Could you elaborate on why Generalized Linear Models (GLM) are often considered superior to Linear Models (LM) in the realm of cryptocurrency and financial analysis? While LMs have their uses, GLMs seem to be gaining popularity. Is it due to their ability to handle non-linear relationships and non-normal distributions, which are prevalent in financial data? Or is it their flexibility in incorporating different link functions that allows for a more nuanced understanding of the data? Furthermore, could you provide examples of scenarios where GLMs have delivered superior predictive power or insights compared to LMs in the field of cryptocurrency and finance?
5 answers
Stefano
Sun Jun 30 2024
In contrast to standard linear regression, GLM possesses greater flexibility.
CryptoWizardry
Sun Jun 30 2024
This flexibility is attributed to GLM's ability to handle non-continuous or unbounded output variables.
TaekwondoMasterStrengthHonor
Sun Jun 30 2024
GLM allows for variations in unconstrained inputs to have an impact on the output variable, but in a manner that is appropriately scaled or constrained.
ZenBalanced
Sun Jun 30 2024
GLM, standing for Generalized Linear Model, is a broad category of statistical methods that extend traditional linear regression.
PhoenixRising
Sun Jun 30 2024
Such flexibility enables GLM to be applied in a wider range of real-world problems, beyond those where traditional linear regression would suffice.