Live analysis of stock and commodity data
Nowadays investors usually want to read and know the information in the fastest and efficient way. Financial data .provided in financial portals are too lengthy and not much summary provided. Irrelevant news is often added as part of the news too. This causes investors to spend their precious tim...
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sg-ntu-dr.10356-689932023-07-07T17:52:42Z Live analysis of stock and commodity data Aung Kyaw Kyaw Tun Foo Say Wei Lim Yong Ching School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Nowadays investors usually want to read and know the information in the fastest and efficient way. Financial data .provided in financial portals are too lengthy and not much summary provided. Irrelevant news is often added as part of the news too. This causes investors to spend their precious time to read and extract the data and they are unable to make immediate decision to response wisely according to the changes of the market. The delay might minimize their investment profit. Buying or selling of shares requires the constant real-time monitoring of its last-changed price quotes. Hence, the stock tracking system that monitor the last-changed price quotes of all the available companies and alerting the user with SMS and email upon hitting a pre-set triggering point would definitely help to cut down the time to sit in one place and monitor the price changes round the clock so that one can buy or sell correspondingly. A delay in one second may change the fortune in the world of fast-paced changing stock market. This report documents the project that employs web scraping technique to extract the stock quotes from real-time data source to better determine the trend of stock. Overall the stock tracking system is based on five technology components, Web Scraper, Microsoft Access Database, Active Server Pages (ASP), SMS Gateway, and Internet Information Service (lIS) Web Server. Bachelor of Engineering 2016-08-23T03:16:17Z 2016-08-23T03:16:17Z 2016 Final Year Project (FYP) http://hdl.handle.net/10356/68993 en Nanyang Technological University 91 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Aung Kyaw Kyaw Tun Live analysis of stock and commodity data |
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Nowadays investors usually want to read and know the information in the fastest and
efficient way. Financial data .provided in financial portals are too lengthy and not much
summary provided. Irrelevant news is often added as part of the news too. This causes
investors to spend their precious time to read and extract the data and they are unable to
make immediate decision to response wisely according to the changes of the market.
The delay might minimize their investment profit. Buying or selling of shares requires
the constant real-time monitoring of its last-changed price quotes. Hence, the stock
tracking system that monitor the last-changed price quotes of all the available
companies and alerting the user with SMS and email upon hitting a pre-set triggering
point would definitely help to cut down the time to sit in one place and monitor the
price changes round the clock so that one can buy or sell correspondingly. A delay in
one second may change the fortune in the world of fast-paced changing stock market.
This report documents the project that employs web scraping technique to extract the
stock quotes from real-time data source to better determine the trend of stock. Overall
the stock tracking system is based on five technology components, Web Scraper,
Microsoft Access Database, Active Server Pages (ASP), SMS Gateway, and Internet
Information Service (lIS) Web Server. |
author2 |
Foo Say Wei |
author_facet |
Foo Say Wei Aung Kyaw Kyaw Tun |
format |
Final Year Project |
author |
Aung Kyaw Kyaw Tun |
author_sort |
Aung Kyaw Kyaw Tun |
title |
Live analysis of stock and commodity data |
title_short |
Live analysis of stock and commodity data |
title_full |
Live analysis of stock and commodity data |
title_fullStr |
Live analysis of stock and commodity data |
title_full_unstemmed |
Live analysis of stock and commodity data |
title_sort |
live analysis of stock and commodity data |
publishDate |
2016 |
url |
http://hdl.handle.net/10356/68993 |
_version_ |
1772827081799892992 |