Wraith Protocol | PUT & CALL VP LevelsThis is a dual Volume Profile indicator built in Pine Script v5. It computes two independent volume profiles — one for a "PUT" lookback window and one for a "CALL" lookback window — and extracts the three key auction market theory levels from each: the Value Area High (VAH), the Point of Control (POC), and the Value Area Low (VAL). These levels are drawn as persistent horizontal lines across the chart with labeled price annotations, a colored histogram, and a summary data table.
The PUT and CALL naming convention frames these levels as options-market analog reference zones — the PUT profile represents a longer-term bearish/support structure, while the CALL profile represents a shorter-term bullish/resistance structure. Neither pulls actual options data; the names are a conceptual framing applied to standard price/volume data.
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Section-by-Section Breakdown
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1. Inputs
Volume Profile group:
Profile Rows — how many horizontal price buckets to divide the range into (default 24). More rows = finer resolution.
Histogram Max Width (bars) — the visual width of the histogram in bar units (default 30).
Show Histogram — toggle the visual bars on/off.
PUT Levels group:
PUT Lookback Bars — how many bars back to include in the PUT profile (default 150, i.e. a longer-term window).
PUT Value Area % — the percentage of total volume that defines the Value Area (default 70%). Standard TPO/VP convention uses 70%.
Show PUT Levels — toggle all PUT lines/labels on/off.
PUT VAH / POC / VAL color pickers — individual line color controls.
CALL Levels group:
Same structure as PUT but defaults to a shorter 70-bar lookback. This creates a faster-moving, nearer-term profile.
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Style group:
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Extend Lines Right — extends all lines to the right edge of the chart (infinite extend).
Label Size — controls the text size of all price labels (tiny → huge).
2. Volume Profile Engine (same logic runs twice — for PUT and CALL)
Step 1 — Find the high/low range of the lookback window.
The script loops backward over the specified number of bars and finds the highest high and lowest low in that window. This becomes the price range for the profile.
Step 2 — Distribute volume into rows (buckets).
The range is divided into rows equally-spaced price buckets. For every bar in the lookback window, its volume is distributed proportionally across whichever buckets its high-low range overlaps. The formula is:
allocated volume = bar volume × (overlap length / bar range)
If a bar's range is zero (doji), it uses the bucket step size as a fallback to avoid division by zero.
Step 3 — Find the POC.
The bucket with the highest accumulated volume is the Point of Control (POC) — the price level where the most trading activity occurred.
Step 4 — Build the Value Area.
Starting from the POC, the script expands outward one bucket at a time, always adding the larger neighbor first (up or down), until the cumulative volume in the growing range reaches the target Value Area % of total volume. The top of the upper boundary is the VAH; the bottom of the lower boundary is the VAL.
3. Histogram Drawing
On the last bar (barstate.islast), old histogram boxes are deleted and new ones are drawn. Each row gets a colored box whose width is proportional to its volume relative to the max-volume row. Opacity varies by context:
POC row → fully opaque (transparency = 0)
Inside Value Area → semi-transparent (40)
Outside Value Area → mostly transparent (70)
PUT histogram uses red; CALL histogram uses teal. Each starts at bar_index - lookback + 1 so the histogram aligns to its respective lookback window.
4. Lines & Labels
All six lines (PUT VAH/POC/VAL, CALL VAH/POC/VAL) are deleted and redrawn on every last-bar execution, which means they update in real time as new bars form.
VAH lines — solid, width 2, extending right
POC lines — dashed, width 2, extending right
VAL lines — solid, width 2, extending right
Labels are placed at histogram_left + histogram_width + 1, i.e. just to the right of each histogram. Label text includes a human-readable role name ("PUT VAH DN SELLER EXIT", "PUT VAL BUYER EXIT", "CALL VAH BUYER EXIT", "CALL VAL DN SELLER EXIT") plus the live price value formatted to 2 decimal places.
