Technical Analysis - Panel Info//A. Oscillators & B. Moving Averages base on TradingView's Technical Analysis by ThiagoSchmitz
//C.Pivot base on Ultimate Pivot Points Alerts by elbartt
//D. Summary & Panel info by anhnguyen14
Panel Info base on these indicators:
A. Oscillators
1. Rsi (14)
2. Stochastic (14,3,3)
3. CCI (20)
4. ADX (14)
5. AO
6. Momentum (10)
7. MACD (12,26)
8. Stoch RSI (3,3,14,14)
9. %R (14)
10. Bull bear
11. UO (7,14,28)
B. Moving Averages
1. SMA & EMA: 5-10-20-30-50-100-200
2. Ichimoku Cloud - Baseline (26)
3. Hull MA (9)
C. Pivot
1. Traditional
2. Fibonacci
3. Woodie
4. Camarilla
D. Summary
Sum_red=A_red+B_red+C_red
Sum_blue=A_blue+B_blue+C_blue
sell_point=(Sum_red/32)*100
buy_point=(Sum_blue/32)*100
sell =
Sum_red>Sum_blue
and sell_point>50
Strong_sell =
A_red>A_blue
and B_red>B_blue
and C_red>C_blue
and sell_point>50
and not crossunder(sell_point,75)
buy =
Sum_red>Sum_blue
and buy_point>50
Strong_buy =
A_red50
and not crossunder(buy_point,75)
neutral = not sell and not Strong_sell and not buy and not Strong_buy
Pesquisar nos scripts por "100年黄金价格走势"
CCI RiderThis is my thank you to the TradingView community, for the people who are sharing their scripts, which allowed me to learn Pine Script.
So here is my first creation, feel free to experiment, modify and use it as you wish.
It is a CCI(default value is 100, can be changed), combined with an EMA of that CCI(default 21,changeable) that then colors the background according to the strength of the signal(if selected to do so).
To generate strong signals, it also uses Bollinger Bands to prevent whipsaws in high volatility situations.
The best signals are generated when the CCI crosses the limits set by the user (default is 100/-100), and is above/belov its EMA.
Exit signals are indicated, when the CCI crosses its EMA.
Unfortunately in strong trends, this exit signal is sometimes premature, using a 3x resolution of the indicator will improve this, maybe I will implement this in a later version.
I use it mostly in 15min charts and higher, I found in shorter timeframes still a lot of whipsaws, maybe experimenting with different lengths and levels will improve this.
As the Indicator allows the user to experiment with different lenghts and levels, and the colors will change according the setting, I find it a nice tool to search for the best mixture for different securities and timeframes.
See below an example of a nice signal.
I do suggest to use it in combination with other indicators.
Yield Curve Version 2.55.2Welcome to Yield Curve Version 2.55.2
US10Y-US02Y
* Please read description to help understand the information displayed.
* NOTE - This script requires 1 real time update before accurate information is displayed, therefore WILL NOT display the correct information if the Bond Market is Closed over the Weekend.
* NOTE - When values are changed Via Input setting they do take a bit to display based off all the information that is required to display this script.
**FEATURES**
* Input Features let you view the information the way YOU like via Input Settings
* Displays Current Version Title - Toggleable On/Off via Input Settings - Default On
* Plots the Yield Curve of the Bonds listed (Middle Green and Red Line)
* Displays the Spread for each Bond (Top Green and Red Labels) - Toggleable On/Off via Input Settings - Change Size via Input Settings - Default On
* Displays the current Yield for each Bond (Bottom Green and Red Labels) - Toggleable On/Off via Input Settings - Change Size via Input Settings - Default On - Large Size
* Plots the Average of the Entire Yield Curve (BLUE Line within the Yield Curve) - Toggleable On/Off via Input Settings - Default On
* Displays messages based off Yield Inversions (Orange Text) - Toggleable On/Off via Input Settings - Default On if Applicable
* Displays 2 10 Inversion Warning Message (Orange Text) - Toggleable On/Off via Input Settings - Default On if Applicable
* Plots Column Data at the Bottom that tries to help determine the Stability of the Yield Curve (More information Below about Stability) - Toggleable On/Off via Input Settings - Default On
* Plots the 7,20 and 100 SMA of the STABILITY MAX OVERLOAD (More information Below about Stability Max Overload) - Toggleable On/Off via Input Settings - Default On for 100 SMA , 20 SMA and 7 SMA
* Ability to Display Indicator Name and Value via Input Settings - Default On - Displays Stability Max Overload SMA Labels. Toggleable to Non SMA Values. See Below.
**Bottom Columns are all about STABILITY**
* I have tried to come up with an algorithm that helps understand the Stability of the Yield Curve. There are 3 Sections to the Bottom Columns.
* Section 1 - STABILITY (Displayed as the lightest Green or Red Column) Values range from 0 to 1 where 1 equals the MOST UNSTABLE Curve and 0 equals the MOST STABLE Curve
* Section 2 - STABILITY OVERLOAD (Displayed just above the Stability Column a shade darker Green or Red Column)
* Section 3 - STABILITY MAX OVERLOAD (Displayed just above the Stability Overload Column a shade darker Green or Red Column)
What this section tries to do is help understand the Stability of the Curve based on the inversions data. Lower values represent a MORE STABLE curve. If the Yield Curve currently has 0 Inversions all Stability factors should equal 0 and therefore not plot any lower columns. As the Yield Curve becomes more inverted each section represents a value based off that data. GREEN columns represent a MORE Stable Curve from the resolution prior and vise versa.
(S SO SMO)
STABILITY - tests the current Stability of the Curve itself again ranging from 0 to 1 where 0 equals the MOST Stable Curve and 1 equals the MOST Unstable Curve.
STABILIY OVERLOAD - adds a value to STABLITY based off STABILITY itself.
STABILITY MAX OVERLOAD - adds the Entire value to STABILITY derived again from STABILITY.
This section also allows us to see the 7,20 and 100 SMA of the STABILITY MAX OVERLOAD which should always be the GREATEST of ALL STABILTY VALUES.
