[blackcat] L2 Ehlers ITrendline Trigger Trend-Following SystemLevel: 2
Background
John F. Ehlers introuced the Instantaneous Trendline and the Trigger of the trend-following system in his "Cybernetic Analysis for Stocks and Futures" chapter 3 on 2004.
Function
The process for creating a trendfollowing trading system from the indicators is simple. One unique aspect of the code is that the ITrend is forced to be a finite impulse response (FIR)-smoothed version of price for the first seven bars of the calculation.
This initialization is included to cause the ITrend to converge more rapidly to its correct value from the beginning transient. The strategy enters a long position when the trigger crosses over the Instantaneous Trendline and enters a short position when the trigger crosses under the Instantaneous Trendline. However, an effective trading system is more than following a simple set of indicators.
First, experience has shown that greater profits result from using limit orders rather than market orders or stop orders. Market orders are selfexplanatory. Stop orders mean the market must be going in the direction of the trade before the order is filled. For example, for long-position trades, the stop order must be placed above the current price. Thus, the price must increase from its current level before you get stopped into the long-position trade. This means you necessarily give up some of the profits you would otherwise have gotten if you had entered on a market order at the instant of your signal. You can lose additional profits from stop orders due to slippage.
Key Signal
Trigger ---> trend-following system fast line
ITrend ---> trend-following system slow line
Pros and Cons
100% John F. Ehlers definition translation of original work, even variable names are the same. This help readers who would like to use pine to read his book. If you had read his works, then you will be quite familiar with my code style.
Remarks
The 22th script for Blackcat1402 John F. Ehlers Week publication.
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.
在腳本中搜尋"indicators"
Stochastic Weights - Basic [BigBitsIO]This script is a compilation of several different stochastic indicators (and RSI) where the K value of each indicator is equally weighted. The purpose of the indicator is to combine many indicators together in a fashion that weights them easier. By default, the Stochastic and Stochastic RSI are both enabled - the idea is to speed up the relatively slower Stochastic and to slow down the relatively fast Stochastic RSI. Other Stochastics are also available, including some of my own custom calculations that can also be added to the weighted calculation. Only the K value is weighted, as the D value is just a moving average of the weighted K.
Explained:
- Calculates enabled indicators
- Calculates the weighted value of K for enabled indicators
- Calculates a D value from the weighted K
FAQ:
- Why is this script useful?
- To weight multiple indicators together so that you can attempt to find optimal values shared amongst the indicators. Ex: If Stochastic RSI is 100 and Stochastic is 50, K would be 75 and not particularly high. If you add in a 50 RSI, the K would be 67 in this example. If we weight indicators together that all have a high value they could potentially help find elements that align together to produce a stronger signal.
DISCLAIMER: For educational and entertainment purposes only. Nothing in this content should be interpreted as financial advice or a recommendation to buy or sell any sort of security or investment including all types of crypto. DYOR, TYOB.
Delta Volume Candles [LucF]█ OVERVIEW
This indicator plots on-chart volume delta information using candles that can replace your normal candles, tops and bottoms appended to normal candles, optional MAs of those tops and bottoms levels, a divergence channel and a chart background. The indicator calculates volume delta using intrabar analysis, meaning that it uses the lower timeframe bars constituting each chart bar.
█ CONCEPTS
Volume Delta
The volume delta concept divides a bar's volume in "up" and "down" volumes. The delta is calculated by subtracting down volume from up volume. Many calculation techniques exist to isolate up and down volume within a bar. The simplest use the polarity of interbar price changes to assign their volume to up or down slots, e.g., On Balance Volume or the Klinger Oscillator . Others such as Chaikin Money Flow use assumptions based on a bar's OHLC values. The most precise calculation method uses tick data and assigns the volume of each tick to the up or down slot depending on whether the transaction occurs at the bid or ask price. While this technique is ideal, it requires huge amounts of data on historical bars, which considerably limits the historical depth of charts and the number of symbols for which tick data is available. Furthermore, historical tick data is not yet available on TradingView.
This indicator uses intrabar analysis to achieve a compromise between the simplest and most precise methods of calculating volume delta. It is currently the most precise method usable on TradingView charts. TradingView's Volume Profile built-in indicators use it, as do the CVD - Cumulative Volume Delta Candles and CVD - Cumulative Volume Delta (Chart) indicators published from the TradingView account . My Delta Volume Channels and Volume Delta Columns Pro indicators also use intrabar analysis. Other volume delta indicators such as my Realtime 5D Profile use realtime chart updates to calculate volume delta without intrabar analysis, but that type of indicator only works in real time; they cannot calculate on historical bars.
This is the logic I use to determine the polarity of intrabars, which determines the up or down slot where its volume is added:
• If the intrabar's open and close values are different, their relative position is used.
• If the intrabar's open and close values are the same, the difference between the intrabar's close and the previous intrabar's close is used.
• As a last resort, when there is no movement during an intrabar, and it closes at the same price as the previous intrabar, the last known polarity is used.
Once all intrabars making up a chart bar have been analyzed and the up or down property of each intrabar's volume determined, the up volumes are added, and the down volumes subtracted. The resulting value is volume delta for that chart bar, which can be used as an estimate of the buying/selling pressure on an instrument. Not all markets have volume information. Without it, this indicator is useless.
Intrabar analysis
Intrabars are chart bars at a lower timeframe than the chart's. The timeframe used to access intrabars determines the number of intrabars accessible for each chart bar. On a 1H chart, each chart bar of an active market will, for example, usually contain 60 bars at the lower timeframe of 1min, provided there was market activity during each minute of the hour.
This indicator automatically calculates an appropriate lower timeframe using the chart's timeframe and the settings you use in the script's "Intrabars" section of the inputs. As it can access lower timeframes as small as seconds when available, the indicator can be used on charts at relatively small timeframes such as 1min, provided the market is active enough to produce bars at second timeframes.
The quantity of intrabars analyzed in each chart bar determines:
• The precision of calculations (more intrabars yield more precise results).
• The chart coverage of calculations (there is a 100K limit to the quantity of intrabars that can be analyzed on any chart,
so the more intrabars you analyze per chart bar, the less chart bars can be calculated by the indicator).
The information box displayed at the bottom right of the chart shows the lower timeframe used for intrabars, as well as the average number of intrabars detected for chart bars and statistics on chart coverage.
Balances
This indicator calculates five balances from volume delta values. The balances are oscillators with a zero centerline; positive values are bullish, and negative values are bearish. It is important to understand the balances as they can be used to:
• Color candle bodies.
• Calculate body and top and bottom divergences.
• Color an EMA channel.
• Color the chart's background.
• Configure markers and alerts.
The five balances are:
1 — Bar Balance : This is the only balance using instant values; it is simply the subtraction of the down volume from the up volume on the bar, so the instant volume delta for that bar.
2 — Average Balance : Calculates a distinct EMA for both the up and down volumes, and subtracts the down EMA from the up EMA.
The result is akin to MACD's histogram because it is the subtraction of two moving averages.
3 — Momentum Balance : Starts by calculating, separately for both up and down volumes, the difference between the same EMAs used in "Average Balance" and
an SMA of twice the period used for the "Average Balance" EMAs. The difference for the up side is subtracted from the difference for the down side,
and an RSI of that value is calculated and brought over the −50/+50 scale.
4 — Relative Balance : The reference values used in the calculation are the up and down EMAs used in the "Average Balance".
From those, we calculate two intermediate values using how much the instant up and down volumes on the bar exceed their respective EMA — but with a twist.
If the bar's up volume does not exceed the EMA of up volume, a zero value is used. The same goes for the down volume with the EMA of down volume.
Once we have our two intermediate values for the up and down volumes exceeding their respective MA, we subtract them. The final value is an ALMA of that subtraction.
The rationale behind using zero values when the bar's up/down volume does not exceed its EMA is to only take into account the more significant volume.
If both instant volume values exceed their MA, then the difference between the two is the signal's value.
The signal is called "relative" because the intermediate values are the difference between the instant up/down volumes and their respective MA.
This balance flatlines when the bar's up/down volumes do not exceed their EMAs, which makes it useful to spot areas where trader interest dwindles, such as consolidations.
The smaller the period of the final value's ALMA, the more easily it will flatline. These flat zones should be considered no-trade zones.
5 — Percent Balance : This balance is the ALMA of the ratio of the "Bar Balance" over the total volume for that bar.
From the balances and marker conditions, two more values are calculated:
1 — Marker Bias : This sums the up/down (+1/‒1) occurrences of the markers 1 to 4 over a period you define, so it ranges from −4 to +4, times the period.
Its calculation will depend on the modes used to calculate markers 3 and 4.
2 — Combined Balances : This is the sum of the bull/bear (+1/−1) states of each of the five balances, so it ranges from −5 to +5.
The periods for all of these balances can be configured in the "Periods" section at the bottom of the script's inputs. As you cannot see the balances on the chart, you can use my Volume Delta Columns Pro indicator in a pane; it can plot the same balances, so you will be able to analyze them.
Divergences
In the context of this indicator, a divergence is any bar where the bear/bull state of a balance (above/below its zero centerline) diverges from the polarity of a chart bar. No directional bias is assigned to divergences when they occur. Candle bodies and tops/bottoms can each be colored differently on divergences detected from distinct balances.
Divergence Channel
The divergence channel is the space between two levels (by default, the bar's open and close ) saved when divergences occur. When price (by default the close ) has breached a channel and a new divergence occurs, a new channel is created. Until that new channel is breached, bars where additional divergences occur will expand the channel's levels if the bar's price points are outside the channel.
Prices breaches of the divergence channel will change its state. Divergence channels can be in one of three different states:
• Bull (green): Price has breached the channel to the upside.
• Bear (red): Price has breached the channel to the downside.
• Neutral (gray): The channel has not yet been breached.
█ HOW TO USE THE INDICATOR
I do not make videos to explain how to use my indicators. I do, however, try hard to include in their description everything one needs to understand what they do. From there, it's up to you to explore and figure out if they can be useful in your trading practice. Communicating in videos what this description and the script's tooltips contain would make for very long videos that would likely exceed the attention span of most people who find this description too long. There is no quick way to understand an indicator such as this one because it uses many different concepts and has quite a bit of settings one can use to modify its visuals and behavior — thus how one uses it. I will happily answer questions on the inner workings of the indicator, but I do not answer questions like "How do I trade using this indicator?" A useful answer to that question would require an in-depth analysis of who you are, your trading methodology and objectives, which I do not have time for. I do not teach trading.
Start by loading the indicator on an active chart containing volume information. See here if you need help.
The default configuration displays:
• Normal candles where the bodies are only colored if the bar's volume has increased since the last bar.
If you want to use this indicator's candles, you may want to disable your chart's candles by clicking the eye icon to the right of the symbol's name in the top left of the chart.
• A top or bottom appended to the normal candles. It represents the difference between up and down volume for that bar
and is positioned at the top or bottom, depending on its polarity. If up volume is greater than down volume, a top is displayed. If down volume is greater, a bottom is plotted.
The size of tops and bottoms is determined by calculating a factor which is the proportion of volume delta over the bar's total volume.
That factor is then used to calculate the top or bottom size relative to a baseline of the average candle body size of the last 100 bars.
• An information box in the bottom right displaying intrabar and chart coverage information.
• A light red background when the intrabar volume differs from the chart's volume by more than 1%.
The script's inputs contain tooltips explaining most of the fields. I will not repeat them here. Following is a brief description of each section of the indicator's inputs which will give you an idea of what the indicator can do:
Normal Candles is where you configure the replacement candles plotted by the script. You can choose from different coloring schemes for their bodies and specify a unique color for bodies where a divergence calculated using the method you choose occurs.
Volume Tops & Botttoms is where you configure the display of tops and bottoms, and their EMAs. The EMAs are calculated from the high point of tops and the low point of bottoms. They can act as a channel to evaluate price, and you can choose to color the channel using a gradient reflecting the advances/declines in the balance of your choice.
Divergence Channel is where you set up the appearance and behavior of the divergence channel. These areas represent levels where price and volume delta information do not converge. They can be interpreted as regions with no clear direction from where one will look for breaches. You can configure the channel to take into account one or both types of divergences you have configured for candle bodies and tops/bottoms.
Background allows you to configure a gradient background color that reflects the advances/declines in the balance of your choice. You can use this to provide context to the volume delta values from bars. You can also control the background color displayed on volume discrepancies between the intrabar and the chart's timeframe.
Intrabars is where you choose the calculation mode determining the lower timeframe used to access intrabars. The indicator uses the chart's timeframe and the type of market you are on to calculate the lower timeframe. Your setting there should reflect which compromise you prefer between the precision of calculations and chart coverage. This is also where you control the display of the information box in the lower right corner of the chart.
Markers allows you to control the plotting of chart markers on different conditions. Their configuration determines when alerts generated from the indicator will fire. Note that in order to generate alerts from this script, they must be created from your chart. See this Help Center page to learn how. Only the last 500 markers will be visible on the chart, but this will not affect the generation of alerts.
Periods is where you configure the periods for the balances and the EMAs used in the indicator.
The raw values calculated by this script can be inspected using the Data Window.
█ INTERPRETATION
Rightly or wrongly, volume delta is considered by many a useful complement to the interpretation of price action. I use it extensively in an attempt to find convergence between my read of volume delta and price movement — not so much as a predictor of future price movement. No system or person can predict the future. Accordingly, I consider people who speak or act as if they know the future with certainty to be dangerous to themselves and others; they are charlatans, imprudent or blissfully ignorant.
I try to avoid elaborate volume delta interpretation schemes involving too many variables and prefer to keep things simple:
• Trends that have more chances of continuing should be accompanied by VD of the same polarity.
