I know that this can be solved more elegantly in pine, but it was just not important to me. As always everyone is free to copy the code and make improvements. Just give me a mention when you do.)
█ DISPLAY OPTIONS
Different display options are available in the settings:
- Display Support/Resistance: Select if you want to see only Support or Resistance lines - or both
- Display High/Extreme Volume: Select if you only want to see the Extreme Value Candles or the High Value Candles or both
- Display WICK / WICK Range: Select if you only want one line at the extreme value (High/Low) of the wick - or if you want to see a range (three lines - one at the top, one at the bottom and one in the middle of the wick)
- Show Signal Triangles?: This gives the option to show little triangles on all the identified candles
█ DISCLAIMER
This is an experimental indicator and I do not know if my theory works in real life. So treat this not as financial advise, but purely for entertainment and educational purposes.
As mentioned above, I publish this code open so that everyone can re-use it or hopefully even improve it.
Let me know if you have any ideas for improvement and if it is within my coding capabilities (which to be honest are quite limited), I will try to accomodate it.
Have fun.
On Chart Anticipated Moving Average Crossover IndicatorIntroducing the on chart moving average crossover indicator.
This is my On Chart Pinescript implementation of the Anticipated Simple Moving Average Crossover idea.
This indicator plots 6 user defined moving averages.
It also plots the 5 price levels required on the next close to cross a user selected moving average with the 5 other user defined moving averages
It also gives signals of anticipated moving average crosses as arrows on chart and also as tradingview alerts with a very high degree of accuracy
Much respect to the creator of the original idea Mr. Dimitris Tsokakis
Moving Averages
A moving average simplifies price data by smoothing it out by averaging closing prices and creating one flowing line which makes seeing the trend easier.
Moving averages can work well in strong trending conditions, but poorly in choppy or ranging conditions.
Adjusting the time frame can remedy this problem temporarily, although at some point, these issues are likely to occur regardless of the time frame chosen for the moving average(s).
While Exponential moving averages react quicker to price changes than simple moving averages. In some cases, this may be good, and in others, it may cause false signals.
Moving averages with a shorter look back period (20 days, for example) will also respond quicker to price changes than an average with a longer look back period (200 days).
Trading Strategies — Moving Average Crossovers
Moving average crossovers are a popular strategy for both entries and exits. MAs can also highlight areas of potential support or resistance.
The first type is a price crossover, which is when the price crosses above or below a moving average to signal a potential change in trend.
Another strategy is to apply two moving averages to a chart: one longer and one shorter.
When the shorter-term MA crosses above the longer-term MA, it's a buy signal, as it indicates that the trend is shifting up. This is known as a "golden cross."
Meanwhile, when the shorter-term MA crosses below the longer-term MA, it's a sell signal, as it indicates that the trend is shifting down. This is known as a "dead/death cross."
MA and MA Cross Strategy Disadvantages
Moving averages are calculated based on historical data, and while this may appear predictive nothing about the calculation is predictive in nature.
Moving averages are always based on historical data and simply show the average price over a certain time period.
Therefore, results using moving averages can be quite random.
At times, the market seems to respect MA support/resistance and trade signals, and at other times, it shows these indicators no respect.
One major problem is that, if the price action becomes choppy, the price may swing back and forth, generating multiple trend reversal or trade signals.
When this occurs, it's best to step aside or utilize another indicator to help clarify the trend.
The same thing can occur with MA crossovers when the MAs get "tangled up" for a period of time during periods of consolidation, triggering multiple losing trades.
Ensure you use a robust risk management system to avoid getting "Chopped Up" or "Whip Sawed" during these periods.
Profit MAX MTF HeatMapThis is a powerfull strategy which is made from combining 3 multi timeframes into one for profit max indicator
In this case we have daily, weekly and montly.
Our long conditions are the next ones :
if we have an uptrend on all 3 at the same time, we go long.
If we have a downtrend on all 3 of them at the same time we go short.
For exit, for long, as soon as one of the 3 converts into downtrend we exit the trade.
For exit, for short, as soon as one of the 3 converts into uptrend we exit the trade.
This tool can be used on all types of markets, and can also be changed the time frames.
MACD Hybrid BSHMACD = Moving Average Convergence and Divergence
Hybrid = Combining the two main MACD signals into one indicator
BSH = Buy Sell Hold
This indicator looks for a crossover of the MACD moving averages (12ema and 26ema) in order to generate a buy/sell signal and a crossover of the MACD line (12ema minus 26ema) and MACD signal line (9ema of MACD line) in order to generate a completely seperate buy/sell signal. The two buy/sell signals are combined into a hybrid buy/sell/hold indicator which looks for one, neither, or both signals to be "buys." If both signals are buys (fast crossed above slow), a "buy" signal is given (green bar color). If only one signal is a buy, a "hold" signal is given (yellow bar color). If neither signal is a buy, a "sell" signal is given (red bar color). Note: MACD moving averages crossing over is the same thing as the MACD line crossing the zero level in the MACD indicator.
It makes sense to have the MACD indicator loaded as a reference when using this but it isn't required. The lines plotted on the chart are the 12ema and a signal line which is the MACD signal line shown relative to the 12ema rather than the MACD line. The 26ema is not plotted on the chart because the chart becomes cluttered, plus the moving averages crossing over is indicated with the MACD indicator.
This indicator should be used with other indicators such as ATR (1), RSI (14), Bollinger bands (20, 2), etc. in order to determine the best course of action when a signal is given. One way to use this as a strict system is to take a neutral cash position when a yellow "hold" signal is given, to go long when a
green "buy" signal is given, and to go short when a red "sell" signal is given. It can be observed that for many tickers and timeframes that green-yellow-green and red-yellow-red sequences are stronger signals than green-yellow-red and red-yellow-green signals.
Note: Chart type must be "bars" in order for the bar colorization to work properly
Excellent ADXThe Average Directional movement indeX (ADX) is an indicator that helps you determine the trend direction, pivot points, and much more else! But it looks not so easy as other famous indicators. It seems strange or even terrible, but don't be afraid. Let's understand how it works and get its power into your analysis tactics.
In the beginning, imagine a drunk man goes through a ladder: step by step. Up, up, down, up, down, down, up...
How can we understand which direction he goes? Exactly! We can count the number of steps in each direction. In the above example, in the upward – 4, in the downward – 3. So, it looks like he goes in an upward direction.
The ADX indicator counts the same steps, but for price. The size of each step equals 1 ATR for "DI Length" candles. On the indicator chart, we have the green and red lines. The green line represents a number of steps upward. The red line shows one downward. When the red line upper green, then the price goes below, then the trend is directed down. Later the green line comes above the red one, and then the trend changes the direction to upward. Wow? After that, you can easy detect the trend direction on the market!
But it is still not the end. On the chart, we also have the fat blue line. This is the ADX line, and it represents the power of the trend. It is calculated from a distance between the green and red curves. The ADX line value grows if the distance is increased. If the movement is really powerful, then a number of steps into a direction much more prominent than one in an opposed direction. Then the blue line grows faster. But if the growth has stopped and the blue line turns back or already had changed self-direction, then it is a signal that the trend has ended too. It's an excellent sign to close the position (but not always). Easy? Not quite. Thresholds help you there. The indicator has two additional parameters: upper and lower thresholds to evaluate the trend-over signal strength. An u-turn of the ADX line above the upper threshold sends a strong signal. If one occurs between both thresholds, it is a bit weak signal. But if the blue line goes below the lower threshold, it looks like there is no trend, and the price goes side. We can also say that the price goes side when the ADX value gradually falls down.