*Indicator Labels How to use*
Indicator Labels by default are turned On and will display Name and Value Labels for Stability Max Overload SMA values. To switch to (S SO SMO) Labels, toggle "Indicator Labels / SMO SMA Labels", via Input Settings. This button allows you to switch between the two Indicator Label Display options. You must have "Indicators" turned On to view the Labels and therefore is turned On by Default. To turn all of the Indicator Labels Off, simply disable "Indicators" via Input Settings.
Remember - All information displayed can be tuned On or Off besides the Curve itself. There are also other Features Accessible Via the Input Settings.
I will continue to update this script as there is more information I would like to gather and display!
I hope you enjoy,
OpptionsOnly
Ultimate Moving Average Package (17 MA's)Included is the:
VWAP
Current time frame 10 EMA
Current time frame 20 EMA
Current time frame 50 EMA
Current time frame 10 SMA
Current time frame 20 SMA
Current time frame 50 SMA
Daily 10 EMA
Daily 20 EMA
Daily 50 EMA
Daily 50 SMA
Daily 100 SMA
Daily 200 SMA
Weekly 100 SMA
Weekly 200 SMA
Monthly 100 SMA
Monthly 200 SMA
All Daily/Weekly/Monthly MA's can be seen on intraday charts. Current time frame MA's change depending on your time frame. Obviously you dont need all 17 on your chart but you can pick the ones you like and disable the rest.
Bilateral Stochastic Oscillator - For The Sake Of EfficiencyIntroduction
The stochastic oscillator is a feature scaling method commonly used in technical analysis, this method is the same as the running min-max normalization method except that the stochastic oscillator is in a range of (0,100) while min-max normalization is in a range of (0,1). The stochastic oscillator in itself is efficient since it tell's us when the price reached its highest/lowest or crossed this average, however there could be ways to further develop the stochastic oscillator, this is why i propose this new indicator that aim to show all the information a classical stochastic oscillator would give with some additional features.
Min-Max Derivation
The min-max normalization of the price is calculated as follow : (price - min)/(max - min) , this calculation is efficient but there is alternates forms such as :
price - (max - min) - min/(max - min)
This alternate form is the one i chosen to make the indicator except that both range (max - min) are smoothed with a simple moving average, there are also additional modifications that you can see on the code.
The Indicator
The indicator return two main lines, in blue the bull line who show the buying force and in red the bear line who show the selling force.
An orange line show the signal line who represent the moving average of the max(bull,bear), this line aim to show possible exit/reversals points for the current trend.
Length control the highest/lowest period as well as the smoothing amount, signal length control the moving average period of the signal line, the pre-filtering setting indicate which smoothing method will be used to smooth the input source before applying normalization.
The default pre-filtering method is the sma.
The ema method is slightly faster as you can see above.
The triangular moving average is the moving average of another moving average, the impulse response of this filter is a triangular function hence its name. This moving average is really smooth.
The lsma or least squares moving average is the fastest moving average used in this indicator, this filter try to best fit a linear function to the data in a certain window by using the least squares method.
No filtering will use the source price without prior smoothing for the indicator calculation.
Relationship With The Stochastic Oscillator
The crosses between the bull and bear line mean that the stochastic oscillator crossed the 50 level. When the Bull line is equal to 0 this mean that the stochastic oscillator is equal to 0 while a bear line equal to 0 mean a stochastic oscillator equal to 100.
The indicator and below a stochastic oscillator of both period 100
Using Levels
Unlike a stochastic oscillator who would clip at the 0 and 100 level the proposed indicator is not heavily constrained in a range like the stochastic oscillator, this mean that you can apply levels to trigger signals
Possible levels could be 1,2,3... even if the indicator rarely go over 3.
Its then possible to create strategies using such levels as support or resistance one.
Conclusion
I've showed a modified stochastic oscillator who aim to show additional information to the user while keeping all the information a classical stochastic oscillator would give. The proposed indicator is no longer constrained in an hard range and posses more liberty to exploit its scale which in return allow to create strategies based on levels.
For pinescript users what you can learn from this is that alternates forms of specific formulas can be extremely interesting to modify, changes can be really surprising so if you are feeling stuck, modifying alternates forms of know indicators can give great results, use tools such as sympy gamma to get alternates forms of formulas.
Thanks for reading !
If you are looking for something or just want to say thanks try to pm me :)
High/Low bandsGives good idea about trend.
In last 100 days the lowest price was this.
In last 100 days the highest price was this.
Price makes new 100 days high! (uptrend)
Chaikin MF% (CMFP) w. Alerts, Bells & Whistles [LucF]This is Chaikin’s Money Flow indicator on a 0-100 scale with buy/sell signals, alerts and other bells & whistles.
It includes:
- a fast EMA (16 periods by default),
- a slow MA (64 periods by default),
- histograms,
- 3 different sorts of crosses,
- big swings identification,
- buy/sell signals on CMFP crossing back from outside user-defined levels,
- buy/sell signals on the slow MA pivots above/below user-defined levels,
- alerts on big swings and buy/sells.
This indicator started with @LazyBear code (VAPI) at:
@cI8DH then changed the scale to 0-100, which I find very useful:
I then added the rest.
The chart above shows both clean and busy versions of the indicator.
Note that the default length is 10 rather than the commonly used 20. I use CMFP in conjunction with VFI and like the fact that it is faster than VFI. The default inputs show the way I normally use this indicator, with the slow MA shown in histogram mode. I find it gives good context to the signal line. Crosses between the two are often useful.
The buy/sell signals aren’t the main attraction of this indicator, and nothing to write home about. Like the big swing markers, I think it’s more realistic to view them as pointers to potentially interesting areas on charts. Their nature makes them more suited to identifying reversals. They certainly aren’t reliable enough to turn this study into a strategy and I normally don’t use them. The levels pre-defined for the buy/sell signals on CMFP are most useful on short intervals. The buy/sell signals on the slow MA pivots work on a more complete range of intervals. Optimization for your specific instruments and intervals will improve their reliability.
As usual when defining alerts, be sure you already have defined proper inputs and that you are on the intended interval, as they will be used when triggering alerts.