In trends, I am looking for "slow and steady". I work from the assumption that traders and systems often overreact, which translates into unproductive volatility.
Wild trends are more susceptible to overreactions.
• I prefer steady VD values over wildly increasing ones, as large VD increases often come with increased price volatility, which can backfire.
Large VD values caused by stopping volume will also often occur on trend reversals with abnormally high candles.
• Prices escaping divergence channels may be leading a trend in that direction, although there is no telling how long that trend will last; could be just a few bars or hundreds.
When price is in a channel, shifts in VD balances can sometimes give us an idea of the direction where price has the most chance of breaking.
• Dwindling VD will often indicate trend exhaustion and predate reversals by many bars, but the problem is that mere pauses in a trend will often produce the same behavior in VD.
I think it is too perilous to infer rigidly from VD decreases.
Divergence Channel
Here I have configured the divergence channels to be visible. First, I set the bodies to display divergences on the default Bar Balance. They are indicated by yellow bodies. Then I activated the divergence channels by choosing to draw levels on body divergences and checked the "Fill" checkbox to fill the channel with the same color as the levels. The divergence channel is best understood as a direction-less area from where a breach can be acted on if other variables converge with the breach's direction:
Tops and Bottoms EMAs
I find these EMAs rather interesting. They have no equivalent elsewhere, as they are calculated from the top and bottom values this indicator plots. The only similarity they have with volume-weighted MAs, including VWAP, is that they use price and volume. This indicator's Tops and Bottoms EMAs, however, use the price and volume delta. While the channel differs from other channels in how it is calculated, it can be used like others, as a baseline from which to evaluate price movement or, alternatively, as stop levels. Remember that you can change the period used for the EMAs in the "Periods" section of the inputs.
This chart shows the EMAs in action, filled with a gradient representing the advances/decline from the Momentum balance. Notice the anomaly in the chart's latest bars where the Momentum balance gradient has been indicating a bullish bias for some time, during which price was mostly below the EMAs. Price has just broken above the channel on positive VD. My interpretation of this situation would be that it is a risky opportunity for a long trade in the larger context where the market has been in a downtrend since the 5th. Intrepid traders choosing to enter here could do so with a "make or break" tight stop that will minimize their losses should the market continue its downtrend while hopefully preserving the potential upside of price continuing on the longer-term uptrend prevalent since the 28th:
█ NOTES
Volume
If you use indicators such as this one which depends on volume information, it is important to realize that the volume data they consume comes from data feeds, and that all data feeds are NOT created equally. Those who create the data feeds we use must make decisions concerning the nature of the transactions they tally and the way they are tallied in each feed, and these decisions affect the nature of our volume data. My Volume X-ray publication discusses some of the reasons why volume information from different timeframes, brokers/exchanges or sectors may vary considerably. I encourage you to read it. This indicator's display of a warning through a background color on volume discrepancies between the timeframe used to access intrabars and the chart's timeframe is an attempt to help you realize these variations in feeds. Don't take things for granted, and understand that the quality of a given feed's volume information affects the quality of the results this indicator calculates.
Markets as ecosystems
I believe it is perilous to think that behavioral patterns you discover in one market through the lens of this or any other indicator will necessarily port to other markets. While this may sometimes be the case, it will often not. Why is that? Because each market is its own ecosystem. As cities do, all markets share some common characteristics, but they also all have their idiosyncrasies. A proportion of a city's inhabitants is always composed of outsiders who come and go, but a core population of regulars and systems is usually the force that actually defines most of the city's observable characteristics. I believe markets work somewhat the same way; they may look the same, but if you live there for a while and pay attention, you will notice the idiosyncrasies. Some things that work in some markets will, accordingly, not work in others. Please keep that in mind when you draw conclusions.
On Up/Down or Buy/Sell Volume
Buying or selling volume are misnomers, as every unit of volume transacted is both bought and sold by two different traders. While this does not keep me from using the terms, there is no such thing as “buy only” or “sell only” volume. Trader lingo is riddled with peculiarities. Without access to order book information, traders work with the assumption that when price moves up during a bar, there was more buying pressure than selling pressure, just as when buy market orders take out limit ask orders in the order book at successively higher levels. The built-in volume indicator available on TradingView uses this logic to color the volume columns green or red. While this script’s calculations are more precise because it analyses intrabars to calculate its information, it uses pretty much the same imperfect logic. Until Pine scripts can have access to how much volume was transacted at the bid/ask prices, our volume delta calculations will remain a mere proxy.
Repainting
• The values calculated on the realtime bar will update as new information comes from the feed.
• Historical values may recalculate if the historical feed is updated or when calculations start from a new point in history.
• Markers and alerts will not repaint as they only occur on a bar's close. Keep this in mind when viewing markers on historical bars,
where one could understandably and incorrectly assume they appear at the bar's open.
To learn more about repainting, see the Pine Script™ User Manual's page on the subject .
Superfluity
In "The Bed of Procrustes", Nassim Nicholas Taleb writes: To bankrupt a fool, give him information . This indicator can display a lot of information. The inevitable adaptation period you will need to figure out how to use it should help you eliminate all the visuals you do not need. The more you eliminate, the easier it will be to focus on those that are the most useful to your trading practice. Don't be a fool.
█ THANKS
Thanks to alexgrover for his Dekidaka-Ashi indicator. His volume plots on candles were the inspiration for my top/bottom plots.
Kudos to PineCoders for their libraries. I use two of them in this script: Time and lower_tf .
The first versions of this script used functionality that I would not have known about were it not for these two guys:
— A guy called Kuan who commented on a Backtest Rookies presentation of their Volume Profile indicator.
— theheirophant , my partner in the exploration of the sometimes weird abysses of request.security() ’s behavior at lower timeframes.
Grover Llorens Activator [alexgrover & Lucía Llorens] Trailing stops play a key role in technical analysis and are extremely popular trend following indicators. Their main strength lie in their ability to minimize whipsaws while conserving a decent reactivity, the most popular ones include the Supertrend, Parabolic SAR and Gann Hilo activator. However, and like many indicators, most trailing stops assume an infinitely long trend, which penalize their ability to provide early exit points, this isn't the case of the parabolic SAR who take this into account and thus converge toward the price at an increasing speed the longer a trend last.
Today a similar indicator is proposed. From an original idea of alexgrover & Lucía Llorens who wanted to revisit the classic parabolic SAR indicator, the Llorens activator aim to converge toward the price the longer a trend persist, thus allowing for potential early and accurate exit points. The code make use of the idea behind the price curve channel that you can find here :
I tried to make the code as concise as possible.
The Indicator
The indicator posses 2 user settings, length and mult , length control the rate of convergence of the indicator, with higher values of length making the indicator output converge more slowly toward the price. Mult is also related with the rate of convergence, basically once the price cross the trailing stop its value will become equal to the previous trailing stop value plus/minus mult*atr depending on the previous trailing stop value, therefore higher values of mult will require more time for the trailing stop to reach the closing price, use higher values of mult if you want to avoid potential whipsaws.
Above the indicator with slow convergence time (high length) and low mult.
Points with early exit points are highlighted.
Usage For Oscillators
The difference between the closing price and an overlay indicator can provide an oscillator with characteristics depending on the indicators used for differencing, Lucía Llorens stated that we should find indicators for differencing that highlight the cycles in the price, in other terms : Price - Signal , where we want to find Signal such that we maximize the visibility of the cycles, it can be demonstrated that in the case where the closing price is an additive model : Trend + Cycles + Noise , the zero lag estimation of the Trend component can allow for the conservation of the cycle and noise component, that is : Price - Estimate(Trend) , for example the difference between the price and moving average isn't optimal because of the moving average lag, instead the use of zero lag moving averages is more suitable, however the proposed indicator allow for a surprisingly good representation of the cycles when using differencing.
The normalization of this oscillator (via the RSI) allow to make the peak amplitude of the cycles more constant. Note however that such method can return an output with a sign inverse to the one of the original cycle component.
Conclusion
We proposed an indicator which share the logic of the SAR indicator, that is using convergence toward the price in order to provide early exit points detection. We have seen that this indicator can be used to highlight cycles when used for differencing and i don't exclude publishing more indicators based on this method.
Lucía Llorens has been a great person to work with, and provided enormous feedback and support while i was coding the indicator, this is why i include her in the indicator name as well as copyright notice. I hope we can make more indicators togethers in the future.
(altho i was against using buy/sells labels xD !)
Thanks for reading !
FVE - Finite Volume Elements [UTS]FVE is a money flow indicator but with two important differences from existing money flow indicators:
It resolves contradictions between intraday money flow indicators (such as Chaikin’s money flow) and interday money flow indicators (like On Balance Volume) by taking into account both intra- and interday price action.
Unlike other money flow indicators which add or subtract all volume even if the security closed just 1 cent higher than the previous close, FVE uses a volatility threshold to take into account minimal price changes.
General Usage
The FVE provides 3 types of signals:
The strongest signal is divergence between price and the indicator. Divergence can provide leading signals of breakouts or warnings of impending corrections. The classic method for detecting divergence is for FVE to make lower highs while price makes higher highs (negative divergence). An alternative method is to draw the linear regression line on both charts, and compare the slopes. A logical buy signal would be for FVE, diverging from price, to rise sharply and make a series higher highs and/or higher lows.
The most obvious and coincident signal is the slope of the FVE line. An upward slope indicates that the bulls are in control and the opposite for downward.
This is a unique and very important property of this indicator. Values above zero are bullish and indicate accumulation while values below zero indicate distribution. FVE crossing the zero line indicates that the short to intermediate balance of power is changing from the bulls to the bears or vice versa. The best scenario is when a stock is in the process of building a base, and FVE diverges from price and rises to cross the zero line from below, at a sharp angle. Conversely the crossing of the zero line from above is a bearish signal to liquidate positions or initiate a short trade.
Trend Visualisation
Optional: If the trend direction is DOWN the moving average is painted red. If the trend direction is UP the moving average is painted in green.
If the movement is FLAT then the color is grey.
Moving Averages
Five different types of Moving Averages are available for both FVE and the optional moving average of the FVE.
ALMA (Arnaud Legoux Moving Average)
Average Value
EMA (Exponential Moving Average)
SMA (Simple Moving Average)
WMA (Weighted Moving Average)
Calculation Methods
Since Markos Katsanos presented the first version of the FVE in April 2003.
Since then there have been various adaptions and improvements on this indicator.
The following are choosable for calculating the FVE:
Thinkscript usethinkscript.com
Linnsoft www.linnsoft.com
Volatility Adapted traders.com
T-Step LSMAIntroduction
The trend step indicator family has produced much interest in the community, those indicators showed in certain cases robustness and reactivity. Their ease of use/interpretation is also a major advantage. Although those indicators have a relatively good fit with the input price, they can still be improved by introducing least-squares fitting on their calculations. This is why i propose a new indicator (T-Step LSMA) which aim to gather all the components of the trend-step indicator family (including the auto-line family).
The indicator will use as a threshold the mean absolute error between the input and the output (T-Channel) scaled with the efficiency ratio (Efficient Trend Step) while using least squares in order to provide a better fit with the price (Auto-Filter).
The Indicator
The interpretation of the indicator is easy, the indicator estimate an up-trending market when in blue, down-trending when in orange, the signal only depend on the trend-step part ( b in the code).
length control the period of the efficiency ratio as well as any components in the lsma calculation. The efficiency ratio allow to provide adaptivity, therefore the threshold will be lower when market is trending and higher when market is ranging.
Sc control the amount of feedback of the indicator, a value of 1 will use only the closing price as input, a value of 0.5 will use 50% of the closing price/indicator output as input, this allow to get smoother results.
It is possible to get the non-smooth version of the indicator by checking "No Smoothing".
This allow the indicator to filter more information.
Least Squares Smoothing - Benefits
One could ask why introducing least squares smoothing, there are several reasons to this choice, we have seen that trend-step indicators are boxy, they filter most of the variational information in the price, introducing least squares smoothing allow to gain back some of this variational information while providing a better fit with the price, the indicator is more noisy but also more practical in certain situations.
For example the indicator in its boxy form can't really be useful as input for other indicators, which is not the case with this version.
Relative strength index of period 14 using the proposed indicator as input.
Down-Sides
The indicator is dependent on the time frame used, larger time frames resulting in an indicator overfitting, sticking with lower time frames might be ideal. The indicator behavior might also change depending on the market in which it is applied.
Setting Up Alerts For The Indicator
Alerts conditions are already set, in order to create an alert based on the indicator follow these steps :
Go to the alert section (the alarm clock) -> create new alert -> select T-Step LSMA in condition -> Below select Up or Dn (Up for a up-trending alert and Dn for a down-trending alert)
In option select "once per bar close", change the message if you want a personalized message.
Conclusion
I don't think i'll post other indicators related to the trend-step framework for the time to comes, nonetheless the ones posted proven to have interesting results as well as many upsides. Although i don't think they would generate positive long-terms returns they could still be of use when using smarter volatility metrics as threshold. The proposed indicator conserve more information than its relatives and might find some use as input for other indicators.
Recommended Use Of The Code
Although i don't put restrictions on the code usage, i still recommend creative and pertinent changes to be made, graphical changes or any minor changes are not necessary, remember that such practice is disrespectful toward the author, you don't want to load up the tradingview servers for nothing right ?
Support Me
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Inverse Fisher Transform COMBO STO+RSI+CCIv2 by KIVANÇ fr3762A combined 3in1 version of pre shared INVERSE FISHER TRANSFORM indicators on RSI , on STOCHASTIC and on CCIv2 to provide space for 2 more indicators for users...