The Excellent ADX indicator helps you catch pivot/pullback signals based on green, red, and blue lines. Each such signal is highlighted as a green (buy) or red (sell) dot on the plot. The size of the dot represents the strength of the signal. You can also check the position of green and red lines from each other to determine the trend direction and the place where it has been changed. The Excellent ADX indicator helps you there too. It highlights the trend direction by the background-color, so you'll never miss it! The Excellent ADX good compliance with the Price Channel indicator built for the same length. You can use them together to be on a trend wave always!
[blackcat] L2 Ehlers Hilbert Channel Breakout Trading SystemLevel: 2
Background
John F. Ehlers introuced Hilbert Channel Breakout Trading System in Nov, 2000.
Function
This indicator will show how the adaptive filter is being applied to a trading strategy. After the Hilbert Channel Breakout Signal is optimized, set the inputs for this indicator to match the corresponding inputs for the signal.
In the March 2000 STOCKS & COMMODITIES, John Ehlers published a algorithm for the Hilbert cycle period, an indicator that plots the length of the current market cycle. The Hilbert transform achieved computational efficiency by using a two-dimensional numbering system. Unfortunately, this introduces amplitude error in calculating the quadrature component. Dr. Ehlers compensated for this error. He have updated the method of compensating for the amplitude error by applying a straight-line compensation term using the frequency calculation from one bar ago. This is possible because the cycle period cannot change drastically from bar to bar. The slowly varying cycle period is adequate to do a good job of amplitude compensation.
In addition, Dr. Ehlers have used a different way to compute the cycle period. He used a homodyne discriminator because it exhibits superior performance in a low signal-to-noise environment. Homodyne means he used the signal multiplied by itself one bar ago to produce a zero-frequency beat note. This beat note carries the phase angle of the one-bar change. Still using the basic definition of a cycle, the one-bar rate of change of phase is exactly the cycle period.
Here is the pine v4 code to generate the signals in the Hilbert channel breakout trading system, as discussed in Dr. Ehlers article in this issue, "Optimizing With Hilbert Indicators." The signal itself is a simple channel breakout system that generates buy and exit signals, that shows whether the system is long or flat; the high of the bar and the value of the entry channel; and the low of the bar and the value of the exit channel. This helps you see on a bar-by-bar basis exactly how the system is behaving.
Key Signal
longcond--> when high breakouts EntryChannel to long
shortcond--> when low breakouts ExitChannel to short
Pros and Cons
100% John F. Ehlers definition translation, even variable names are the same. This help readers who would like to use pine to read his book.
Remarks
The 66th script for Blackcat1402 John F. Ehlers Week publication.
I tested it and believe it work better in small time frame e.g. 15m than large time frames.
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Universal Global SessionUniversal Global Session
This Script combines the world sessions of: Stocks, Forex, Bitcoin Kill Zones, strategic points, all configurable, in a single Script, to capitalize the opening and closing times of global exchanges as investment assets, becoming an Universal Global Session .
It is based on the great work of @oscarvs ( BITCOIN KILL ZONES v2 ) and the scripts of @ChrisMoody. Thank you Oscar and Chris for your excellent judgment and great work.
At the end of this writing you can find all the internet references of the extensive documentation that I present here. To maximize your benefits in the use of this Script, I recommend that you read the entire document to create an objective and practical criterion.
All the hours of the different exchanges are presented at GMT -6. In Market24hClock you can adjust it to your preferences.
After a deep investigation I have been able to show that the different world sessions reveal underlying investment cycles, where it is possible to find sustained changes in the nominal behavior of the trend before the passage from one session to another and in the natural overlaps between the sessions. These underlying movements generally occur 15 minutes before the start, close or overlap of the session, when the session properly starts and also 15 minutes after respectively. Therefore, this script is designed to highlight these particular trending behaviors. Try it, discover your own conclusions and let me know in the notes, thank you.
Foreign Exchange Market Hours
It is the schedule by which currency market participants can buy, sell, trade and speculate on currencies all over the world. It is open 24 hours a day during working days and closes on weekends, thanks to the fact that operations are carried out through a network of information systems, instead of physical exchanges that close at a certain time. It opens Monday morning at 8 am local time in Sydney —Australia— (which is equivalent to Sunday night at 7 pm, in New York City —United States—, according to Eastern Standard Time), and It closes at 5pm local time in New York City (which is equivalent to 6am Saturday morning in Sydney).
The Forex market is decentralized and driven by local sessions, where the hours of Forex trading are based on the opening range of each active country, becoming an efficient transfer mechanism for all participants. Four territories in particular stand out: Sydney, Tokyo, London and New York, where the highest volume of operations occurs when the sessions in London and New York overlap. Furthermore, Europe is complemented by major financial centers such as Paris, Frankfurt and Zurich. Each day of forex trading begins with the opening of Australia, then Asia, followed by Europe, and finally North America. As markets in one region close, another opens - or has already opened - and continues to trade in the currency market. The seven most traded currencies in the world are: the US dollar, the euro, the Japanese yen, the British pound, the Australian dollar, the Canadian dollar, and the New Zealand dollar.
Currencies are needed around the world for international trade, this means that operations are not dominated by a single exchange market, but rather involve a global network of brokers from around the world, such as banks, commercial companies, central banks, companies investment management, hedge funds, as well as retail forex brokers and global investors. Because this market operates in multiple time zones, it can be accessed at any time except during the weekend, therefore, there is continuously at least one open market and there are some hours of overlap between the closing of the market of one region and the opening of another. The international scope of currency trading means that there are always traders around the world making and satisfying demands for a particular currency.
The market involves a global network of exchanges and brokers from around the world, although time zones overlap, the generally accepted time zone for each region is as follows:
Sydney 5pm to 2am EST (10pm to 7am UTC)
London 3am to 12 noon EST (8pm to 5pm UTC)
New York 8am to 5pm EST (1pm to 10pm UTC)
Tokyo 7pm to 4am EST (12am to 9am UTC)
Trading Session
A financial asset trading session refers to a period of time that coincides with the daytime trading hours for a given location, it is a business day in the local financial market. This may vary according to the asset class and the country, therefore operators must know the hours of trading sessions for the securities and derivatives in which they are interested in trading. If investors can understand market hours and set proper targets, they will have a much greater chance of making a profit within a workable schedule.
Kill Zones
Kill zones are highly liquid events. Many different market participants often come together and perform around these events. The activity itself can be event-driven (margin calls or option exercise-related activity), portfolio management-driven (asset allocation rebalancing orders and closing buy-in), or institutionally driven (larger players needing liquidity to complete the size) or a combination of any of the three. This intense cross-current of activity at a very specific point in time often occurs near significant technical levels and the established trends emerging from these events often persist until the next Death Zone approaches or enters.
Kill Zones are evolving with time and the course of world history. Since the end of World War II, New York has slowly invaded London's place as the world center for commercial banking. So much so that during the latter part of the 20th century, New York was considered the new center of the financial universe. With the end of the cold war, that leadership appears to have shifted towards Europe and away from the United States. Furthermore, Japan has slowly lost its former dominance in the global economic landscape, while Beijing's has increased dramatically. Only time will tell how these death zones will evolve given the ever-changing political, economic, and socioeconomic influences of each region.
Financial Markets
New York
New York (NYSE Chicago, NASDAQ)
7:30 am - 2:00 pm
It is the second largest currency platform in the world, followed largely by foreign investors as it participates in 90% of all operations, where movements on the New York Stock Exchange (NYSE) can have an immediate effect (powerful) on the dollar, for example, when companies merge and acquisitions are finalized, the dollar can instantly gain or lose value.