3 of SlowStochastics
스토캐스틱 3개를 한번에 볼수 있습니다. 천장과 바닥은 각 100의 위치마다 존재합니다
You can see three slow stochastics at once. The ceiling and floor are located at each 100 (0 - 100 - 200- 300)
Percentage Price Oscillator (PPO)The Percentage Price Oscillator (PPO) is a momentum oscillator that measures the difference between two moving averages as a percentage of the larger moving average. As with its cousin, MACD, the Percentage Price Oscillator is shown with a signal line, a histogram and a centerline. Signals are generated with signal line crossovers, centerline crossovers, and divergences. First, PPO readings are not subject to the price level of the security. Second, PPO readings for different securities can be compared, even when there are large differences in the price.
Calculations
PPO: {(12-day EMA - 26-day EMA)/26-day EMA} x 100
Signal Line: 9-day EMA of PPO
PPO Histogram: PPO - Signal Line
While MACD measures the absolute difference between two moving averages, PPO makes this a relative value by dividing the difference by the slower moving average (26-day EMA). PPO is simply the MACD value divided by the longer moving average. The result is multiplied by 100 to move the decimal place two spots.
Interpretation
As with MACD, the PPO reflects the convergence and divergence of two moving averages. PPO is positive when the shorter moving average is above the longer moving average. The indicator moves further into positive territory as the shorter moving average distances itself from the longer moving average. This reflects strong upside momentum. The PPO is negative when the shorter moving average is below the longer moving average. Negative readings grow when the shorter moving average distances itself from the longer moving average (goes further negative). This reflects strong downside momentum. The histogram represents the difference between PPO and its 9-day EMA, the signal line. The histogram is positive when PPO is above its 9-day EMA and negative when PPO is below its 9-day EMA. The PPO-Histogram can be used to anticipate signal line crossovers in the PPO.
MACD, PPO and Price
MACD levels are affected by the price of a security. A high-priced security will have higher or lower MACD values than a low-priced security, even if volatility is basically equal. This is because MACD is based on the absolute difference in the two moving averages. Because MACD is based on absolute levels, large price changes can affect MACD levels over an extended period of time. If a stock advances from 20 to 100, its MACD levels will be considerably smaller around 20 than around 100. The PPO solves this problem by showing MACD values in percentage terms.
Conclusions
The Percentage Price Oscillator (PPO) generates the same signals as the MACD, but provides an added dimension as a percentage version of MACD. The PPO levels of the Dow Industrials (price > 20K) can be compared against the PPO levels of IBM (price < 200) because the PPO “levels” the playing field. In addition, PPO levels in one security can be compared over extended periods of time, even if the price has doubled or tripled. This is not the case for the MACD.
Limitations
Despite its advantages, the PPO is still not the best oscillator to identify overbought or oversold conditions because movements are unlimited (in theory). Levels for RSI and the Stochastic Oscillator are limited and this makes them better suited to identify overbought and oversold levels.
Source: Stockcharts
Multiple Moving AveragesThis is really simple. But useful for me as I don't have a paid account. No-pro users can only use 3 indicators at once and because I rely heavily on simple moving averages it can be a real pain.
This one indicator features:
20 MA
50 MA
100 MA
200 MA
which I find are the most useful overall. The 20 and 50 over all time frame but in particular < 1 day, the 100 and 200 at > 4 hr time frames. In general I don't use the 100 MA that much. The daily 200 MA is a critical support for many assets like stocks and cryptos. I'm by no means a pro and if you are learning I recommend becoming familiar with moving averages right at the beginning.
If you want to deactivate some of the lines, you can do it via the indicator's settings icon.
Exponential Moving Average (Set of 3) [Krypt] + 13/34 EMAsI took Krypt's script and essentially added on to it.
the 20/50/100/200 EMAs should be used together as support and resistance as normal.
Wait for price to break 200 EMA
Wait for 50 EMA to cross 200 EMA
Wait for pullback to 50 EMA to open position
20 and 100 EMAs are for extra information about moving support and resistance
and 13/34 EMAs should be used in conjunction
When 13 EMA crosses 34 EMA, open position
When price gets far from 13/34, close position (because price will attempt to revert back to mean)
This is better for scalping and swing trades than the 20/50/100/200 setup.
Twitter: @AzorAhai06
Ichimoku Cloud Score v1.0This script calculates a simple Ichimoku Score based on the signals documented here , with a few additions. Each of the score components can be individually weighted via the script inputs . The output is a plot of the normalized Ichimoku score, in the range of -100 to 100.
This script has been heavily modified from 'Ichimoku Cloud Signal Score v2.0.0 '. Credit to user 'dashed' for the initial implementation.
This has been modified with several refinements:
Clean/Organized Code
Simplified Inputs
Improved Style
Scores normalized to a range (-100, 100)
Bugfixes and Improvements
Script Inputs: i.imgur.com
Volume RatioDefinition:
Volume ratio can be obtained in a similar way to RSI.
Volume Ratio (%) = 100 - 100/(1+vr)
The parameter "vr" is defined as
vr=(A+U/2)/(D+U/2)
A=Total volume of the periods when the price advanced
D=Total volume of the periods when the price declined
U=Total volume of the periods when the price unchanged
After substitution, following expression can be derived and the denominator represents total volume of all periods.
Volume Ratio (%) = 100 x (A+U/2)/(A+D+U)
Notes:
A similar method to interpret RSI can be employed.
1) Overbought level over 70% and oversold level under 30%. These levels need to be adjusted according to the periods, time frames and issues.
2) Bullish picture over 50% line and bearish picture under 50% line.
3) Crossing oversold level to the upside can be taken as a confirmation of bullish reversal. - and vice versa for a bearish reversal.
4) After a long-term bearish market, the increase of volume can happen in the early stage of a bullish market.
5) Buying opportunity can be suggested when the volume ratio is declining and the price is either advancing or leveling off.
CCI with Volume Weighted EMA Here is an attempt to improve on the CCI using a volume weighted ema which is then plugged into the CCI formula.
Use:
The CCI with VW EMA is an oscillator that gives readings between -100 and +100. The usual use is to 'go long' with values over +100 and short on values less than -100.
Another use of this oscillator is a countertrend indicator where one sells at crosses under +100 and buys on crosses over -100.
