Combo Strategy 123 Reversal & Bill Williams. AC with Signal Line This is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
This indicator plots the oscillator as a histogram where blue denotes
periods suited for buying and red . for selling. If the current value
of AO (Awesome Oscillator) is above previous, the period is considered
suited for buying and the period is marked blue. If the AO value is not
above previous, the period is considered suited for selling and the
indicator marks it as red.
You can make changes in the property for set calculating strategy MA, EMA, WMA
WARNING:
- For purpose educate only
- This script to change bars colors.
Pesquisar nos scripts por "oscillator"
Recursive StochasticThe Self Referencing Stochastic Oscillator
The stochastic oscillator bring values in range of (0,100). This process is called Feature scaling or Unity-Based Normalization
When a function use recursion you can highlights cycles or create smoother results depending on various factors, this is the goal of a recursive stochastic.
For example : k = s(alpha*st+(1-alpha)*nz(k )) where st is the target source.
Using inputs with different scale level can modify the result of the indicator depending on which instrument it is applied, therefore the input must be normalized, here the price is first passed through a stochastic, then this result is used for the recursion.
In order to control the level of the recursion, weights are distributed using the alpha parameter. This parameter is in a range of (0,1), if alpha = 1, then the indicator act as a normal stochastic oscillator, if alpha = 0, then the indicator return na since the initial value for k = 0. The smaller the alpha parameter, the lower the correlation between the price and the indicator, but the indicator will look more periodic.
Comparison
Recursive Stochastic oscillator with alpha = 0.1 and bellow a classic oscillator (alpha = 1)
The use of recursion can both smooth the result and make it more reactive as well.
Filter As Source
It is possible to stabilize the indicator and make it less affected by outliers using a filter as input.
Lower alpha can be used in order to recover some reactivity, this will also lead to more periodic results (which are not inevitably correlated with price)
Hope you enjoy
For any questions/demands feel free to pm me, i would be happy to help you
A Multi 10 indicatorREAD NOTE BEFORE APPLYING or you may think indicator doesnt work.
This indicator is a revise of another i made and contains 10 Optional Indicators allowing you to load more then 3 indicators at once if you so choose and dont pay for the platform!
Hopefully someone will find use for this script besides me :) I dont suggest turning all on at once because it
will not look right. Alot will overlap if you wish but i only use the Session and trend bar at once in
conjuction with a Oscillator setting like MacD , RSI , Stoch , Aroon or CCI .
In the chart you see i only have a few indicators active ENJOY!!
---------- NOTE ----------- ( Everything is OFF by default and indicator SHOULD show up BLANK when loaded) ------------ NOTE -------------
(Can turn EVERYTHING on AND change any values in the format tab once indicator loads)
Indicators included are listed below
Sessions, including, NY session, Aussie session, Asian session, and Europe market sessions.
MacD Split Colored , aroon oscillator
CCI Oscillator , classic aroon
RSI Oscillator , Elliot wave
Stoch RSI Oscillator , ATR%
My own Trend bar
---------- NOTE ----------- ( Everything is OFF by default and indicator SHOULD show up BLANK when loaded) ------------ NOTE -------------
(Can turn EVERYTHING on AND change any values in the format tab once indicator loads) CODE probably looks messey but this is something i made for me so i didnt really care lol
A Multi 10 indicatorREAD NOTE BEFORE APPLYING or you may think indicator doesnt work.
This indicator is a revise of another i made and contains 10 Optional Indicators allowing you to load more then 3 indicators at once if you so choose and dont pay for the platform!
Hopefully someone will find use for this script besides me :) I dont suggest turning all on at once because it
will not look right. Alot will overlap if you wish but i only use the Session and trend bar at once in
conjuction with a Oscillator setting like MacD , RSI , Stoch , Aroon or CCI .
In the chart you see i only have a few indicators active ENJOY!!
---------- NOTE ----------- ( Everything is OFF by default and indicator SHOULD show up BLANK when loaded) ------------ NOTE -------------
(Can turn EVERYTHING on AND change any values in the format tab once indicator loads)
NY session, Aussie session, Asian session, and Europe market sessions.
MacD Split Colored , aroon oscillator
CCI Oscillator , classic aroon
RSI Oscillator , Elliot wave
Stoch RSI Oscillator
Aroon Oscillator
My own Trend bar
---------- NOTE ----------- ( Everything is OFF by default and indicator SHOULD show up BLANK when loaded) ------------ NOTE -------------
(Can turn EVERYTHING on AND change any values in the format tab once indicator loads) CODE probably looks messey but this is something i made for me so i didnt really care lol
Fisher Volume Transform | AlphaNattFisher Volume Transform | AlphaNatt
A powerful oscillator that applies the Fisher Transform - converting price into a Gaussian normal distribution - while incorporating volume weighting to identify high-probability reversal points with institutional participation.
