The goal of a time series regression problem is best explained by a concrete example. Suppose you own an airline company and you want to predict the number of passengers you'll have next month based ...

Artificial intelligence (AI) technologies are currently revolutionizing industries and enabling automation on a scale we've never seen before. Of course, none of this is possible without data. These ...

1. Difference Equations -- 2. Lag Operators -- 3. Stationary ARMA Processes -- 4. Forecasting -- 5. Maximum Likelihood Estimation -- 6. Spectral Analysis -- 7 ...

Time series forecasts are used to predict a future value or a classification at a particular point in time. Here’s a brief overview of their common uses and how they are developed. Industries from ...

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 ...

Regression is a statistical tool used to understand and quantify the relation between two or more variables. Regressions range from simple models to highly complex equations. The two primary uses for ...

Modern oscilloscopes capture, view, measure, and analyze complex RF signals in the time, frequency, and modulation domains. Time-domain analysis, the original oscilloscope function, allows users to ...

Emily Norris is the managing editor of Traders Reserve; she has 10+ years of experience in financial publishing and editing and is an expert on business, personal finance, and trading. Thomas J ...