Multi-Functional Fisher Transform MTF with MACDL TRIGGERWhat this indicator gives you is a true signal when price is exhausted and ready for a fast turnaround. Fisher Transform is set for multi-time frame and also allows the user to change the length. This way a user can compare two or more time spans and lengths to look for these MACDL divergent triggers after a Fisher exhaustion. With so many indicators, it's probably best to merge these indicators and change the Fisher and Trigger colors so you can still have a look at price action (remember to scale right after merger). I've noticed from time to time when you have Fisher 34 100 and 300 up and running on two different time frames such as 5 and 15 min charts, with MACDL triggers on the 100/300 or 34/100 you get a high probability trade trigger. However, there are rare exceptions such as when price moves in a parabolic state up or down for a long period where this indication does not work. Ideally this indicator works best in a sideways market or slow rising/descending moving market.
This indicator was worked on by Glaz, nmike and myself
LazyBear also introduced the MACDL indicator
CCI Crossover AlertThis very simple indicator will give you a blue background where the CCI crossed from below -100 to above -100, and a red background where it crossed from above 100 to below 100.
INFLECTION NEXUS - Shadow Portfolio AdaptiveINFLECTION NEXUS - SPA (Shadow Portfolio Adaptive)
Foreword: The Living Algorithm
For decades, technical analysis has been a conversation between a trader and a static chart. We draw our lines, we apply our indicators with their fixed-length inputs, and we hope that our rigid tools can somehow capture the essence of a market that is fluid, chaotic, and perpetually evolving. When our tools fail, we are told to "adapt." But what if the tools themselves could learn that lesson? What if our indicators could adapt not just for us, but with us?
This script, INFLECTION NEXUS - SPA, is the first step in that direction. It is an experimental framework, a research project shared publicly, built around a radical new core: the Shadow Portfolio Adaptive (SPA) Engine . Let's be clear from the outset: the signal logic you see—the buy and sell labels—is a refined version from my previous work, "Turning Point." The signals are not the star of this show. This entire publication is a showcase of the groundbreaking, self-learning engine that now powers them.
You will likely feel that this system is overwhelmingly complex when you first load it. That is by design. This is not another simple crossover indicator. This is a look under the hood of a system designed to emulate the perpetual learning cycle of a human mind. My goal with this document is to break down every single component, every color, every number, into simple, understandable pieces. We will go through this step-by-step, so that by the end, you will not only understand how it works, but you will appreciate the depth of the analysis it performs on your behalf.
This is a beta release. Not all planned features are fully functional, and I will be updating it as the research continues. But the core engine is here, and it represents a new paradigm. Prepare to engage with a script that doesn't just analyze the market—it actively seeks to understand it.
Chapter 1: The Paradigm Shift - Why the SPA Engine is a Leap Forward
To grasp the innovation here, we must first deconstruct the old way of thinking about "adaptive" indicators.
Part A: The Traditional Model - Driving by the Rear-View Mirror
Imagine a self-driving car that can only make adjustments after it has already completed a trip. This is, in essence, how most "adaptive" trading systems work. Their process is fundamentally reactive and inefficient:
Wait for a Signal: The system is idle until its specific, hard-coded logic (e.g., a moving average crossover) generates a buy or sell signal.
Wait for an Outcome: It then waits for that entire trade to play out and close, resulting in a win or a loss.
Collect Limited Data: It only learns from the performance of its own signals. If the market is moving but not generating signals, the system is blind and learns nothing.
Require a Massive Sample Size: To avoid making changes based on random luck, it must wait for a huge number of trades—often 50, 100, or even more—before it has a statistically significant sample of wins and losses.
Make a Belated Adjustment: Finally, after this long "warm-up" period, it will make a tiny, retrospective adjustment to its parameters.
The fatal flaw is obvious: this model is always adapting to a market that no longer exists. It is slow, data-starved, and hopelessly biased by its own signal logic.
Part B: The SPA Model - The Proactive Co-Pilot
The Shadow Portfolio Adaptive (SPA) engine is a complete re-imagining of this process. It is not a reactive historian; it is a proactive, ever-present co-pilot, constantly learning and recalibrating.
It Never Waits: The SPA engine does not wait for a signal to learn. From the moment you load it on the chart, its Shadow Portfolio begins running constant, 5-bar long and short trades in the background. It is not testing a "signal"; it is testing the very fabric of the market, bar by bar.
It is Data-Saturated: Because it learns from every 5-bar slice of price action, the SPA engine gathers a colossal amount of unbiased data. While a traditional system might learn from one trade every 50 bars, the SPA engine learns from a long and a short trade every single bar after its initial cycle.
Instantaneous Market Awareness - The End of the "Warm-Up": This is the core innovation. A traditional adaptive system is effectively useless for the first 50-100 trades. The SPA engine's warm-up period is exactly five bars . On the 6th bar of the chart, the first shadow trade closes, a data point is generated, and the learning process begins. From the 6th bar onward, the engine is market-aware and capable of making intelligent adjustments. The SPA engine isn't adapting to old wins and losses. It is adapting, in near real-time, to the market's ever-shifting character, volatility, and personality.
Chapter 2: The Anatomy of the SPA Engine - A Toddler's Guide to a Complex Brain
The engine is composed of three primary systems that work in a beautiful, interconnected symphony. Let's break them down.
Section 1: The Shadow Portfolio (The Information Harvester)
What it is, Simply: Think of this as the script's eyes and ears. It's a team of 10 virtual traders (5 long, 5 short) who are constantly taking small, quick trades to feel out the market.
How it Works, Simply: On every new bar, a new "long" trader and a new "short" trader enter the market. Exactly 5 bars later, they close their positions. This cycle is perpetual and relentless.
The Critical 'Why': Because these virtual traders enter and exit based on a fixed time (5 bars), not on a "good" or "bad" signal, their results are completely unbiased . They are simply measuring: "What happened to price over the last 5 bars?" This provides the raw, untainted truth about the market's behavior that the rest of the system needs to learn effectively.
The Golden Metric (ATR Normalization): The engine doesn't just look at dollar P&L. It's smarter than that. It asks a more intelligent question: "How much did this trade make relative to the current volatility?"
Analogy: Imagine a flea and an elephant. If they both jump 1 inch, who is more impressive? The flea. The SPA engine understands this. A $10 profit when the market is dead quiet is far more significant than a $10 profit during a wild, volatile swing.
The Formula: realized_atr = (close - trade.entry) / trade.atr_entry. It takes the raw profit and divides it by the Average True Range (a measure of volatility) at the moment of entry. This gives a pure, "apples-to-apples" score for every single trade, which is the foundational data point for all learning.