About John EHLERS:
From California, USA, John is a veteran trader. With 35 years trading experience he has seen it all. John has an engineering background that led to his technical approach to trading ignoring fundamental analysis (with one important exception).
John strongly believes in cycles. He’d rather exit a trade when the cycle ends or a new one starts. He uses the MESA principle to make predictions about cycles in the market and trades one hundred percent automatically.
In the show John reveals:
• What is more appropriate than trading individual stocks
• The one thing he relies upon in his approach to the market
• The detail surrounding his unique trading style
• What important thing underpins the market and gives every trader an edge
About INVERSE FISHER TRANSFORM:
The purpose of technical indicators is to help with your timing decisions to buy or
sell. Hopefully, the signals are clear and unequivocal. However, more often than
not your decision to pull the trigger is accompanied by crossing your fingers.
Even if you have placed only a few trades you know the drill.
In this article I will show you a way to make your oscillator-type indicators make
clear black-or-white indication of the time to buy or sell. I will do this by using the
Inverse Fisher Transform to alter the Probability Distribution Function ( PDF ) of
your indicators. In the past12 I have noted that the PDF of price and indicators do
not have a Gaussian, or Normal, probability distribution. A Gaussian PDF is the
familiar bell-shaped curve where the long “tails” mean that wide deviations from
the mean occur with relatively low probability. The Fisher Transform can be
applied to almost any normalized data set to make the resulting PDF nearly
Gaussian, with the result that the turning points are sharply peaked and easy to
identify. The Fisher Transform is defined by the equation
1)
Whereas the Fisher Transform is expansive, the Inverse Fisher Transform is
compressive. The Inverse Fisher Transform is found by solving equation 1 for x
in terms of y. The Inverse Fisher Transform is:
2)
The transfer response of the Inverse Fisher Transform is shown in Figure 1. If
the input falls between –0.5 and +0.5, the output is nearly the same as the input.
For larger absolute values (say, larger than 2), the output is compressed to be no
larger than unity . The result of using the Inverse Fisher Transform is that the
output has a very high probability of being either +1 or –1. This bipolar
probability distribution makes the Inverse Fisher Transform ideal for generating
an indicator that provides clear buy and sell signals.
Creator: John EHLERS
Finite Volume Elementwww.prorealcode.com
From ProRealTime,
"FVE is a money flow indicator but with two important differences from existing money flow indicators:
It resolves contradictions between intraday money flow indicators (such as Chaikin’s money flow) and interday money flow indicators (like On Balance Volume) by taking into account both intra- and interday price action. Unlike other money flow indicators which add or subtract all volume even if the security closed just 1 cent higher than the previous close, FVE uses a volatility threshold to take into account minimal price changes. The FVE provides 3 types of signals: The strongest signal is divergence between price and the indicator. Divergence can provide leading signals of breakouts or warnings of impending corrections. The classic method for detecting divergence is for FVE to make lower highs while price makes higher highs (negative divergence). An alternative method is to draw the linear regression line on both charts, and compare the slopes. A logical buy signal would be for FVE, diverging from price, to rise sharply and make a series higher highs and/or higher lows. The most obvious and coincident signal is the slope of the FVE line. An upward slope indicates that the bulls are in control and the opposite for downward. This is a unique and very important property of this indicator. Values above zero are bullish and indicate accumulation while values below zero indicate distribution. FVE crossing the zero line indicates that the short to intermediate balance of power is changing from the bulls to the bears or vice versa. The best scenario is when a stock is in the process of building a base, and FVE diverges from price and rises to cross the zero line from below, at a sharp angle. Conversely the crossing of the zero line from above is a bearish signal to liquidate positions or initiate a short trade."
Bear Market Probability Model# Bear Market Probability Model: A Multi-Factor Risk Assessment Framework
The Bear Market Probability Model represents a comprehensive quantitative framework for assessing systemic market risk through the integration of 13 distinct risk factors across four analytical categories: macroeconomic indicators, technical analysis factors, market sentiment measures, and market breadth metrics. This indicator synthesizes established financial research methodologies to provide real-time probabilistic assessments of impending bear market conditions, offering institutional-grade risk management capabilities to retail and professional traders alike.
## Theoretical Foundation
### Historical Context of Bear Market Prediction
Bear market prediction has been a central focus of financial research since the seminal work of Dow (1901) and the subsequent development of technical analysis theory. The challenge of predicting market downturns gained renewed academic attention following the market crashes of 1929, 1987, 2000, and 2008, leading to the development of sophisticated multi-factor models.
Fama and French (1989) demonstrated that certain financial variables possess predictive power for stock returns, particularly during market stress periods. Their three-factor model laid the groundwork for multi-dimensional risk assessment, which this indicator extends through the incorporation of real-time market microstructure data.
### Methodological Framework
The model employs a weighted composite scoring methodology based on the theoretical framework established by Campbell and Shiller (1998) for market valuation assessment, extended through the incorporation of high-frequency sentiment and technical indicators as proposed by Baker and Wurgler (2006) in their seminal work on investor sentiment.
The mathematical foundation follows the general form:
Bear Market Probability = Σ(Wi × Ci) / ΣWi × 100
Where:
- Wi = Category weight (i = 1,2,3,4)
- Ci = Normalized category score
- Categories: Macroeconomic, Technical, Sentiment, Breadth
## Component Analysis
### 1. Macroeconomic Risk Factors
#### Yield Curve Analysis
The inclusion of yield curve inversion as a primary predictor follows extensive research by Estrella and Mishkin (1998), who demonstrated that the term spread between 3-month and 10-year Treasury securities has historically preceded all major recessions since 1969. The model incorporates both the 2Y-10Y and 3M-10Y spreads to capture different aspects of monetary policy expectations.
Implementation:
- 2Y-10Y Spread: Captures market expectations of monetary policy trajectory
- 3M-10Y Spread: Traditional recession predictor with 12-18 month lead time
Scientific Basis: Harvey (1988) and subsequent research by Ang, Piazzesi, and Wei (2006) established the theoretical foundation linking yield curve inversions to economic contractions through the expectations hypothesis of the term structure.
#### Credit Risk Premium Assessment
High-yield credit spreads serve as a real-time gauge of systemic risk, following the methodology established by Gilchrist and Zakrajšek (2012) in their excess bond premium research. The model incorporates the ICE BofA High Yield Master II Option-Adjusted Spread as a proxy for credit market stress.
Threshold Calibration:
- Normal conditions: < 350 basis points
- Elevated risk: 350-500 basis points
- Severe stress: > 500 basis points
#### Currency and Commodity Stress Indicators
The US Dollar Index (DXY) momentum serves as a risk-off indicator, while the Gold-to-Oil ratio captures commodity market stress dynamics. This approach follows the methodology of Akram (2009) and Beckmann, Berger, and Czudaj (2015) in analyzing commodity-currency relationships during market stress.
### 2. Technical Analysis Factors
#### Multi-Timeframe Moving Average Analysis
The technical component incorporates the well-established moving average convergence methodology, drawing from the work of Brock, Lakonishok, and LeBaron (1992), who provided empirical evidence for the profitability of technical trading rules.
Implementation:
- Price relative to 50-day and 200-day simple moving averages
- Moving average convergence/divergence analysis
- Multi-timeframe MACD assessment (daily and weekly)
#### Momentum and Volatility Analysis
The model integrates Relative Strength Index (RSI) analysis following Wilder's (1978) original methodology, combined with maximum drawdown analysis based on the work of Magdon-Ismail and Atiya (2004) on optimal drawdown measurement.
### 3. Market Sentiment Factors
#### Volatility Index Analysis
The VIX component follows the established research of Whaley (2009) and subsequent work by Bekaert and Hoerova (2014) on VIX as a predictor of market stress. The model incorporates both absolute VIX levels and relative VIX spikes compared to the 20-day moving average.
Calibration:
- Low volatility: VIX < 20
- Elevated concern: VIX 20-25
- High fear: VIX > 25
- Panic conditions: VIX > 30
#### Put-Call Ratio Analysis
Options flow analysis through put-call ratios provides insight into sophisticated investor positioning, following the methodology established by Pan and Poteshman (2006) in their analysis of informed trading in options markets.
### 4. Market Breadth Factors
#### Advance-Decline Analysis
Market breadth assessment follows the classic work of Fosback (1976) and subsequent research by Brown and Cliff (2004) on market breadth as a predictor of future returns.
Components:
- Daily advance-decline ratio
- Advance-decline line momentum
- McClellan Oscillator (Ema19 - Ema39 of A-D difference)
#### New Highs-New Lows Analysis
The new highs-new lows ratio serves as a market leadership indicator, based on the research of Zweig (1986) and validated in academic literature by Zarowin (1990).
## Dynamic Threshold Methodology
The model incorporates adaptive thresholds based on rolling volatility and trend analysis, following the methodology established by Pagan and Sossounov (2003) for business cycle dating. This approach allows the model to adjust sensitivity based on prevailing market conditions.
Dynamic Threshold Calculation:
- Warning Level: Base threshold ± (Volatility × 1.0)
- Danger Level: Base threshold ± (Volatility × 1.5)
- Bounds: ±10-20 points from base threshold
## Professional Implementation
### Institutional Usage Patterns
Professional risk managers typically employ multi-factor bear market models in several contexts:
#### 1. Portfolio Risk Management
- Tactical Asset Allocation: Reducing equity exposure when probability exceeds 60-70%
- Hedging Strategies: Implementing protective puts or VIX calls when warning thresholds are breached
- Sector Rotation: Shifting from growth to defensive sectors during elevated risk periods
#### 2. Risk Budgeting
- Value-at-Risk Adjustment: Incorporating bear market probability into VaR calculations
- Stress Testing: Using probability levels to calibrate stress test scenarios
- Capital Requirements: Adjusting regulatory capital based on systemic risk assessment
#### 3. Client Communication
- Risk Reporting: Quantifying market risk for client presentations
- Investment Committee Decisions: Providing objective risk metrics for strategic decisions
- Performance Attribution: Explaining defensive positioning during market stress
### Implementation Framework
Professional traders typically implement such models through:
#### Signal Hierarchy:
1. Probability < 30%: Normal risk positioning
2. Probability 30-50%: Increased hedging, reduced leverage
3. Probability 50-70%: Defensive positioning, cash building
4. Probability > 70%: Maximum defensive posture, short exposure consideration
#### Risk Management Integration:
- Position Sizing: Inverse relationship between probability and position size
- Stop-Loss Adjustment: Tighter stops during elevated risk periods
- Correlation Monitoring: Increased attention to cross-asset correlations
## Strengths and Advantages
### 1. Comprehensive Coverage
The model's primary strength lies in its multi-dimensional approach, avoiding the single-factor bias that has historically plagued market timing models. By incorporating macroeconomic, technical, sentiment, and breadth factors, the model provides robust risk assessment across different market regimes.
### 2. Dynamic Adaptability
The adaptive threshold mechanism allows the model to adjust sensitivity based on prevailing volatility conditions, reducing false signals during low-volatility periods and maintaining sensitivity during high-volatility regimes.
### 3. Real-Time Processing
Unlike traditional academic models that rely on monthly or quarterly data, this indicator processes daily market data, providing timely risk assessment for active portfolio management.
### 4. Transparency and Interpretability
The component-based structure allows users to understand which factors are driving risk assessment, enabling informed decision-making about model signals.
### 5. Historical Validation
Each component has been validated in academic literature, providing theoretical foundation for the model's predictive power.
## Limitations and Weaknesses
### 1. Data Dependencies
The model's effectiveness depends heavily on the availability and quality of real-time economic data. Federal Reserve Economic Data (FRED) updates may have lags that could impact model responsiveness during rapidly evolving market conditions.
### 2. Regime Change Sensitivity
Like most quantitative models, the indicator may struggle during unprecedented market conditions or structural regime changes where historical relationships break down (Taleb, 2007).
### 3. False Signal Risk
Multi-factor models inherently face the challenge of balancing sensitivity with specificity. The model may generate false positive signals during normal market volatility periods.
### 4. Currency and Geographic Bias
The model focuses primarily on US market indicators, potentially limiting its effectiveness for global portfolio management or non-USD denominated assets.
### 5. Correlation Breakdown
During extreme market stress, correlations between risk factors may increase dramatically, reducing the model's diversification benefits (Forbes and Rigobon, 2002).
## References
Akram, Q. F. (2009). Commodity prices, interest rates and the dollar. Energy Economics, 31(6), 838-851.
Ang, A., Piazzesi, M., & Wei, M. (2006). What does the yield curve tell us about GDP growth? Journal of Econometrics, 131(1-2), 359-403.
Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross‐section of stock returns. The Journal of Finance, 61(4), 1645-1680.
Baker, S. R., Bloom, N., & Davis, S. J. (2016). Measuring economic policy uncertainty. The Quarterly Journal of Economics, 131(4), 1593-1636.
Barber, B. M., & Odean, T. (2001). Boys will be boys: Gender, overconfidence, and common stock investment. The Quarterly Journal of Economics, 116(1), 261-292.
Beckmann, J., Berger, T., & Czudaj, R. (2015). Does gold act as a hedge or a safe haven for stocks? A smooth transition approach. Economic Modelling, 48, 16-24.
Bekaert, G., & Hoerova, M. (2014). The VIX, the variance premium and stock market volatility. Journal of Econometrics, 183(2), 181-192.
Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. The Journal of Finance, 47(5), 1731-1764.
Brown, G. W., & Cliff, M. T. (2004). Investor sentiment and the near-term stock market. Journal of Empirical Finance, 11(1), 1-27.