A. Complementary Stock Exchanges
Brazil (BOVESPA - Brazilian Stock Exchange)
07:00 am - 02:55 pm
Canada (TSX - Toronto Stock Exchange)
07:30 am - 02:00 pm
New York (NYSE - New York Stock Exchange)
08:30 am - 03:00 pm
B. North American Trading Session
07:00 am - 03:00 pm
(from the beginning of the business day on NYSE and NASDAQ, until the end of the New York session)
New York, Chicago and Toronto (Canada) open the North American session. Characterized by the most aggressive trading within the markets, currency pairs show high volatility. As the US markets open, trading is still active in Europe, however trading volume generally decreases with the end of the European session and the overlap between the US and Europe.
C. Strategic Points
US main session starts in 1 hour
07:30 am
The euro tends to drop before the US session. The NYSE, CHX and TSX (Canada) trading sessions begin 1 hour after this strategic point. The North American session begins trading Forex at 07:00 am.
This constitutes the beginning of the overlap of the United States and the European market that spans from 07:00 am to 10:35 am, often called the best time to trade EUR / USD, it is the period of greatest liquidity for the main European currencies since it is where they have their widest daily ranges.
When New York opens at 07:00 am the most intense trading begins in both the US and European markets. The overlap of European and American trading sessions has 80% of the total average trading range for all currency pairs during US business hours and 70% of the total average trading range for all currency pairs during European business hours. The intersection of the US and European sessions are the most volatile overlapping hours of all.
Influential news and data for the USD are released between 07:30 am and 09:00 am and play the biggest role in the North American Session. These are the strategically most important moments of this activity period: 07:00 am, 08:00 am and 08:30 am.
The main session of operations in the United States and Canada begins
08:30 am
Start of main trading sessions in New York, Chicago and Toronto. The European session still overlaps the North American session and this is the time for large-scale unpredictable trading. The United States leads the market. It is difficult to interpret the news due to speculation. Trends develop very quickly and it is difficult to identify them, however trends (especially for the euro), which have developed during the overlap, often turn the other way when Europe exits the market.
Second hour of the US session and last hour of the European session
09:30 am
End of the European session
10:35 am
The trend of the euro will change rapidly after the end of the European session.
Last hour of the United States session
02:00 pm
Institutional clients and very large funds are very active during the first and last working hours of almost all stock exchanges, knowing this allows to better predict price movements in the opening and closing of large markets. Within the last trading hours of the secondary market session, a pullback can often be seen in the EUR / USD that continues until the opening of the Tokyo session. Generally it happens if there was an upward price movement before 04:00 pm - 05:00 pm.
End of the trade session in the United States
03:00 pm
D. Kill Zones
11:30 am - 1:30 pm
New York Kill Zone. The United States is still the world's largest economy, so by default, the New York opening carries a lot of weight and often comes with a huge injection of liquidity. In fact, most of the world's marketable assets are priced in US dollars, making political and economic activity within this region even more important. Because it is relatively late in the world's trading day, this Death Zone often sees violent price swings within its first hour, leading to the proven adage "never trust the first hour of trading in America. North.
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London
London (LSE - London Stock Exchange)
02:00 am - 10:35 am
Britain dominates the currency markets around the world, and London is its main component. London, a central trading capital of the world, accounts for about 43% of world trade, many Forex trends often originate from London.
A. Complementary Stock Exchange
Dubai (DFM - Dubai Financial Market)
12:00 am - 03:50 am
Moscow (MOEX - Moscow Exchange)
12:30 am - 10:00 am
Germany (FWB - Frankfurt Stock Exchange)
01:00 am - 10:30 am
Afríca (JSE - Johannesburg Stock Exchange)
01:00 am - 09:00 am
Saudi Arabia (TADAWUL - Saudi Stock Exchange)
01:00 am - 06:00 am
Switzerland (SIX - Swiss Stock Exchange)
02:00 am - 10:30 am
B. European Trading Session
02:00 am - 11:00 am
(from the opening of the Frankfurt session to the close of the Order Book on the London Stock Exchange / Euronext)
It is a very liquid trading session, where trends are set that start during the first trading hours in Europe and generally continue until the beginning of the US session.
C. Middle East Trading Session
12:00 am - 06:00 am
(from the opening of the Dubai session to the end of the Riyadh session)
D. Strategic Points
European session begins
02:00 am
London, Frankfurt and Zurich Stock Exchange enter the market, overlap between Europe and Asia begins.
End of the Singapore and Asia sessions
03:00 am
The euro rises almost immediately or an hour after Singapore exits the market.
Middle East Oil Markets Completion Process
05:00 am
Operations are ending in the European-Asian market, at which time Dubai, Qatar and in another hour in Riyadh, which constitute the Middle East oil markets, are closing. Because oil trading is done in US dollars, and the region with the trading day coming to an end no longer needs the dollar, consequently, the euro tends to grow more frequently.
End of the Middle East trading session
06:00 am
E. Kill Zones
5:00 am - 7:00 am
London Kill Zone. Considered the center of the financial universe for more than 500 years, Europe still has a lot of influence in the banking world. Many older players use the European session to establish their positions. As such, the London Open often sees the most significant trend-setting activity on any trading day. In fact, it has been suggested that 80% of all weekly trends are set through the London Kill Zone on Tuesday.
F. Kill Zones (close)
2:00 pm - 4:00 pm
London Kill Zone (close).
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Tokyo
Tokyo (JPX - Tokyo Stock Exchange)
06:00 pm - 12:00 am
It is the first Asian market to open, receiving most of the Asian trade, just ahead of Hong Kong and Singapore.
A. Complementary Stock Exchange
Singapore (SGX - Singapore Exchange)
07:00 pm - 03:00 am
Hong Kong (HKEx - Hong Kong Stock Exchange)
07:30 pm - 02:00 am
Shanghai (SSE - Shanghai Stock Exchange)
07:30 pm - 01:00 am
India (NSE - India National Stock Exchange)
09:45 pm - 04:00 am
B. Asian Trading Session
06:00 pm - 03:00 am
From the opening of the Tokyo session to the end of the Singapore session
The first major Asian market to open is Tokyo which has the largest market share and is the third largest Forex trading center in the world. Singapore opens in an hour, and then the Chinese markets: Shanghai and Hong Kong open 30 minutes later. With them, the trading volume increases and begins a large-scale operation in the Asia-Pacific region, offering more liquidity for the Asian-Pacific currencies and their crosses. When European countries open their doors, more liquidity will be offered to Asian and European crossings.
C. Strategic Points
Second hour of the Tokyo session
07:00 pm
This session also opens the Singapore market. The commercial dynamics grows in anticipation of the opening of the two largest Chinese markets in 30 minutes: Shanghai and Hong Kong, within these 30 minutes or just before the China session begins, the euro usually falls until the same moment of the opening of Shanghai and Hong Kong.
Second hour of the China session
08:30 pm
Hong Kong and Shanghai start trading and the euro usually grows for more than an hour. The EUR / USD pair mixes up as Asian exporters convert part of their earnings into both US dollars and euros.
Last hour of the Tokyo session
11:00 pm
End of the Tokyo session
12:00 am
If the euro has been actively declining up to this time, China will raise the euro after the Tokyo shutdown. Hong Kong, Shanghai and Singapore remain open and take matters into their own hands causing the growth of the euro. Asia is a huge commercial and industrial region with a large number of high-quality economic products and gigantic financial turnover, making the number of transactions on the stock exchanges huge during the Asian session. That is why traders, who entered the trade at the opening of the London session, should pay attention to their terminals when Asia exits the market.
End of the Shanghai session
01:00 am
The trade ends in Shanghai. This is the last trading hour of the Hong Kong session, during which market activity peaks.
D. Kill Zones
10:00 pm - 2:00 am
Asian Kill Zone. Considered the "Institutional" Zone, this zone represents both the launch pad for new trends as well as a recharge area for the post-American session. It is the beginning of a new day (or week) for the world and as such it makes sense that this zone often sets the tone for the remainder of the global business day. It is ideal to pay attention to the opening of Tokyo, Beijing and Sydney.
