Understanding State Modeling™
A complete educational guide to OIAMR's proprietary ML-powered quantitative framework — how it works, what the eight states mean, and how to apply them to your trading.
See State Modeling™ In Action
A quick foundational walkthrough of OIAMR's proprietary algorithmic indicator — created by— Ashok Yarlagadda.
What Is State Modeling™?
State Modeling™ is OIAMR's proprietary algorithmic indicator, created by founder and quantitative analyst Ashok Yarlagadda. It uses machine-learning quantitative mathematics to classify every covered stock, index, and ETF into one of eight directional states.
At its core, the system analyzes massive historical and real-time datasets, identifies repeating behavioral patterns, and correlates them to statistically probable future price outcomes — creating a completely data-driven, emotion-free view of market direction.
Unlike traditional technical indicators that react to price, State Modeling™ generates forward-looking, probabilistic classifications — telling you not just where a stock is, but where it is statistically likely to go.
Machine-Learning Core
Trained on vast datasets of historical price action, volume, momentum, and volatility patterns across thousands of assets and market cycles.
Rules-Based, Emotion-Free
Every classification is fully objective — no discretionary judgment. The same rules applied the same way, every single time, for every single asset.
Actionable Outputs
Every state comes pre-packaged with three tiered price targets and a defined stop-loss level — giving you a complete trade plan, not just a signal.
Universal Coverage
Applied across 4,500+ equities, major indices (SPX, NDX, RUT), and ETFs — giving you a consistent analytical lens regardless of asset class.
How State Modeling™ Works
The State Modeling™ engine runs a multi-layer quantitative pipeline — from raw data ingestion all the way to actionable trade classifications.
Data Ingestion & Preprocessing
The system continuously ingests price, volume, and options flow data across 4,500+ tickers. Historical data spanning 10+ years is normalized, cleaned, and fed through preprocessing pipelines that extract hundreds of quantitative features — including momentum signals, volatility regimes, volume profiles, and cross-asset correlations.
Pattern Recognition & ML Classification
OIAMR's proprietary ML models — trained over years of real market data — analyze the extracted features and match them against statistically similar historical periods. The models identify which of the eight directional states best describes the current market condition for each asset, weighted by confidence and historical outcome probabilities.
State Assignment & Strength Scoring
Each asset is assigned a state (1 through 8) along with a strength score. Bullish states carry positive strength ratings (+1 to +4), and bearish states carry negative ratings (-1 to -4). This scoring captures not just direction but conviction — how strongly the data supports the current classification.
Target & Stop Generation
Based on the state assignment, strength score, and current price, the system computes three statistically-derived price targets (T1, T2, T3) and a risk-defined stop-loss level. These levels are anchored to historically observed price moves from similar state configurations — giving you high-probability exit and risk parameters for every trade.
The Eight States Explained
States 1–4 are bullish (varying degrees of upward conviction). States 5–8 are bearish (varying degrees of downward conviction). Strength ranges from +4 (extreme bullish) to -4 (extreme bearish).
Extreme Bullish
Maximum upward acceleration. Price is trading cleanly above all major moving averages with accelerating buy-side volume. The strongest and most conviction-backed bullish classification in the OIAMR system.
Established Bullish
Steady, healthy uptrend with solid consolidation patterns. Supported by institutional buy levels. Not as explosive as State 1, but high-quality and persistent upward directional bias.
Mild Bullish
Emergent upward bias. Early MACD/EMA crossovers are turning positive and price is testing key resistances. Bullish, but not yet confirmed with full momentum. Early-stage or recovering uptrend.
Transition Bullish
Short-term bottoming pattern or relief bounce in progress. Neutral-to-mild bullish conviction. The market may be transitioning from bearish to bullish — confirmation is pending and caution is advised.
Transition Bearish
Initial distribution patterns or early trend exhaustion signs. Bearish crossover warnings are emerging. The asset may be transitioning from bullish to bearish — risk management should be tightened.
Mild Bearish
Emergent downward bias. Key support lines are converting into ceiling resistances; sellers are holding control at most tested price levels. Options premium-selling setups are often favorable here.
Established Bearish
Clear downtrend channels in place. Temporary price rallies are heavily sold into, breaking local support floors on each successive leg down. Persistence of selling pressure is the defining characteristic.
Extreme Bearish
High-velocity downward momentum. Heavy capitulation volume, price trading below all critical moving averages. The most aggressive bearish classification — often associated with panic-selling or macro-driven dislocations.
Price Targets &
Stop Loss Levels
One of State Modeling™'s most powerful features is that it doesn't just tell you direction — it gives you a complete trade plan. Each state assignment is automatically accompanied by three tiered price targets and a defined stop-loss level.
Targets (T1, T2, T3) are computed from statistically observed price moves associated with the current state, asset characteristics, and volatility environment. They represent high-probability price levels the asset has historically reached when in a given state — from most conservative (T1) to most ambitious (T3).
Stop Loss Levels are derived from the same historical analysis — representing the price level at which the state's directional thesis would be invalidated by past behavior. They define where the trade is "wrong" and risk should be exited.
Having pre-defined targets and stops before entering a trade eliminates emotional decision-making mid-trade. You enter knowing your max risk (stop), your profit milestones (T1, T2), and your maximum objective (T3) — creating a professional, systematic trade management framework.
| Level | Price | % Move | Status |
|---|---|---|---|
| Target 3 | $277.03 | +31.29% | Met ✅ |
| Target 2 | $243.77 | +15.53% | Met ✅ |
| Target 1 | $235.46 | +11.59% | Met ✅ |
| Entry | $211.00 | - | Signal |
| Stop Loss | $196.20 | -7.01% | Risk Level |
How to Apply State Modeling™
A practical workflow for integrating State Modeling™ into your daily trading process — from macro regime identification to trade execution.
Check the Macro State
Start with major indices: SPY, QQQ, IWM. What state are they in? A bullish macro state (S1–S4) provides tailwind for long setups; bearish states (S5–S8) favor short or neutral strategies.
Open Predictive AnalyticsFind Aligned Assets
Use the Trade Scanners to identify individual stocks and ETFs whose State classification aligns with the macro environment. Look for S1 or S2 stocks when macro is bullish for the highest-conviction longs.
Open Trade ScannersStructure Your Trade
Use the three targets and stop-loss from State Modeling™ to define your entry, exit levels, and risk parameters before placing a trade. Use T1 as initial profit-taking, T2–T3 as scale-out targets, and the stop as your hard exit.
View Chart ExamplesPro Tip: State Transitions Are Signals
When an asset transitions from State 5 to State 4, or from State 4 to State 3, these inflection points often represent the highest-conviction entry opportunities — catching a trend at its earliest confirmed inflection. Monitoring state transitions, not just static states, is a key advanced technique.
Frequently Asked Questions
Ready to See State Modeling™
In Action?
Explore live state classifications, interactive charts, and real trade targets across 4,500+ assets on the Predictive Analytics dashboard.