Campbell, J. Y., & Shiller, R. J. (1998). Valuation ratios and the long-run stock market outlook. The Journal of Portfolio Management, 24(2), 11-26.
Dow, C. H. (1901). Scientific stock speculation. The Magazine of Wall Street.
Estrella, A., & Mishkin, F. S. (1998). Predicting US recessions: Financial variables as leading indicators. Review of Economics and Statistics, 80(1), 45-61.
Fama, E. F., & French, K. R. (1989). Business conditions and expected returns on stocks and bonds. Journal of Financial Economics, 25(1), 23-49.
Forbes, K. J., & Rigobon, R. (2002). No contagion, only interdependence: measuring stock market comovements. The Journal of Finance, 57(5), 2223-2261.
Fosback, N. G. (1976). Stock market logic: A sophisticated approach to profits on Wall Street. The Institute for Econometric Research.
Gilchrist, S., & Zakrajšek, E. (2012). Credit spreads and business cycle fluctuations. American Economic Review, 102(4), 1692-1720.
Harvey, C. R. (1988). The real term structure and consumption growth. Journal of Financial Economics, 22(2), 305-333.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291.
Magdon-Ismail, M., & Atiya, A. F. (2004). Maximum drawdown. Risk, 17(10), 99-102.
Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175-220.
Pagan, A. R., & Sossounov, K. A. (2003). A simple framework for analysing bull and bear markets. Journal of Applied Econometrics, 18(1), 23-46.
Pan, J., & Poteshman, A. M. (2006). The information in option volume for future stock prices. The Review of Financial Studies, 19(3), 871-908.
Taleb, N. N. (2007). The black swan: The impact of the highly improbable. Random House.
Whaley, R. E. (2009). Understanding the VIX. The Journal of Portfolio Management, 35(3), 98-105.
Wilder, J. W. (1978). New concepts in technical trading systems. Trend Research.
Zarowin, P. (1990). Size, seasonality, and stock market overreaction. Journal of Financial and Quantitative Analysis, 25(1), 113-125.
Zweig, M. E. (1986). Winning on Wall Street. Warner Books.
Mehul - ADX Zero LagThis script combines two popular technical indicators into a single visualization:
1. **Average Directional Index (ADX)**:
- Measures trend strength on a scale from 0-100 (now normalized to 0-1 by dividing by 100)
- Displayed as a red line
- Adjustable smoothing and length parameters
2. **Zero Lag MACD (Modified Moving Average Convergence Divergence)**:
- An enhanced version of the traditional MACD with reduced lag
- Shows the relationship between fast and slow moving averages
- Main components include:
- MACD line (black)
- Signal line (gray)
- Histogram (green for positive, purple for negative)
- EMA of the MACD line (red)
- Optional crossing dots
Key features of the combined indicator:
- **Scale Adjustment**: Both indicators can be scaled independently (adxScale and macdScale parameters)
- **Visibility Toggles**: Each indicator can be shown or hidden
- **Advanced Customization**: Parameters for both indicators can be fine-tuned
- **Algorithm Selection**: Option to choose between the "Glaz" algorithm or the "real" zero lag algorithm
- **Display Options**: Toggles for visualization elements like crossing dots
The most significant technical aspect is that both indicators are displayed in the same pane with compatible scaling, achieved by normalizing the ADX values and applying user-defined scale factors to both indicators.
This combined indicator is designed to give traders a comprehensive view of both trend strength (from ADX) and momentum/direction (from Zero Lag MACD) in a single, easy-to-read visualization.
Aj's DikFat Adjusted ADXRAj's DikFat Adjusted ADXR
This indicator is designed to plot the Average Directional Index (ADX) and Average Directional Movement Rating (ADXR) on the chart. The ADX and ADXR are both used to measure the strength of a trend in the market. The script allows you to customize several parameters, including the ADX Length and the Moving Average Method used for smoothing the directional movement indicators.
Key Features:
- ADX Length : Defines the number of periods over which the ADX is calculated. This value can be adjusted by the user to suit different trading styles and timeframes.
- Moving Average Method : Choose between several smoothing methods, including Simple Moving Average (SMA), Exponential Moving Average (EMA), Wilder's Moving Average, Weighted Moving Average (WMA), Hull Moving Average (HMA), or a Super Smooth Moving Average.
- Directional Indicators : The script calculates the +DI and -DI, which represent the positive and negative directional indicators respectively. These are then used to calculate the ADX.
- ADXR : The ADXR is calculated as the average of the current ADX value and the ADX value from 14 periods ago, providing a more smoothed representation of the trend strength.
How Traders Use ADX and ADXR:
- ADX : A rising ADX indicates an increasing trend strength, while a falling ADX suggests a weakening trend. A value above 25 is often considered an indication of a strong trend.
- ADXR : This indicator smooths the ADX over time, helping traders identify persistent trends. The ADXR can help filter out noise and provide a clearer picture of the trend's health.
Please note that this script and its indicators are designed to be used as tools for analysis, not as guarantees of market outcomes. Adjustments to the moving average method or ADX length can change the behavior of the indicators based on market conditions.
Options Series - Technical Analysis Chart➤ Simple Technical Chart Only:
➤ With MA-20 Overlay and Volatility background bars:
➤ With RSI Candles:
⭐ Overview and How It Works:
This script provides a multi-asset analysis tool to assess various market conditions across four symbols simultaneously. It combines several indicators such as daily price change, Moving Averages (MA), Bollinger Bands (BB), Parabolic SAR, RSI, and VWAP to generate buy/sell signals and trend indicators. Its strength lies in the layered use of indicators to enhance signal reliability, making it valuable for traders needing cross-validation in decision-making.
⭐ Key Features and Functionality:
The script evaluates each symbol's price against various indicators and conditions:
Daily Price Conditions: It checks if each symbol’s close price is above or below the previous day’s open, close, and intra-day ranges, forming a foundational bullish/bearish condition.
Range Breakout 1st 5min Candle (ORB): Opening Range Breakout levels are calculated and compared with current close prices, detecting breakout/breakdown conditions.
ORB Body: This basically calculates the previous day Daily candle body size, if todays Daily candle body size is greater than previous day, then we can say that we are having good momentum else its likely to be in-sidebar trading.
Moving Averages (MA): It leverages EMA-20, 2-day, and 3-day exponential moving averages to gauge short to medium-term trends.
RSI and VWAP: Relative Strength Index (RSI) determines overbought or oversold conditions, while VWAP compares prices to volume-weighted levels.
Bollinger Bands and Trend Analysis: Detects volatility and potential breakout conditions.
Concept of ORB Body:
Current_PrevDay_Body = (math.max(var_Current_PrevD_Open, var_Current_PrevD_Close) - math.min(var_Current_PrevD_Open, var_Current_PrevD_Close))
Current_Upper_ORB = var_Current_D_Open + Current_PrevDay_Body
Current_Lower_ORB = var_Current_D_Open - Current_PrevDay_Body
Current_TodayDay_Body = math.max(var_Current_D_Open, var_Current_Close) - math.min(var_Current_D_Open, var_Current_Close)
Current_ORBBody = Current_TodayDay_Body > Current_PrevDay_Body
Current_Upper_ORB_bull = (var_Current_Close > Current_Upper_ORB)
Current_Lower_ORB_bear = (var_Current_Close < Current_Lower_ORB)
🎨 Visualizations and User Experience:
The script can dynamically display colored backgrounds indicating trends when conditions are met. For example, the bgcolor function changes the background when certain trend-based criteria are satisfied, offering visual cues to users. Additionally, the checkbox input toggles trend bar visualizations, enhancing user experience by providing a quick visual reference without needing to interpret individual data points manually.
RSI-Based Candle Coloring:
➤ The script customizes candle colors based on RSI thresholds, specifically defining upper (60) and lower (40) RSI levels. When the RSI value exceeds the upper threshold, candles are colored as bullish (green), and if it falls below the lower threshold, candles are colored as bearish (red). Neutral RSI values result in a default color (gray).
➤ This setup offers a visually intuitive way to identify potential trend directions based on RSI levels, making it ideal for traders looking to gauge momentum visually.
⭐ Settings and Customization:
With multiple user-configurable inputs, the script allows for tailored analysis. Customizable parameters, such as enabling/disabling trend bars and setting various look-back periods for indicators like Bollinger Bands and Moving Averages, make it adaptable to various trading styles and preferences. It also allows users to modify visual elements like colors and styles, improving flexibility.
⭐ Uniqueness of the Concept:
The unique aspect of this script is its multi-symbol approach combined with complex conditions. By comparing not only one but four symbols simultaneously, it provides a broader market view and allows traders to correlate signals across different assets, offering a potential edge for diversified or comparative strategies. Additionally, the incorporation of ORB and multi-timeframe MAs gives it a robustness often lacking in simpler single-symbol scripts.
🚀 Conclusion:
This script is a powerful multi-indicator tool suited for traders looking for a comparative, multi-symbol analysis. With features like ORB, Bollinger Band-based trend detection, and MA cross-verification, it can assist traders in identifying and validating trend signals across assets. The user-friendly visualizations and customizable settings further enhance its usability, making it versatile for various trading strategies and preferences.
Price Action All In OneThis indicator represents the most advanced level of price action indicators, incorporating six useful features: traditional gaps, shadow gaps, bar counting, moving averages, previous values, and IO pattern matching .
When I refer to price action, I mean the teachings of Dr. Al Brooks.
While you can find these features in other indicators, mine is more advanced. The default settings are designed to work on a 5-minute timeframe, but you can also use this indicator on other time periods if you prefer.
Gaps
Traditional Gaps: Occurs when the lowest price of a bar is higher than the highest price of the previous bar, or the highest price of a bar is lower than the lowest price of the previous bar.
Shadow/Tail Gaps: Occurs when the lowest price of a bar is higher than the highest price of the second last bar, or the highest price of a bar is lower than the lowest price of the second last bar.
Gaps indicate strength, and consecutive gaps in one direction are characteristic of a strong trend. They offer a perspective on the strength of a trend, signifying that limit orders on one side are at a loss with no opportunity to exit at breakeven. Can bulls or bears create gaps? Are the gaps they create filled, or do they remain open?
Traditional Gaps & Shadow/Tail Gaps
Bar Counting
The ability to use different timeframes (e.g., to determine the minute within an hour or the hour within a week).
Consistent display of 1; in other indicators, if you set intervals to 2, you see 2, 4, 6, etc., or 1, 2, 4, 6. In my indicator, you will see 1, 3, 5, etc.
In intraday trading, certain specific times are more important than others. For example, a form of reversal is more likely to occur at the midpoint of the trading day (if there are 80 candles in a day, the midpoint is at the 40th candle).
This doesn't mean you should make reversal trades at the 40th candle. The bar count feature simply reminds you of the current time, helping you gauge how long until the trading day ends. For instance, if there are 80 candles in a day and you're an intraday trader, you probably shouldn't make a swing trade at the 70th candle because there are only 10 candles left until the close—likely not enough time for a swing to develop.
Additionally, if you trade on a 5-minute timeframe, seeing candles numbered 3, 6, 9, etc. indicates the close of a 15-minute candle. This means that in addition to 5-minute timeframe traders, 15-minute timeframe traders will also pay attention to these candles, making them more significant. For the same reason, the 12th candle is crucial, as its close also marks the close of an hourly candle.
Day Time Frame & Week Time Frame
Moving Averages
Provides three EMAs. You can set different timeframes and choose between continuous or discrete modes.
Moving averages are excellent tools for determining trends. The 20 EMA is particularly popular, which increases its significance. Traders using different timeframes, such as 5-minute, 15-minute, and 1-hour, all utilize the 20 EMA. This indicator allows you to see what traders on 15-minute and 1-hour timeframes are observing, even when you're on a 5-minute timeframe.
Once again, the default settings of this indicator assume that the user is trading intraday on a 5-minute timeframe. However, if that's not the case, you can easily adjust the moving average periods. For instance, if you trade on a 1-hour timeframe and want to display the 4-hour and daily moving averages on your chart, this can be done effortlessly.
5m 20, 15m 20 & 1h 20
Previous Values
Features three previous value displays. You can set their sources and timeframes independently and define the range for all previous values.
For intraday trading, marking the previous day's high, low, and close prices can be crucial. While some other indicators provide this feature, mine does it better. You can set different timeframes and choose various sources. For example, you might want to display the average of (O+H+L+C)/4 for the last week.
In addition to setting the timeframe and source, you can also configure the display range:
All: This will show the data in all positions. For example, you can see the high price from two days ago on yesterday's chart.
Today: This will only display the previous day's high price on the current day's chart.
Timeframe: This will display the data based on the specified timeframe you set.
Last Week High, Last Day Close & Low(Timeframe Display)
IO Pattern Matching
More advanced than other IO pattern matching indicators. For adjacent IIs, it merges to display as III, IIII, and so on. The same applies to OO patterns. Additionally, it automatically merges adjacent IOI and II into IOII, and adjacent OO and IOI into IIOI.
II Pattern: This refers to two consecutive inside bar candles. On a lower timeframe, the II pattern forms a converging triangle, which is a breakout pattern. The II pattern could also potentially become a final flag, which is the last flag in a trend.
OO Pattern: This refers to two consecutive outside bar candles. On a lower timeframe, the OO pattern forms an expanding triangle. You can use the OO pattern similarly to how you would use an expanding triangle.
IOI Pattern: This pattern occurs when the first candle is contained within the second candle, and the third candle is also contained within the second candle. This is a breakout pattern and could similarly represent a terminal flag in a trend.
