OLS handles linear models; maximum likelihood handles nearly everything else. These slides build the likelihood function from a distributional assumption, define the MLE, and explain why it is the estimator behind ARMA and GARCH model fitting in every econometrics package.
What these materials cover
- From distributional assumptions to the likelihood function
- The maximum likelihood estimator: definition and intuition
- MLE vs OLS: when they coincide and when they differ
- Why ARMA and GARCH estimation relies on maximum likelihood
- Reading MLE output from econometrics software
Download
Free to download and use for personal study. Written for my own university teaching; shared here as evidence of teaching style and depth.
Lecture slides: maximum likelihood estimation (PDF)
Who this is for
MSc students meeting MLE in econometrics or finance courses, and anyone estimating ARMA/GARCH models who wants to know what the software is doing.
Working on this topic?
Send the module topic list, the problem set and where you're stuck. A free consultation diagnoses whether the difficulty is definitions, derivations or software output — and proposes a plan.
Related free resources
- Financial Econometrics — all lecture slides & problem sets
- Maximum likelihood estimation explained — study note
- ARMA estimation and model selection — study note
- All teaching materials — notes, exercises and solutions
One-to-one help
For help with this material — or the module it belongs to — see econometrics tuition or financial econometrics tuition. The first consultation is free, with no obligation.
Free worked video lectures: @economaths on YouTube.