Tehran Institute for Advanced Studies (TeIAS)

/ Forecasting in Big Data Environments __ Ali Habibnia


Forecasting in Big Data Environments

May 24, 2017


Khatam University, Building No2.
Address: Mollasadra Blvd., North Shirazi St., East Daneshvar St., No.17. See location on Google map


Dr. Ali Habibnia

Ph.D. in Statistics (Time Series and Statistical Learning) at London School of Economics


In this talk, we consider forecasting in big data environments. We develop a category of high-dimensional nonlinear forecasting to benefit from many potential predictors while accounting for any possible nonlinear dynamics within the environment. Combining these two elements is a developing area of research. To overcome the curse of dimensionality and to manage data and model complexity, we suggest a shrinkage estimation of a backpropagation algorithm of a neural network with skip-layer connections including both linear and nonlinear structure. We apply this approach to forecast equity returns, and show that capturing nonlinear dynamics between equities significantly improves the quality of forecasts over current univariate and multivariate factor models.

Target Audience

All students and enthusiasts are invited to attend this lecture



Ali Habibnia is a Ph.D. in Statistics (Time Series and Statistical Learning) at London School of Economics. He received his MSc in Quantitative Finance from Cass Business School, and he also holds an MSc and a BA in Economics from the University of Tehran. His research focuses on the intersection of statistics, machine learning, and big data analytics, with a particular interest in the high-dimensional nonlinear time series analysis and their applications in financial forecasting and identifying risk in highly interconnected financial networks