The label role convention follows auction market logic:
Level Interpretation PUT VAHDownside seller exhaustion — sellers who pushed price into the PUT range may exit here PUT VAL Buyers who entered in the PUT range may exit here CALL VAH Buyers who pushed price into the CALL range may exit here CALL VAL Downside sellers may exit here, near the base of CALL value
5. Data Window Plots
Six plot() calls with display=display.data_window expose all six levels in TradingView's Data Window panel. They are not drawn on the chart (no display.pane) — they exist purely for external access, alerts, or Pine Strategy consumption.
6. Info Table (Bottom Right)
A persistent 3-column × 8-row table summarizes everything in one glance:
Row Content Header "Level", "PUT (Nb)", "CALL (Nb)"VAHPUT and CALL VAH prices POC PUT and CALL POC prices VAL PUT and CALL VAL prices Spread VAH − VAL for each profile (range of the Value Area)PUT Bias "ABOVE POC" / "BELOW POC" relative to current close — green or red CALL Bias Same for CALL profile VA %The configured value area percentage for each profile
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Key Design Decisions:
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Why barstate.islast only? Volume profiles are computationally expensive. Running them on every bar would be slow and generate thousands of orphaned drawing objects. By running only on the last bar and deleting/redrawing all objects, the script stays clean and efficient.
Why two separate lookbacks? The asymmetry between a 150-bar PUT profile and a 70-bar CALL profile is intentional. It creates structural levels at two different temporal horizons — analogous to how options traders think about near-term (gamma) vs. longer-term (delta) positioning zones.
Why var declarations for lines/labels? var preserves the last-assigned object reference across bars so the script can explicitly delete the previous versions before drawing new ones — preventing object accumulation.
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Usage Notes:
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Works on any instrument and timeframe; the lookback bars are bar-count based, not time-based.
Lowering Profile Rows to 10–15 gives broader, more tradeable zones. Increasing it to 40+ gives precision but may over-fit to noise.
The "Extend Lines Right" toggle is useful when you want clean horizontal levels extending into the future for forward reference.
The PUT/CALL bias rows in the table provide a quick structural read: if price is above both POCs, the profile structure is broadly bullish; below both is broadly bearish; split is a contested/transitional market.
Ref: My previous Script- Wraith Protocol
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IMPORTANT NOTES
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• This indicator is for informational and educational purposes only.
It does not constitute financial advice.
• Past performance of any level or signal does not guarantee future results.
• Always use proper risk management and combine with your own analysis.
• The Estimate field is a directional bias tool, not a trade signal.
• Best used as a confluence layer alongside your primary strategy. Enjoy !! Indicatore
Put/Call RatioPut/Call Ratio Indicator
This indicator visualizes the Put/Call Ratio for various market symbols, helping traders assess market sentiment and potential reversals. It offers a dropdown menu to select from a range of Put/Call Ratios, including broad equities (CBOE), major indices (SPX, QQQ, IWM, VIX), and individual stocks (TSLA, GOOG, META, AMZN, MSFT, INTC).
The indicator plots the Put/Call Ratio with adjustable moving averages and standard deviation bands to highlight overbought or oversold conditions. A short-term moving average (default: 10 periods) is displayed with trend-based coloring, while longer-term moving averages (defaults: 30 and 200 periods) are calculated but hidden by default. Bands at 1, 1.5, and 2 standard deviations provide context for extreme readings.
Key Overbought/Oversold Signals:
Short-Term Extremes: The 10-day moving average moves beyond 1 standard deviation from the 200-day moving average, signaling potential overbought (above) or oversold (below) conditions. This will be highlighted by red or green background color.
Ratio Extremes: The Put/Call Ratio line itself crosses outside 2 standard deviations from the 200-day moving average, indicating stronger overbought or oversold zones.
Conditional coloring of the ratio line reflects its position relative to the bands, and background shading highlights when the short-term moving average crosses key levels.
Key Features:
Selectable Put/Call Ratio symbols.
Trend-colored moving averages.
Standard deviation bands for volatility analysis.
Dynamic line and background coloring for quick insights.
Usage:
Use this indicator to gauge market sentiment—high ratios may suggest bearish sentiment or oversold conditions, while low ratios may indicate bullish sentiment or overbought conditions. Combine with price action or other tools for confirmation. Indicatore
Indicatore
Put to Call Ratio CorrelationHello!
