The Reverse Cutlers (RCRSI) OC is an indicator which tells the user what price is required to give a particular Cutlers ( ) value, or cross its Moving Average (MA) signal line.
Background & Credits:
The ( ) is a used in that was originally developed by J. Welles Wilder Jr. and introduced in his seminal 1978 book, “New Concepts in Technical Trading Systems.”.
Cutler created a variation of the known as “Cutlers RSI” using a different formulation to avoid an inherent accuracy problem which arises when using Wilders method of smoothing.
Further developments in the use, and more nuanced interpretations of the have been developed by Cardwell, and also by well-known chartered market technician, Constance Brown C.M.T., in her acclaimed book "Technical Analysis for the Trading Professional” 1999 where she described the idea of bull and bear market ranges for , and while she did not actually reveal the formulas, she introduced the concept of “reverse engineering” the to give price level outputs.
Renowned financial software developer, co-author of academic books on finance, and scientific fellow to the Department of Finance and Insurance at the Technological Educational Institute of Crete, Giorgos Siligardos PHD . brought a new perspective to Wilder’s when he published his excellent and well-received articles "Reverse Engineering " and "Reverse Engineering II " in the June 2003, and August 2003 issues of Stocks & magazine, where he described his methods of reverse engineering Wilders .
Several excellent Implementations of the Reverse Wilders have been published here on Tradingview and elsewhere.
My utmost respect, and all due credits to authors of related prior works.
It is worth noting that while the general formula, and the logic dictating the UpMove and DownMove data series has remained the same as the Wilders original formulation, it has been interpreted in a different way by using a different method of averaging the upward, and downward moves.
Cutler recognized the issue of data length dependency when using wilders smoothing method of calculating which means that wilders standard will have a potential initialization error which reduces with every new data point calculated meaning early results should be regarded as unreliable until enough calculation iterations have occurred for convergence.
Hence Cutler proposed using Simple Moving Averaging for gain and loss data which this Indicator is based on.
Having "Reverse engineered" prices for any oscillator makes the planning, and execution of strategies around that oscillator far simpler, more timely and effective.
Introducing the Reverse Cutlers which consists of plotted lines on a scale of 0 to 100, and an optional infobox.
The scale is divided into zones:
• Scale high (100)
• Bull critical zone (80 - 100)
• Bull control zone (62 - 80)
• Scale midline (50)
• Bear control zone (20 - 38)
• Bear critical zone (0 - 20)
• Scale low (0)
The plots which graphically display output closing price levels where Cutlers value will crossover:
• (eq) (previous value)
• MA signal line
• Test price
• Alert level high
• Alert level low
The info box displays output closing price levels where Cutlers value will crossover:
• Its previous value. ( )
• Bull critical zone.
• Bull control zone.
• Bear control zone.
• Bear critical zone.
• MA signal line
• Alert level High
• Alert level low
And also displays the resultant for a user defined closing price:
• Test price
The infobox outputs can be shown for the current bar close, or the next bar close.
The user can easily select which information they want in the infobox from the setttings
All info box price levels for the current bar are calculated immediately upon the current bar closing and a new bar opening, they will not change until the current bar closes.
All info box price levels for the next bar are projections which are continually recalculated as the current price changes, and therefore fluctuate as the current price changes.
At its simplest the is a measure of how quickly traders are bidding the price of an asset up or down.
It does this by calculating the difference in magnitude of price gains and losses over a specific lookback period to evaluate market conditions.
The is displayed as an oscillator (a line graph that can move between two extremes) and outputs a value limited between 0 and 100.
It is typically accompanied by a moving average signal line.
Overbought and oversold:
An value of 70 or above indicates that an asset is becoming overbought (overvalued condition), and may be may be ready for a trend reversal or corrective pullback in price.
An value of 30 or below indicates that an asset is becoming oversold (undervalued condition), and may be may be primed for a trend reversal or corrective pullback in price.
When the crosses above its midline ( > 50%) a bias signal is generated. (only take long trades)
When the crosses below its midline ( < 50%) a bias signal is generated. (only take short trades)
and moving average signal Line crossovers:
When the line crosses above its signal line, a buy signal is generated
When the line crosses below its signal line, a sell signal is generated.
Swing Failures and classic rejection patterns:
If the makes a lower high, and then follows with a downside move below the previous low, a Top Swing Failure has occurred.
If the makes a higher low, and then follows with an upside move above the previous high, a Bottom Swing Failure has occurred.
Examples of classic swing rejection patterns
swing rejection pattern:
The moves into oversold zone (below 30%).
The rejects back out of the oversold zone (above 30%)
The forms another dip without crossing back into oversold zone.
The then continues the bounce to break up above the previous high.
swing rejection pattern:
The moves into overbought zone (above 70%).
The rejects back out of the overbought zone (below 70%)
The forms another peak without crossing back into overbought zone.
The then continues to break down below the previous low.
A regular divergence is when the price makes lower lows in a downtrend and the indicator makes higher lows.
A regular divergence is when the price makes higher highs in an uptrend and the indicator makes lower highs.
A is when the price makes higher lows in an uptrend and the indicator makes lower lows.
A is when the price makes lower highs in a downtrend and the indicator makes higher highs.
Regular divergences can signal a reversal of the trending direction.
Hidden divergences can signal a continuation in the direction of the trend.
regularly forms classic chart patterns that may not show on the underlying price chart, such as ascending and descending triangles & , double tops, bottoms and etc.
Support and Resistance:
It is very often easier to define support or resistance levels on the itself rather than the price chart.
Modern interpretations in trending markets:
Modern interpretations of the stress the context of the greater trend when using signals such as crossovers, overbought/oversold conditions, divergences and patterns.
Constance Brown, CMT , was one of the first who promoted the idea that an oversold reading on the in an uptrend is likely much higher than 30%, and that an overbought reading on the during a downtrend is much lower than the 70% level.
In an uptrend or bull market, the tends to remain in the 40 to 90 range, with the 40-50 zone acting as support.
During a downtrend or bear market, the tends to stay between the 10 to 60 range, with the 50-60 zone acting as resistance.
For ease of executing more modern and nuanced interpretations of it is very useful to break the scale into bull and bear control and critical zones.
These ranges will vary depending on the settings and the strength of the specific market’s underlying trend.
Limitations of the
Like most technical indicators, its signals are most reliable when they conform to the long-term trend.
True trend reversal signals are rare, and can be difficult to separate from false signals.
False signals or “fake-outs”, e.g. a crossover, followed by a sudden decline in price, are common.
Since the indicator displays momentum, it can stay overbought or oversold for a long time when an asset has significant sustained momentum in either direction.
Data Length Dependency when using wilders smoothing method of calculating means that wilders standard will have a potential initialization error which reduces with every new data point calculated meaning early results should be regarded as unreliable until calculation iterations have occurred for convergence.
Where I am a moderator, my username there is The Caretaker also.
My Private indicators are available through https://app.krowntrading.net/
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