Finance

GloassaRy of Empirical Finance

• Topic: Common scripts used in quantitative finance / financial economics

• Code: (github)

• Language: R

• Intended Audience:

  • Used in some of my daytime MBA classes at KFBS (UNC)
  • No prior knowledge of R is expected
  • Users are expected to have an understanding of asset pricing, asset allocation, and a working knowledge of basis statistics

• Content:

  • Covers 4 key stages of any empirical project in this field
  1. Explore (data acquisition, cleaning, EDA),
  2. Explain (model development for CAPM, APT, Event Studies, etc..),
  3. Predict (forecasting techniques),
  4. Protect (via portfolio construction and risk measurement)

Constructing CMAs

• Topic: Guide on constructing long term capital market assumptions for asset allocation
• Slides: Slide Deck
• Intended Audience: Intended for those with basic knowledge of macro and financial markets
• Content:
  • I provide a structural framework for developing long-term capital market assumptions, which are vital for allocating investment funds.
  • I then apply this framework to the current macro environment.

Quantitative Methods in Finance

• Topic: Lecture notes for basic quantitative methods used in asset allocation
• Slides:
  • Step 1: Explore the data
  • Step 2: Explain the asset movement
  • Step 3: Forecast returns / vol / comovement
  • Step 4: Protect via diversification
• Intended Audience:
  • Slides in a 14 session daytime MBA course at KFBS (UNC)
  • Users are expected to have some working knowledge of asset allocation (e.g. CAPM, MPT), basic statistics and regression