Stock Market Prediction Using Machine Learning(ML)Algorithms
<p>Stocks are possibly the most popular financial instrument invented for building wealth and are the centerpiece of any investment portfolio. The advances in trading technology has opened up the markets so that nowadays nearly anybody can own stocks. From last few decades, there seen explosiv...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Ediciones Universidad de Salamanca
2020-06-01
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| Series: | Advances in Distributed Computing and Artificial Intelligence Journal |
| Subjects: | |
| Online Access: | https://revistas.usal.es/index.php/2255-2863/article/view/21366 |
| _version_ | 1818042863964913664 |
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| author | Muhammad UMER Muhammad AWAIS Muhammad MUZAMMUL |
| author_facet | Muhammad UMER Muhammad AWAIS Muhammad MUZAMMUL |
| author_sort | Muhammad UMER |
| collection | DOAJ |
| description | <p>Stocks are possibly the most popular financial instrument invented for building wealth and are the centerpiece of any investment portfolio. The advances in trading technology has opened up the markets so that nowadays nearly anybody can own stocks. From last few decades, there seen explosive increase in the average person’s interest for stock market. In a financially explosive market, as the stock market, it is important to have a very accurate prediction of a future trend. Because of the financial crisis and recording profits, it is compulsory to have a secure prediction of the values of the stocks. Predicting a non-linear signal requires progressive algorithms of machine learning with help of Artificial Intelligence (AI).</p><p>In our research, we are going to use Machine Learning Algorithm specially focus on Linear Regression (LR), Three month Moving Average(3MMA), Exponential Smoothing (ES) and Time Series Forecasting using MS Excel as best statistical tool for graph and tabular representation of prediction results. We obtained data from Yahoo Finance for Amazon (AMZN) stock, AAPL stock and GOOGLE stock after implementation LR we successfully predicted stock market trend for next month and also measured accuracy according to measurements.</p> |
| first_indexed | 2024-12-10T08:53:05Z |
| format | Article |
| id | doaj.art-9d269a3b3e1f4bf28fee1d8fb07ebff7 |
| institution | Directory Open Access Journal |
| issn | 2255-2863 |
| language | English |
| last_indexed | 2024-12-10T08:53:05Z |
| publishDate | 2020-06-01 |
| publisher | Ediciones Universidad de Salamanca |
| record_format | Article |
| series | Advances in Distributed Computing and Artificial Intelligence Journal |
| spelling | doaj.art-9d269a3b3e1f4bf28fee1d8fb07ebff72022-12-22T01:55:31ZengEdiciones Universidad de SalamancaAdvances in Distributed Computing and Artificial Intelligence Journal2255-28632020-06-01849711610.14201/ADCAIJ2019849711618345Stock Market Prediction Using Machine Learning(ML)AlgorithmsMuhammad UMER0Muhammad AWAISMuhammad MUZAMMUL1gcufGCUF<p>Stocks are possibly the most popular financial instrument invented for building wealth and are the centerpiece of any investment portfolio. The advances in trading technology has opened up the markets so that nowadays nearly anybody can own stocks. From last few decades, there seen explosive increase in the average person’s interest for stock market. In a financially explosive market, as the stock market, it is important to have a very accurate prediction of a future trend. Because of the financial crisis and recording profits, it is compulsory to have a secure prediction of the values of the stocks. Predicting a non-linear signal requires progressive algorithms of machine learning with help of Artificial Intelligence (AI).</p><p>In our research, we are going to use Machine Learning Algorithm specially focus on Linear Regression (LR), Three month Moving Average(3MMA), Exponential Smoothing (ES) and Time Series Forecasting using MS Excel as best statistical tool for graph and tabular representation of prediction results. We obtained data from Yahoo Finance for Amazon (AMZN) stock, AAPL stock and GOOGLE stock after implementation LR we successfully predicted stock market trend for next month and also measured accuracy according to measurements.</p>https://revistas.usal.es/index.php/2255-2863/article/view/21366stock market predictionmachine learning(ml)algorithmslinear regressionexponential smoothingtime series forecasting |
| spellingShingle | Muhammad UMER Muhammad AWAIS Muhammad MUZAMMUL Stock Market Prediction Using Machine Learning(ML)Algorithms Advances in Distributed Computing and Artificial Intelligence Journal stock market prediction machine learning(ml) algorithms linear regression exponential smoothing time series forecasting |
| title | Stock Market Prediction Using Machine Learning(ML)Algorithms |
| title_full | Stock Market Prediction Using Machine Learning(ML)Algorithms |
| title_fullStr | Stock Market Prediction Using Machine Learning(ML)Algorithms |
| title_full_unstemmed | Stock Market Prediction Using Machine Learning(ML)Algorithms |
| title_short | Stock Market Prediction Using Machine Learning(ML)Algorithms |
| title_sort | stock market prediction using machine learning ml algorithms |
| topic | stock market prediction machine learning(ml) algorithms linear regression exponential smoothing time series forecasting |
| url | https://revistas.usal.es/index.php/2255-2863/article/view/21366 |
| work_keys_str_mv | AT muhammadumer stockmarketpredictionusingmachinelearningmlalgorithms AT muhammadawais stockmarketpredictionusingmachinelearningmlalgorithms AT muhammadmuzammul stockmarketpredictionusingmachinelearningmlalgorithms |