"The Fisher Transform reveals what statistics professors have known for decades: when you transform market data into a normal distribution, turning points become crystal clear."
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🎲 THE MATHEMATICS
Fisher Transform Formula:
The Fisher Transform converts any bounded dataset into a Gaussian distribution:
y = 0.5 × ln((1 + x) / (1 - x))
Where x is normalized price (-1 to 1 range)
Why This Matters:
Market extremes become statistically identifiable
Turning points are amplified and clarified
Removes the skew from price distributions
Creates nearly instantaneous signals at reversals
Volume Integration:
Unlike standard Fisher Transform, this version weights price by relative volume:
High volume moves get more weight
Low volume moves get filtered out
Identifies institutional participation
Reduces false signals from retail chop
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💎 KEY ADVANTAGES
Statistical Edge: Transforms price into normal distribution where extremes are mathematically defined
Volume Confirmation: Only signals with volume support
Early Reversal Detection: Fisher Transform amplifies turning points
Clean Signals: Gaussian distribution reduces noise
No Lag: Mathematical transformation, not averaging
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⚙️ SETTINGS OPTIMIZATION
Fisher Period (5-30):
5-9: Very sensitive, many signals
10: Default - balanced sensitivity
15-20: Moderate smoothing
25-30: Major reversals only
Volume Weight (0.1-1.0):
0.1-0.3: Minimal volume influence
0.5-0.7: Balanced price/volume
0.7: Default - strong volume weight
0.8-1.0: Volume dominant
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📊 TRADING SIGNALS
Primary Signals:
Zero Cross Up: Bullish momentum shift
Zero Cross Down: Bearish momentum shift
Signal Line Cross: Early reversal warning
Extreme Readings (±75): Potential reversal zones
Visual Interpretation:
Cyan zones: Bullish momentum
Magenta zones: Bearish momentum
Gradient intensity: Strength of move
Histogram: Raw momentum power
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🎯 OPTIMAL USAGE
Best Market Conditions:
Range-bound markets (reversals clear)
High volume periods
Major support/resistance levels
Divergence hunting
Trading Strategies:
1. Extreme Reversal:
Enter when oscillator exceeds ±75 and reverses
2. Zero Line Momentum:
Trade crosses of zero line with volume confirmation
3. Signal Line Strategy:
Early entry on signal line crosses
4. Divergence Trading:
Price makes new high/low but Fisher doesn't
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Developed by AlphaNatt | Quantitative Trading Systems
Version: 1.0
Classification: Statistical Transform Oscillator
Not financial advice. Always DYOR.
Adaptive Valuation [BackQuant]Adaptive Valuation
What this is
A composite, zero-centered oscillator that standardizes several classic indicators and blends them into one “valuation” line. It computes RSI, CCI, Demarker, and the Price Zone Oscillator, converts each to a rolling z-score, then forms a weighted average. Optional smoothing, dynamic overbought and oversold bands, and an on-chart table make the inputs and the final score easy to inspect.
How it works
Components
• RSI with its own lookback.
• CCI with its own lookback.
• DM (Demarker) with its own lookback.
• PZO (Price Zone Oscillator) with its own lookback.
Standardization via z-score
Each component is transformed using a rolling z-score over lookback bars:
z = (value − mean) ÷ stdev , where the mean is an EMA and the stdev is rolling.
This puts all inputs on a comparable scale measured in standard deviations.
Weighted blend
The z-scores are combined with user weights w_rsi, w_cci, w_dm, w_pzo to produce a single valuation series. If desired, it is then smoothed with a selected moving average (SMA, EMA, WMA, HMA, RMA, DEMA, TEMA, LINREG, ALMA, T3). ALMA’s sigma input shapes its curve.
Dynamic thresholds (optional)
Two ways to set overbought and oversold:
• Static : fixed levels at ob_thres and os_thres .
• Dynamic : ±k·σ bands, where σ is the rolling standard deviation of the valuation over dynLen .
Bands can be centered at zero or around the valuation’s rolling mean ( centerZero ).
Visualization and UI
• Zero line at 0 with gradient fill that darkens as the valuation moves away from 0.
• Optional plotting of band lines and background highlights when OB or OS is active.
• Optional candle and background coloring driven by the valuation.
• Summary table showing each component’s current z-score, the final score, and a compact status.
How it can be used
• Bias filter : treat crosses above 0 as bullish bias and below 0 as bearish bias.