Section 2: The Cognitive Map (The Long-Term Brain)
What it is, Simply: This is the engine's deep memory, its library of experiences. Imagine a giant, 64-square chessboard (8x8 grid). Each square on the board represents a very specific type of market environment.
The Two Dimensions of Thought (The 'How'): How does it know which square we are on? It looks at two things:
The Market's Personality (X-Axis): Is the market behaving like a disciplined soldier, marching in a clear trend? Or is it like a chaotic, unpredictable child, running all over the place? The engine calculates a "Regime" score to figure this out.
The Market's Energy Level (Y-Axis): Is the market sleepy and quiet, or is it wide-awake and hyperactive? The engine measures "Normalized Volatility" to determine this.
The Power of Generalization (The 'Why'): When a Shadow Portfolio trade closes, its result is recorded in the corresponding square on the chessboard. But here's the clever part: it also shares a little bit of that lesson with the squares immediately next to it (using a Gaussian Kernel).
Analogy: If you touch a hot stove and learn "don't touch," your brain is smart enough to know you probably shouldn't touch the hot oven door next to it either, even if you haven't touched it directly. The Cognitive Map does the same thing, allowing it to make intelligent inferences even in market conditions it has seen less frequently. Each square remembers what indicator settings worked best in that specific environment.
Section 3: The Adaptive Engine (The Central Nervous System)
What it is, Simply: This is the conductor of the orchestra. It takes information from all other parts of the system and decides exactly what to do.
The Symphony of Inputs: It listens to three distinct sources of information before making a decision:
The Short-Term Memory (Rolling Stats): It looks at the performance of the last rollN shadow trades. This is its immediate, recent experience.
The Long-Term Wisdom (Cognitive Map): It consults the grand library of the Cognitive Map to see what has worked best in the current market type over the long haul.
The Gut Instinct (Bin Learning): It keeps a small "mini-batch" of the most recent trades. If this batch shows a very strong, sudden pattern, it can trigger a rapid, reflexive adjustment, like pulling your hand away from a flame.
The Fusion Process: It then blends these three opinions together in a sophisticated way. It gives more weight to the opinions it's more confident in (e.g., a Cognitive Map square with hundreds of trades of experience) and uses your Adaptation Intensity (dialK) input to decide how much to listen to its "gut instinct." The final decision is then smoothed to ensure the indicator's parameters change in a stable, intelligent way.
Chapter 3: The Control Panel - A Granular Guide to the Inputs
Every input is a lever to tune the engine. Let's demystify them.
🧾 Signal Engine (Original): These inputs control the "Turning Point" signal logic.
What they are: Toggles for Reversal Mode (catch tops/bottoms) and Breakout Mode (follow the trend), plus filters like Require New Extreme to ensure signals come from points of extension.
How to use them: For a ranging market, you might favor Reversal mode. For a strongly trending market, Breakout mode might be better. These settings fine-tune the final alert, which is powered by the adaptive engine.
🎛️ Master Control:
Adaptation Intensity (dialK): THIS IS THE MOST IMPORTANT INPUT. It controls the personality of the learning engine.
Low Setting (1-5): Creates a "Wise Old Professor" engine. It's patient, learns from larger batches of data, and makes slow, deliberate, and highly confident adjustments. Use this for stable assets like indices or blue-chip stocks.
High Setting (15-20): Creates a "Hyper-Reactive Day Trader" engine. It learns from tiny samples, trusts its gut instinct, and makes large, aggressive adjustments to keep up with a frantic market. Use this for highly volatile assets like crypto or meme stocks.
🧠 Adaptive Engine & 🎯 Learning:
What they are: The deep mechanics of the learning process. Base Learn Rate is the fundamental step size of adjustments. Rolling Window Size is the length of its "short-term memory." Adaptation Momentum controls how smoothly the parameters transition to their new learned values.
How to use them: For most users, the defaults are well-balanced. Advanced users can tweak these to make the engine even more or less sensitive to new information.
🗺️ Cognitive Map, STM & Checkpoints:
What they are: Controls for the engine's brain. Enable Cognitive Map turns on the long-term memory.
The Checkpoint System - Your "Save Game" Feature: This is incredibly powerful.
To Save: Toggle Emit Checkpoint Now. Go to your alert log, and you will see a very long string of text. Copy this entire string.
To Load: Paste that string into the Memory Checkpoint input box. Toggle Apply Checkpoint On Next Bar. The script will instantly load its entire "brain"—every learned parameter and all 64 cells of the Cognitive Map. You can train the engine on one chart and transfer its intelligence to another.
Chapter 4: The Command Center - Decoding the Dashboard
This is your window into the engine's mind. Do not be intimidated. Let's break it down.
PANEL A (INFLECTION NEXUS): The high-level overview.
Market Context: See how the engine classifies the market's Trend and Regime (personality).
Shadow Portfolio Summary: The engine's report card. Watch the Win Rate and Avg P&L to see the quality of the raw data it's learning from.
PANEL B (SHADOW PORTFOLIO ADAPTIVE): The deep diagnostics.
Performance Metrics: Advanced stats like Sharpe Ratio (return vs. risk) and Sortino Ratio (return vs. downside risk). This tells you about the quality and consistency of the market movements the engine is analyzing.
Adaptive Parameters (Live vs Base): THIS IS THE MOST IMPORTANT SECTION. It shows the engine's Live parameters right next to your (Base) inputs.
How to interpret it: If you see the Live ATR Len is 45 while your Base input is 20, the engine is telling you: "The market is in a long, smooth trend right now. Short-term noise is a trap. I have learned that we must use a longer-term perspective to see clearly." This section translates the engine's learning directly into actionable insight.
Memory Log: A live ticker of the engine's thoughts, showing every trade it learns from and every adaptation it makes.
Chapter 5: Reading the Canvas - On-Chart Visuals
The Bands (Green/Blue Lines): These are not static Supertrend lines. They are the
physical manifestation of the engine's current thinking. As the engine learns and adapts its ATR Period and Multiplier, you will see these bands widen, tighten, and adjust their distance from price. They are alive.
The Labels (BUY/SELL): These are the final output of the "Turning Point" logic, now supercharged and informed by the fully adaptive SPA engine.