Excited to share this with the community!
This is actually a very simple indicator but actually usurpingly helpful, especially for those who trade indices such as SPX, IWM, QQQ, etc.
Before I get into the indicator itself, let me explain to you its development.
I have been interested in the use of option data to detect sentiment and potential reversals in the market. However, I found option data on its own is full of noise. Its very difficult if not impossible for a trader to make their own subjective assessment about how option data is reflecting market sentiment.
Generally speaking, put to call ratios generally range between 0.8 to 1.1 on average. Unless there is a dramatic pump in calls or puts causing an aggressive spike up to over this range, or fall below this range, its really difficult to make the subjective assessment about what is happening.
So what I thought about trying to do was, instead of looking directly at put to call ratio, why not see what happens when you perform a correlation analysis of the PTC ratio to the underlying stock.
So I tried this in pinescript, pulling for Tradingview's ticker PCC (Total Equity Put to Call Ratio) and using the ta.correlation function against whichever ticker I was looking at.
I played around with this idea a bit, pulled the data into excel and from this I found something interesting. When there is a very significant negative or positive correlation between PTC ratio and price movement, we see a reversal impending. In fact, a significant negative or positive correlation (defined as a R value of 0.8 or higher or -0.8 or lower) corresponded to a stock reversal about 92% of the time when data was pulled on a 5 minute timeframe on SPY.
But wait, what is a correlation?
If you are not already familiar, a correlation is simply a statistical relationship. It is defined with a Pearson R correlation value which ranges from 0 (no correlation) to 1 (significant positive correlation) and 0 to -1 (significant negative correlation).
So what does positive vs negative mean?
A significant positive correlation means the correlation is moving the same as the underlying. In the case of this indicator, if there is a significant positive correlation could mean the stock price is climbing at the same time as the PTC ratio.
Inversely, it could mean the stock price is falling as well as the PTC ratio.
A significant negative correlation means the correlation is moving in the opposite direction. So in this case, if the stock price is climbing and the PTC ratio is falling proportionately, we would see a significant negative correlation.
So how does this work in real life?
To answer this, let's get into the actual indicator!
In the image above, you will see the arrow pointing to an area of significant POSITIVE correlation.
The indicator will paint the bars on the actual chart purple (customizable of course) to signify this is an area of significant correlation.
So, in the above example this means that the PTC ratio is increase proportionately to the increase in the stock price in the SAME direction (Puts are going up proportionately to the stock price). Thus, we can make the assumption that the underlying sentiment is overwhelmingly BEARISH. Why? Because option trading activity is significantly proportionate to stock movement, meaning that there is consensus among the options being traded and the movement of the market itself.
And in the above example we will see, the stock does indeed end up selling:
In this case, IWM fell roughly 1 point from where there was bearish consensus in the market.
Let's use this same trading day and same example to show the inverse:
You will see a little bit later, a significant NEGATIVE correlation developed.
In this case identified, the stock wise RISING and the PTC ratio was FALLING.
This means that Puts were not being bought up as much as calls and the sentiment had shifted to bullish .
And from that point, IWM ended up going up an additional 0.75 points from where there was a significant INVERSE correlation.
So you can see that it is helpful for identifying reversals. But what is also can be used for is identifying areas of LOW conviction. Meaning, areas where there really is no relationship between option activity and stock movement. Let's take spy on the 1 hour timeframe for this example:
You can see in the above example there really is no consensus in the option trading activity with the overarching sentiment. The price action is choppy and so too is option trading activity. Option traders are not pushing too far in one direction or the other. We can also see the lack of conviction in the option trading activity by looking at the correlation SMA (the white line).
When a ticker is experiencing volatile and good movement up and down, the SMA will generally trade to the top of the correlation range (roughly + 1.0) and then make a move down to the bottom (roughly - 1.0), see the example below:
When the SMA is not moving much and accumulating around the centerline, it generally means a lot of indecision.
Additional Indicator Information:
As I have said, the indicator is very simple. It pulls the data from the ticker PCC and runs a correlation assessment against whichever ticker you are on.
