STOCK ANALYSIS AND PREDICTION USING PYTHON |
Author(s): |
Prof. J. M. Waghmare |
Keywords: |
machine learning, stock market prediction, artificial neural network, algorithm, investment decision, ARIMA Model |
Abstract |
In Prediction of stock prize is complex and hard task to perform for human abilities, it need complex calculation and also logical understanding of stock market nature and risk factor. Stock market investing strategies are multiple and complex and depends on data or information that you have and this information provides huge possibilities of decision to make Stock analysis and prediction in financial world always to be unpredictable and even not logical, financial data is hard find relationship between the data should necessarily offers a complex structure due to the which if often makes it hard to find any relation or reliable patterns. For developing or modeling complex structures in python needs machine learning and its algorithms that capable of finding hidden structures within the data and predict how they will affect them in the future. The most efficient methodology to use is Machine Learning Machine Learning is good example who can copy human behavior and improve performance on some task or set of tasks Machine learning has the strength and facility to ease the whole process by analyzing large dataset, analyzing different particular patterns and create a single output that give row burst idea to traders towards a particular asset decision on prediction. In now days we can download dataset as per our requirement for such model building and training and testing, For example from Kaggle. It is popular place to search for datasets. |
Other Details |
Paper ID: IJSARTV Published in: Volume : 8, Issue : 12 Publication Date: 12/6/2022 |
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