The appearance of II, OO, or IOI patterns does not necessarily mean you should make a reversal trade. These patterns are meant to mark potential moves in a lower timeframe within the current cycle, providing a new perspective on the market and reminding you to stay vigilant.
You shouldn't look for IO patterns in a tight trading range. There are many IO patterns in a tight trading range, but they don't hold much significance.
II, OO & IOI
CPR by NKDCentral Pivot Range (CPR) Trading Strategy:
The Central Pivot Range (CPR) is a widely-used tool in technical analysis, helping traders pinpoint potential support and resistance levels in the market. By using the CPR effectively, traders can better gauge market trends and determine favorable entry and exit points. This guide explores how the CPR works, outlines its calculation, and describes how traders can enhance their strategies using an extended 10-line version of CPR.
What Really Central Pivot Range (CPR) is?
At its core, the CPR consists of three key lines:
Pivot Point (PP) – The central line, calculated as the average of the previous day’s high, low, and closing prices.
Upper Range (R1) – Positioned above the Pivot Point, acting as a potential ceiling where price may face resistance.
Lower Range (S1) – Found below the Pivot Point, serving as a potential floor where price might find support.
Advanced traders often expand on the traditional three-line CPR by adding extra levels above and below the pivot, creating up to a 10-line system. This extended CPR allows for a more nuanced understanding of the market and helps identify more detailed trading opportunities.
Applying CPR for Trading Success
1. How CPR is Calculation
The CPR relies on the previous day's high (H), low (L), and close (C) prices to create its structure:
Pivot Point (PP) = (H + L + C) / 3
First Resistance (R1) = (2 * PP) - L
First Support (S1) = (2 * PP) - H
Additional resistance levels (R2, R3) and support levels (S2, S3) are calculated by adding or subtracting multiples of the previous day’s price range (H - L) from the Pivot Point.
2. Recognizing the Market Trend
To effectively trade using CPR, it’s essential to first determine whether the market is trending up (bullish) or down (bearish). In an upward-trending market, traders focus on buying at support levels, while in a downward market, they look to sell near resistance.
3. Finding Ideal Entry Points
Traders often look to enter trades when price approaches key levels within the CPR range. Support levels (S1, S2) offer buying opportunities, while resistance levels (R1, R2) provide selling opportunities. These points are considered potential reversal zones, where price may bounce or reverse direction.
4. Managing Risk with Stop-Loss Orders
Proper risk management is crucial in any trading strategy. A stop-loss should be set slightly beyond the support level for buy positions and above the resistance level for sell positions, ensuring that losses are contained if the market moves against the trader’s position.
5. Determining Profit Targets
Profit targets are typically set based on the distance between entry points and the next support or resistance level. Many traders apply a risk-reward ratio, aiming for larger potential profits compared to the potential losses. However, if the next resistance and support level is far then middle levels are used for targets (i.e. 50% of R1 and R2)
6. Confirmation Through Other Indicators
While CPR provides strong support and resistance levels, traders often use additional indicators to confirm potential trade setups. Indicators such as moving averages can
help validate the signals provided by the CPR.
7. Monitoring Price Action At CPR Levels
Constantly monitoring price movement near CPR levels is essential. If the price fails to break through a resistance level (R1) or holds firm at support (S1), it can offer cues on when to exit or adjust a trade. However, a strong price break past these levels often signals a continued trend.
8. Trading Breakouts with CPR
When the price breaks above resistance or below support with strong momentum, it may signal a potential breakout. Traders can capitalize on these movements by entering positions in the direction of the breakout, ideally confirmed by volume or other technical indicators.
9. Adapting to Changing Market Conditions
CPR should be used in the context of broader market influences, such as economic reports, news events, or geopolitical shifts. These factors can dramatically affect market direction and how price reacts to CPR levels, making it important to stay informed about external market conditions.
10. Practice and Backtesting for Improvements
Like any trading tool, the CPR requires practice. Traders are encouraged to backtest their strategies on historical price data to get a better sense of how CPR works in different market environments. Continuous analysis and practice help improve decision-making and strategy refinement.
The Advantages of Using a 10-Line CPR System
An extended 10-line CPR system—comprising up to five resistance and five support levels—provides more granular control and insight into market movements. This expanded view helps traders better gauge trends and identify more opportunities for entry and exit. Key benefits include:
R2, S2 Levels: These act as secondary resistance or support zones, giving traders additional opportunities to refine their trade entries and exits.
R3, S3 Levels: Provide an even wider range for identifying reversals or trend continuations in more volatile markets.
Flexibility: The broader range of levels allows traders to adapt to changing market conditions and make more precise decisions based on market momentum.
So in Essential:
The Central Pivot Range is a valuable tool for traders looking to identify critical price levels in the market. By providing a clear framework for identifying potential support and resistance zones, it helps traders make informed decisions about entering and exiting trades. However, it’s important to combine CPR with sound risk management and additional confirmation through other technical indicators for the best results.
Although no trading tool guarantees success, the CPR, when used effectively and combined with practice, can significantly enhance a trader’s ability to navigate market fluctuations.
Advanced Economic Indicator by USCG_VetAdvanced Economic Indicator by USCG_Vet
tldr:
This comprehensive TradingView indicator combines multiple economic and financial metrics into a single, customizable composite index. By integrating key indicators such as the yield spread, commodity ratios, stock indices, and the Federal Reserve's QE/QT activities, it provides a holistic view of the economic landscape. Users can adjust the components and their weights to tailor the indicator to their analysis, aiding in forecasting economic conditions and market trends.
Detailed Description
Overview
The Advanced Economic Indicator is designed to provide traders and investors with a powerful tool to assess the overall economic environment. By aggregating a diverse set of economic indicators and financial market data into a single composite index, it helps identify potential turning points in the economy and financial markets.
Key Features:
Comprehensive Coverage: Includes 14 critical economic and financial indicators.
Customizable Components: Users can select which indicators to include.
Adjustable Weights: Assign weights to each component based on perceived significance.
Visual Signals: Clear plotting with threshold lines and background highlights.
Alerts: Set up alerts for when the composite index crosses user-defined thresholds.
Included Indicators
Yield Spread (10-Year Treasury Yield minus 3-Month Treasury Yield)
Copper/Gold Ratio
High Yield Spread (HYG/IEF Ratio)
Stock Market Performance (S&P 500 Index - SPX)
Bitcoin Performance (BLX)
Crude Oil Prices (CL1!)
Volatility Index (VIX)
U.S. Dollar Index (DXY)
Inflation Expectations (TIP ETF)
Consumer Confidence (XLY ETF)
Housing Market Index (XHB)
Manufacturing PMI (XLI ETF)
Unemployment Rate (Inverse SPY as Proxy)
Federal Reserve QE/QT Activities (Fed Balance Sheet - WALCL)
How to Use the Indicator
Configuring the Indicator:
Open Settings: Click on the gear icon (⚙️) next to the indicator's name.
Inputs Tab: You'll find a list of all components with checkboxes and weight inputs.
Including/Excluding Components
Checkboxes: Check or uncheck the box next to each component to include or exclude it from the composite index.
Default State: By default, all components are included.
Adjusting Component Weights:
Weight Inputs: Next to each component's checkbox is a weight input field.
Default Weights: Pre-assigned based on economic significance but fully adjustable.
Custom Weights: Enter your desired weight for each component to reflect your analysis.
Threshold Settings:
Bearish Threshold: Default is -1.0. Adjust to set the level below which the indicator signals potential economic downturns.
Bullish Threshold: Default is 1.0. Adjust to set the level above which the indicator signals potential economic upswings.
Setting the Timeframe:
Weekly Timeframe Recommended: Due to the inclusion of the Fed's balance sheet data (updated weekly), it's best to use this indicator on a weekly chart.
Changing Timeframe: Select 1W (weekly) from the timeframe options at the top of the chart.
Interpreting the Indicator:
Composite Index Line
Plot: The blue line represents the composite economic indicator.
Movement: Observe how the line moves relative to the threshold lines.
Threshold Lines
Zero Line (Gray Dotted): Indicates the neutral point.
Bearish Threshold (Red Dashed): Crossing below suggests potential economic weakness.
Bullish Threshold (Green Dashed): Crossing above suggests potential economic strength.
Background Highlights
Red Background: When the composite index is below the bearish threshold.
Green Background: When the composite index is above the bullish threshold.
No Color: When the composite index is between the thresholds.
Understanding the Components
1. Yield Spread
Description: The difference between the 10-year and 3-month U.S. Treasury yields.
Economic Significance: An inverted yield curve (negative spread) has historically preceded recessions.
2. Copper/Gold Ratio
Description: The price ratio of copper to gold.
Economic Significance: Copper is tied to industrial demand; gold is a safe-haven asset. The ratio indicates risk sentiment.
3. High Yield Spread (HYG/IEF Ratio)
Description: Ratio of high-yield corporate bonds (HYG) to intermediate-term Treasury bonds (IEF).
Economic Significance: Reflects investor appetite for risk; widening spreads can signal credit stress.
4. Stock Market Performance (SPX)
Description: S&P 500 Index levels.
Economic Significance: Broad measure of U.S. equity market performance.
5. Bitcoin Performance (BLX)
Description: Bitcoin Liquid Index price.
Economic Significance: Represents risk appetite in speculative assets.
6. Crude Oil Prices (CL1!)
Description: Front-month crude oil futures price.
Economic Significance: Influences inflation and consumer spending.
7. Volatility Index (VIX)
Description: Market's expectation of volatility (fear gauge).
Economic Significance: High VIX indicates market uncertainty; inverted in the indicator to align directionally.
8. U.S. Dollar Index (DXY)
Description: Value of the U.S. dollar relative to a basket of foreign currencies.
Economic Significance: Affects international trade and commodity prices; inverted in the indicator.
9. Inflation Expectations (TIP ETF)
Description: iShares TIPS Bond ETF prices.
Economic Significance: Reflects market expectations of inflation.
10. Consumer Confidence (XLY ETF)
Description: Consumer Discretionary Select Sector SPDR Fund prices.
Economic Significance: Proxy for consumer confidence and spending.
11. Housing Market Index (XHB)
Description: SPDR S&P Homebuilders ETF prices.
Economic Significance: Indicator of the housing market's health.
12. Manufacturing PMI (XLI ETF)
Description: Industrial Select Sector SPDR Fund prices.
Economic Significance: Proxy for manufacturing activity.
13. Unemployment Rate (Inverse SPY as Proxy)
Description: Inverse of the SPY ETF price.
Economic Significance: Represents unemployment trends; higher inverse SPY suggests higher unemployment.
14. Federal Reserve QE/QT Activities (Fed Balance Sheet - WALCL)
Description: Total assets held by the Federal Reserve.
Economic Significance: Indicates liquidity injections (QE) or withdrawals (QT); impacts interest rates and asset prices.
Customization and Advanced Usage
Adjusting Weights:
Purpose: Emphasize components you believe are more predictive or relevant.
Method: Increase or decrease the weight value next to each component.
Example: If you think the yield spread is particularly important, you might assign it a higher weight.
Disclaimer
This indicator is for educational and informational purposes only. It is not financial advice. Trading and investing involve risks, including possible loss of principal. Always conduct your own analysis and consult with a professional financial advisor before making investment decisions.
TPS Short Strategy by Larry ConnersThe TPS Short strategy aims to capitalize on extreme overbought conditions in an ETF by employing a scaling-in approach when certain technical indicators signal potential reversals. The strategy is designed to short the ETF when it is deemed overextended, based on the Relative Strength Index (RSI) and moving averages.
Components:
200-Day Simple Moving Average (SMA):
Purpose: Acts as a long-term trend filter. The ETF must be below its 200-day SMA to be eligible for shorting.
Rationale: The 200-day SMA is widely used to gauge the long-term trend of a security. When the price is below this moving average, it is often considered to be in a downtrend (Tushar S. Chande & Stanley Kroll, "The New Technical Trader: Boost Your Profit by Plugging Into the Latest Indicators").
2-Period RSI:
Purpose: Measures the speed and change of price movements to identify overbought conditions.
Criteria: Short 10% of the position when the 2-period RSI is above 75 for two consecutive days.
Rationale: A high RSI value (above 75) indicates that the ETF may be overbought, which could precede a price reversal (J. Welles Wilder, "New Concepts in Technical Trading Systems").
Scaling-In Mechanism:
Purpose: Gradually increase the short position as the ETF price rises beyond previous entry points.
Scaling Strategy:
20% more when the price is higher than the first entry.
30% more when the price is higher than the second entry.
40% more when the price is higher than the third entry.
Rationale: This incremental approach allows for an increased position size in a worsening trend, potentially increasing profitability if the trend continues to align with the strategy’s premise (Marty Schwartz, "Pit Bull: Lessons from Wall Street's Champion Day Trader").
Exit Conditions:
Criteria: Close all positions when the 2-period RSI drops below 30 or the 10-day SMA crosses above the 30-day SMA.
Rationale: A low RSI value (below 30) suggests that the ETF may be oversold and could be poised for a rebound, while the SMA crossover indicates a potential change in the trend (Martin J. Pring, "Technical Analysis Explained").
Risks and Considerations:
Market Risk:
The strategy assumes that the ETF will continue to decline once shorted. However, markets can be unpredictable, and price movements might not align with the strategy's expectations, especially in a volatile market (Nassim Nicholas Taleb, "The Black Swan: The Impact of the Highly Improbable").
Scaling Risks:
Scaling into a position as the price increases may increase exposure to adverse price movements. This method can amplify losses if the market moves against the position significantly before any reversal occurs.
