Category: Quantitative Analysis

In this video from FRM Part 1 Quantitative Analysis section, we construct an appropriate null hypothesis and alternative hypothesis and distinguish between the two.

In this short video from FRM Part 1 curriculum, we try and understand the Wold’s Representation Theorem for representing a zero mean covariance stationary series.

In this short video from FRM Part 1 curriculum, we look at estimating parameters of the GARCH(1,1) model using Maximum Likelihood Estimation (MLE).

In this short video from FRM Part 1 curriculum, we take a first (and close) look at the Generalised Autoregressive Conditional Heteroskedasticity (GARCH) model.

In this short video, we cover the concept of conditional expectation, a concept that is relevant to both FRM Part 1 and FRM Part 2, notably with regards to Expected Shortfall.

In this short video from FRM Part 1 curriculum, we take a look at the inverse Transform Method used for repeatedly sampling or simulating a random variable that is stated to follow a certain (given) distribution.

In this short video from FRM Part 1, we go deeper into the concept of Partial Autocorrelations – explore what they mean, how they’re different from autocorrelations and how they’re estimated.

In this short video, we apply various concepts we learned from chapters in Quantitative Analysis section of FRM Part 1, to answer this question: What is the distribution of the sum of two random variables, each of which follows the uniform distribution?

In this short video, we explore the distribution of option payoffs for simple options like calls and puts and for contracts like forwards, given the distribution of the driver of their payoffs – the stock price.

In this swatch, we spend some time exploring a very important distribution in option pricing – the lognormal distribution.