Data Loader - Valuation101

Module: `lib/lookup.py`

Loads and queries the reference datasets used throughout the valuation. Designed for token efficiency — returns only the single relevant row (~200 tokens) instead of loading full files (~35K tokens).

Key functions

`get_industry()`

Look up industry averages for a given industry name and region. Parameters:

industry_name — canonical Damodaran industry name (e.g., “Software (Internet)”)
region — 'US' or 'Global'

Returns: Dictionary with revenue_growth_5y, pretax_operating_margin, sales_to_capital, aftertax_roc, cost_of_capital, beta, std_dev.

`get_distribution()`

Look up quartile distributions for an industry (Q1, median, Q3). Parameters:

industry_name — canonical Damodaran industry name

Returns: Nested dictionary with distribution stats for revenue_growth_3y, pretax_operating_margin, sales_to_capital. Returns None if distribution data is not available for the industry.

`get_country_erp()`

Look up equity risk premium for a given country. Parameters:

country — country name (e.g., “United States”, “India”)

Returns: Dictionary with equity_risk_premium, country_risk_premium, rating.

`get_industry_by_ticker()`

Look up which Damodaran industry a ticker belongs to. Parameters:

ticker — stock ticker symbol

Returns: Industry name string.

Reference data

File	Contents	Size	Refresh cycle
`country_erp.json`	Country equity risk premiums (192 countries)	43 KB	January (annual)
`industry_averages_us.json`	US industry stats (96 industries): growth, margins, betas, ROIC	85 KB	January (annual)
`industry_averages_global.json`	Global equivalents	86 KB	January (annual)
`input_stat_distributions.json`	Quartile distributions for benchmarking	87 KB	January (annual)
`indname_us.json`	~6,000 US companies → industry classification	1.9 MB	January (annual)
`synthetic_rating_spreads.json`	ICR → rating → default spread tables	3.7 KB	Infrequent
`rating_default_probabilities.json`	Moody’s/S&P cumulative default rates	1.7 KB	Infrequent
`bls_survival_rates.json`	Corporate failure rates by sector + age	1.5 KB	Infrequent
`rd_amortization_by_industry.json`	R&D useful life by industry (2–10 years)	3.2 KB	Infrequent
`wacc_distribution_percentiles.json`	WACC decile distribution by region	1.4 KB	Infrequent
`xbrl_ticker_overrides.json`	Manual XBRL tag overrides for edge cases	1.7 KB	As needed

All datasets are sourced from Damodaran’s data pages (January 2026 update).

​Module: lib/lookup.py

​Key functions

​get_industry()

​get_distribution()

​get_country_erp()

​get_industry_by_ticker()

​Reference data