The Purple Pulse (Dot and Background Glow): This is your visual cue that the engine is "thinking." Every time you see this pulse, it means the SPA has just completed a learning cycle and updated its parameters. It is actively recalibrating itself to the market.
Chapter 6: A Personal Manifesto on Innovation
I want to conclude with a personal note on why I dedicate countless hours to building systems like this and sharing them openly.
My purpose is to drive innovation, period. I am not in this space to follow the crowd or to re-package old ideas. The world does not need a 100th version of a slightly modified MACD. Real progress comes from venturing into the wilderness, from asking difficult questions, and from pursuing concepts that lie at the very edge of possibility.
I am not afraid of being wrong. I am not afraid of being bested by my peers. In fact, I welcome it. If another developer takes an idea from this engine, improves it, and builds something even more magnificent, that is a profound win for our entire community. The only failure I recognize is the failure to try. The only trap I fear is the creative complacency of producing sterile, recycled work just to appease the status quo.
I love this community, and I believe with every fiber of my being that we have barely scratched the surface of what can be discovered and created. This script is my contribution to that shared journey. It is a tool, an idea, and a challenge to all of us: let's keep pushing.
DISCLAIMER: This script is an experimental framework provided for educational and research purposes ONLY. It is not financial advice. All trading involves substantial risk of loss. Past performance is not indicative of future results. Please use this tool responsibly and as part of a comprehensive trading plan.
As the great computer scientist Herbert A. Simon, a pioneer of artificial intelligence, famously said:
"Learning is any process by which a system improves performance from experience."
May this engine enhance your experience.
— Dskyz, for DAFE Trading Systems
Momentum Shift Oscillator (MSO) [SharpStrat]Momentum Shift Oscillator (MSO)
The Momentum Shift Oscillator (MSO) is a custom-built oscillator that combines the best parts of RSI, ROC, and MACD into one clean, powerful indicator. Its goal is to identify when momentum shifts are happening in the market, filtering out noise that a single momentum tool might miss.
Why MSO?
Most traders rely on just one momentum indicator like RSI, MACD, or ROC. Each has strengths, but also weaknesses:
RSI → great for overbought/oversold, but often lags in strong trends.
ROC (Rate of Change) → captures price velocity, but can be too noisy.
MACD Histogram → shows trend strength shifts, but reacts slowly at times.
By blending all three (with adjustable weights), MSO gives a balanced view of momentum. It captures trend strength, velocity, and exhaustion in one oscillator.
How MSO Works
Inputs:
RSI, ROC, and MACD Histogram are calculated with user-defined lengths.
Each is normalized (so they share the same scale of -100 to +100).
You can set weights for RSI, ROC, and MACD to emphasize different components.
The components are blended into a single oscillator value.
Smoothing (SMA, EMA, or WMA) is applied.
MSO plots as a smooth line, color-coded by slope (green rising, red falling).
Overbought and oversold levels are plotted (default: +60 / -60).
A zero line helps identify bullish vs bearish momentum shifts.
How to trade with MSO
Zero line crossovers → crossing above zero suggests bullish momentum; crossing below zero suggests bearish momentum.
Overbought and oversold zones → values above +60 may indicate exhaustion in bullish moves; values below -60 may signal exhaustion in bearish moves.
Slope of the line → a rising line shows strengthening momentum, while a falling line signals fading momentum.
Divergences → if price makes new highs or lows but MSO does not, it can point to a possible reversal.
Why MSO is Unique
Combines trend + momentum + velocity into one view.
Filters noise better than standalone RSI/MACD.
Adapts to both trend-following and mean-reversion styles.
Can be used across any timeframe for confirmation.
Japan Yen Carry Trade to Risk Ratio Sharpe Ratio By UncleBFMStep-by-Step Calculation in the ScriptFetch Rates:Pulls rates dynamically using request.security() from user-specified symbols (e.g., TVC:JP10Y for yen, TVC:US10Y for target). If unavailable (NA), uses fallback inputs (e.g., 0.25% for yen, 4.50% for target).
Converts rates to decimals: (target_rate - yen_rate) / 100.
Calculate Carry:Carry = (Target Rate - Yen Rate) / 100
Example: If US 10Y yield is 4.50% and Japan 10Y is 0.25%, carry = (4.50 - 0.25) / 100 = 0.0425 (4.25% annual yield).
Calculate Daily Log Returns:Log Returns = ln(Close / Close ), where Close is the current price of the pair (e.g., USDJPY) and Close is the previous day's price.
This measures daily percentage changes in a way suitable for volatility calculations.
Calculate Annualized Volatility:Volatility = Standard Deviation of Log Returns over a lookback period (default 63 days, ~3 months) × √252.
Example: If the standard deviation of USDJPY log returns is 0.005 (0.5% daily), annualized volatility = 0.005 × √252 ≈ 0.0794 (7.94%).
Compute the Ratio:Ratio = Carry / Volatility
Example: Using above, 0.0425 / 0.0794 ≈ 0.535.
If volatility is zero, the ratio is set to NA to avoid division errors.
Plot:Plots the ratio as a line, with optional thresholds (e.g., 0.2 for "high attractiveness") to guide interpretation.
NotesDynamic Rates: Using bond yields (e.g., TVC:JP10Y) or policy rates (e.g., ECONOMICS:JPINTR) makes the indicator responsive to historical and current rate changes, unlike static inputs.
Context: BIS reports use similar ratios to assess carry trade viability. For USDJPY in 2025, with Fed rates around 4.5% and BoJ at 0.25–0.5%, the carry is positive but sensitive to volatility spikes (e.g., during 2024 unwind events).
Usage: Apply to a yen pair chart (e.g., USDJPY, AUDJPY). Adjust symbols for the target currency (e.g., TVC:AU10Y for AUD). The ratio helps compare carry trade profitability across pairs or over time.
ORB + Session VWAP Pro (London & NY) — fixedORB + Session VWAP Pro (London & NY) — Listing copy (EN)
What it is
A clean, non-repainting intraday tool that fuses the classic Opening Range Breakout (ORB) with a session-anchored VWAP filter for London and New York. It highlights only the higher-quality breakouts (above/below session VWAP), adds an optional retest confirmation, and scores each signal with an intuitive Confidence metric (0–100).
Why it works
• ORB provides the day’s first actionable structure (range high/low).