• Mean-reversion context : look for exhaustion when the valuation enters the OB or OS region, then watch for exits from those regions or a return toward 0.
• Signal confirmation : use the final score to confirm setups from structure or price action.
• Adaptive banding : with dynamic thresholds, OB and OS adjust to prevailing variability rather than relying on fixed lines.
• Component tuning : change weights to emphasize trend (raise DM, reduce RSI/CCI) or range behavior (raise RSI/CCI, reduce DM). PZO can help in swing environments.
Why z-score blending helps
Indicators often live on different scales. Z-scoring places them on a common, unitless axis, so a one-sigma move in RSI has comparable influence to a one-sigma move in CCI. This reduces scale bias and allows transparent weighting. It also facilitates regime-aware thresholds because the dynamic bands scale with recent dispersion.
Inputs to know
• Component lookbacks : rsilb, ccilb, dmlb, pzolb control each raw signal.
• Standardization window : lookback sets the z-score memory. Longer smooths, shorter reacts.
• Weights : w_rsi, w_cci, w_dm, w_pzo determine each component’s influence.
• Smoothing : maType, smoothP, sig govern optional post-blend smoothing.
• Dynamic bands : dyn_thres, dynLen, thres_k, centerZero configure the adaptive OB/OS logic.
• UI : toggle the plot, table, candle coloring, and threshold lines.
Reading the plot
• Above 0 : composite pressure is positive.
• Below 0 : composite pressure is negative.
• OB region : valuation above the chosen OB line. Risk of mean reversion rises and momentum continuation needs evidence.
• OS region : mirror logic on the downside.
• Band exits : leaving OB or OS can serve as a normalization cue.
Strengths
• Normalizes heterogeneous signals into one interpretable series.
• Adjustable component weights to match instrument behavior.
• Dynamic thresholds adapt to changing volatility and drift.
• Transparent diagnostics from the on-chart table.
• Flexible smoothing choices, including ALMA and T3.
Limitations and cautions
• Z-scores assume a reasonably stationary window. Sharp regime shifts can make recent bands unrepresentative.
• Highly correlated components can overweight the same effect. Consider adjusting weights to avoid double counting.
• More smoothing adds lag. Less smoothing adds noise.
• Dynamic bands recalibrate with dynLen ; if set too short, bands may swing excessively. If too long, bands can be slow to adapt.
Practical tuning tips
• Trending symbols: increase w_dm , use a modest smoother like EMA or T3, and use centerZero dynamic bands.
• Choppy symbols: increase w_rsi and w_cci , consider ALMA with a higher sigma , and widen bands with a larger thres_k .
• Multiday swing charts: lengthen lookback and dynLen to stabilize the scale.
• Lower timeframes: shorten component lookbacks slightly and reduce smoothing to keep signals timely.
Alerts
• Enter and exit of Overbought and Oversold, based on the active band choice.
• Bullish and bearish zero crosses.
Use alerts as prompts to review context rather than as stand-alone trade commands.
Final Remarks
We created this to show people a different way of making indicators & trading.
You can process normal indicators in multiple ways to enhance or change the signal, especially with this you can utilise machine learning to optimise the weights, then trade accordingly.
All of the different components were selected to give some sort of signal, its made out of simple components yet is effective. As long as the user calibrates it to their Trading/ investing style you can find good results. Do not use anything standalone, ensure you are backtesting and creating a proper system.
Trend Reversal Probability [Algoalpha]Introducing Trend Reversal Probability by AlgoAlpha – a powerful indicator that estimates the likelihood of trend reversals based on an advanced custom oscillator and duration-based statistics. Designed for traders who want to stay ahead of potential market shifts, this indicator provides actionable insights into trend momentum and reversal probabilities.
Key Features :
🔧 Custom Oscillator Calculation: Combines a dual SMA strategy with a proprietary RSI-like calculation to detect market direction and strength.
📊 Probability Levels & Visualization: Plots average signal durations and their statistical deviations (±1, ±2, ±3 SD) on the chart for clear visual guidance.
🎨 Dynamic Color Customization: Choose your preferred colors for upward and downward trends, ensuring a personalized chart view.
📈 Signal Duration Metrics: Tracks and displays signal durations with columns representing key percentages (80%, 60%, 40%, and 20%).
🔔 Alerts for High Probability Events: Set alerts for significant reversal probabilities (above 84% and 98% or below 14%) to capture key trading moments.
How to Use :
Add the Indicator: Add Trend Reversal Probability to your favorites by clicking the star icon.
