Package com.quantfinlib.examples

package com.quantfinlib.examples

Runnable demonstrations and benchmarks (excluded from coverage — they are run manually or by the Benchmarks (Linux) workflow): QuickStartDemo tours every capability on synthetic data; HftLatencyBenchmark measures the market data hot path and HftOrderBenchmark the order path (both print a HiccupMonitor summary to attribute tail outliers to platform stalls). See docs/ULTRA_LOW_LATENCY.md for how to run them meaningfully.

Classes

Class	Description
HftBookBenchmark	Benchmarks the venue-grade matching engine (HftOrderBook), completing the fast-lane benchmark family with the venue side: Passive churn: add/cancel throughput with a deep resting book — the id-map + pool + bitmap machinery under load; Matching: aggressive flow sweeping resting liquidity — fills/sec through the FIFO levels; Per-op latency: submit-to-return percentiles for a realistic 70/20/10 add/cancel/aggress mix.
HftLatencyBenchmark	Self-contained benchmark of the HFT hot path with a realistic tick-to-signal workload on the consumer (streaming EMA crossover + RSI per tick).
HftOrderBenchmark	Benchmarks the fast-lane order path, mirroring HftLatencyBenchmark: Risk gate: ns per pre-trade check (tight loop). Submit-to-venue: paced one-in-flight latency from HftOrderGateway.submit() to the venue thread receiving the order. Tick-to-order end-to-end: market tick published on the HftMarketDataBus → strategy (2×EMA) on the bus consumer thread → risk check → order ring → venue thread.
HftQuoterBenchmark	Benchmarks the market-making loop end-to-end, completing the fast-lane benchmark family (HftLatencyBenchmark: publish→strategy, HftOrderBenchmark: tick→order):
LiveTradingDemo	The five-minute live demo: real market data → streaming strategy → paper execution → live dashboard, in one command.
QuickStartDemo	End-to-end tour of the platform on synthetic data: the 11 research capabilities (indicators, backtesting, DSL, risk, ML, optimization, Monte Carlo, screening, market data, reporting with SVG charts) plus the trading and research extensions — data I/O, order book analytics, smart order routing, execution-aware backtests with TCA, options hedging and vol surfaces, fixed income, GARCH/EWMA, cointegration, walk-forward validation, portfolio backtesting, and a risk-gated paper trading session.
ScaleBenchmark	Scale probe, parameterized: args = [crossCount, measuredTicks, crossMinMove]. 200 direct pairs, crossCount synthetic crosses with legs spread across the direct pairs (~crossCount/100 crosses touched per direct tick).
ShardScaleBenchmark	Horizontal-scaling probe: 300 direct symbols spread across k shards, all quoted two-sided on every tick (conflation off = worst case), single producer round-robin. args[0] = shard count.