• Session VWAP filters “cheap” breaks and favors flows aligned with session value.
• Optional retest reduces first-tick whipsaws.
• Confidence blends breakout depth (vs ATR), VWAP slope and band distance.
Key visuals
• LDN/NY OR High/Low (line break style) + optional OR boxes.
• Active Session VWAP (resets per signal window; falls back to daily VWAP outside).
• Optional VWAP bands (stdev or %).
• Session shading (London/NY windows).
• Signal markers (LDN BUY/SELL, NY BUY/SELL) fired with cooldown.
Signals
• London Long / Short: Break of LDN OR High/Low ± ATR buffer, aligned with VWAP side.
• NY Long / Short: Same logic during NY window.
• Retest (optional): Requires a tag back to the OR level ± tolerance before confirmation.
• Confidence: 0–100; gate via Min Confidence (default 55).
Inputs that matter
• Open Range Length (min): Default 15.
• London/NY times & timezones.
• ATR buffer & retest tolerance.
• Bands mode: Stdev (with lookback) or % (e.g., 1%).
• Signal cooldown: Avoids clutter on fast moves.
Non-repaint policy
• OR lines build within fixed time windows using the current bar’s timestamp.
• VWAP is cumulative within the session window; no lookahead.
• All ta.crossover/ta.crossunder are precomputed every bar (no conditional execution).
• Signals are based on live bar values, not future bars.
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Quick start (examples)
1) EURUSD, London momentum
• Chart: 5m or 15m.
• OR: 15 min starting 08:00 Europe/London.
• Signals: Use defaults; keep ATR buffer = 0.2 and Retest = ON, Min Confidence ≥ 55.
• Play:
• BUY when price breaks LDN OR High + buffer and stays above VWAP; retest confirms.
• Trail behind VWAP or band #1; partials into band #2.
2) NAS100, New York breakout & run
• Chart: 5m.
• NY window: 09:30 America/New_York, OR = 15 min.
• Retest OFF on high momentum days; Min Confidence ≥ 60.
• Use band mode Stdev, bandLen=50, show ±1/±2.
• Momentum continuation: add on pullbacks that hold above VWAP after the breakout.
3) XAUUSD, London fake & VWAP fade
• Chart: 5m.
• Keep Retest ON; accept only shorts that break OR Low but retest fails back under VWAP.
• Confidence gate ≥ 50 to allow more mean-reversion setups.
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Pro tips
• Adjust ATR buffer to the instrument: FX 0.15–0.25, indices 0.20–0.35, metals 0.20–0.30.
• Retest ON for choppy conditions; OFF for news momentum.
• Use VWAP bands: take partials at ±1; stretch targets at ±2/±3.
• Session timezones are explicit (London/New York). Ensure they match your instrument’s behavior.
• Pair with a higher-TF bias (e.g., 1H/4H trend) for directional filtering.
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Alerts (ready to use)
• ORB+SVWAP — LDN Long, LDN Short, NY Long, NY Short
(Respect your cooldown; alerts fire only after confirmation and confidence gate.)
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Known limits & notes
• Designed for intraday. On 1D+ charts, session windows compress.
• If your broker session differs from London/NY clocks on a holiday, adjust input times.
• Session-anchored VWAP uses the script’s signal window, not exchange sessions, by design.
DynamoSent DynamoSent Pro+ — Professional Listing (Preview)
— Adaptive Macro Sentiment (v6)
— Export, Adaptive Lookback, Confidence, Boxes, Heatmap + Dynamic OB/OS
Preview / Experimental build. I’m actively refining this tool—your feedback is gold.
If you spot edge cases, want new presets, or have market-specific ideas, please comment or DM me on TradingView.
⸻
What it is
DynamoSent Pro+ is an adaptive, non-repainting macro sentiment engine that compresses VIX, DXY and a price-based activity proxy (e.g., SPX/sector ETF/your symbol) into a 0–100 sentiment line. It scales context by volatility (ATR%) and can self-calibrate with rolling quantile OB/OS. On top of that, it adds confidence scoring, a plain-English Context Coach, MTF agreement, exportable sentiment for other indicators, and a clean Light/Dark UI.
Why it’s different
• Adaptive lookback tracks regime changes: when volatility rises, we lengthen context; when it falls, we shorten—less whipsaw, more relevance.
• Dynamic OB/OS (quantiles) self-calibrates to each instrument’s distribution—no arbitrary 30/70 lines.
• MTF agreement + Confidence gate reduce false positives by highlighting alignment across timeframes.
• Exportable output: hidden plot “DynamoSent Export” can be selected as input.source in your other Pine scripts.
• Non-repainting rigor: all request.security() calls use lookahead_off + gaps_on; signals wait for bar close.
Key visuals
• Sentiment line (0–100), OB/OS zones (static or dynamic), optional TF1/TF2 overlays.
• Regime boxes (Overbought / Oversold / Neutral) that update live without repaint.
• Info Panel with confidence heat, regime, trend arrow, MTF readout, and Coach sentence.
• Session heat (Asia/EU/US) to match intraday behavior.
• Light/Dark theme switch in Inputs (auto-contrasted labels & headers).
⸻
How to use (examples & recipes)
1) EURUSD (swing / intraday blend)
• Preset: EURUSD 1H Swing
• Chart: 1H; TF1=1H, TF2=4H (default).
• Proxies: Defaults work (VIX=D, DXY=60, Proxy=D).
• Dynamic OB/OS: ON at 20/80; Confidence ≥ 55–60.
• Playbook:
• When sentiment crosses above 50 + margin with Δ ≥ signalK and MTF agreement ≥ 0.5, treat as trend breakout.
• In Oversold with rising Coach & TF agreement, take fade longs back toward mid-range.
• Alerts: Enable Breakout Long/Short and Fade; keep cooldown 8–12 bars.
2) SPY (daytrading)
• Preset: SPY 15m Daytrade; Chart: 15m.
• VIX (D) matters more; preset weights already favor it.
• Start with static 30/70; later try dynamic 25/75 for adaptive thresholds.
• Use Coach: in US session, when it says “Overbought + MTF agree → sell rallies / chase breakouts”, lean momentum-continuation after pullbacks.
3) BTCUSD (crypto, 24/7)
• Preset: BTCUSD 1H; Chart: 1H.
