Package com.quantfinlib.persist

package com.quantfinlib.persist

Multi-day persistence of learned state: Checkpoint — one binary file of named sections, written at end of day (atomic temp-then-rename, so a crash mid-save never corrupts yesterday's file) and restored at session start.

The models that learn across days expose writeState(DataOutput) / readState(DataInput) pairs: the seasonality trio (microstructure.VolumeCurve, VolatilityCurve, SpreadForecaster), microstructure.OnlineAlphaLearner (weights AND the out-of-sample IC evidence — restored trust must be earned trust), microstructure.LeadLagEstimator, microstructure.EwmaCovariance (the basket risk matrix), microstructure.KylesLambda (learned depth), microstructure.ClosingAuctionModel (learned auction share), microstructure.AlphaEnsemble (per-component IC evidence), rfq.RfqDealerScorecard (learned dealer-panel quality), and the venue-quality cards (execution.VenueScorecard — format v2 with fill markouts, still reads v1 — and fx.LpScorecard). Intraday state resets on read; configuration (bucket/venue counts) must match or the read throws. HiddenLiquidityDetector is deliberately NOT persistable: its state is keyed by price level, and overnight the price ladder moves — restoring it would attribute yesterday's icebergs to today's unrelated levels.

Class	Description
Checkpoint	Multi-day persistence of learned state: everything the models learn across sessions — volume/vol/spread baselines, alpha weights and their out-of-sample IC evidence, venue and LP scorecards — is exactly what a desk does NOT want to relearn from zero every morning.
Checkpoint.Reader	Random access to a loaded checkpoint's sections by name.
Checkpoint.StateReader	A model's state deserializer — typically a readState reference.
Checkpoint.StateWriter	A model's state serializer — typically a writeState reference.
Checkpoint.Writer	Collects named sections and commits them atomically on close.