PCC pulls averaged data from all equities within the market and is not limited to a single equity. As such, its helpful to use this with indices such as SPY, IWM and QQQ, but I have had success with using it on individual tickers such as NVDA and AMD.
The correlation length is defaulted to 14. You can modify it if you wish, but I do recommend leaving it at this as the default and the testing I have done with this have all been on the 14 correlation length.
You can chose to smooth the SMA over whichever length of period you wish as well.
When the indicator is approaching a significant negative or positive relationship, you will see the indicator flash red in the upper or lower band to signify the relationship. As well, the chart will change the bar colour to purple:
Everything else is pretty straight forward.
Let me know your questions/comments or suggestions around the indicator and its applications.
As always, no indicator is meant to provide a single, reliable strategy to your trading regimen and no indicator or group of indicators should be relied on solely. Be sure to do your own analysis and assessments of the stock prior to taking any trades.
Safe trades everyone!
Indicatore
Indicatore
Implied Volatility Estimator using Black Scholes [Loxx]Implied Volatility Estimator using Black Scholes derives a estimation of implied volatility using the Black Scholes options pricing model. The Bisection algorithm is used for our purposes here. This includes the ability to adjust for dividends.
Implied Volatility
The implied volatility (IV) of an option contract is that value of the volatility of the underlying instrument which, when input in an option pricing model (such as Black–Scholes), will return a theoretical value equal to the current market price of that option. The VIX , in contrast, is a model-free estimate of Implied Volatility. The latter is viewed as being important because it represents a measure of risk for the underlying asset. Elevated Implied Volatility suggests that risks to underlying are also elevated. Ordinarily, to estimate implied volatility we rely upon Black-Scholes (1973). This implies that we are prepared to accept the assumptions of Black Scholes (1973).
Inputs
Spot price: select from 33 different types of price inputs
Strike Price: the strike price of the option you're wishing to model
Market Price: this is the market price of the option; choose, last, bid, or ask to see different results
Historical Volatility Period: the input period for historical volatility ; historical volatility isn't used in the Bisection algo, this is to serve as a comparison, even though historical volatility is from price movement of the underlying asset where as implied volatility is the volatility of the option
Historical Volatility Type: choose from various types of implied volatility , search my indicators for details on each of these
Option Base Currency: this is to calculate the risk-free rate, this is used if you wish to automatically calculate the risk-free rate instead of using the manual input. this uses the 10 year bold yield of the corresponding country
% Manual Risk-free Rate: here you can manually enter the risk-free rate
Use manual input for Risk-free Rate? : choose manual or automatic for risk-free rate
% Manual Yearly Dividend Yield: here you can manually enter the yearly dividend yield
Adjust for Dividends?: choose if you even want to use use dividends
Automatically Calculate Yearly Dividend Yield? choose if you want to use automatic vs manual dividend yield calculation
Time Now Type: choose how you want to calculate time right now, see the tool tip
Days in Year: choose how many days in the year, 365 for all days, 252 for trading days, etc
Hours Per Day: how many hours per day? 24, 8 working hours, or 6.5 trading hours
Expiry date settings: here you can specify the exact time the option expires
*** the algorithm inputs for low and high aren't to be changed unless you're working through the mathematics of how Bisection works.
Included
Option pricing panel
Loxx's Expanded Source Types
Related Indicators
Cox-Ross-Rubinstein Binomial Tree Options Pricing Model
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Cox-Ross-Rubinstein Binomial Tree Options Pricing Model [Loxx]Cox-Ross-Rubinstein Binomial Tree Options Pricing Model is an options pricing panel calculated using an N-iteration (limited to 300 in Pine Script due to matrices size limits) "discrete-time" (lattice based) method to approximate the closed-form Black–Scholes formula. Joshi (2008) outlined varying binomial options pricing model furnishes a numerical approach for the valuation of options. Significantly, the American analogue can be estimated using the binomial tree. This indicator is the complex calculation for Binomial option pricing. Most folks take a shortcut and only calculate 2 iterations. I've coded this to allow for up to 300 iterations. This can be used to price American Puts/Calls and European Puts/Calls. I'll be updating this indicator will be updated with additional features over time. If you would like to learn more about options, I suggest you check out the book textbook Options, Futures and other Derivative by John C Hull.
