Datasets:
Tasks:
Tabular Classification
Formats:
parquet
Languages:
English
Size:
< 1K
Tags:
economics
quantitative-finance
causal-inference
macroeconomics
housing-economics
market-microstructure
License:
File size: 2,834 Bytes
ebcde1f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 | # Repository instructions
These instructions apply to the entire repository.
## Mission and safety boundary
Build a reproducible research and simulation system for short-horizon market
microstructure. The repository must never place live orders, authenticate to a
trading account, or imply that a simulated result is executable profit.
## Research integrity
- Never invent observations, performance, statistical significance, or a data
source. Label synthetic, fixture, smoke-test, partial, and full-data results.
- Keep predictive quality, execution assumptions, and strategy results separate.
- Every generated result must include the configuration hash, input manifest
hashes, UTC data interval, code version or explicit `UNBORN`, and dirty state.
- Preserve raw observations. Put transformations in normalized or derived data
and log exclusions; do not silently repair suspect events.
- Treat a timestamp at decision time `t` as unavailable unless its event and
receipt ordering prove it was observable at `t`. Features use information at
or before `t`; labels begin strictly after `t`.
- Do not tune against the final test period. Use time-ordered splits, purge
overlapping label horizons, and embargo adjacent folds when configured.
## Engineering conventions
- Target Python 3.12 and a local Apple Silicon machine with 16 GB RAM.
- Keep core logic in `src/microstructure`; notebooks may call but not duplicate it.
- Prefer Polars lazy/streaming scans and partitioned Parquet. DuckDB may query
partitions without loading the full data set.
- New data sources implement the adapter interfaces; exchange-specific fields do
not leak into normalized research modules.
- Store timestamps as UTC epoch nanoseconds and prices/quantities as decimal-safe
integer ticks/lots where the adapter supplies metadata; floating research
columns must document their units.
- Randomized procedures require an explicit seed.
- External raw data belongs under ignored `data/raw`; only small, documented test
fixtures belong in Git.
## Verification
Run focused tests after each meaningful phase and `make check` before handoff.
Tests must cover sequence gaps and book invariants, temporal leakage, purged
splits, deterministic simulations, partial fills, fees, and latency. A test may
not call the public internet; mock adapters at the HTTP boundary.
Primary commands:
```text
make setup
make download-sample
make validate-data
make smoke
make test
make reproduce-sample
make report
make dashboard
```
## Documentation discipline
Record material assumptions and reversals in `docs/DECISION_LOG.md`. Keep
`STATUS.md` honest and current. Update `docs/PROJECT_PLAN.md` acceptance evidence
when a milestone moves state. Do not manually paste model metrics into prose;
reports must read machine-generated run artifacts.
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