# Discussion 1: The New Quant - LLMs in Finance

## Session Plan

1. **Who am I** — Introductions and background
2. **Syllabus** — Course overview, structure, and expectations
3. **The New Quant** — Survey of LLM applications in finance (Fu 2025)
4. **Expected Returns and LLMs** — The Lopez-Lira & Tang finding on scale and financial sentiment
5. **HW0 in class** — Environment setup and tool installation
6. **HW1** — Will be released in the next day or two

## Topics

- **LLMs Transforming Finance** — A tour of how LLMs are reshaping quantitative finance across 6+ application categories
- **AI Copilots Intro** — Getting started with Claude Code and Cursor for AI-assisted development
- **Expected Returns and LLMs** — Why model scale matters for financial sentiment classification
- **ChartBook: Cataloging Research** — Using ChartBook to make research repositories discoverable by humans and AI agents

## Read on Your Own

- **API and Structured Outputs** — Calling LLM APIs (OpenAI, OpenRouter) and extracting structured data with Pydantic

```{toctree}
:maxdepth: 1
discussions/llms_transforming_finance.md
discussions/expected_returns_llms.md
discussions/chartbook_research_catalog.md
discussions/api_and_structured_outputs.md
discussions/review_w01.md
```