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Sidney
Sydney (ASX - Australia Stock Exchange)
06:00 pm - 12:00 am
A. Complementary Stock Exchange
New Zealand (NZX - New Zealand Stock Exchange)
04:00 pm - 10:45 pm
It's where the global trading day officially begins. While it is the smallest of the megamarkets, it sees a lot of initial action when markets reopen Sunday afternoon as individual traders and financial institutions are trying to regroup after the long hiatus since Friday afternoon. On weekdays it constitutes the end of the current trading day where the change in the settlement date occurs.
B. Pacific Trading Session
04:00 pm - 12:00 am
(from the opening of the Wellington session to the end of the Sydney session)
Forex begins its business hours when Wellington (New Zealand Exchange) opens local time on Monday. Sydney (Australian Stock Exchange) opens in 2 hours. It is a session with a fairly low volatility, configuring itself as the calmest session of all. Strong movements appear when influential news is published and when the Pacific session overlaps the Asian Session.
C. Strategic Points
End of the Sydney session
12:00 am
---------------
Conclusions
The best time to trade is during overlaps in trading times between open markets. Overlaps equate to higher price ranges, creating greater opportunities.
Regarding press releases (news), it should be noted that these in the currency markets have the power to improve a normally slow trading period. When a major announcement is made regarding economic data, especially when it goes against the predicted forecast, the coin can lose or gain value in a matter of seconds. In general, the more economic growth a country produces, the more positive the economy is for international investors. Investment capital tends to flow to countries that are believed to have good growth prospects and subsequently good investment opportunities, leading to the strengthening of the country's exchange rate. Also, a country that has higher interest rates through its government bonds tends to attract investment capital as foreign investors seek high-yield opportunities. However, stable economic growth and attractive yields or interest rates are inextricably intertwined. It's important to take advantage of market overlaps and keep an eye out for press releases when setting up a trading schedule.
References:
www.investopedia.com
www.investopedia.com
www.investopedia.com
www.investopedia.com
market24hclock.com
market24hclock.com
Square Root Moving AverageAbstract
This script computes moving averages which the weighting of the recent quarter takes up about a half weight.
This script also provides their upper bands and lower bands.
You can apply moving average or band strategies with this script.
Introduction
Moving average is a popular indicator which can eliminate market noise and observe trend.
There are several moving average related strategies used by many traders.
The first one is trade when the price is far from moving average.
To measure if the price is far from moving average, traders may need a lower band and an upper band.
Bollinger bands use standard derivation and Keltner channels use average true range.
In up trend, moving average and lower band can be support.
In ranging market, lower band can be support and upper band can be resistance.
In down trend, moving average and upper band can be resistance.
An another group of moving average strategy is comparing short term moving average and long term moving average.
Moving average cross, Awesome oscillators and MACD belong to this group.
The period and weightings of moving averages are also topics.
Period, as known as length, means how many days are computed by moving averages.
Weighting means how much weight the price of a day takes up in moving averages.
For simple moving averages, the weightings of each day are equal.
For most of non-simple moving averages, the weightings of more recent days are higher than the weightings of less recent days.
Many trading courses say the concept of trading strategies is more important than the settings of moving averages.
However, we can observe some characteristics of price movement to design the weightings of moving averages and make them more meaningful.
In this research, we use the observation that when there are no significant events, when the time frame becomes 4 times, the average true range becomes about 2 times.
For example, the average true range in 4-hour chart is about 2 times of the average true range in 1-hour chart; the average true range in 1-hour chart is about 2 times of the average true range in 15-minute chart.
Therefore, the goal of design is making the weighting of the most recent quarter is close to the weighting of the rest recent three quarters.
For example, for the 24-day moving average, the weighting of the most recent 6 days is close to the weighting of the rest 18 days.
Computing the weighting
The formula of moving average is
sum ( price of day n * weighting of day n ) / sum ( weighting of day n )
Day 1 is the most recent day and day k+1 is the day before day k.
For more convenient explanation, we don't expect sum ( weighting of day n ) is equal to 1.
To make the weighting of the most recent quarter is close to the weighting of the rest recent three quarters, we have
sum ( weighting of day 4n ) = 2 * sum ( weighting of day n )
If when weighting of day 1 is 1, we have
sum ( weighting of day n ) = sqrt ( n )
weighting of day n = sqrt ( n ) - sqrt ( n-1 )
weighting of day 2 ≒ 1.414 - 1.000 = 0.414
weighting of day 3 ≒ 1.732 - 1.414 = 0.318
weighting of day 4 ≒ 2.000 - 1.732 = 0.268
If we follow this formula, the weighting of day 1 is too strong and the moving average may be not stable.
To reduce the weighting of day 1 and keep the spirit of the formula, we can add a parameter (we call it as x_1w2b).
The formula becomes
weighting of day n = sqrt ( n+x_1w2b ) - sqrt ( n-1+x_1w2b )
if x_1w2b is 0.25, then we have
weighting of day 1 = sqrt(1.25) - sqrt(0.25) ≒ 1.1 - 0.5 = 0.6
weighting of day 2 = sqrt(2.25) - sqrt(1.25) ≒ 1.5 - 1.1 = 0.4
weighting of day 3 = sqrt(3.25) - sqrt(2.25) ≒ 1.8 - 1.5 = 0.3
weighting of day 4 = sqrt(4.25) - sqrt(3.25) ≒ 2.06 - 1.8 = 0.26
weighting of day 5 = sqrt(5.25) - sqrt(4.25) ≒ 2.3 - 2.06 = 0.24
weighting of day 6 = sqrt(6.25) - sqrt(5.25) ≒ 2.5 - 2.3 = 0.2
weighting of day 7 = sqrt(7.25) - sqrt(6.25) ≒ 2.7 - 2.5 = 0.2
What you see and can adjust in this script
This script plots three moving averages described above.
The short term one is default magenta, 6 days and 1 atr.
The middle term one is default yellow, 24 days and 2 atr.
The long term one is default green, 96 days and 4 atr.
I arrange the short term 6 days to make it close to sma(5).
The other twos are arranged according to 4x length and 2x atr.
There are 9 curves plotted by this script. I made the lower bands and the upper bands less clear than moving averages so it is less possible misrecognizing lower or upper bands as moving averages.
x_src : how to compute the reference price of a day, using 1 to 4 of open, high, low and close.
len : how many days are computed by moving averages
atr : how many days are computed by average true range
multi : the distance from the moving average to the lower band and the distance from the moving average to the lower band are equal to multi * average true range.
x_1w2b : adjust this number to avoid the weighting of day 1 from being too strong.
Conclusion
There are moving averages which the weighting of the most recent quarter is close to the weighting of the rest recent three quarters.
We can apply strategies based on moving averages. Like most of indicators, oversold does not always means it is an opportunity to buy.
If the short term lower band is close to the middle term moving average or the middle term lower band is close to the long term moving average, it may be potential support value.
References
Computing FIR Filters Using Arrays
How to trade with moving averages : the eight trading signals concluded by Granville
How to trade with Bollinger bands
How to trade with double Bollinger bands
Renko MTF - Traditional and ATRSomehow there aren't too many renko bars that have the traditional setting built-in so I put one up. This one has the option to choose between Traditional and ATR, the size number corresponds to the option that was chosen. And just in case if anyone wanted, I put up a multi-time frame option to choose the time frame the bars take place. D is for day, W is for week, flat numbers are in minutes, and leaving it blank looks at the current time frame the chart is in. The calculation comes from how Tradingview handles renko bars.
