QuanTAlib/docs/glossary.md

Glossary

Short reference for core QuanTAlib terminology and types.

Term	Definition
Accuracy	Measure of how well an indicator preserves the important structure of the original price series while still filtering out noise. It captures closeness to the original data: more smoothness removes zigzagging noise but will also reduce accuracy if it starts erasing meaningful swings and cycles.
AVX2	256-bit SIMD extension for x86-64 (AMD64) CPUs from Intel and AMD. Used to accelerate vectorized span-based calculations.
AVX-512	512-bit SIMD extension available on many x86-64 (AMD64) desktop and server CPUs released since around 2015. Doubles vector width over AVX2 and adds masking and extra math operations.
Array of Structs (AoS)	Memory layout where each element is a full record, for example struct Bar { double Open, High, Low, Close; } stored as Bar[]. Simple to model but cache-inefficient for single-field operations and harder to SIMD-vectorize than structure of arrays (SoA). Avoided in QuanTAlib.
Batch Mode	Mode where indicators operate on TSeries objects instead of raw spans. Handles timestamps, resizing, and time alignment while still using span-based implementations internally. Best for historical analysis where you want time-aware series without managing arrays directly.
Eventing Mode	Reactive usage pattern where indicators implement ITValuePublisher and raise events as values change or warmup completes (IsHot). Used to build chains of indicators and trading logic that react to state changes instead of polling for values.
FIR filter	Finite impulse response filter. Output depends on a finite window of past inputs with no feedback from the past. Always stable. Typical examples in TA are a simple moving average, weighted moving average or hull moving average.
Hot path	Code that executes for every incoming tick or bar during live trading. In QuanTAlib, hot paths (such as Update and span-based Calculate loops) must avoid heap allocations, run in constant time O(1) where possible, and be SIMD-optimized when the algorithm allows.
IIR filter	Infinite impulse response filter. Output depends on both current input and past outputs via feedback. More responsive for a given period but requires care for numerical stability. Typical examples in TA are an exponential moving average, kaufman adaptive moving average and variable index moving average.
isHot	Boolean property on indicators that becomes true after sufficient data has been processed (for example once the internal period / warmup length is reached). Before isHot is true, output values are considered not fully reliable.
isNew flag	Boolean parameter on Update(TValue input, bool isNew = true) that controls bar-correction behavior: isNew = true advances state to the next bar; isNew = false updates the most recent bar in-place (intra-bar correction) for streaming feeds where the latest bar can change before it closes.
NEON	128-bit SIMD architecture for ARM CPUs (including many mobile devices and Apple Silicon). .NET exposes NEON via System.Runtime.Intrinsics.Arm so the same span-based indicator code can vectorize on ARM hardware.
O(1)	Constant-time complexity. Work per update does not grow with the length of the time series or lookback window. Target complexity for streaming Update methods in QuanTAlib whenever mathematically possible.
O(n)	Linear-time complexity in the number of input points n. Typical for batch calculations that walk the series once. Acceptable for one-off batch work, not for hot-path streaming updates.
Overshoot	Degree to which an indicator overreacts around turning points, swinging past the underlying price or signal before settling. High overshoot produces dramatic but potentially misleading signals, especially near reversals.
Period	Configuration parameter that describes how many bars or samples an indicator considers for its calculation. Relevant for FIR, not so much for IIR indicators.
RingBuffer	Fixed-size circular buffer used for sliding-window calculations. New values overwrite the oldest entries once the buffer is full, keeping time and memory usage effectively constant regardless of history length.
SIMD	Single Instruction, Multiple Data. Hardware feature allowing the CPU to apply one instruction to many values at once. QuanTAlib uses .NET SIMD support (for example AVX2, AVX-512, or NEON when available) to accelerate span-based calculations.
Smoothness	Measure of how visually and numerically calm an indicator's line is. More smoothness filters random noise but usually increases lag; less smoothness responds faster but exposes more short-term fluctuation.
Span Mode	Lowest-level, zero-allocation mode operating directly on Span<double> / ReadOnlySpan<double>. Designed for backtesting and research workloads that process large arrays with maximum SIMD acceleration and no object overhead.
Streaming Mode	Real-time update mode using Update(TValue input, bool isNew = true). Maintains internal state between calls and distinguishes between new bars and intra-bar corrections via the isNew flag. Intended for live feeds and tick-by-tick data.
Structure of Arrays (SoA)	Memory layout where each field of a logical record is stored in its own contiguous buffer (for example, prices and timestamps in separate arrays). Improves cache locality and enables vectorized operations across large segments of a single field.
TBar	Struct representing an OHLCV bar: time, open, high, low, close, and volume. Used when indicators need full bar context instead of a single price.
TSeries	Primary time series container. Uses structure-of-arrays layout: timestamps and values stored in separate buffers and exposed as ReadOnlySpan<T> for SIMD-friendly access. Represents a sequence of scalar values over time.
Throughput	Number of ticks or bars an indicator can process per second on a given machine. Driven by per-update complexity (target O(1)), SIMD utilization, and zero-allocation hot paths.
Timeliness	Measures how much an indicator lags behind the underlying price series. Excessive lag pushes entries and exits late and can cut profits. For classic moving averages (SMA, WMA, EMA) more smoothness almost always means more lag; designs like DEMA, HMA or JMA aim to stay close to price while still filtering noise.
TValue	Struct pairing a DateTime with a single double value. Standard input and output type for indicators in streaming mode.
Zero-allocation design	Design rule that hot paths must not allocate on the managed heap. Achieved by using Span<T> or ReadOnlySpan<T> for batch APIs, preferring stackalloc for small temporaries, and reusing internal state instead of creating new objects on each update.