Quantitative financeProject record · Sep 2026

Quantitative Finance & Markets

LPPLS market-state research and interactive cockpits

LPPLS bubble detection, an inspectable research cockpit, and related market-mechanism studies with frozen-history checks and rollback controls.

PythonLPPLSFastAPIPurged cross-validationIsotonic calibrationParquetInteractive dashboards
Why it sits here. A strong research-system bridge: a detector, inspectable dashboards, regression safeguards, and documented falsification.
06 / Two sides. One uncertain future.STUDY IN SPACE

01 / IMPLEMENTATION & CONTRIBUTION

What the work involves

Local implementations connect LPPLS fitting, meta-labeling, validation, backtests, and two research cockpits. The A-share service supports dated research and historical reconciliation; the global monitor fits trailing windows on indices and ETFs.

Technical depth

Nested trailing-window LPPLS fits; purged out-of-fold meta-models and calibration; PIT entry/label clocks; frozen histories; incremental data refresh with rollback and regression guards; separating timing, stock selection, sizing and hedging; serving prebuilt research artifacts through FastAPI without recomputing the engine on each request.

The project family

A_Share/openassetpricing/metalabelA_Share/openassetpricing/global_bubbleA_Share/openassetpricing/frame_attackA_Share/openassetpricing/tail_runwayA_Share/openassetpricing/pm_systemA_Share/openassetpricing/report/cbsf_factor

02 / RESULTS

What came out of it

Inspectable dashboards expose market states, signals, simulated books, performance, and data freshness. Research records preserve rejected mechanisms and checks that stopped unsupported conclusions from advancing.

03 / SUPPORTING EVIDENCE

Follow the source

Implementation notes, project records, and supporting artifacts.

Source context & project scope

This pass inspected documentation and source only; it did not launch or validate current services, scheduled refresh, accounts or model results. Local documents use live for a current cockpit or paper workflow, which must not be presented as verified real-money execution. Historical return/Sortino/capacity figures are not promoted. Cost-basis histograms are vendor-imputed price/turnover proxies, not direct observations of investor intentions.

June 2026 preregistration separates meta-label selection from timing/sizing and specifies PIT availability, entry and evaluation gates. Goals are not outcomes.

SOURCE · 2026-09-17

Current FastAPI source includes startup reconciliation plus date, regime, signal, candidate, simulated-book, performance and status endpoints.

SOURCE · 2026-09-17

Current source includes snapshots, restoration, staged updates, frozen-window regression guards, dry verification and explicit status handling. Code presence does not establish that scheduling is active.

SOURCE · 2026-09-17

Current source contains purged OOF fitting, isotonic calibration, ensemble construction and strict-OOS evaluation.

SOURCE · 2026-09-17

Separate global monitor for 23 indices/ETFs using trailing nested LPPLS fits; supported by lppls_scan.py and a cockpit API.

SOURCE · 2026-09-17

Dated hypothesis scorecard records failed conditional-information tests, a confirmatory gate not run, null exploratory results and killed mechanisms.

SOURCE · 2026-09-17

The proposed supply-runway primary hypothesis was rejected; a later candidate remained parked pending stronger forward evidence.

SOURCE · 2026-09-17

Mechanism gate distinguishes a fitted effect from an explained decomposition and quarantines the unexplained residual.

SOURCE · 2026-09-17

Cost-basis factor study explicitly notes that vendor chips are imputed from price/volume, so the experiment tests predictive transforms rather than disposition-physics claims.

SOURCE · 2026-09-17
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