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Stock exchange prediction system

By: Material type: TextTextPublication details: Islamabad. Department of Computer Science ( Air University Main Campus) 2013.Description: 55p. CDDDC classification:
  • KHA
Summary: The “Stock Exchange Forecasting and Monitoring System “is a software through which we can make predictions based on the past trends of that company and find out if the upcoming stock prices will rise or fall beforehand . Stock traders and investors are constantly looking for a way to yield significant profit on their investments in the stock market and we intend to make an attempt to make this process more accurate and computationally effortless. This software will provide an efficient and an accurate way for stock traders and investors to buy or sell stocks at a profitable margin. Our software also takes over the man in the middle and eliminates the need for a stockbroker. Through it every person can act as their own stockbroker with a powerful tool by their side. We intend to do this using various techniques which include Moving Averages, Hidden Markov Model’s and Support Vector Machines. The Hidden Markov Model using the old values to predict the new values. The Support Vector Machine enables us to predict the next day’s close value as a set of either high or low. We also intend to use some data visualization techniques through which we can visualize data so that even a layman can understand the results.
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The “Stock Exchange Forecasting and Monitoring System “is a software through which we can make predictions based on the past trends of that company and find out if the upcoming stock prices will rise or fall beforehand . Stock traders and investors are constantly looking for a way to yield significant profit on their investments in the stock market and we intend to make an attempt to make this process more accurate and computationally effortless. This software will provide an efficient and an accurate way for stock traders and investors to buy or sell stocks at a profitable margin. Our software also takes over the man in the middle and eliminates the need for a stockbroker. Through it every person can act as their own stockbroker with a powerful tool by their side. We intend to do this using various techniques which include Moving Averages, Hidden Markov Model’s and Support Vector Machines. The Hidden Markov Model using the old values to predict the new values. The Support Vector Machine enables us to predict the next day’s close value as a set of either high or low. We also intend to use some data visualization techniques through which we can visualize data so that even a layman can understand the results.

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