Liquidity Risk:
Depending on the ETF’s liquidity, executing large trades in increments might affect the price and increase trading costs. It is crucial to ensure that the ETF has sufficient liquidity to handle large trades without significant slippage (James Altucher, "Trade Like a Hedge Fund").
Execution Risk:
The strategy relies on timely execution of trades based on specific conditions. Delays or errors in order execution can impact performance, especially in fast-moving markets.
Technical Indicator Limitations:
Technical indicators like RSI and SMA are based on historical data and may not always predict future price movements accurately. They can sometimes produce false signals, leading to potential losses if used in isolation (John Murphy, "Technical Analysis of the Financial Markets").
Conclusion
The TPS Short strategy utilizes a combination of long-term trend filtering, overbought conditions, and incremental shorting to potentially profit from price reversals. While the strategy has a structured approach and leverages well-known technical indicators, it is essential to be aware of the inherent risks, including market volatility, liquidity issues, and potential limitations of technical indicators. As with any trading strategy, thorough backtesting and risk management are crucial to its successful implementation.
Uptrick: RSI Histogram
1. **Introduction to the RSI and Moving Averages**
2. **Detailed Breakdown of the Uptrick: RSI Histogram**
3. **Calculation and Formula**
4. **Visual Representation**
5. **Customization and User Settings**
6. **Trading Strategies and Applications**
7. **Risk Management**
8. **Case Studies and Examples**
9. **Comparison with Other Indicators**
10. **Advanced Usage and Tips**
---
## 1. Introduction to the RSI and Moving Averages
### **1.1 Relative Strength Index (RSI)**
The Relative Strength Index (RSI) is a momentum oscillator developed by J. Welles Wilder and introduced in his 1978 book "New Concepts in Technical Trading Systems." It is widely used in technical analysis to measure the speed and change of price movements.
**Purpose of RSI:**
- **Identify Overbought/Oversold Conditions:** RSI values range from 0 to 100. Traditionally, values above 70 are considered overbought, while values below 30 are considered oversold. These thresholds help traders identify potential reversal points in the market.
- **Trend Strength Measurement:** RSI also indicates the strength of a trend. High RSI values suggest strong bullish momentum, while low values indicate bearish momentum.
**Calculation of RSI:**
1. **Calculate the Average Gain and Loss:** Over a specified period (e.g., 14 days), calculate the average gain and loss.
2. **Compute the Relative Strength (RS):** RS is the ratio of average gain to average loss.
3. **RSI Formula:** RSI = 100 - (100 / (1 + RS))
### **1.2 Moving Averages (MA)**
Moving Averages are used to smooth out price data and identify trends by filtering out short-term fluctuations. Two common types are:
**Simple Moving Average (SMA):** The average of prices over a specified number of periods.
**Exponential Moving Average (EMA):** A type of moving average that gives more weight to recent prices, making it more responsive to recent price changes.
**Smoothed Moving Average (SMA):** Used to reduce the impact of volatility and provide a clearer view of the underlying trend. The RMA, or Running Moving Average, used in the USH script is similar to an EMA but based on the average of RSI values.
## 2. Detailed Breakdown of the Uptrick: RSI Histogram
### **2.1 Indicator Overview**
The Uptrick: RSI Histogram (USH) is a technical analysis tool that combines the RSI with a moving average to create a histogram that reflects momentum and trend strength.
**Key Components:**
- **RSI Calculation:** Determines the relative strength of price movements.
- **Moving Average Application:** Smooths the RSI values to provide a clearer trend indication.
- **Histogram Plotting:** Visualizes the deviation of the smoothed RSI from a neutral level.
### **2.2 Indicator Purpose**
The primary purpose of the USH is to provide a clear visual representation of the market's momentum and trend strength. It helps traders identify:
- **Bullish and Bearish Trends:** By showing how far the smoothed RSI is from the neutral 50 level.
- **Potential Reversal Points:** By highlighting changes in momentum.
### **2.3 Indicator Design**
**RSI Moving Average (RSI MA):** The RSI MA is a smoothed version of the RSI, calculated using a running moving average. This smooths out short-term fluctuations and provides a clearer indication of the underlying trend.
**Histogram Calculation:**
- **Neutral Level:** The histogram is plotted relative to the neutral level of 50. This level represents a balanced market where neither bulls nor bears have dominance.
- **Histogram Values:** The histogram bars show the difference between the RSI MA and the neutral level. Positive values indicate bullish momentum, while negative values indicate bearish momentum.
## 3. Calculation and Formula
### **3.1 RSI Calculation**
The RSI calculation involves:
1. **Average Gain and Loss:** Calculated over the specified length (e.g., 14 periods).
2. **Relative Strength (RS):** RS = Average Gain / Average Loss.
3. **RSI Formula:** RSI = 100 - (100 / (1 + RS)).
### **3.2 Moving Average Calculation**
For the USH indicator, the RSI is smoothed using a running moving average (RMA). The RMA formula is similar to that of the EMA but is based on averaging RSI values over the specified length.
### **3.3 Histogram Calculation**
The histogram value is calculated as:
- **Histogram Value = RSI MA - 50**
**Plotting the Histogram:**
- **Positive Histogram Values:** Indicate that the RSI MA is above the neutral level, suggesting bullish momentum.
- **Negative Histogram Values:** Indicate that the RSI MA is below the neutral level, suggesting bearish momentum.
## 4. Visual Representation
### **4.1 Histogram Bars**
The histogram is plotted as bars on the chart:
- **Bullish Bars:** Colored green when the RSI MA is above 50.
- **Bearish Bars:** Colored red when the RSI MA is below 50.
### **4.2 Customization Options**
Traders can customize:
- **RSI Length:** Adjust the length of the RSI calculation to match their trading style.
- **Bull and Bear Colors:** Choose colors for histogram bars to enhance visual clarity.
### **4.3 Interpretation**
**Bullish Signal:** A histogram bar that moves from red to green indicates a potential shift to a bullish trend.
**Bearish Signal:** A histogram bar that moves from green to red indicates a potential shift to a bearish trend.
## 5. Customization and User Settings
### **5.1 Adjusting RSI Length**
The length parameter determines the number of periods over which the RSI is calculated and smoothed. Shorter lengths make the RSI more sensitive to price changes, while longer lengths provide a smoother view of trends.
### **5.2 Color Settings**
Traders can adjust:
- **Bull Color:** Color of histogram bars indicating bullish momentum.
- **Bear Color:** Color of histogram bars indicating bearish momentum.
**Customization Benefits:**
- **Visual Clarity:** Traders can choose colors that stand out against their chart’s background.
- **Personal Preference:** Adjust settings to match individual trading styles and preferences.
## 6. Trading Strategies and Applications
### **6.1 Trend Following**
**Identifying Entry Points:**
- **Bullish Entry:** When the histogram changes from red to green, it signals a potential entry point for long positions.
- **Bearish Entry:** When the histogram changes from green to red, it signals a potential entry point for short positions.
**Trend Confirmation:** The histogram helps confirm the strength of a trend. Strong, consistent green bars indicate robust bullish momentum, while strong, consistent red bars indicate robust bearish momentum.
### **6.2 Swing Trading**
**Momentum Analysis:**
- **Entry Signals:** Look for significant shifts in the histogram to time entries. A shift from bearish to bullish (red to green) indicates potential for upward movement.
- **Exit Signals:** A shift from bullish to bearish (green to red) suggests a potential weakening of the trend, signaling an exit or reversal point.
### **6.3 Range Trading**
**Market Conditions:**
- **Consolidation:** The histogram close to zero suggests a range-bound market. Traders can use this information to identify support and resistance levels.
- **Breakout Potential:** A significant move away from the neutral level may indicate a potential breakout from the range.
### **6.4 Risk Management**
**Stop-Loss Placement:**
- **Bullish Positions:** Place stop-loss orders below recent support levels when the histogram is green.
- **Bearish Positions:** Place stop-loss orders above recent resistance levels when the histogram is red.
**Position Sizing:** Adjust position sizes based on the strength of the histogram signals. Strong trends (indicated by larger histogram bars) may warrant larger positions, while weaker signals suggest smaller positions.
## 7. Risk Management
### **7.1 Importance of Risk Management**
Effective risk management is crucial for long-term trading success. It involves protecting capital, managing losses, and optimizing trade setups.
### **7.2 Using USH for Risk Management**
**Stop-Loss and Take-Profit Levels:**
- **Stop-Loss Orders:** Use the histogram to set stop-loss levels based on trend strength. For instance, place stops below support levels in bullish trends and above resistance levels in bearish trends.
- **Take-Profit Targets:** Adjust take-profit levels based on histogram changes. For example, lock in profits as the histogram starts to shift from green to red.
**Position Sizing:**
- **Trend Strength:** Scale position sizes based on the strength of histogram signals. Larger histogram bars indicate stronger trends, which may justify larger positions.
- **Volatility:** Consider market volatility and adjust position sizes to mitigate risk.
## 8. Case Studies and Examples
### **8.1 Example 1: Bullish Trend**
**Scenario:** A trader notices a transition from red to green histogram bars.
**Analysis:**
- **Entry Point:** The transition indicates a potential bullish trend. The trader decides to enter a long position.
- **Stop-Loss:** Set stop-loss below recent support levels.
- **Take-Profit:** Consider taking profits as the histogram moves back towards zero or turns red.
**Outcome:** The bullish trend continues, and the histogram remains green, providing a profitable trade setup.
### **8.2 Example 2: Bearish Trend**
**Scenario:** A trader observes a transition from green to red histogram bars.
**Analysis:**
- **Entry Point:** The transition suggests a potential
bearish trend. The trader decides to enter a short position.
- **Stop-Loss:** Set stop-loss above recent resistance levels.
- **Take-Profit:** Consider taking profits as the histogram approaches zero or shifts to green.
**Outcome:** The bearish trend continues, and the histogram remains red, resulting in a successful trade.
## 9. Comparison with Other Indicators
### **9.1 RSI vs. USH**
**RSI:** Measures momentum and identifies overbought/oversold conditions.
**USH:** Builds on RSI by incorporating a moving average and histogram to provide a clearer view of trend strength and momentum.
### **9.2 RSI vs. MACD**
**MACD (Moving Average Convergence Divergence):** A trend-following momentum indicator that uses moving averages to identify changes in trend direction.
**Comparison:**
- **USH:** Provides a smoothed RSI perspective and visual histogram for trend strength.
- **MACD:** Offers signals based on the convergence and divergence of moving averages.
### **9.3 RSI vs. Stochastic Oscillator**
**Stochastic Oscillator:** Measures the level of the closing price relative to the high-low range over a specified period.
**Comparison:**
- **USH:** Focuses on smoothed RSI values and histogram representation.
- **Stochastic Oscillator:** Provides overbought/oversold signals and potential reversals based on price levels.
## 10. Advanced Usage and Tips
### **10.1 Combining Indicators**
**Multi-Indicator Strategies:** Combine the USH with other technical indicators (e.g., Moving Averages, Bollinger Bands) for a comprehensive trading strategy.
**Confirmation Signals:** Use the USH to confirm signals from other indicators. For instance, a bullish histogram combined with a moving average crossover may provide a stronger buy signal.
### **10.2 Customization Tips**
**Adjust RSI Length:** Experiment with different RSI lengths to match various market conditions and trading styles.
**Color Preferences:** Choose histogram colors that enhance visibility and align with personal preferences.
### **10.3 Continuous Learning**
**Backtesting:** Regularly backtest the USH with historical data to refine strategies and improve accuracy.
**Education:** Stay updated with trading education and adapt strategies based on market changes and personal experiences.
Strategy SEMA SDI WebhookPurpose of the Code:
The strategy utilizes Exponential Moving Averages (EMA) and Smoothed Directional Indicators (SDI) to generate buy and sell signals. It includes features like leverage, take profit, stop loss, and trailing stops. The strategy is intended for backtesting and automating trades based on the specified indicators and conditions.
Key Components and Functionalities:
1.Strategy Settings:
Overlay: The strategy will overlay on the price chart.
Slippage: Set to 1.
Commission Value: Set to 0.035.
Default Quantity Type: Percent of equity.
Default Quantity Value: 50% of equity.
Initial Capital: Set to 1000 units.
Calculation on Order Fills: Enabled.
Process Orders on Close: Enabled.
2.Date and Time Filters:
Inputs for enabling/disabling start and end dates.
Filters to execute strategy only within specified date range.
3.Leverage and Quantity:
Leverage: Adjustable leverage input (default 3).
USD Percentage: Adjustable percentage of equity to use for trades (default 50%).
Initial Capital: Calculated based on leverage and percentage of equity.
4.Take Profit, Stop Loss, and Trailing Stop:
Inputs for enabling/disabling take profit, stop loss, and trailing stop.
Adjustable parameters for take profit percentage (default 25%), stop loss percentage (default 4.8%), and trailing stop percentage (default 1.9%).
Calculations for take profit, stop loss, trailing price, and maximum profit tracking.
5.EMA Calculations:
Fast and slow EMAs.
Smoothed versions of the fast and slow EMAs.
6.SDI Calculations:
Directional movement calculation for positive and negative directional indicators.
Difference between the positive and negative directional indicators, smoothed.
7.Buy/Sell Conditions:
Long (Buy) Condition: Positive DI is greater than negative DI, and fast EMA is greater than slow EMA.
Short (Sell) Condition: Negative DI is greater than positive DI, and fast EMA is less than slow EMA.
8.Strategy Execution:
If buy conditions are met, close any short positions and enter a long position.
If sell conditions are met, close any long positions and enter a short position.
Exit conditions for long and short positions based on take profit, stop loss, and trailing stop levels.
Close all positions if outside the specified date range.