Market Analysis: Use the plotted probability levels (average duration and ±SD bands) to identify overextended trends and potential reversals. Use the color of the duration counter to identify the current trend.
Leverage Alerts: Enable alerts to stay informed of high or extreme reversal probabilities without constant chart monitoring.
How It Works :
The indicator begins by calculating a custom oscillator using short and long simple moving averages (SMA) of the midpoint price. A proprietary RSI-like formula then transforms these values to estimate trend direction and momentum. The duration between trend reversals is tracked and averaged, with standard deviations plotted to provide probabilistic guidance on trend longevity. Additionally, the indicator incorporates a cumulative probability function to estimate the likelihood of a trend reversal, displaying the result in a data table for easy reference. When probability levels cross key thresholds, alerts are triggered, helping traders take timely action.
Slow Volume Strength Index (SVSI)The Slow Volume Strength Index (SVSI), introduced by Vitali Apirine in Stocks & Commodities (Volume 33, Chapter 6, Page 28-31), is a momentum oscillator inspired by the Relative Strength Index (RSI). It gauges buying and selling pressure by analyzing the disparity between average volume on up days and down days, relative to the underlying price trend. Positive volume signifies closes above the exponential moving average (EMA), while negative volume indicates closes below. Flat closes register zero volume. The SVSI then applies a smoothing technique to this data and transforms it into an oscillator with values ranging from 0 to 100.
Traders can leverage the SVSI in several ways:
1. Overbought/Oversold Levels: Standard thresholds of 80 and 20 define overbought and oversold zones, respectively.
2. Centerline Crossovers and Divergences: Signals can be generated by the indicator line crossing a midline or by divergences from price movements.
3. Confirmation for Slow RSI: The SVSI can be used to confirm signals generated by the Slow Relative Strength Index (SRSI), another oscillator developed by Apirine.
🔹 Algorithm
In the original article, the SVSI is calculated using the following formula:
SVSI = 100 - (100 / (1 + SVS))
where:
SVS = Average Positive Volume / Average Negative Volume
* Volume is considered positive when the closing price is higher than the six-day EMA.
* Volume is considered negative when the closing price is lower than the six-day EMA.
* Negative volume values are expressed as absolute values (positive).
* If the closing price equals the six-day EMA, volume is considered zero (no change).
* When calculating the average volume, the indicator utilizes Wilder's smoothing technique, as described in his book "New Concepts In Technical Trading Systems."
Note that this indicator, the formula has been simplified to be
SVSI = 100 * Average Positive Volume / (Average Positive Volume + Average Negative Volume)
This formula achieves the same result as the original article's proposal, but in a more concise way and without the need for special handling of division by zero
🔹 Parameters
The SVSI calculation offers configurable parameters that can be adjusted to suit individual trading styles and goals. While the default lookback periods are 6 for the EMA and 14 for volume smoothing, alternative values can be explored. Additionally, the standard overbought and oversold thresholds of 80 and 20 can be adapted to better align with the specific security being analyzed.
RedK Chop & Breakout Scout (C&B_Scout)The RedK Chop & Breakout Scout (C&BS or just CBS) is a centered oscillator that helps traders identify when the price is in a chop zone, where it's recommended to avoid trading or exit existing trades - and helps identify (good & tradeable) price breakouts.
i receive many questions asking for simple ways to identify chops .. Here's one way we can do that.
(This is work in progress - i was exploring with the idea, and wasn't sure how interesting other may find it. )
Quick Intro:
==================
Quick techno piece: This concept is similar to a Stochastic Oscillator - with the main difference being that we're utilizing units of ATR (instead of a channel width) to calculate the main indicator line - which will then lead to a non-restricted oscillator (rather than a +/- 100%) - given that ATR changes with the underlying and the timeframe, among other variables.
to make this easy, and avoid a lot of technical speak in the next part, :) i created (on the top price panel) the same setup that the C&B Scout represents as a lower-panel indicator.
So as you read below, please look back and compare what C&BS is doing in its lower panel, with how the price is behaving on the price chart.
how this works
========================
- To identify chops and breakouts, we need to first agree on a definition that we will use for these terms.
- for the sake of this exercise, let's agree that the price is in a chop zone, as long as the price is moving within a certain distance from a "price baseline" of choice ( which we can adjust based on the underlying, the volatility, the timeframe, the trading style..etc)
- when the price moves out of that chop zone, we consider this a breakout
- Now not all breakouts are "good" = they need to at least happen in the direction of the longer term trend. In this case, we can apply a long Moving Average to act as a filter - and consider breakouts to be "good" if they are in the same direction as the filter line
- With the above background in mind, we establish a price baseline (as you see on the top panel, this is based on the midline of a Donchian Channel - but we can use other slow moving averages in future versions)
- we will decide how far above/below that baseline is considered to be "chop zone" - we do this in terms of units of Average True Range (ATR) - using ATR here is valuable for so many reasons, most of all, how it adjusts to timeframe and volatility of underlying.
