LQM solution / Forecasting
Forecast what happens next.
Time-series forecasting, model competition, calibration, adaptive selection and evidence-linked outcomes.
Relevant models
01
Linear Trend Forecast
Available through the governed LargeQuant model/runtime stack where applicable.
02
AR(1) Forecast
Available through the governed LargeQuant model/runtime stack where applicable.
03
Walk-Forward Forecast Model Competition
Available through the governed LargeQuant model/runtime stack where applicable.
04
Prequential Streaming Forecast Skill
Available through the governed LargeQuant model/runtime stack where applicable.
Why LQM-first
The output can be scored against reality.
LargeQuant keeps numerical authority explicit so results can be benchmarked, governed, observed and revisited when outcomes arrive.
01
Explicit model identity.
Know which quantitative method produced the result.
Know which quantitative method produced the result.
02
Benchmarkable.
Evaluate numerical performance rather than eloquence.
Evaluate numerical performance rather than eloquence.
03
Evidence-linked.
Preserve execution lineage where the result matters.
Preserve execution lineage where the result matters.