Degree
Master of Science in Economics
Faculty / School
Faculty of Business Administration (FBA)
Department
Department of Economics
Date of Submission
2018-01-01
Supervisor
Dr. Mohammad Nishat, Institute of Business Administration, Karachi
Project Type
MSECO Research Project
Access Type
Restricted Access
Keywords
Neuroeconomics, Long-short term memory model (LSTM), KSE-100 index returns, Exponential moving average (EMA)
Abstract
Economics has inherited ideas from psychology and neuroscience to form a multidisciplinary subject ‘Neuroeconomics’. On the other hand, statistics, inspired by neuroscientific research, has embraced computational methods similar to neural network inside the human brain. We are at the center of a historic convergence among these subjects, aiming to understand how brain makes complex economic decisions and which model can better predict economic decisions. This paper explores the multidisciplinary research in economics, psychology, neuroscience and data science, with an attempt to demonstrate the application of neural network models in economic forecasting. The paper explores the latest methods in the field of artificial intelligence that are inspired by neural network models inside human brain. As demonstration, we have applied Long-Short Term Memory Model (LSTM) to forecast KSE-100 Index returns using non-parametric modelling.
Pages
x, 34
Recommended Citation
Jafri, B. A. (2018). Convergence of neuroeconomics and data science: an illustration through neural network modelling (Unpublished graduate research project). Institute of Business Administration, Pakistan. Retrieved from https://ir.iba.edu.pk/research-projects-mseco/3
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