- The C&B Scout line simply calculates how far the price is above/below the baseline in terms of "ATR units". and shows how that value compares to our own definition of a "chop zone"
- so as long as the price is within the chop zone, the CBS line will be inside the shaded area - and when the price "breaks out" of the chop zone, the CBS line will also breakout (or down) from the chop zone.
- C&B Scout will give a visual clue to help take trades in the direction of the prevailing trend - the chop zone is green when the price is in "long mode", as in, the price is above the filter line - and will be red when we are in "short mode" - so the price is below the filter line. in green mode, we should only consider breakouts to the upside, and ignore breakouts to the downside (or breakdowns) - in red mode, we should only consider breakouts to the downside., and ignore the ones to the upside.
- i added some examples of "key actions" on the chart to help explain the approach here further.
Usage & settings Notes:
========================
- even though for many traders this will be a basic concept/setup, i still highly suggest you spend time getting used to how it works/reacts and adjusting the settings to suit your own trading style, timeframe, tolerance, what you trade....etc
- for example, if i am a conservative trader, i may consider any price movement within 1 x ATR above and below the baseline to be in "chop" (ATR Channel width = 2 x ATR) - and i want to only take trades when the price moves outside of that range *and* in the direction of the prevailing trend
- An aggressive trader may use a smaller ATR-based value, say 0.5 x ATR above/below the baseline, as their chop zone.
- A swing trader may use a shorter filter line and focus on the CBS line crossing the 0 line.
- .... and so on.
- Also note that the "tradeable" signal is when the CBS line "exits" the chop zone (upward on green background, or downward on red background) - however, an aggressive trader may take the crossing of the CBS line with the 0 line as the signal to open a trade.
- As usual please do not use this indicator "in isolation" and ensure you have other confirming signals from your setups before trading.
conclusion
===========
As i mentioned, this is really a simple concept - and i'm a big fan of those :) -- and there's so much that could be done to expand around it (add more visuals/colors, add alerts, add options for ATR calculation, Filter line calculations, baseline..etc) - but with this v1.0, i wanted to share this initially and see how much interest and how valuable fellow traders find it, before playing any further with it. so please be generous with your comments.
TFO + ATR Strategy with Trailing Stop LossThis strategy is an experiment to learn what happens when The Trend Flex Oscillator (by Dr. John Ehlers) is used in conjunction with a volatility indicator like ATR. It was designed with cryptocurrency trading in mind.
The way I coded this experiment makes it unsuitable for bear market conditions.
When applied to a bull market, this trend-following strategy will open long positions when oversold price action appear to be reversing. It will typically close a position within a few days unless it gets caught in a bear market, in which case it holds on for dear life. I have tried to make back-testing very simple, but you should never trust it. It's merely and interesting tool for adjusting the many parameters that I've made editable in the configuration window. Those values include the ATR and TFO parameters, as well as setting a trailing stop loss. When closing a position, the strategy can optionally be told to ignore the trend analysis and only obey the trailing stop loss value. I've made an attempt to allow the user to define the minimum profit necessary to allow the strategy to close all all positions. In my observations, the 2H candlestick charts seem to produce the best results, although the parameters of the strategy could theoretically be adjusted to suit other time periods.
In summary...
This strategy has a bias for HODL (Holds on to Losses) meaning that it provides NO STOP LOSS protection!
Also note that the default behavior is designed for up to 15 open long orders, and executes one order to close them all at once.
Opening a long position is predicated on The Trend Flex Oscillator (TFO) rising after being oversold, and ATR above a certain volatility threshold.
Closing a long is handled either by TFO showing overbought while above a certain ATR level, or the Trailing Stop Loss. Pick one or both.
If the strategy is allowed to sell before a Trailing Stop Loss is triggered, you can set a "must exceed %". Do not mistake this for a stop loss.
Short positions are not supported in this version. Back-testing should NEVER be considered an accurate representation of actual trading results.
// portions © allanster (date window code)
// portions © Dr. John Ehlers (Trend Flex Oscillator)
This code is provided for educational purposes only. The results of this strategy should not be considered investment advice.