Usage:
This strategy is used to automate trading based on the specified conditions involving EMAs and SDI. It allows backtesting to evaluate performance based on historical data. The strategy includes risk management through take profit, stop loss, and trailing stops to protect gains and limit losses. Traders can customize the parameters to fit their specific trading preferences and risk tolerance. Differently, it can perform leverage analysis and use it as a template.
By using this strategy, traders can systematically execute trades based on technical indicators, helping to remove emotional bias and improve consistency in trading decisions.
Important Note:
This script is provided for educational and template purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
Sessions Lite [TradingFinder] New York, London, Asia, NYSE Forex🔵 Introduction
A trading session is one of the basic concepts in the financial market that refers to specific time periods. In fact, a session means hours during the day and night, during which traders in a certain part of the world conduct their transactions.
Although the "Forex" and "CFDs" market is open 24 hours a day and it is possible to trade in it, but in some hours the activity in this market decreases so much that many traders prefer not to trade and only watch the market. On the other hand, there are specific times when the market is very busy and dynamic, and many traders tend to trade during these hours of the day and night.
Trading sessions are usually divided into three main categories, which are "Asian", "European" and "North American" sessions. These trading sessions are also called the "Tokyo", "London" and "New York" sessions, respectively. But they also categorized these sessions in more detailed ways such as "Sydney session", "Shanghai session" or "NYSE session".
🔵 Tokyo trading session (Asian session)
After the weekend that happens on Saturday and Sunday, the Forex market starts with the Asian session. In this continent, most of the transactions are done in the Tokyo session, and for this reason, it is usually called the Asian session or the Tokyo session. However, other countries such as Australia, China and Singapore also do a lot of trading in this session.
The Tokyo session has a lower volume of transactions compared to the London and New York sessions, and therefore the liquidity is lower. In this session, most of the Forex currency pairs move in a price range. For this reason, different people use the ups and downs with the trading strategy in the range and get profit.
The low liquidity of the Tokyo session means that trading spreads are also higher during these hours. Besides, most of the transactions of this session are done in the early hours and at the same time as the planned news release.
In the Tokyo or Asia session, the best currency pairs to trade are the "Japanese yen", the "Australian dollar", and the "New Zealand dollar".
"Nikkei" index is also a good option for trading. If you trade in the Tokyo session, you should also be aware of the release of economic news and data from Australian, New Zealand and Japanese financial institutions.
🔵 London trading session (European session)
After the Asian session, it is time for the European session. In this period of time, transactions are very large and many European markets are involved. However, the European session is usually known as the London session.
Because of its specific time zone, London is not only known as the Forex trading center in Europe, but it is also known as the Forex trading center in the world. The London session overlaps with two other major trading sessions in the world, Asia and America. This means that most of the Forex transactions are done in this session. According to the latest statistics, 32% of Forex transactions are related to the London session, which shows that about a third of the activity performed in Forex takes place during this period.
This will increase the volume of Forex transactions and increase liquidity. An event that causes the spread of transactions to decrease. Of course, high liquidity also leads to greater volatility, which is desirable for many traders.
In the European session, the pound and euro currencies and the "DAX", "FTSE100", and "CAC40" indices are known as the best tradable assets. Also, traders of this session should pay attention to the news and data published by the "European Central Bank" and the "Bank of England". The news of countries like Germany, France and Italy are also very important.
🔵 American trading session (New York session)
When the New York session begins, several hours have passed since the end of the Tokyo session, but the European session is in the middle. In this session, they usually affect the financial activities carried out in America, but they also affect other countries such as Canada, Mexico and several South American countries.
The "US dollar" and stock indices such as "S&P", "Dow Jones" and "Nasdaq" are the most important assets that are traded in this session.
The early hours of the American session have a lot of liquidity and volatility due to the overlap with the European session, but with the end of the European session, the activity in the American session also decreases.
You can trade all major Forex currency pairs in the New York trading session. In this session, the "Federal Reserve", as the most important central bank in the world, is the institution that you should pay attention to its news and data.
The trading session indicator is an analytical tool in the financial markets that is used to display and analyze specific trading periods during a day. These indicators are generally useful for determining support and resistance levels during any trading session and for detecting different trading patterns.
For example, usually these indicators display the open and close price levels, the highest and lowest prices during a trading session. Also, you may notice various price patterns such as price channels, price phase phases and market trend changes during different trading sessions using these indicators.
🔵 cause of construction
In particular, the session light indicator version is designed and built for those traders who use many different tools on their chart at the same time. These traders can include "Volume Traders", "ICT traders", "Day Traders" and... These individuals can use "Session Lite" without disturbing the display of their other trading tools such as "Order Blocks", "Liquidity", "Zigzag", "FVG" etc.
But in general, there are several reasons for making tools like trading session indicators in financial markets, some of which include the following :
1. Analysis of specific time frames : Some traders and investors like to consider specific time frames for price analysis and review. For example, analyzing price changes during each trading session can help analyze trading patterns and identify trading opportunities.
2. Recognize different price patterns : Different price patterns may be observed during trading sessions. Trading session indicators can help to make better trading decisions by analyzing these patterns and their strengths and weaknesses.
3. Identifying Support and Resistance Levels : These tools may help to identify support and resistance levels during any trading session which can be helpful in deciding whether to enter or exit the market.
🔵 How to use
The Session Lite indicator displays 8 sessions by default. Asia session, Sydney session, Tokyo session, Shanghai session, Europe session, London session, New York session and New York Stock Exchange (NYSE) session are the sessions that are displayed.
You can activate or deactivate the display of each session by using the tick button next to the name of each session.
Two gray vertical dashes are also displayed by default, which indicate the beginning of the European session and the New York session. This feature is available for all sessions, but it is enabled by default only for these two sessions, and you can activate it for the rest of the session. You can enable or disable the display of this line by using the Start Session tick key.
Likewise, the information table is displayed by default, which includes the open or closed information of each session and the start and end times of each session. These timings are based on the UTC time zone.
Accordingly, the schedule of trading sessions is as follows :
Asia session from 23:00 to 06:00
Sydney session from 23:00 to 05:00
Tokyo session from 00:00 to 00:06
Shanghai session from 01:30 to 06:57
European session from 07:00 to 16:30
London session from 08:00 to 16:30
New York session from 13:00 to 22:00
New York Stock Exchange (NYSE) session from 14:30 to T 22:00
Important note : the beginning of the European session coincides with the opening of the Frankfurt market.
🔵 Settings
• In the settings section, there are customization capabilities according to the type of use of each user. The settings related to showing or not showing the box of each session, the start indicator of each session, setting the start and end time of the session and choosing the desired color to display each session are among the things that can be set from this section.
• At the end of the settings, you will see the "Info Table" option; By disabling this option, the "sessions" clock table displayed on the upper right side will be disabled.
RSI Missmatch(Divergence) OSC. by Neo_ with Missmatch Alert█ Definition
A divergence or missmatch occurs when an asset’s price is moving opposite to a specific technical indicator or is moving in a different direction from other relevant data. The divergence indicator warns traders and technical analysts of changes in a price trend, oftentimes that it is weakening or changing direction.
Divergence or missmatch can be either positive, signifying the possibility of a move that is higher in the asset’s price, or it can be negative, signifying the possibility of a move that is lower in the asset’s price.
█ Takeaways
Divergence or missmatch often works with other indicators and data. It is usually used by technical analysts and traders when the asset’s price is moving counter to the direction of another indicator.
As mentioned above, positive divergence or missmatch indicates that the price could start rising and usually occurs when the price is moving lower, but while another indicator counters this direction by moving higher. In other words, showing bullish signals.
Negative divergence or missmatch indicates that the price could start declining and usually occurs when the price is moving higher, while another indicator moves lower as well. In other words, showing bearish signals.
█ What to look for
Divergence or missmatch is most often used to track and analyze the momentum in an asset’s price and the odds of a price reversal within the current trend. While using divergence, traders and analysts can decide on whether or not they would like to exit the position or set a stop loss in the case the divergence is negative and prices begin to fall.
█ Limitations
It is best to use divergence or missmatch with the aid of other indicators and analysis tools in order to help identify and confirm trend reversals and major market patterns. Divergence should not be relied on by itself to tell you the pertinent information you need to know as an investor. Risk control is key in your analysis and the fact that divergence is not always present in price reversals should definitely be what pushes you to combine it with other tools and indicators.
Additionally, divergence or missmatch can reflect long-term or short-term changes. When making snap decisions, acting on divergence alone could prove detrimental to your trading. Make sure you have other risk factors applied to your charting and general market analysis.
█ What exactly is RSI Missmatches discrepancies using a lookback period in trading?
In trading, lookback period is the number of periods of historical data used for observation and calculation. It is how far into the past the system looks when trying to calculate the variable under consideration. The concept was based on the fact that history can provide information about the future, and my aim was to predict the periods when trend changes would begin within these periods with the RSI oscillator. But this is only true if you're locked back far enough, not locked any further or less!
We already use the idea of looking back in different aspects of our lives, and even in the world of financial trading it can be used in various ways. Of course you will want to learn more about the concept, so in this article we will cover the following topics:
█ What kind of hindsight is this?
The aim here is to check whether trends will change in certain cycles, so we chose the High + Low / 2 formula as the source. Because no matter how much the prices swing up or down, sometimes the rebound can go further. The aim here is to notice the points where the price leaves a needle at the levels where it oscillates and the slowdown in momentum.
█ What does look-back period mean in trade?
To understand what a lookback period means in trading, you need to ask yourself: What is a lookback period in trading? In financial trading, period refers to the duration of a particular trading session. For example, a one-week period means one full week of trading sessions or five trading days. In 5 trading days, the average time is 120 hours in FX markets and 40 hours in stock markets. Regardless of what happens in these cycles, I prefer to choose a time period of 55 periods. Because I noticed that in all the charts I examined, the cycles generally changed during this time period.
█ Let's talk about the meaning of catching Missmatches
As you know, technical indicators are all a mathematical calculation using historical market data (price, volume, or a combination of both). It shows the behavior of the price better and helps in the analysis of price movement. But the indicator can only serve your intended purpose if you get the lookback time right. What we mean here is the setting parameter that determines how much historical data it will use in its calculation. In other words, it is the retrospective review period.
For example, on the RSI indicator you can set this period to 13 periods (default setting) or even 2 periods. The period you choose can determine what the indicator tells you, which in turn determines the strategy you can create with the indicator. The 13- period RSI gives you information about price momentum, so you can effectively use it to create a momentum strategy. On the other hand, the 2-periods RSI can be used to create a mean reversion strategy. To catch any incompatibilities, I set this period to 55 periods. Nothing more, nothing less!
█ Summary
The missmatch indicator helps traders assess changes in the price trend and indicates when price will move with or against the direction of another indicator. It can be either positive or negative, but it is important to note its limitations and that it should be used with other indicators that can also monitor price trends.
We wish you to identify these incompatibilities in the market in the best way possible... Good luck.
█ Tanım
Bir varlığın fiyatı belirli bir teknik göstergenin tersi yönünde hareket ettiğinde veya diğer ilgili verilerden farklı bir yönde hareket ettiğinde bir sapma veya uyumsuzluk meydana gelir. Farklılık göstergesi, tüccarları ve teknik analistleri fiyat eğilimindeki değişiklikler konusunda uyarır; çoğu zaman zayıflıyor veya yön değiştiriyor.
Farklılık veya uyumsuzluk, varlığın fiyatında daha yüksek bir hareket olasılığını işaret ederek pozitif olabilir veya varlığın fiyatında daha düşük bir hareket olasılığını işaret ederek negatif olabilir.
█ Çıkarımlar
Farklılık veya uyumsuzluk çoğu zaman diğer göstergeler ve verilerle de çalışır. Genellikle teknik analistler ve yatırımcılar tarafından varlığın fiyatı başka bir göstergenin yönünün tersine hareket ettiğinde kullanılır.
Yukarıda bahsedildiği gibi pozitif sapma veya uyumsuzluk, fiyatın yükselmeye başlayabileceğini gösterir ve genellikle fiyat düşerken meydana gelir, ancak başka bir gösterge bu yöne yükselerek karşı koyar. Başka bir deyişle yükseliş sinyalleri veriyor.
Negatif sapma veya uyumsuzluk, fiyatın düşmeye başlayabileceğini gösterir ve genellikle fiyat yükselirken başka bir gösterge de düşerken meydana gelir. Başka bir deyişle düşüş sinyalleri veriyor.
█ Nelere bakılmalı
Farklılık veya uyumsuzluk çoğunlukla bir varlığın fiyatındaki momentumu ve mevcut trend içinde fiyatın tersine dönme olasılığını izlemek ve analiz etmek için kullanılır. Farklılaşmayı kullanırken tüccarlar ve analistler, sapmanın negatif olması ve fiyatların düşmeye başlaması durumunda pozisyondan çıkmak isteyip istemeyeceklerine veya zararı durdurma kararı verip veremeyeceklerine karar verebilirler.
█ Sınırlamalar
Trend dönüşlerini ve ana piyasa modellerini tanımlamaya ve doğrulamaya yardımcı olmak için diğer göstergeler ve analiz araçlarının yardımıyla sapmayı veya uyumsuzluğu kullanmak en iyisidir. Bir yatırımcı olarak bilmeniz gereken ilgili bilgileri size söylemesi için farklılığa tek başına güvenilmemelidir. Risk kontrolü analizinizin anahtarıdır ve fiyat dönüşlerinde farklılığın her zaman mevcut olmaması gerçeği kesinlikle sizi onu diğer araç ve göstergelerle birleştirmeye iten şey olmalıdır.
