Indicator
Vector Sniper Pro Vector Sniper Pro V3 | Session Edge
Overview
Vector Sniper Pro V3 is a multi-layered signal detection system built around four core concepts: institutional order flow, smart money manipulation patterns, volume-weighted momentum, and inter-session directional bias. It paints candles to reflect signal state — no separate panel required.
Core Signal Engine
The foundation is a volatility-normalized momentum filter. Each bar is scored using a Z-score of ATR(1) against a rolling mean and standard deviation — this isolates bars where volatility is statistically elevated above baseline noise rather than simply "large." Volume is scored the same way. A signal requires both to exceed their respective thresholds simultaneously, filtering out high-volume low-range bars (absorption) and high-range low-volume bars (false breakouts) from the primary vector set.
Delta volume is approximated by weighting bar volume by the close position within the range: bull volume = volume × (close − low) / range, bear volume = volume × (high − close) / range. The delta ratio (net delta / total volume) must confirm directional conviction, requiring >0.2 for bull signals and <−0.2 for bear. This proxy for order flow imbalance eliminates candles where volume was present but directionally uncommitted.
Structure Break Requirement
Rather than using a raw N-bar highest/lowest comparison, the script identifies confirmed swing points — a pivot high requires the bar to be higher than the two bars on each side. Price must close beyond the most recent confirmed swing high (for bulls) or swing low (for bears) to qualify as a structure break. This reduces false signals during consolidation where price repeatedly tests but never genuinely breaks a level.
Smart Money / Manipulation Detection
Five manipulation signatures are detected independently and fed into the scoring system:
Stop Hunt: Price spikes below the N-bar low (or above the N-bar high) then immediately closes back in the opposite direction with elevated volume — characteristic of liquidity sweeps before reversal.
Absorption: High volume Z-score but very low ATR Z-score (range < 0.5 SD). When volume is present but range is compressed, large participants are absorbing retail orders rather than moving price.
Wick Rejection: A wick exceeding a configurable percentage of the total bar range, combined with volume above the 20-bar average — institutional rejection at a level.
Cumulative Delta Divergence: Price makes a new N-bar high but the current delta is lower than the prior period's highest delta (distribution). Conversely, price makes a new low while delta is rising (accumulation). This is the most reliable leading indicator of manipulation in the system and carries the highest score weight (2.0 points).
RSI Divergence: Price makes a new 14-bar extreme while RSI fails to confirm, indicating momentum exhaustion.
Pre-Signal Scoring System
Before a full vector fires, each bar receives a weighted composite score (maximum ~14 points) across 13 factors:
Factor Weight
Spring / Upthrust (Wyckoff) 2.0
Cumulative Delta Divergence 2.0
RSI Divergence 1.5
Stop Hunt detection 1.5
VWAP + EMA trend alignment 1.5
Session bias alignment 1.5 (configurable)
Fade of prior session level 1.5
No Supply / No Demand (VSA) 1.0
Delta imbalance ratio 1.0
Near structure break zone 1.0
Break of prior session level 1.0
Volume ratio > 1.2× average 0.5
Bar direction (close vs open) 1.0
A pre-signal requires the score to meet a configurable minimum threshold and to appear N times within a rolling M-bar window, preventing single-bar spikes from triggering. A cooldown period prevents signal clustering, and a hysteresis lock prevents rapid directional flipping.
Session Edge System
The script tracks live OHLC for Asia (20:00–02:00 ET), London (02:00–08:00 ET), NY Pre-Market (04:00–09:30 ET), NY Regular (09:30–16:00 ET), and NY After-Hours (16:00–20:00 ET). All times and timezone are configurable.
When a session closes, its high, low, midpoint, and directional close (green or red) are stored. During the following session:
Prior session levels (H/L/Mid) are plotted as reference lines — yellow for Asia levels during London, aqua for London levels during NY.
Session bias activates based on the closing direction of the prior session. A green Asia close generates a bull bias for London; a red Asia close generates a bear bias. The same logic applies London→NY. Bias adds configurable weight to the scoring system and can optionally hard-block counter-trend signals.
Level interaction detection fires when price touches a prior session level: a fade signal requires a wick rejection back through the level with volume; a break signal requires a close through the level with volume. Both feed the scoring system.
Live hit-rate table (toggle-able) tracks how often the prior session's direction correctly predicted the current session's direction — validated on your specific instrument and timeframe in real time rather than relying on aggregate statistics.
Candle Color System
Color Meaning
Neon green Bull vector (base condition met)
Red Bear vector
White Confirmed bull trend change (regime flip + extreme conditions)
Purple Confirmed bear trend change
Blue Pre-bull signal (score threshold met, not yet full vector)
Orange Pre-bear signal
Dark green (faint) Regular bull reversal (regime flip, standard strength)
Dark purple (faint) Regular bear reversal
Grey No qualifying condition
How to Use
The indicator is designed to be used on any liquid instrument with real volume data. Session times are set for US Eastern Time by default — adjust the timezone input for your exchange.
Start with candle colors only (all markers off by default). Enable the hit-rate table to validate whether the Asia→London and London→NY bias is statistically meaningful on your specific symbol before relying on it. Enable prior session levels to identify the key prices where fade and break decisions occur. The pre-signal (blue/orange) candles appear before a full vector fires and can be used for earlier entries with the understanding that confirmation has not yet occurred.