The user of this script acknowledges that it can result in serious financial loss when used as a trading tool
Reverse Cutlers Relative Strength Index On ChartIntroduction
The Reverse Cutlers Relative Strength Index (RCRSI) OC is an indicator which tells the user what price is required to give a particular Cutlers Relative Strength Index ( RSI ) value, or cross its Moving Average (MA) signal line.
Overview
Background & Credits:
The relative strength index ( RSI ) is a momentum indicator used in technical analysis 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 RSI 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 RSI 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 RSI , and while she did not actually reveal the formulas, she introduced the concept of “reverse engineering” the RSI 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 RSI when he published his excellent and well-received articles "Reverse Engineering RSI " and "Reverse Engineering RSI II " in the June 2003, and August 2003 issues of Stocks & Commodities magazine, where he described his methods of reverse engineering Wilders RSI .
Several excellent Implementations of the Reverse Wilders Relative Strength Index have been published here on Tradingview and elsewhere.
My utmost respect, and all due credits to authors of related prior works.
Introduction
It is worth noting that while the general RSI 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 RSI which means that wilders standard RSI 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 RSI which consists of plotted lines on a scale of 0 to 100, and an optional infobox.
The RSI 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 RSI plots which graphically display output closing price levels where Cutlers RSI value will crossover:
• RSI (eq) (previous RSI value)
• RSI MA signal line
• RSI Test price
• Alert level high
• Alert level low
The info box displays output closing price levels where Cutlers RSI value will crossover:
• Its previous value. ( RSI )
• Bull critical zone.
• Bull control zone.
• Mid-Line.
• Bear control zone.
• Bear critical zone.
• RSI MA signal line
• Alert level High
• Alert level low
And also displays the resultant RSI for a user defined closing price:
• Test price RSI
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
Importantly:
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.
Understanding the Relative Strength Index
At its simplest the RSI 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 RSI 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.
Traditional interpretations
Overbought and oversold:
An RSI 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 RSI 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.
Midline Crossovers:
When the RSI crosses above its midline ( RSI > 50%) a bullish bias signal is generated. (only take long trades)
When the RSI crosses below its midline ( RSI < 50%) a bearish bias signal is generated. (only take short trades)
Bullish and bearish moving average signal Line crossovers:
When the RSI line crosses above its signal line, a bullish buy signal is generated
When the RSI line crosses below its signal line, a bearish sell signal is generated.
Swing Failures and classic rejection patterns:
If the RSI makes a lower high, and then follows with a downside move below the previous low, a Top Swing Failure has occurred.
If the RSI 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
Bullish swing rejection pattern:
The RSI moves into oversold zone (below 30%).
The RSI rejects back out of the oversold zone (above 30%)
The RSI forms another dip without crossing back into oversold zone.
The RSI then continues the bounce to break up above the previous high.
Bearish swing rejection pattern:
The RSI moves into overbought zone (above 70%).
The RSI rejects back out of the overbought zone (below 70%)
The RSI forms another peak without crossing back into overbought zone.
The RSI then continues to break down below the previous low.
Divergences:
A regular bullish RSI divergence is when the price makes lower lows in a downtrend and the RSI indicator makes higher lows.
A regular bearish RSI divergence is when the price makes higher highs in an uptrend and the RSI indicator makes lower highs.
A hidden bullish RSI divergence is when the price makes higher lows in an uptrend and the RSI indicator makes lower lows.
A hidden bearish RSI divergence is when the price makes lower highs in a downtrend and the RSI 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.
Chart Patterns:
RSI regularly forms classic chart patterns that may not show on the underlying price chart, such as ascending and descending triangles & wedges , double tops, bottoms and trend lines etc.
Support and Resistance:
It is very often easier to define support or resistance levels on the RSI itself rather than the price chart.
Modern interpretations in trending markets:
Modern interpretations of the RSI stress the context of the greater trend when using RSI 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 RSI in an uptrend is likely much higher than 30%, and that an overbought reading on the RSI during a downtrend is much lower than the 70% level.
In an uptrend or bull market, the RSI tends to remain in the 40 to 90 range, with the 40-50 zone acting as support.
During a downtrend or bear market, the RSI 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 RSI it is very useful to break the RSI scale into bull and bear control and critical zones.
These ranges will vary depending on the RSI settings and the strength of the specific market’s underlying trend.
Limitations of the RSI
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 bullish 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 RSI means that wilders standard RSI 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.
