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dissertation-dataset

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item-1a
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bert
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metadata 
license: other
tags:
  - finance
  - nlp
  - sec-filings
  - item-1a
  - volatility
  - bert
  - bertopic
pretty_name: Dissertation Phase 1 Dataset — Hybrid Financial Risk Modelling

Dissertation Dataset — Phase 1 Data Pipeline

Project: Hybrid Topic and Domain-Adaptive Modelling for Financial Risk and Forecasting Institution: University of Edinburgh, School of Informatics Supervisor: Prof Tiejun Ma

This is a private research dataset. All files are used exclusively within the scope of this dissertation project and must not be redistributed.

What This Repo Contains

This dataset repo holds all Phase 1 pipeline outputs needed to run Phases 2–5 of the dissertation. It is the single source of truth for the cluster environment.

File Size Description
sp500_1A.tar.gz ~440 MB Item 1A Risk Factor text corpus — 8,247 pickle files, one per {TICKER}_{YEAR}, covering S&P 500 firms 2006–2025. Each pickle is a plain string of the full Item 1A section.
feature_table.parquet ~0.2 MB Phase 1 master table — 8,105 rows, one per filing. Columns: ticker, cik, permno, sic, fiscal_year, filing_date, report_date, lagged_vol_30d, fwd_vol_30d. Placeholder columns for embedding (Phase 2) and topic_vector (Phase 4).
filings_index.csv ~0.9 MB EDGAR submissions API output — filing dates, SIC codes, and has_pickle flag for all 656 CIKs. 11,447 total 10-K filings (2006–2025).
volatility_labels.csv ~0.7 MB 30-day annualised volatility windows per filing. lagged_vol_30d = AR(1) baseline; fwd_vol_30d = prediction target. 94.9% coverage.
permno_linkage.csv <0.1 MB CIK → PERMNO mapping from WRDS CCM. 651/656 firms matched.
sp500_union_constituents(1).csv <0.1 MB S&P 500 universe — 656 unique CIK/ticker pairs (historical constituents).
README.md — This file.

How to Download on the Cluster 

# One-time login
huggingface-cli login

# Download all files
huggingface-cli download SarthakVishnu/dissertation-dataset \
    --repo-type dataset \
    --local-dir ~/dissertation/datasets/

# Unzip the Item 1A corpus
cd ~/dissertation/datasets/
tar -xzf sp500_1A.tar.gz && rm sp500_1A.tar.gz

How Each File Is Used Per Phase

Phase Files Used
Phase 2 — DAPT sp500_1A/ (MLM pretraining corpus, train split ≤2024)
Phase 3 — Contrastive FT sp500_1A/ + filings_index.csv (SIC codes for sector-view positive pairs)
Phase 4 — BERTopic sp500_1A/ + feature_table.parquet (per-filing topic vectors)
Phase 5 — Ablation feature_table.parquet + volatility_labels.csv (downstream vol forecasting)

Temporal Split

Split Criterion Approx. Filings Role
Train filing_date < 2025-01-01 ~7,700 DAPT, contrastive FT, BERTopic
Val 2025-01-01 ≤ filing_date < 2026-01-01 ~280 Perplexity checkpointing, FinMTEB eval
Test filing_date ≥ 2026-01-01 ~125 Held-out volatility forecasting

Licence & Ethics

  • Item 1A text and EDGAR-derived data are from publicly available SEC filings.
  • WRDS/CRSP-derived data (permno_linkage.csv, volatility_labels.csv, feature_table.parquet) is used under the University of Edinburgh's institutional licence and must not be redistributed externally.
  • No personal data or human subjects are involved.