Ek olarak, farklılık veya uyumsuzluk uzun vadeli veya kısa vadeli değişiklikleri yansıtabilir. Ani kararlar verirken yalnızca farklılıklara göre hareket etmek ticaretinize zarar verebilir. Grafiğinize ve genel piyasa analizinize başka risk faktörlerinin uygulandığından emin olun.
█ Ticarette yeniden inceleme dönemi kullanan RSI Missmatches tutarsızlıkları tam olarak nedir?
Ticarette yeniden inceleme süresi, gözlem ve hesaplama için kullanılan geçmiş verilerin dönemlerinin sayısıdır. Söz konusu değişkeni hesaplamaya çalışırken sistemin ne kadar geçmişe baktığıdır. Konsept tarihin geleceğe dair bilgi verebileceği gerçeği üzerine kuruluydu ve amacım RSI osilatörü ile bu dönemler içerisinde trend değişimlerinin başlayacağı dönemleri tahmin etmekti. Ancak bu yalnızca yeterince geriye kilitlenmişseniz geçerlidir, daha fazla veya daha az kilitlenmemişseniz!
Geriye bakma fikrini hayatımızın farklı yönlerinde zaten kullanıyoruz ve hatta finansal ticaret dünyasında bile bu fikir çeşitli şekillerde kullanılabilir. Elbette konsept hakkında daha fazla bilgi edinmek isteyeceksiniz, bu nedenle bu yazıda aşağıdaki konuları ele alacağız:
█ Bu nasıl bir sonradan görmedir?
Burada amaç belli döngülerde trendlerin değişip değişmeyeceğini kontrol etmek olduğundan kaynak olarak Yüksek + Düşük / 2 formülünü seçtik. Çünkü fiyatlar ne kadar yukarı veya aşağı hareket ederse etsin bazen toparlanma daha da ileri gidebiliyor. Burada amaç fiyatın salınım yaptığı seviyelerde iğne bıraktığı noktaları ve momentumdaki yavaşlamayı fark etmektir.
█ Ticarette geriye bakma süresi ne anlama geliyor?
Ticarette yeniden inceleme süresinin ne anlama geldiğini anlamak için kendinize şu soruyu sormanız gerekir: Ticarette yeniden inceleme süresi nedir? Finansal ticarette dönem, belirli bir ticaret seansının süresini ifade eder. Örneğin, bir haftalık dönem, bir tam haftalık işlem seansı veya beş işlem günü anlamına gelir. 5 işlem gününde ortalama süre döviz piyasalarında 120 saat, borsalarda ise 40 saattir. Bu döngülerde ne olursa olsun 55 periyotluk bir zaman dilimini seçmeyi tercih ediyorum. Çünkü incelediğim tüm grafiklerde bu zaman diliminde döngülerin genel olarak değiştiğini fark ettim.
█ Kaçak Eşleşmeleri yakalamanın anlamı hakkında konuşalım
Bildiğiniz gibi teknik göstergeler, geçmiş piyasa verileri (fiyat, hacim veya her ikisinin birleşimi) kullanılarak yapılan matematiksel hesaplamalardır. Fiyatın davranışını daha iyi gösterir ve fiyat hareketinin analizine yardımcı olur. Ancak gösterge yalnızca yeniden inceleme süresini doğru yaparsanız amacınıza hizmet edebilir. Burada kast ettiğimiz, hesaplamasında ne kadar geçmiş veri kullanacağını belirleyen ayar parametresidir. Bir başka deyişle geriye dönük inceleme dönemidir.
Örneğin RSI göstergesinde bu süreyi 13 döneme (varsayılan ayar) ve hatta 2 döneme ayarlayabilirsiniz. Seçeceğiniz dönem, göstergenin size ne söyleyeceğini belirleyebilir ve bu da gösterge ile oluşturabileceğiniz stratejiyi belirler. 13 dönemlik RSI size fiyat momentumu hakkında bilgi verir, böylece onu bir momentum stratejisi oluşturmak için etkili bir şekilde kullanabilirsiniz. Öte yandan, ortalamaya dönüş stratejisi oluşturmak için 2 dönemlik RSI kullanılabilir. Herhangi bir uyumsuzluğu yakalamak için bu periyodu 55 periyoda ayarladım. Ne fazla ne eksik!
█ Özet
Uyumsuzluk göstergesi, yatırımcıların fiyat eğilimindeki değişiklikleri değerlendirmesine yardımcı olur ve fiyatın ne zaman başka bir göstergenin yönüne göre veya ona karşı hareket edeceğini gösterir. Olumlu ya da olumsuz olabilir, ancak sınırlamalarına dikkat etmek ve fiyat eğilimlerini de izleyebilecek diğer göstergelerle birlikte kullanılması gerektiğini unutmamak önemlidir.
Piyasadaki bu uyumsuzlukları en iyi şekilde tespit etmenizi dileriz... Bol Kazançlar.
RSI/MFI Selling Sentiment IndexPsychological Sales Index (Psychological Sales Index)
Fundamental Indicators of Market Sentiment: The Importance of MFI and RSI
The two fundamental indicators that best reflect market sentiment are Money Flow Index (MFI) and Relative Strength Index (RSI). MFI is an indicator of the flow of funds in a market by combining price and volume, which is used to determine whether a stock is over-bought or over-selling. RSI is an indicator of the overheating of the market by measuring the rise and fall of prices, which is applied to the analysis of the relative strength of stock prices. These two indicators allow a quantitative assessment of the market's buying and selling pressure, which provides important information to understand the psychological state of market participants.
Using timing and fundamental metrics
In order to grasp the effective timing of the sale, in-depth consideration was needed on how to use basic indicators. MFI and RSI represent the buying and selling pressures of the market, respectively, but there is a limit to reflecting the overall trend of the market alone. As a result, a study on how to capture more accurate selling points was conducted by comprehensively considering technical analysis along with psychological factors of the market.
The importance of ADX integration and weighting
The "Average Regional Index (ADX)" was missing in the early version. ADX is an indicator of the strength of a trend, and has experienced a problem of less accuracy in selling sentiment indicators, especially in the upward trend. To address this, we incorporated ADX and adopted a method of adjusting the weights of MFI and RSI according to the values of ADX. A high ADX value implies the existence of a strong trend, in which case it is appropriate to reduce the influence of MFI and RSI to give more importance to the strength of the trend. Conversely, a low ADX value increases the influence of MFI and RSI, putting more weight on the psychological elements of the market.
How to use and interpret
The user can adjust several parameters. Key inputs include 'Length', 'Overbought Threshold', 'DI Length', and 'ADX Smoothing'. These parameters are used to set the calculation period, overselling threshold, DI length, and ADX smoothing period of the indicator, respectively. The script calculates the psychological selling index based on MFI, RSI, and ADX. The calculated index is normalized to values between 0 and 100 and is displayed in the graph. Values above 'Overbought Threshold' indicate an overselling state, which can be interpreted as a potential selling signal. This index allows investors to comprehensively evaluate the psychological state of the market and the strength of trends, which can be used to make more accurate selling decisions.
Educational Inidicators - Ichimoku CloudThis indicator is part of the Indicator Educational Series, intended to help newer traders understand and interact with various indicators. The goal is to allow users to gain a stronger understanding of an indicator's underlying philosophy, and visually see how changes to an indicator's parameters affects the trades suggested by that indicator.
The scripts in this series are all open source, with the code broken up into logical section and notated so beginner users can also understand some PineScript fundamentals.
Please understand that no indicator presented in and of itself constitutes a complete trading strategy. Rather, this series is to help users determine which indicators make sense to them, and which ones to combine to create their own trading strategy. All material presented is purely for educational purposes.
Presented here is the Ichimoku Cloud.
The Ichimoku Cloud was developed by Goichi Hosada, and first published in the late 1960s. It is used by traders to understand price momentum, and help forecast future price movements.
The indicator at its core can be understood from four component parts:
The Conversion Line - An average of the highest and lowest price in a given window. Typically, this is a "fast" average, and as such, this line has the lowest period
The Base Line - An average of the highest and lowest price in a given window. This is a "slower" average than the Conversion Line, and as such should have a larger period than the Conversion Line
Leading Span A - The average of the Conversion Line and the Base Line
[*}Leading Span B - An average of the highest and lowest price in a given window. This is the "slowest" average of all three, and as such should have the largest period
When plotted, the Conversion Line (orange by default), Base Line (purple by default), Leading Span A (blue by default), and Leading Span B (red by defaults) are all drawn on the chart along with the price candles. The area between the Leading Span A and Leading Span B lines are also shaded depending on which of the two lines is greater: whenever Leading Span A is greater the area is shaded positively (blue by default), whenever Leading Span B is greater the area is shaded negatively (red by defaults).
One interesting feature of the Ichimoku Cloud is that it drawn a certain number of candles forward. What this means is that where the cloud is drawn on the chart is reflective of prices that have occurred a number of candles in the past. This is done intentionally to help traders see how the current price is moving in relation to historical price movements on the asset.
See below for how the indicators look in their default colors on the chart
These indicators can then be used to start analyzing the price movement, and making trade decisions.
The first inference we can make is the momentum of the price. Since the lines are drawn from averages of varying speeds, the shaded area between the Leading Span lines can tell us whether the momentum is bullish (up) or bearish (down).
Whenever Leading Span A, the faster of the two lines, is above Leading Span B, that means that price is moving upward faster than it typically has, ergo we are in Bullish Momentum. On the chart, this is indicated in two ways:
The area is shaded positively (blue by default)
A green upward triangle is added to the chart to indicate where the momentum first turned Bullish
Whenever Leading Span A is below Leading Span B, that means that price is moving downward faster than it typically has, ergo we are in Bearish Momentum. On the chart, this is indicated in two ways:
The area is shaded negatively (red by default)
A red downward triangle is added to the chart to indicate where the momentum first turned Bearish
The next inference we can make is possible trading points. When we're in a period of momentum, as determined above, we know that price is going up or down, depending on the momentum we're in. We can then use the Conversion Line, Base Line, and the Price itself to confirm a good trade price.
When the asset is in Bullish Momentum, and the Conversion Line, our fastest average, is above the Base Line, our mid speed average, we know that the price is coming up quickly in the short term. When the Base Line and current Price are also above the cloud, then we have triple confirmation that price is going up, and we should enter a Long position. On the chart, this point is indicated with a green flag.
When the asset is in Bearish Momentum, and the Conversion Line is below the Base Line, we know that the price is going down quickly in the short term. When the Base Line and current Price are also below the cloud, then we have triple confirmation that price is going down, and we should enter a Short position. On the chart, this point is indicated with a red flag.
The script presented here also allows users to customize the various parameters of the Ichimoku Cloud, and visually see how analysis is affected by these changes. This is designed to allow users to modify parameters as they see fit, within certain constraints, to find the best set for them. The lines, cloud, and chart indicators will all update automatically with the users' inputs.
RSI-CCI Fusion StrategyRSI-CCI Fusion Strategy: Harnessing the Power of RSI and CCI
The "RSI-CCI Fusion Strategy" is a powerful trading approach that combines the strengths of the Relative Strength Index (RSI) and the Commodity Channel Index (CCI) to provide enhanced trading insights. This strategy is based on the popular "RSI & CCI Fusion + Alerts" indicator, which utilizes the RSI and CCI indicators from TradingView .
1. Overview of RSI and CCI:
The Relative Strength Index (RSI) is a widely used momentum oscillator that measures the speed and change of price movements. It helps traders identify overbought and oversold conditions in the market. On the other hand, the Commodity Channel Index (CCI) is a versatile indicator that identifies cyclical trends and provides insights into overbought and oversold levels.
2. The RSI-CCI Fusion Strategy:
The RSI-CCI Fusion Strategy harnesses the combined power of the RSI and CCI indicators to generate robust trading signals. By blending the RSI and CCI, this strategy captures both momentum and cyclical trend dynamics, offering a more comprehensive view of the market.
3. Utilizing the RSI-CCI Fusion Indicator + Alerts:
The "RSI & CCI Fusion + Alerts" indicator serves as the backbone of the RSI-CCI Fusion Strategy. It integrates the RSI and CCI indicators from TradingView, providing traders with a clear and actionable trading signal.
4. How it Works:
- The indicator calculates the RSI and CCI values, standardizes them using z-score, and combines them with a weighted fusion approach.
- The resulting RSI-CCI Fusion indicator is plotted on the chart, accompanied by dynamic upper and lower bands, which help identify potential overbought and oversold conditions.
- Traders can customize alerts based on their preferred thresholds and timeframes, enabling them to receive timely notifications for potential buy and sell signals.
5. Implementing the RSI-CCI Fusion Strategy:
Traders following the RSI-CCI Fusion Strategy can utilize the buy and sell signals generated by the RSI-CCI Fusion indicator. When the indicator crosses below the upper band, it may signal a potential selling opportunity. Conversely, when it crosses above the lower band, it may indicate a potential buying opportunity. Traders can also consider additional factors and technical analysis tools to validate the signals before making trading decisions.
Conclusion: The RSI-CCI Fusion Strategy provides traders with a robust approach to analyze the market and make well-informed trading decisions. By incorporating the RSI and CCI indicators through the "RSI & CCI Fusion + Alerts" indicator, traders can take advantage of the combined strengths of these indicators. However, it is important to remember that no strategy guarantees success, and traders should always practice risk management and conduct thorough analysis before executing trades using this strategy.
Disclaimer: Trading involves risks, and it is important to conduct your own research and consult with a financial advisor before making any investment decisions.
Note: The RSI-CCI Fusion Strategy serves as a general guide, and individual traders may have different preferences and trading styles.