WMA Combo CrossoverBefore I begin I want to mention:
1. This is an inspiration from the Ultimate Oscillator by zinlytics. (Link: )
2. I wanted to make an indicator similar to the Ultimate Oscillator by making it more responsive to price
3. This indicator is a trend indicator which uses the Weighted Moving Average (WMA)
4. Also, I want to thank PhoenixBinary for helping me out
The indicator:
1. Made several changes such as switching over to a WMA instead of an EMA
2. When WMA 20 is blue and is going upwards, it means there is an uptrend
3. When WMA 20 is red and is going down, it means there is a downtrend
4. During a trend, the color may switch to red and blue occasionally. When the color switches back to the direction of the trend, it can be used for re-entries
RedK Bar Strength Inspector / Bar Strength Index (BSI)Summary
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The Bar Strength Inspector / Bar Strength Index (BSI) is an indicator that evaluates each price bar against a user-selectable set of "strength categories" - BSI then calculates a combined score from these categories and provides an index - plotted as a centered oscillator - roughly similar to the way Relative Strength Index (RSI) works, which can be used to evaluate the strength of price move and the possibilities of trend continuation or reversal.
Background
=============
BSI is like a Swiss-army knife with many components - so apologies upfront if this guide gets long - and i know i will still miss few pieces that needs explaining. please alert me if something is not clear.
BSI is an advanced / re-built version of my Ultimate Trader Oscillator (UTO)
I continue to believe that one of the best trading tools that i can use, is a tool that can automate the visual inspection of the price chart - a tool that simulates (and quantifies in numbers/score) the way we visually look at a certain price bar, and make a judgement that "this is a strong bar, so I expect the trend down to possibly reverse" - BSI is a an attempt to achieve that. An attempt to answer a simple question (in a quantifiable manner):
how strong / weak is this price bar - how does it compare to previous bars ? what is the average of that strength (or weakness) for the last few bars ?(based on the trader's preferred timeframe)
How does BSI work
====================
* BSI will inspect and evaluate each bar against various (selectable) strength categories.
* BSI will give a -100/+100 score against each "strength category", then combine these scores into an index and create an average of that index
* the average index (also called BSI) will be calculated for both a short and long lengths
* the short length represents "local / short-term" strength - plotted as a blue/orange line (with an additional signal line to make easier to "read")
* the long-term reflects the broader bias (sentiment) - plotted as green/red area (or mountain)
How is BSI different from UTO
=============================
- I wrote BSI from the ground up to validate each scoring calculation and the resulting outcomes - so i would consider BSI to be more accurate than UTO
- i wrote BSI in a way to make it a lot more flexible. BSI allows me to choose which category to include in the "inspection"
- the strength categories are streamlined to reflect single bar strength, strength from bar-to-bar, and relative strength (range and volume) - they have also been chosen in a way that map to commonly used Technical Analysis concepts, to increase the value of BSI and the ability to compare with other common indicators (for example, BoP, Stochastic, Relative Volume and RSI)
- added the table view - which i use mainly to track the action within the current bar - and to learn more about how to evaluate strength vs weakness with various chart patterns
- UTO still represents the foundation of this work - but i will not update UTO any longer so all changes will be applied to the BSI- i have been using both UTO and BSI to guide my trading for the past few months.
- couple of other features in BSI:
- support for instruments with no volume data (even if the user chooses volume) - number of inspection categories will show as "7" in that case
- ability to plot the individual category scores, and the total weighted score (for the selected categories) - these plots are hidden by default
- ability to see the total score for all 8 (or 7 in case no volume data) categories regardless of how many are active - but only in the table view
- ability to be used as both a lower (independent) and a top indicator (on the price chart) -- see below examples.
Structure of the BSI Strength Categories
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The first 3 inspected strength categories focus on "single bar strength", they evaluate how the bar closes compared to the low, the Balance of Power (BoP) and the relative BoP
The next 3 categories focus on evaluating the bar-to-bar strength: how the bar closes compared to the low of the 2-bar range, how the bar closes compared to prior close - and the relative "shift"
The last 2 "strength" categories evaluate the relative range of bar compared to recent average range and the relative volume.
Understanding the bar inspection & scoring approach
==================================
During inspection for each category, a score is calculated with a value between 0 to 100, then it will be made "directional" - which means that +100 represents highest possible strength score and a value of -100 is the highest possible "weakness" score
Note that a 0 score doesn't mean "weak" - but rather "neutral" - this can be a bit confusing until we get used to the way BSI scoring works.