All inputs have been grouped and labelled to allow systematic adjustment: tighten the Z-score thresholds to reduce signal frequency, raise the minimum score to require stronger multi-factor confluence, and use the cooldown and hysteresis settings to control how often the system can re-trigger in the same direction. Indicator
Sniffer
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Overview
A vast majority of modern data analysis & modelling techniques rely upon the idea of hidden patterns, wether it is some type of visualisation tool or some form of a complex machine learning algorithm, the one thing that they have in common is the belief, that patterns tell us what’s hidden behind plain numbers. The same philosophy has been adopted by many traders & investors worldwide, there’s an entire school of thought that operates purely based on chart patterns. This is where Sniffer comes in, it is a tool designed to simplify & quantify the job of pattern recognition on any given price chart, by combining various factors & techniques that generate high-quality results.
This tool analyses bars selected by the user, and highlights bar clusters on the chart that exhibit similar behaviour across multiple dimensions. It can detect a single candle pattern like hammers or dojis, or it can handle multiple candles like morning/evening stars or double tops/bottoms, and many more. In fact, the tool is completely independent of such specific candle formations, instead, it works on the idea of vector similarity and generates a degree of similarity for every single combination of candles. Only the top-n matches are highlighted, users get to choose which patterns they want to analyse and to what degree, by customising the feature-space.
Background
In the world of trading, a common use-case is to scan a price chart for some specific candlestick formations & price structures, and then the chart is further analysed in reference to these events. Traders are often trying to answer questions like, when was the last time price showed similar behaviour, what are the instances similar to what price is doing right now, what happens when price forms a pattern like this, what were some of other indicators doing when this happened last(RSI, CCI, ADX etc), and many other abstract ideas to have a stronger confluence or to confirm a bias.Having such a context can be vital in making better informed decisions, but doing this manually on a chart that has thousands of candles can have many disadvantages. It’s tedious, human errors are rather likely, and even if it’s done with pin-point accuracy, chances are that we’ll miss out on many pieces of information. This is the thought that gave birth to Sniffer .
Sniffer tries to provide a general solution for pattern-based analysis by deploying vector-similarity computation techniques, that cover the full-breadth of a price chart and generate a list of top-n matches based on the criteria selected by the user. Most of these techniques come from the data science space, where vector similarity is often implemented to solve classification & clustering problems. Sniffer uses same principles of vector comparison, and computes a degree of similarity for every single candle formation within the selected range, and as a result generates a similarity matrix that captures how similar or dissimilar a set of candles is to the input set selected by the user.
How It Works
A brief overview of how the tool is implemented:
- Every bar is processed, and a set of features are mapped to it.
- Bars selected by the user are captured, and saved for later use.
- Once the all the bars have been processed, candles are back-tracked and degree of similarity is computed for every single bar(max-limit is 5000 bars).
- Degree of similarity is computed by comparing attributes like price range, candle breadth & volume etc.
- Similarity matrix is sorted and top-n results are highlighted on the chart through boxes of different colors.
A brief overview of the features space for bars:
- Range: Difference between high & low
- Body: Difference between close & open
- Volume: Traded volume for that candle
- Head: Upper wick for green candles & lower wick for red candles
- Tail: Lower wick for green candles & upper wick for red candles
- BTR: Body to Range ratio
- HTR: Head to Range ratio
- TTR: Tail to Range ratio
- HTB: Head to Body ratio
- TTB: Tail to Body ratio
- ROC: Rate of change for HL2 for four different periods
- RSI: Relative Strength Index
- CCI: Commodity Channel Index
- Stochastic: Stochastic Index
- ADX: DMI+, DMI- & ADX
A brief overview of how degree of similarity is calculated:
- Each bar set is compared to the inout bar set within the selected feature space
- Features are represented as vectors, and distance between the vectors is calculated
- Shorter the distance, greater the similarity
- Different distance calculation methods are available to choose from, such as Cosine, Euclidean, Lorentzian, Manhattan, & Pearson
- Each method is likely to generate slightly different results, users are expected to select the method & the feature space that best fits their use-case
How To Use It
- Usage of this tool is relatively straightforward, users can add this indicator to their chart and similar clusters will be highlighted automatically
- Users need to select a time range that will be treated as input, and bars within that range become the input formation for similarity calculations
- Boxes will be draw around the clusters that fit the matching criteria
- Boxes are color-coded, green color boxes represent the top one-third of the top-n matches, yellow boxes represent the middle third, red boxes are for bottom third, and white box represents user-input
- Boxes colors will be adjusted as you adjust input parameters, such as number of matches or look-back period
User Settings
Users can configure the following options:
- Select the time-range to set input bars
- Select the look-back period, number of candles to backtrack for similarity search
- Select the number of top-n matches to show on the chart
- Select the method for similarity calculation
- Adjust the feature space, this enables addition of custom features, such as pattern recognition, technical indicators, rate of change etc
- Toggle verbosity, shows degree of similarity as a percentage value inside the box
Top Features
- Pattern Agnostic: Designed to work with variable number of candles & complex patterns
- Customisable Feature Space: Users get to add custom features to each bar
- Comprehensive Comparison: Generates a degree of similarity for all possible combinations
Final Note
- Similarity matches will be shown only within last 4500 bars.
- In theory, it is possible to compute similarity for any size candle formations, indicator has been tested with formations of 50+ candles, but it is recommended to select smaller range for faster & cleaner results.
- As you move to smaller time frames, selected time range will provide a larger number of candles as input, which can produce undesired results, it is advised to adjust your selection when you change time frames. Seeking suggestions on how to directly receive bars as user input, instead of time range.
- At times, users may see array index out of bound error when setting up this indicator, this generally happens when the input range is not properly configured. So, it should disappear after you select the input range, still trying to figure out where it is coming from, suggestions are welcome.
Credits
- @HeWhoMustNotBeNamed for publishing such a handy PineScript Logger, it certainly made the job a lot easier. Indicator
