Implementation of time series approaches to financial data

Thumbnail Image

Date

2016-08

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.

Keywords

Time series approaches, Autocorrelation function

Citation

Endorsement

Review

Supplemented By

Referenced By