Renko bars don't paint a color unless the market moves a certain amount based on its settings. When the market moves up it turns green, if it moves down it turns red, simple color changes alone can say a lot. They're a good way to try to find trends somewhat objectively and seem to be a good way to eliminate time and can replace other time-based indicators that can whipsaw or lag. The bars have a tendency to repeat themselves so it's a good way to find trends. There aren't too many settings for the box size, most people either just choose 5, 10, 14, etc where as other indicators have many options that differ on different markets. The numbers can be chosen easily enough to pick a sweet spot with just a single input where other indicators such as MACD have multiple inputs to pick the right number that can make it difficult to choose from(although it won't be as precise as a MACD would sometimes but can be worth the objectiveness and consistency and same setting repeatability in different markets in my opinion). Some example strategies could be to use them as an alternative trailing stop, finding trends, a simple color change for entry and exit on top of other strategies, etc. It can do the job of many in an all in one price action type indicator(although not better all the time, it can come close enough). Despite all this, it does seem to depend on which time-frame it's being looked at, how TV does the calculation for it, and how one can use this with the lack of practical information on it out there.
VWAP + Fibo Dev Extensions StrategyBased on my VWAP + Fibo deviations indicator, I tested some strategies to see if the indicator can be profitable; and I got it !
This strategy uses:
H1 timeframe
Weekly VWAP
+1.618 / +2.618 / -1.618 / -2.618 Deviations Extensions to create 2 bands
The value of the deviation
First, the 2 bands are plotted : +1.618/+2.618 painted in red and -1.618/-2.618 painted in lime.
Then, we wait for the deviation value to reach at least 150 (see thumbnail) to avoid littles moves when the gaps between bands are too short.
Entry long position :
first candle must crossunder the -1.618 level and low have to stay over the -2.618
low of the second one must stay in the lime band
enter the third one if the deviation value is over limit (150)
Exit long position :
TP : when a high crossover VWAP
SL : when a low crossunder -2.618
Entry short position :
first candle must crossover the +1.618 level and high have to stay under the +2.618
high of the second one must stay in the red band
enter the third one if the deviation value is over limit (150)
Exit short position :
TP : when a low crossunder VWAP
SL : when a high crossover +2.618
Notes :
this strategy uses pyramiding (5), be careful and calculate your risk management
the comission value is set to 0.08% to include slippages when entering a trade because of market orders
This strategy is not an advice to invest, make your own decisions.
Volatility Bands by DGTVolatility represents how large an asset's prices swing around the mean price, the degree of variation of a trading price over time, and is commonly measured with beta (β) coefficients, standard deviations (σ) of returns where tools such as Average True Range, Bollinger Bands, Keltner Channel, Squeeze Indicator, etc presents volatility concept
Volatility often refers to the amount of uncertainty or risk related to the size of changes in a security's value. The higher the volatility, the riskier the security - the price of the security can change dramatically over a short time period in either direction. A lower volatility - security's value does not fluctuate dramatically, and tends to be more steady
This study, Volatility Bands , attempts to present a way to measure and visualize volatility , using standard deviations (σ) and average true range indicator, and aims to point out areas that might indicate potential trading opportunities
I will try to explain the usage with examples,
same setup with different option selected
as you may observe from the examples different setting may have advantages and disadvantages over one another, it is recommended to verify a trading setup with different available options.
Additionally, It is recommended to use this indicator in conjunction with other technical indicators, or verify using chart/candle patterns. Below is an usage example using in conjunction with other indicator, in the given example “Neglected Volume by DGT” is selected
Similarities and Differences
Bollinger Bands depicts two standard deviations above and below a simple moving average, and Keltner Channel depicts two times average true range (ATR) above and below an exponential moving average
Volatility Bands study combines the approach of both Bollinger Bands and Keltner Channel, with different settings and different visualization
Default settings are one standard deviations and one time average true range (ATR) above and below 13 period exponential moving average. Setting can be adjusted by users but let me remind all testes are performed with the default settings.
Mathematically expressed as
Upper band area between “ema + stdev” and “ema + atr”
Lower band area between “ema – stdev” and “ema – atr”
A different display is added with the inspiration I get from one of the @quantgym ‘s study, many thanks @quantgym 😉
When difference band display is selected the study will reflect the area between “ema + stdev – atr” and “ema – stdev + atr”. As shown in the examples above
Note: standard deviation calculation can be adjusted based on price action or its moving average.
Other differentiation between BB and KC is with V-BANDS mostly we look for trade opportunities when price action move out of the bands and in most cases we assume market is consolidating when the price action is within the bands
The other indicator that presents similarities to Volatility Bands is Squeeze Indicator, which measures the relationship between Bollinger Bands and Keltner's Channels to help identify consolidations and signal when prices are likely to break out. Mainly Volatility Bands is different version of Squeeze indicator, in fact the purpose is almost same but visualization is completely different. Additionally Volatility Bands Offers trading opportunities whereas Squeeze indicator only presents market states unless a momentum indicator is adapted to Squeeze indicator.
Disclaimer:
Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely
The script is for informational and educational purposes only. Use of the script does not constitute professional and/or financial advice. You alone have the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script
Dynamic Dots Dashboard (a Cloud/ZLEMA Composite)The purpose of this indicator is to provide an easy-to-read binary dashboard of where the current price is relative to key dynamic supports and resistances. The concept is simple, if a dynamic s/r is currently acting as a resistance, the indicator plots a dot above the histogram in the red box. If a dynamic s/r is acting as support, a dot is plotted in the green box below.
There are some additional features, but the dot graphs are king.
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KEY:
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Currently the dynamic s/r's being used in the dot plots are:
Ichimoku Cloud:
Tenkan (blue)
Kijun (pink)
Senkou A (red)
Senkou B (green)
ZLEMA (Zero Lag Exponential Moving Average)
99 ZLEMA (lavender)
200 ZLEMA (salmon)
You'll see a dashed line through the middle of the resistances section (red) and supports section (green). Cloud indicators are plotted above the dashed line, and ZLEMA's are below.
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How it Works - Visual
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As stated in the intro - if a dynamic s/r is currently above the current price and acting as a resistance, the indicator plots a dot above the histogram in the red box. If a dynamic s/r is acting as support, a dot is plotted in the green box below. Additionally, there is an optional histogram (default is on) that will further visualize this relationship. The histogram is a simple summation of the resistances above and the supports below.
Here's a visual to assist with what that means. This chart includes all of those dynamic s/r's in the dynamic dot dashboard (the on-chart parts are individually added, not part of this tool).
You can see that as a dynamic support is lost, the corresponding dot is moved from the supports section at the bottom (green), to the resistances section at the top (red). The opposite being true as resistances are being overtaken (broken resistances are moved to the support section (red)). You can see that the raw chart is just... a mess. Which kinda of accentuates one of the key goals of this indicator: to get all that dynamic support info without a mess of a chart like that.
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How To Use It
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There are a lot of ways to use this information, but the most notable of which is to detect shifts in the market cycle.
For this example, take a look at the dynamic s/r dots in the resistances category (red background). You can see clearly that there are distinctive blocks of high density dots that have clear beginnings and ends. When we transition from a high density of dots to none in resistances, that means we are flipping them as support and entering a bull cycle. On the other hand, when we go from low density of dots as resistances to high density, we're pivoting to a bear cycle. Easy as that, you can quickly detect when market cycles are beginning or ending.
Alternatively, you can add your preferred linear SR's, fibs, etc. to the chart and quickly glance at the dashboard to gauge how dynamic SR's may be contributing to the risk of your trade.
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Who It's For
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New traders: by looking at dot density alone, you can use Dot Dynamics to spot transitionary phases in market cycles.
Experienced traders: keep your charts clean and the information easy to digest.
Developers: I created this originally as a starting point for more complex algos I'm working on. One algo is reading this dot dashboard and taking a position size relative to the s/r's above and below. Another cloud algo is using the results as inputs to spot good setups.
