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Technical Indicators
Technical indicators are not predictions. They are measurements. In SEIOO, indicators are treated as structured observations about market state, not as buy or sell buttons.
Each indicator answers a narrow question about price behavior, momentum, volatility, trend, or participation. When combined correctly, they form higher-level signals that describe market regimes, strength, alignment, and risk.
The purpose of this system is not to overwhelm you with tools, but to give you clean, composable primitives that can be reasoned about consistently across assets and timeframes.
Core Price and Statistical Measures
At the foundation of all analysis are basic price-derived operations. These form the raw signal layer from which everything else is derived.
The closing price represents the final consensus value of a market over a given period. It is the reference point for most indicators and is rarely used directly as a signal, but instead as an input into transformations.
Price change expresses relative movement between periods. It is useful for short-term momentum detection, return-based comparisons, and normalization pipelines where direction and magnitude matter more than absolute price.
Volume captures participation and commitment. Price can move on low volume, but those moves tend to be fragile. Volume is most powerful when compared against its own history or against price movement itself.
Standard deviation measures dispersion and instability. It does not tell you direction, only how violently price is behaving. This makes it a key input for volatility regimes, risk filters, and position sizing logic.
These measures are rarely decisive on their own. Their value emerges when they are contextualized.
Momentum Indicators
Momentum indicators describe how fast price is moving and whether that movement is accelerating, decelerating, or stalling. They are most useful for timing, confirmation, and exhaustion detection.
RSI, Stochastic, StochRSI, Williams %R, and MFI all operate on bounded ranges. They are best interpreted as relative position indicators rather than absolute signals. Overbought and oversold conditions are contextual, not universal. In strong trends, momentum can remain extreme for long periods.
MACD, ROC, KST, TRIX, and the Awesome Oscillator measure rate, convergence, and momentum structure. These indicators are particularly useful when normalized and compared across assets, or when evaluated relative to their own moving averages.
Parabolic SAR is a state-based momentum tool. It does not describe strength, but rather whether price behavior remains consistent with a trailing directional bias. It is best used as a persistence or invalidation signal rather than an entry trigger.
Momentum indicators are strongest when used together as a cluster. Agreement across multiple momentum measures carries more meaning than any single reading.
Trend Indicators
Trend indicators answer a different question than momentum. Momentum asks how fast price is moving. Trend asks whether movement has structure and persistence.
Moving averages are the simplest trend abstraction. Simple, exponential, weighted, and Wilder-style averages all smooth price, but with different sensitivities. Short-period averages respond quickly but are noisy. Long-period averages are stable but slow. Crossovers are not signals by themselves; they are state transitions.
ADX measures trend strength without regard to direction. A rising ADX tells you that the market is committing to movement, not which way it will go. This makes it valuable as a regime filter. Trend-following logic behaves very differently in low-ADX versus high-ADX environments.
Trend indicators are most effective when separated into two roles: structure detection and regime qualification. One tells you what is happening. The other tells you whether it is worth acting on.
Volatility Indicators
Volatility indicators measure uncertainty, expansion, and compression. They are not directional tools.
ATR describes average movement size. It is essential for risk management, stop placement, and volatility-adjusted logic. A strategy that ignores ATR implicitly assumes constant risk, which markets never provide.
Bollinger Bands and Keltner Channels frame price relative to expected variation. Band expansion signals regime shifts. Compression often precedes large moves, but does not predict direction.
Volatility indicators are most powerful when used as gates. They determine when other signals are allowed to matter. A momentum signal in a compressed volatility regime does not mean the same thing as the same signal in an expanding one.
Volume-Based Indicators
Volume indicators explain whether price movement is supported by participation.
On-Balance Volume and the Accumulation Distribution Line track whether volume confirms price direction over time. Divergences between price and these indicators often precede structural changes, but should be treated as diagnostics rather than triggers.
Volume surge compares current volume to its own baseline. It is useful for detecting abnormal activity, breakouts, and event-driven moves.
VWAP anchors price to volume-weighted consensus. It is a contextual reference rather than a signal. Price above or below VWAP describes positioning, not opportunity.
MFI and Force Index combine price and volume into hybrid momentum measures. These indicators are especially useful when normalized and compared across assets or sectors.
Volume Profile exists in the system but should be used with caution due to known limitations. Until resolved, it should be treated as experimental.
Volume indicators add conviction. They tell you whether the market agrees with what price appears to be doing.
Advanced and Cross-Series Indicators
Some indicators operate across assets or across signals rather than within a single price series.
Correlation and rolling correlation describe alignment, not direction. They are not trading signals. They answer questions like whether assets are behaving together, whether diversification is real, or whether a composite signal is internally consistent.
Correlation becomes valuable when it changes. Rising or collapsing correlation often signals regime transitions, risk-on or risk-off behavior, and structural market shifts.
The formula engine is the most powerful tool in the system. It allows indicators to be combined, transformed, normalized, averaged, thresholded, and composed into higher-order signals. This is where indicators stop being outputs and start becoming building blocks.
A composite signal is not an indicator. It is a structured opinion built from multiple indicators, each contributing partial information.
How Indicators Are Meant to Be Used
In SEIOO, indicators are not endpoints. They are inputs.
They should be:
Normalized before comparison
Combined into composites rather than traded alone
Used as state descriptors, not predictions
Evaluated relative to regime and context
A single indicator rarely carries enough information to justify action. Systems built on isolated readings tend to overfit and underperform. Systems built on aligned, normalized, and gated signals scale.
Summary
Technical indicators in SEIOO form a modular measurement system. Each indicator answers a small, specific question about market behavior. When combined thoughtfully, they describe regimes, strength, alignment, and risk with clarity.
The goal is not to chase signals, but to understand state. When state becomes clear, decisions follow naturally.
Indicators are the vocabulary. Signal engines are the language.
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