Paper: arXiv 2611.01355

Authors: Matthew Lorig

Abstract

These lecture notes give a broad introduction to financial derivatives at the level of a Masters program in quantitative finance. Topics include forward and futures contracts, no-arbitrage bounds and put-call parity, the binomial model, the fundamental theorems of asset pricing, Brownian motion and Itô calculus, the Black-Scholes model, the Greeks, variance swaps, local and stochastic volatility models including Heston, and static hedging of barrier options. Each chapter ends with exercises, and complete solutions, including Python code for the computational exercises, are provided in an appendix. The notes are open source: the LaTeX source is available at https://github.com/mattlorig/intro-financial-derivatives, and readers are invited to submit corrections and additions.

Complexity vs Empirical Score

  • Math Complexity: 8.0/10
  • Empirical Rigor: 2.0/10
  • Quadrant: Lab Rats — theoretically deep, empirically untested

Why this score: This paper is a set of lecture notes, not a research paper. As such, it excels in clarity, completeness, and reproducibility for educational purposes. However, it lacks empirical rigor and novelty, as its purpose is to introduce established concepts rather than present new research or backtesting.

Research Flowchart

  flowchart TD
    A[Research Goal/Question: Introduce Financial Derivatives] --> B{Key Methodology: Quantitative Finance Concepts};
    B --> C{Data/Inputs: Real-World Derivatives, Market Data, Theoretical Models};
    C --> D[Computational Processes: Python for Pricing/Hedging, Stochastic Calculus];
    D --> E[Key Findings/Outcomes: Understanding of Derivatives Pricing (Black-Scholes), Hedging (Greeks), Arbitrage-Free Principles];
    E --> F[Further Outcomes: Open-Source Notes, Exercises, Python Solutions];