Colored Bars
There is an option (off by default, shown in the headline image above) to fill the bar colors based on how many dynamic s/r's are above or below the current price. This can make things easier for some users, confusing for others. I defaulted them to off as I don't want colors to confuse the primary value proposition of the indicators, which is the dot heat map. You can turn on colored bars in the settings.
One thing to note with the colored bars: they plot the color purely by the dot densities. Random spikes in the gradient colors (i.e. red to lime or green) can be a useful thing to notice, as they commonly occur at places where the price is bouncing between dynamic s/r's and can indicate a paradigm shift in the market cycle.
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Timeframes and Assets
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This can be used effectively on all assets (stocks, crypto, forex, etc) and all time frames. As always with any indicator, the higher TF's are generally respected more than lower TF's.
Thanks for checking it out! I've been trading crypto for years and am just now beginning to publish my ideas, secret-sauce scripts and handy tools (like this one). If you enjoyed this indicator and would like to see more, a like and a follow is greatly appreciated 😁.
Every single moving average (ALMA, EMA, HMA, KAMA, RMA, SMA...)So you may be looking at the graph and thinking "this is a mess", and I agree.
The purpose of this script is to plot in the same graph every single type of moving average that I could think of, so you can find the ones that are better for your timeframe and for your asset. Once you add it, disable those types that doesn't seem to serve your purpose, until you can select one you like.
The average types are: ALMA, EMA, HMA, KAMA, RMA, SMA, SWMA, VIDYA, VWAP, VWMA, and WMA. Each one is ploted two times (except SWMA and VWAP), one with a short period, and another with a long, both of which you can configure.
Ruckard TradingLatinoThis strategy tries to mimic TradingLatino strategy.
The current implementation is beta.
Si hablas castellano o espanyol por favor consulta MENSAJE EN CASTELLANO más abajo.
It's aimed at BTCUSDT pair and 4h timeframe.
STRATEGY DEFAULT SETTINGS EXPLANATION
max_bars_back=5000 : This is a random number of bars so that the strategy test lasts for one or two years
calc_on_order_fills=false : To wait for the 4h closing is too much. Try to check if it's worth entering a position after closing one. I finally decided not to recheck if it's worth entering after an order is closed. So it is false.
calc_on_every_tick=false
pyramiding=0 : We only want one entry allowed in the same direction. And we don't want the order to scale by error.
initial_capital=1000 : These are 1000 USDT. By using 1% maximum loss per trade and 7% as a default stop loss by using 1000 USDT at 12000 USDT per BTC price you would entry with around 142 USDT which are converted into: 0.010 BTC . The maximum number of decimal for contracts on this BTCUSDT market is 3 decimals. E.g. the minimum might be: 0.001 BTC . So, this minimal 1000 amount ensures us not to entry with less than 0.001 entries which might have happened when using 100 USDT as an initial capital.
slippage=1 : Binance BTCUSDT mintick is: 0.01. Binance slippage: 0.1 % (Let's assume). TV has an integer slippage. It does not have a percentage based slippage. If we assume a 1000 initial capital, the recommended equity is 142 which at 11996 USDT per BTC price means: 0.011 BTC. The 0.1% slippage of: 0.011 BTC would be: 0.000011 . This is way smaller than the mintick. So our slippage is going to be 1. E.g. 1 (slippage) * 0.01 (mintick)
commission_type=strategy.commission.percent and commission_value=0.1 : According to: binance . com / en / fee / schedule in VIP 0 level both maker and taker fees are: 0.1 %.
BACKGROUND
Jaime Merino is a well known Youtuber focused on crypto trading
His channel TradingLatino
features monday to friday videos where he explains his strategy.
JAIME MERINO STANCE ON BOTS
Jaime Merino stance on bots (taken from memory out of a 2020 June video from him):
'~
You know. They can program you a bot and it might work.
But, there are some special situations that the bot would not be able to handle.
And, I, as a human, I would handle it. And the bot wouldn't do it.
~'
My long term target with this strategy script is add as many
special situations as I can to the script
so that it can match Jaime Merino behaviour even in non normal circumstances.
My alternate target is learn Pine script
and enjoy programming with it.
WARNING
This script might be bigger than other TradingView scripts.
However, please, do not be confused because the current status is beta.
This script has not been tested with real money.
This is NOT an official strategy from Jaime Merino.
This is NOT an official strategy from TradingLatino . net .
HOW IT WORKS
It basically uses ADX slope and LazyBear's Squeeze Momentum Indicator
to make its buy and sell decisions.
Fast paced EMA being bigger than slow paced EMA
(on higher timeframe) advices going long.
Fast paced EMA being smaller than slow paced EMA
(on higher timeframe) advices going short.
It finally add many substrats that TradingLatino uses.
SETTINGS
__ SETTINGS - Basics
____ SETTINGS - Basics - ADX
(ADX) Smoothing {14}
(ADX) DI Length {14}
(ADX) key level {23}
____ SETTINGS - Basics - LazyBear Squeeze Momentum
(SQZMOM) BB Length {20}
(SQZMOM) BB MultFactor {2.0}
(SQZMOM) KC Length {20}
(SQZMOM) KC MultFactor {1.5}
(SQZMOM) Use TrueRange (KC) {True}
____ SETTINGS - Basics - EMAs
(EMAS) EMA10 - Length {10}
(EMAS) EMA10 - Source {close}
(EMAS) EMA55 - Length {55}
(EMAS) EMA55 - Source {close}
____ SETTINGS - Volume Profile
Lowest and highest VPoC from last three days
is used to know if an entry has a support
VPVR of last 100 4h bars
is also taken into account
(VP) Use number of bars (not VP timeframe): Uses 'Number of bars {100}' setting instead of 'Volume Profile timeframe' setting for calculating session VPoC
(VP) Show tick difference from current price {False}: BETA . Might be useful for actions some day.
(VP) Number of bars {100}: If 'Use number of bars (not VP timeframe)' is turned on this setting is used to calculate session VPoC.
(VP) Volume Profile timeframe {1 day}: If 'Use number of bars (not VP timeframe)' is turned off this setting is used to calculate session VPoC.
(VP) Row width multiplier {0.6}: Adjust how the extra Volume Profile bars are shown in the chart.
(VP) Resistances prices number of decimal digits : Round Volume Profile bars label numbers so that they don't have so many decimals.
(VP) Number of bars for bottom VPOC {18}: 18 bars equals 3 days in suggested timeframe of 4 hours. It's used to calculate lowest session VPoC from previous three days. It's also used as a top VPOC for sells.
(VP) Ignore VPOC bottom advice on long {False}: If turned on it ignores bottom VPOC (or top VPOC on sells) when evaluating if a buy entry is worth it.
(VP) Number of bars for VPVR VPOC {100}: Number of bars to calculate the VPVR VPoC. We use 100 as Jaime once used. When the price bounces back to the EMA55 it might just bounce to this VPVR VPoC if its price it's lower than the EMA55 (Sells have inverse algorithm).
____ SETTINGS - ADX Slope
ADX Slope
help us to understand if ADX
has a positive slope, negative slope
or it is rather still.
(ADXSLOPE) ADX cut {23}: If ADX value is greater than this cut (23) then ADX has strength
(ADXSLOPE) ADX minimum steepness entry {45}: ADX slope needs to be 45 degrees to be considered as a positive one.
(ADXSLOPE) ADX minimum steepness exit {45}: ADX slope needs to be -45 degrees to be considered as a negative one.
(ADXSLOPE) ADX steepness periods {3}: In order to avoid false detection the slope is calculated along 3 periods.