Example: in relative volume, a bar associated with the lowest volume observed during the lookback length, will have a 0 relative volume score -- while a bar associated with the highest volume observed will have either a +100 or a -100 score (depending on whether it's an up or down bar) - same thing for relative range.. and so on
Here are the 8 strength categories evaluated by the BSI
1 Bar closing score
2 Body : Spread (BoP) ratio
3 Relative BoP
4 2-bar Closing Score
5 2-bar Shift Ratio (Shift : 2R)
6 Relative Shift
7 Relative Range
8 Relative Volume
Specific meaning of keywords / concepts (within BSI context):
======================================================
Relative : compared to recently observed values (= within Lookback # bars)
Shift : the change in closing value vs prior bar
Bar Spread : high - low
Range : True Range ..... as in the tr() Pine function, so not to be confused with "spread"
More detailed notes about scoring and calculations for each strength category are included within the code
BSI Settings:
=============
Here is a chart showing the main sections in the BSI Settings box and how to configure it to your preference
Using the BSI:
================
- I use BSI for 2 main scenarios
(1) Guiding my Day-to-day trading: the usage here is roughly similar to a volume-weighted dual-period RSI .. with a lot more options - picking and choosing between the 8 strength categories in BSI allows for 255 variations of "strength evaluations" - a trader can choose to focus only on "single bar strength" score categories, so only picks the top 3 in the settings - another trader wants to track only the strength reflected by the relative range and relative volume, so picks the lower 2 categories. another trader wants to use BSI as a volume weighted Balance of Power.. and so on. Many combinations are possible.
i have added couple of charts that explain some of the "signals" we can expect from BSI (below chart) - note that i use the "Green/Red mountain plot" as the "prevailing sentiment" - as it confirms the longer term strength (or weakness). the BSI line plot reflects the short term strength and not necessarily tied directly to how the price is moving (see example in the chart - and also compare to how RSI works)
- 2 important points here if you plan to use BSI in trading: set BSI up on a 1-min or 5-min chart and watch how it works to learn how it evaluates each bar - and always use BSI in combination with other indicators that you are familiar with to validate and confirm any signals
(Important note: do not react to the values in the table as they change in real time - i found that to be very tempting - rather look at the broader context and the flow of the BSI / sentiment) - you can also test BSI with Paper Trading in TV - it's like a new car that you need some time to get used to :)
(2) Use BSI to help learn chart / pattern analysis - watch BSI print scores against the various categories in real time to hone your chart (pattern) reading skills and how to evaluate strength of various bar shapes - for example, a bar that closes at the high but does not reach the mid point of the prior bar - strong or weak ? how about a doji or a hammer ? ...etc
Chart showing main usage scenarios
Example BSI in real time:
======================
I hope this work helps few fellow traders hone their trading skills, or help inspire other ideas - please let me know if you have feedback or suggestions.
Boom Hunter ProBoom Hunter Pro is the ultimate indicator for targeting perfect long entries and epic shorts. Boom Hunter comes with a super fast oscillator that uses Ehlers Early Onset Trend (EOT). This is the Center Of Gravity Oscillator (COG) with a super smoothing filter and a roofing filter. This indicator is tuned for 1 hour charts but can be used on any time frame.
Colored bars can be turned on to assist in finding an entry. Purple signifies a drag and potential dump.
Fibonacci lines can be turned on to track price action and find entries/exit.
This indicator follows the same rules as COG. For more information please see my COG HOWTO here:
Combo Backtest 123 Reversal & Smoothed RSIThis is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
This is new version of RSI oscillator indicator, developed by John Ehlers.
The main advantage of his way of enhancing the RSI indicator is smoothing
with minimum of lag penalty.
WARNING:
- For purpose educate only
- This script to change bars colors.
Wave Trend w/ VWMA overlayThis is a trend-following strategy and indicator which combines the Wave Trend Strategy (Lazy Bear) by thomas.gigure with the cRSI + Waves Strategy with VWMA overlay by Dr_Roboto .
You may update the parameters of the Wave Trend oscillator or the VWMA indicator to match your own preferences. You may also adjust the Base Quantity used for determining trade size (as described below) to suit your account size and risk tolerance.
The strategy identifies potential signals based on the on the Wave Trend oscillator, originally ported to TradingView by LazyBear. When a signal is produced by the Wave Trend oscillator, trade size is determined by the VWMA.
When the VWMA is trending against the direction of the Wave Trend signal, Base Quantity x 1 is used
When the VWMA is trending neutral, Base Quantity x 2 is used
When the VWMA is trending with the direction of the Wave Trend signal, Base Quantity x 4 is used
The strategy includes the ability to limit trade signals to certain defined periods of time ("Sessions") during the trading day and, optionally, to close any open position at the end of either or both "Sessions." This may be enabled/disabled via the Limit Signals to Trading Sessions? option on the "Inputs" tab of the strategy's "Settings" window.
If you are trading on a daily chart (or longer) you must disable the Limit Signals to Trading Sessions? in order for the strategy to produce signals.