***This indicator only works on the daily timeframe!***
A quick graphic of what this all means:
In the graphic, "n" are the steps, in this case we can do up to 300, in production we'd need to do 5-15K. That's a lot of steps! You can see here how the binomial tree fans out. As I said previously, most folks only calculate 2 steps, here we are calculating up to 300.
Want to learn more about Simple Introduction to Cox, Ross Rubinstein (1979) ?
Watch this short series "Introduction to Basic Cox, Ross and Rubinstein (1979) model."
Limitations of Black Scholes options pricing model
This is a widely used and well-known options pricing model, factors in current stock price, options strike price, time until expiration (denoted as a percent of a year), and risk-free interest rates. The Black-Scholes Model is quick in calculating any number of option prices. But the model cannot accurately calculate American options, since it only considers the price at an option's expiration date. American options are those that the owner may exercise at any time up to and including the expiration day.
What are Binomial Trees in options pricing?
A useful and very popular technique for pricing an option involves constructing a binomial tree. This is a diagram representing different possible paths that might be followed by the stock price over the life of an option. The underlying assumption is that the stock price follows a random walk. In each time step, it has a certain probability of moving up by a certain percentage amount and a certain probability of moving down by a certain percentage amount. In the limit, as the time step becomes smaller, this model is the same as the Black–Scholes–Merton model.
What is the Binomial options pricing model ?
This model uses a tree diagram with volatility factored in at each level to show all possible paths an option's price can take, then works backward to determine one price. The benefit of the Binomial Model is that you can revisit it at any point for the possibility of early exercise. Early exercise is executing the contract's actions at its strike price before the contract's expiration. Early exercise only happens in American-style options. However, the calculations involved in this model take a long time to determine, so this model isn't the best in rushed situations.
What is the Cox-Ross-Rubinstein Model?
The Cox-Ross-Rubinstein binomial model can be used to price European and American options on stocks without dividends, stocks and stock indexes paying a continuous dividend yield, futures, and currency options. Option pricing is done by working backwards, starting at the terminal date. Here we know all the possible values of the underlying price. For each of these, we calculate the payoffs from the derivative, and find what the set of possible derivative prices is one period before. Given these, we can find the option one period before this again, and so on. Working ones way down to the root of the tree, the option price is found as the derivative price in the first node.
Inputs
Spot price: select from 33 different types of price inputs
Calculation Steps: how many iterations to be used in the Binomial model. In practice, this number would be anywhere from 5000 to 15000, for our purposes here, this is limited to 300
Strike Price: the strike price of the option you're wishing to model
% Implied Volatility: here you can manually enter implied volatility
Historical Volatility Period: the input period for historical volatility; historical volatility isn't used in the CRRBT process, this is to serve as a sort of benchmark for the implied volatility,
Historical Volatility Type: choose from various types of implied volatility, search my indicators for details on each of these
Option Base Currency: this is to calculate the risk-free rate, this is used if you wish to automatically calculate the risk-free rate instead of using the manual input. this uses the 10 year bold yield of the corresponding country
% Manual Risk-free Rate: here you can manually enter the risk-free rate
Use manual input for Risk-free Rate? : choose manual or automatic for risk-free rate
% Manual Yearly Dividend Yield: here you can manually enter the yearly dividend yield
Adjust for Dividends?: choose if you even want to use use dividends
Automatically Calculate Yearly Dividend Yield? choose if you want to use automatic vs manual dividend yield calculation
Time Now Type: choose how you want to calculate time right now, see the tool tip
Days in Year: choose how many days in the year, 365 for all days, 252 for trading days, etc
Hours Per Day: how many hours per day? 24, 8 working hours, or 6.5 trading hours
Expiry date settings: here you can specify the exact time the option expires
Take notes:
Futures don't risk free yields. If you are pricing options of futures, then the risk-free rate is zero.
Dividend yields are calculated using TradingView's internal dividend values
This indicator only works on the daily timeframe
Included
Option pricing panel
Loxx's Expanded Source Types
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