____ SETTINGS - Next to EMA55
(NEXTEMA55) EMA10 to EMA55 bounce back percentage {80}: EMA10 might bounce back to EMA55 or maybe to 80% of its complete way to EMA55
(NEXTEMA55) Next to EMA55 percentage {15}: How much next to the EMA55 you need to be to consider it's going to bounce back upwards again.
____ SETTINGS - Stop Loss and Take Profit
You can set a default stop loss or a default take profit.
(STOPTAKE) Stop Loss % {7.0}
(STOPTAKE) Take Profit % {2.0}
____ SETTINGS - Trailing Take Profit
You can customize the default trailing take profit values
(TRAILING) Trailing Take Profit (%) {1.0}: Trailing take profit offset in percentage
(TRAILING) Trailing Take Profit Trigger (%) {2.0}: When 2.0% of benefit is reached then activate the trailing take profit.
____ SETTINGS - MAIN TURN ON/OFF OPTIONS
(EMAS) Ignore advice based on emas {false}.
(EMAS) Ignore advice based on emas (On closing long signal) {False}: Ignore advice based on emas but only when deciding to close a buy entry.
(SQZMOM) Ignore advice based on SQZMOM {false}: Ignores advice based on SQZMOM indicator.
(ADXSLOPE) Ignore advice based on ADX positive slope {false}
(ADXSLOPE) Ignore advice based on ADX cut (23) {true}
(STOPTAKE) Take Profit? {false}: Enables simple Take Profit.
(STOPTAKE) Stop Loss? {True}: Enables simple Stop Loss.
(TRAILING) Enable Trailing Take Profit (%) {True}: Enables Trailing Take Profit.
____ SETTINGS - Strategy mode
(STRAT) Type Strategy: 'Long and Short', 'Long Only' or 'Short Only'. Default: 'Long and Short'.
____ SETTINGS - Risk Management
(RISKM) Risk Management Type: 'Safe', 'Somewhat safe compound' or 'Unsafe compound'. ' Safe ': Calculations are always done with the initial capital (1000) in mind. The maximum losses per trade/day/week/month are taken into account. ' Somewhat safe compound ': Calculations are done with initial capital (1000) or a higher capital if it increases. The maximum losses per trade/day/week/month are taken into account. ' Unsafe compound ': In each order all the current capital is gambled and only the default stop loss per order is taken into account. That means that the maximum losses per trade/day/week/month are not taken into account. Default : 'Somewhat safe compound'.
(RISKM) Maximum loss per trade % {1.0}.
(RISKM) Maximum loss per day % {6.0}.
(RISKM) Maximum loss per week % {8.0}.
(RISKM) Maximum loss per month % {10.0}.
____ SETTINGS - Decimals
(DECIMAL) Maximum number of decimal for contracts {3}: How small (3 decimals means 0.001) an entry position might be in your exchange.
EXTRA 1 - PRICE IS IN RANGE indicator
(PRANGE) Print price is in range {False}: Enable a bottom label that indicates if the price is in range or not.
(PRANGE) Price range periods {5}: How many previous periods are used to calculate the medians
(PRANGE) Price range maximum desviation (%) {0.6} ( > 0 ): Maximum positive desviation for range detection
(PRANGE) Price range minimum desviation (%) {0.6} ( > 0 ): Mininum negative desviation for range detection
EXTRA 2 - SQUEEZE MOMENTUM Desviation indicator
(SQZDIVER) Show degrees {False}: Show degrees of each Squeeze Momentum Divergence lines to the x-axis.
(SQZDIVER) Show desviation labels {False}: Whether to show or not desviation labels for the Squeeze Momentum Divergences.
(SQZDIVER) Show desviation lines {False}: Whether to show or not desviation lines for the Squeeze Momentum Divergences.
EXTRA 3 - VOLUME PROFILE indicator
WARNING: This indicator works not on current bar but on previous bar. So in the worst case it might be VP from 4 hours ago. Don't worry, inside the strategy calculus the correct values are used. It's just that I cannot show the most recent one in the chart.
(VP) Print recent profile {False}: Show Volume Profile indicator
(VP) Avoid label price overlaps {False}: Avoid label prices to overlap on the chart.
EXTRA 4 - ZIGNALY SUPPORT
(ZIG) Zignaly Alert Type {Email}: 'Email', 'Webhook'. ' Email ': Prepare alert_message variable content to be compatible with zignaly expected email content format. ' Webhook ': Prepare alert_message variable content to be compatible with zignaly expected json content format.
EXTRA 5 - DEBUG
(DEBUG) Enable debug on order comments {False}: If set to true it prepares the order message to match the alert_message variable. It makes easier to debug what would have been sent by email or webhook on each of the times an order is triggered.
HOW TO USE THIS STRATEGY
BOT MODE: This is the default setting.
PROPER VOLUME PROFILE VIEWING: Click on this strategy settings. Properties tab. Make sure Recalculate 'each time the order was run' is turned off.
NEWBIE USER: (Check PROPER VOLUME PROFILE VIEWING above!) You might want to turn on the 'Print recent profile {False}' setting. Alternatively you can use my alternate realtime study: 'Resistances and supports based on simplified Volume Profile' but, be aware, it might consume one indicator.
ADVANCED USER 1: Turn on the 'Print price is in range {False}' setting and help us to debug this subindicator. Also help us to figure out how to include this value in the strategy.
ADVANCED USER 2: Turn on the all the (SQZDIVER) settings and help us to figure out how to include this value in the strategy.
ADVANCED USER 3: (Check PROPER VOLUME PROFILE VIEWING above!) Turn on the 'Print recent profile {False}' setting and report any problem with it.
JAIME MERINO: Just use the indicator as it comes by default. It should only show BUY signals, SELL signals and their associated closing signals. From time to time you might want to check 'ADVANCED USER 2' instructions to check that there's actually a divergence. Check also 'ADVANCED USER 1' instructions for your amusement.
EXTRA ADVICE
It's advised that you use this strategy in addition to these two other indicators:
* Squeeze Momentum Indicator
* ADX
so that your chart matches as close as possible to TradingLatino chart.
ZIGNALY INTEGRATION
This strategy supports Zignaly email integration by default. It also supports Zignaly Webhook integration.
ZIGNALY INTEGRATION - Email integration example
What you would write in your alert message:
||{{strategy.order.alert_message}}||key=MYSECRETKEY||
ZIGNALY INTEGRATION - Webhook integration example
What you would write in your alert message:
{ {{strategy.order.alert_message}} , "key" : "MYSECRETKEY" }
CREDITS
I have reused and adapted some code from
'Directional Movement Index + ADX & Keylevel Support' study
which it's from TradingView console user.
I have reused and adapted some code from
'3ema' study
which it's from TradingView hunganhnguyen1193 user.
I have reused and adapted some code from
'Squeeze Momentum Indicator ' study
which it's from TradingView LazyBear user.
I have reused and adapted some code from
'Strategy Tester EMA-SMA-RSI-MACD' study
which it's from TradingView fikira user.
I have reused and adapted some code from
'Support Resistance MTF' study
which it's from TradingView LonesomeTheBlue user.
I have reused and adapted some code from
'TF Segmented Linear Regression' study
which it's from TradingView alexgrover user.
I have reused and adapted some code from
"Poor man's volume profile" study
which it's from TradingView IldarAkhmetgaleev user.
FEEDBACK
Please check the strategy source code for more detailed information
where, among others, I explain all of the substrats
and if they are implemented or not.
Q1. Did I understand wrong any of the Jaime substrats (which I have implemented)?
Q2. The strategy yields quite profit when we should long (EMA10 from 1d timeframe is higher than EMA55 from 1d timeframe.
Why the strategy yields much less profit when we should short (EMA10 from 1d timeframe is lower than EMA55 from 1d timeframe)?
Any idea if you need to do something else rather than just reverse what Jaime does when longing?
