Uses of Record Class
com.quantfinlib.execution.Slice

Packages that use Slice

Package

Description

com.quantfinlib.execution

Execution strategy support: SmartOrderRouter (fee-adjusted multi-venue splitting, dark-first option), its zero-allocation hot-lane sibling HftSor, and the full-checklist AdaptiveSor (expected-cost routing over displayed + hidden liquidity, fees/rebates, latency, fill probability and a reliability veto, with contingent dark probes) learning from VenueScorecard (streaming per-venue fill rate, measured latency, realized dark fills), TwapScheduler / VwapScheduler (schedule design with anti-gaming jitter and exact largest-remainder allocation), PovTracker (streaming percentage-of-volume participation), ImplementationShortfallScheduler (Almgren-Chriss-optimal slicing), WmrFixingScheduler (benchmark-window TWAP replication), BenchmarkExecutor (the DYNAMIC benchmark algo: one stateful executor tracking VWAP / TWAP / Arrival / Implementation Shortfall / Closing / Opening / Participation, re-deciding each interval from live spread, depth, volatility, volume curve, alpha and liquidity — cross-asset), LiquiditySeekingAlgo (the opportunistic archetype: burst when the spread is under its time-of-day forecast in a calm regime, guaranteed by a completion floor over the final stretch), PortfolioExecutor (multi-symbol portfolio-level scheduling over per-symbol BenchmarkExecutor children: leg-balance band for two-sided transitions, per-interval notional budget allocated risk-weighted — overlays only ever damp a child's own due, so per-symbol benchmark integrity holds), IcebergOrder (display/reload state machine), DarkPoolSimulator (midpoint cross with minimum-execution-quantity), MidPegTracker (peg repricing with thresholds) and VenueBenchmark (fill rate, effective spread, markout per venue).

Uses of Slice in com.quantfinlib.execution

Methods in com.quantfinlib.execution that return types with arguments of type Slice

Modifier and Type	Method	Description
static List<Slice>	ImplementationShortfallScheduler.schedule(AlmgrenChriss.Params params, long durationMillis)	The optimal IS schedule for the given market parameters.
static List<Slice>	TwapScheduler.schedule(long totalQty, long durationMillis, int numSlices)	Equal slices at equal intervals starting at t=0.
static List<Slice>	VwapScheduler.schedule(long totalQty, double[] volumeProfile, long durationMillis)
static List<Slice>	WmrFixingScheduler.schedule(long totalQty, int numSlices)	WmrFixingScheduler.schedule(long, long, int) with the standard 5-minute window.
static List<Slice>	WmrFixingScheduler.schedule(long totalQty, long windowMillis, int numSlices)	Even slices across the fixing window.
static List<Slice>	TwapScheduler.scheduleRandomized(long totalQty, long durationMillis, int numSlices, double jitterPct, long seed)	Randomized TWAP: slice sizes jittered by up to jitterPct (e.g. 0.3 = ±30%), deterministic for a given seed.