Prices & Corporate Actions
Adjusted and raw price series, splits, dividends, delisting awareness, and return construction suitable for research workflows.
Reliable Data
Data
Reliable financial data built for serious research and investing workflows.
Code & Kapital provides research-ready financial data with a focus on timestamp integrity, entity resolution, and dependable daily coverage. The goal is simple: data you can trust when real decisions depend on it.
Why it matters
Good research starts with dependable inputs. Clean timestamps, stable identifiers, and consistent dataset coverage are what make a data product useful in practice.
Coverage
Datasets and structures tracked across the stack.
The operating model is built around daily market workflows and the canonical layers required to support robust research, analytics, and dependable data products.
Fundamentals & Estimates
Structured statement data, revisions, estimate histories, and the timing detail needed for factor and event work.
Index & Universe Data
Holdings histories, membership changes, benchmark alignment, and investable universe controls.
Security Master
Identifier mapping, ticker changes, exchange metadata, classification systems, and instrument lineage.
Macro & Alternative Data
Macro series, rates, calendar data, and selectively useful alternative inputs for research and portfolio workflows.
Daily Infrastructure
Pipelines designed to support real workflows.
A research-ready data system needs predictable refresh windows, visible exceptions, stable models, and enough auditability that prior conclusions remain explainable.
That means daily ingestion routines, validation checkpoints, security master logic, canonical storage layers, and downstream delivery mechanisms that research workflows can depend on with confidence.
Point-in-time discipline
Research outputs depend on timestamp integrity, corporate action handling, security mapping, and reproducible joins.
Daily refresh workflows
Pipelines are designed around repeatable ingestion, validation, and issue detection rather than ad hoc data pulls.
Entity resolution
Security master quality matters. Symbol changes, delistings, and identifier mapping cannot be an afterthought.
Auditability
Analyses should be explainable months later. Inputs, transforms, and assumptions need a clear trail.
Data products
Reliable internal data systems create the path to external data products.
Access structured, research-ready datasets and supporting workflow outputs designed for teams that need dependable financial data they can use with confidence.