FREQUENTLY ASKED QUESTIONS
FAQ1. Why are you giving this strategy for free?
TradingLatino and his fellow enthusiasts taught me this strategy. Now I'm giving back to them.
FAQ2. Seriously! Why are you giving this strategy for free?
I'm confident his strategy might be improved a lot. By keeping it to myself I would avoid other people contributions to improve it.
Now that everyone can contribute this is a win-win.
FAQ3. How can I connect this strategy to my Exchange account?
It seems that you can attach alerts to strategies.
You might want to combine it with a paying account which enable Webhook URLs to work.
I don't know how all of this works right now so I cannot give you advice on it.
You will have to do your own research on this subject. But, be careful. Automating trades, if not done properly,
might end on you automating losses.
FAQ4. I have just found that this strategy by default gives more than 3.97% of 'maximum series of losses'. That's unacceptable according to my risk management policy.
You might want to reduce default stop loss setting from 7% to something like 5% till you are ok with the 'maximum series of losses'.
FAQ5. Where can I learn more about your work on this strategy?
Check the source code. You might find unused strategies. Either because there's not a substantial increases on earnings. Or maybe because they have not been implemented yet.
FAQ6. How much leverage is applied in this strategy?
No leverage.
FAQ7. Any difference with original Jaime Merino strategy?
Most of the times Jaime defines an stop loss at the price entry. That's not the case here. The default stop loss is 7% (but, don't be confused it only means losing 1% of your investment thanks to risk management). There's also a trailing take profit that triggers at 2% profit with a 1% trailing.
FAQ8. Why this strategy return is so small?
The strategy should be improved a lot. And, well, backtesting in this platform is not guaranteed to return theoric results comparable to real-life returns. That's why I'm personally forward testing this strategy to verify it.
MENSAJE EN CASTELLANO
En primer lugar se agradece feedback para mejorar la estrategia.
Si eres un usuario avanzado y quieres colaborar en mejorar el script no dudes en comentar abajo.
Ten en cuenta que aunque toda esta descripción tenga que estar en inglés no es obligatorio que el comentario esté en inglés.
CHISTE - CASTELLANO
¡Pero Jaime!
¡400.000!
¡Tu da mun!
McGinley Dynamic (Improved) - John R. McGinley, Jr.For all the McGinley enthusiasts out there, this is my improved version of the "McGinley Dynamic", originally formulated and publicized in 1990 by John R. McGinley, Jr. Prior to this release, I recently had an encounter with a member request regarding the reliability and stability of the general algorithm. Years ago, I attempted to discover the root of it's inconsistency, but success was not possible until now. Being no stranger to a good old fashioned computational crisis, I revisited it with considerable contemplation.
I discovered a lack of constraints in the formulation that either caused the algorithm to implode to near zero and zero OR it could explosively enlarge to near infinite values during unusual price action volatility conditions, occurring on different time frames. A numeric E-notation in a moving average doesn't mean a stock just shot up in excess of a few quintillion in value from just "10ish" moments ago. Anyone experienced with the usual McGinley Dynamic, has probably encountered this with dynamically dramatic surprises in their chart, destroying it's usability.
Well, I believe I have found an answer to this dilemma of 'susceptibility to miscalculation', to provide what is most likely McGinley's whole hearted intention. It required upgrading the formulation with two constraints applied to it using min/max() functions. Let me explain why below.
When using base numbers with an exponent to the power of four, some miniature numbers smaller than one can numerically collapse to near 0 values, or even 0.0 itself. A denominator of zero will always give any computational device a horribly bad day, not to mention the developer. Let this be an EASY lesson in computational division, I often entertainingly express to others. You have heard the terminology "$#|T happens!🙂" right? In the programming realm, "AnyNumber/0.0 CAN happen!🤪" too, and it happens "A LOT" unexpectedly, even when it's highly improbable. On the other hand, numbers a bit larger than 2 with the power of four can tremendously expand rapidly to the numeric limits of 64-bit processing, generating ginormous spikes on a chart.
The ephemeral presence of one OR both of those potentials now has a combined satisfactory remedy, AND you as TV members now have it, endowed with the ever evolving "Power of Pine". Oh yeah, this one plots from bar_index==0 too. It also has experimental settings tweaks to play with, that may reveal untapped potential of this formulation. This function now has gain of function capabilities, NOT to be confused with viral gain of function enhancements from reckless BSL-4 leaking laboratories that need to be eternally abolished from this planet. Although, I do have hopes this imd() function has the potential to go viral. I believe this improved function may have utility in the future by developers of the TradingView community. You have the source, and use it wisely...
I included an generic ema() plot for a basic comparison, ultimately unveiling some of this algorithm's unique characteristics differing on a variety of time frames. Also another unconstrained function is included to display some the disparities of having no limitations on a divisor in the calculation. I strongly advise against the use of umd() in any published script. There is simply just no reason to even ponder using it. I also included notes in the script to warn against this. It's funny now, but some folks don't always read/understand my advisories... You have been warned!
NOTICE: You have absolute freedom to use this source code any way you see fit within your new Pine projects, and that includes TV themselves. You don't have to ask for my permission to reuse this improved function in your published scripts, simply because I have better things to do than answer requests for the reuse of this simplistic imd() function. Sufficient accreditation regarding this script and compliance with "TV's House Rules" regarding code reuse, is as easy as copying the entire function as is. Fair enough? Good! I have a backlog of "computational crises" to contend with, including another one during the writing of this elaborate description.
When available time provides itself, I will consider your inquiries, thoughts, and concepts presented below in the comments section, should you have any questions or comments regarding this indicator. When my indicators achieve more prevalent use by TV members, I may implement more ideas when they present themselves as worthy additions. Have a profitable future everyone!
Matrix functions - JD/////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// The arrays provided in Pinescript are linear 1D strucures that can be seen either as a large vertical stack or
// a horizontal row containing a list of values, colors, bools,..
//
// With the FUNCTIONS in this script the 1D ARRAY LIST can be CONVERTED INTO A 2D MATRIX form
//
//
///////////////////////////////////////////
/// BASIC INFO ON THE MATRIX STRUCTURE: ///
///////////////////////////////////////////
//
// The matrix is set up as an 2D structure and is devided in ROWS and COLUMNS.
// following the standard mathematical notation:
//
// a 3 x 4 matrix = 4 columns
// 0 1 2 3 column index
// 0
// 3 rows 1
// 2
// row
// index
//
// With the use of some purpose-built functions, values can be placed or retrieved in a specific column of a certain row
// this can be done by intuitively using row_nr and column_nr coördinates,
// without having to worry on what exact index of the Pine array this value is located (the functions do these conversions for you)
//
//
// the syntax I propose for the 2D Matrix array has the following structure:
//
// - the array starts with 2 VALUES describing the DIMENSION INFORMATION, (rows, columns)
// these are ignored in the actual calculations and serve as a metadata header (similar to the "location, time,... etc." data that is stored in photo files)
// so the array always carries it's own info about the nr. of rows and columns and doesn't need is seperate "info" file!
//
// To stay consistent with the standard Pinescript (array and ) indexing:
// - indexes for sheets and columns start from 0 (first) and run up to the (total nr of sheets or columns) - 1
// - indexes for rows also start from 0 (most recent, cfr. ) and run up to the (total nr of rows) - 1
//
// - this 2 value metadata header is followed by the actual df data
// the actual data array can consist of (100,000 - 2) usable items,
//
// In a theoretical example, you can have a matrix with almost 20,000 rows with each 5 columns of data (eg. open, high, low, close, volume) in it!!!
//
//
///////////////////////////////////
/// SCHEMATIC OF THE STRUCTURE: ///
///////////////////////////////////
//
////// (metadata header with dimensions info)
//
// (0) (1) (array index)
//
