> ## Documentation Index
> Fetch the complete documentation index at: https://valuation-101.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Data Loader

> Load Damodaran's reference datasets efficiently — returns only the relevant row instead of the full file.

## 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](https://pages.stern.nyu.edu/~adamodar/New_Home_Page/data.html) (January 2026 update).