Implementation of time series approaches to financial data
Date
2016-08
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
BRAC University
Abstract
We study a time series approach to nancial data, speci cally the ARIMA models, and
build a web based platform for stock market enthusiasts to analyze time series of stock
market returns data and to t ARIMA models to the series to forecast future returns.
This system also acts as an informative tool by providing helpful instructions to the users
regarding the analysis and model- tting procedure. It uses R to perform the statistical
computations.
Description
Cataloged from PDF version of thesis report.
Includes bibliographical references (page 82-83).
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016.
Includes bibliographical references (page 82-83).
This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016.
Keywords
Time series approaches, Autocorrelation function