• DXY and BTC.D inform macro tone; keep Carry-forward ON to bridge sparse ticks.
• Prefer Dynamic OB/OS (15/85) for wider swings.
• Fade signals on weekend chop; Breakout when Confidence > 60 and MTF ≥ 1.0.
4) XAUUSD (gold, macro blend)
• Preset: XAUUSD 4H; Chart: 4H.
• Weights tilt to DXY and US10Y (handled by preset).
• Coach + MTF helps separate trend legs from news pops.
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Best practices
• Theme: Switch Light/Dark in Inputs; the panel adapts contrast automatically.
• Export: In another script → Source → DynamoSent Pro+ → DynamoSent Export. Build your own filters/strategies atop the same sentiment.
• Dynamic vs Static OB/OS:
• Static 30/70: fast, universal baseline.
• Dynamic (quantiles): instrument-aware; use 20/80 (default) or 15/85 for choppy markets.
• Confidence gate: Start at 50–60% to filter noise; raise when you want only A-grade setups.
• Adaptive Lookback: Keep ON. For ultra-liquid indices, you can switch it OFF and set a fixed lookback.
⸻
Non-repainting & safety notes
• All request.security() calls use lookahead=barmerge.lookahead_off and gaps=barmerge.gaps_on.
• No forward references; signals & regime flips are confirmed on bar close.
• History-dependent funcs (ta.change, ta.percentile_linear_interpolation, etc.) are computed each bar (not conditionally).
• Adaptive lookback is clamped ≥ 1 to avoid lowest/highest errors.
• Missing-data warning triggers only when all proxies are NA for a streak; carry-forward can bridge small gaps without repaint.
⸻
Known limits & tips
• If a proxy symbol isn’t available on your plan/exchange, you’ll see the NA warning: choose a different symbol via Symbol Search, or keep Carry-forward ON (it defaults to neutral where needed).
• Intraday VIX is sparse—using Daily is intentional.
• Dynamic OB/OS needs enough history (see dynLenFloor). On short histories it gracefully falls back to static levels.
Thanks for trying the preview. Your comments drive the roadmap—presets, new proxies, extra alerts, and integrations.
EMA50 + SR Boxes + VP Right + ATR + SL% + Entries + SentimentThis indicator combines several pro-grade building blocks to read the market at a glance:
EMA50 as a trend filter.
Smart Support/Resistance zones (rectangles) detected where price has touched multiple times.
“U / Inverted U” markers (confirmed pivots).
Optional Buy/Sell signals: only when a U appears inside a support zone with price above the EMA50 (buy), or an inverted U inside a resistance zone with price below the EMA50 (sell).
Simplified right-side Volume Profile (with a special Forex fallback if volume isn’t usable).
ATR & SL%: displays current ATR and an SL% based on ATR(100) Daily / Close × 100, attached to the latest candle.
Trinity Multi-Timeframe MA TrendOriginal script can be found here: {Multi-Timeframe Trend Analysis } www.tradingview.com
1. all credit the original author www.tradingview.com
2. why change this script:
- added full transparency function to each EMA
- changed to up and down arrows
- change the dashboard to be able to resize and reposition
How to Use This Indicator
This indicator, "Trinity Multi-Timeframe MA Trend," is designed for TradingView and helps visualize Exponential Moving Average (EMA) trends across multiple timeframes. It plots EMAs on your chart, fills areas between them with directional colors (up or down), shows crossover/crossunder labels, and displays a dashboard table summarizing EMA directions (bullish ↑ or bearish ↓) for selected timeframes. It's useful for multi-timeframe analysis in trading strategies, like confirming trends before entries.
Configure Settings (via the Gear Icon on the Indicator Title):
Timeframes Group: Set up to 5 custom timeframes (e.g., "5" for 5 minutes, "60" for 1 hour). These determine the multi-timeframe analysis in the dashboard. Defaults: 5m, 15m, 1h, 4h, 5h.
EMA Group: Adjust the lengths of the 5 EMAs (defaults: 5, 10, 20, 50, 200). These are the moving averages plotted on the chart.
Colors (Inline "c"): Choose uptrend color (default: lime/green) and downtrend color (default: purple). These apply to plots, fills, labels, and dashboard cells.
Transparencies Group: Set transparency levels (0-100) for each EMA's plot and fill (0 = opaque, 100 = fully transparent). Defaults decrease from EMA1 (80) to EMA5 (0) for a gradient effect.
Dashboard Settings Group (newly added):
Dashboard Position: Select where the table appears (Top Right, Top Left, Bottom Right, Bottom Left).
Dashboard Size: Choose text size (Tiny, Small, Normal, Large, Huge) to scale the table for better visibility on crowded charts.
Understanding the Visuals:
EMA Plots: Five colored lines on the chart (EMA1 shortest, EMA5 longest). Color changes based on direction: uptrend (your selected up color) if rising, downtrend (down color) if falling.
Fills Between EMAs: Shaded areas between consecutive EMAs, colored and transparent based on the faster EMA's direction and your transparency settings.
Crossover Labels: Arrow labels (↑ for crossover/uptrend start, ↓ for crossunder/downtrend start) appear on the chart at EMA direction changes, with tooltips like "EMA1".
Dashboard Table (top-right by default):
Rows: EMA1 to EMA5 (with lengths shown).
Columns: Selected timeframes (converted to readable format, e.g., "5m", "1h").
Cells: ↑ (bullish/up) or ↓ (bearish/down) arrows, colored green/lime or purple based on trend, with fading transparency for visual hierarchy.
Use this to quickly check alignment across timeframes (e.g., all ↑ in multiple TFs might signal a strong uptrend).
Trading Tips:
Trend Confirmation: Look for alignment where most EMAs in higher timeframes are ↑ (bullish) or ↓ (bearish).
Entries/Exits: Use crossovers on the chart EMAs as signals, confirmed by the dashboard (e.g., enter long if lower TF EMA crosses up and higher TFs are aligned).
Customization: On lower timeframe charts, set dashboard timeframes to higher ones for top-down analysis. Adjust transparencies to avoid chart clutter.
Limitations: This is a trend-following tool; combine with volume, support/resistance, or other indicators. Backtest on historical data before live use.
Performance: Works best on trending markets; may whipsaw in sideways conditions.
