Investopedia

Understanding Prior Probability in Bayesian Statistics

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...
Nature

Bayesian Estimation and Maximum Likelihood Methods

Bayesian estimation and maximum likelihood methods represent two central paradigms in modern statistical inference. Bayesian estimation incorporates prior beliefs through Bayes’ theorem, updating ...
Scientific American

What is Bayes's theorem, and how can it be used to assign probabilities to questions such as the existence of God? What scientific value does it have?

Chris Wiggins, an associate professor of applied mathematics at Columbia University, offers this explanation. A patient goes to see a doctor. The doctor performs a test with 99 percent ...
Risk

Volatility-sensitive Bayesian estimation of portfolio value-at-risk and conditional value-at-risk

We suggest a new method for integrating volatility information for estimating the value-at-risk and conditional value-at-risk of a portfolio. This new method is developed from the perspective of ...
Investopedia

Bayes' Theorem: What It Is, Formula, and Examples

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...