It is difficult to predict stock market performance and involves a certain amount of risk. An accurate prediction could result in a significant amount of profit. The stock market is influenced by a number of factors:
- News, both domestic and international
- Government reports
- Natural disasters
The stock market is constantly evolving and it regularly generates a huge amount of data regarding bids, buys and puts. Data scientists have found out that using Big Data mining techniques and machine learning strategies, the movements in the markets can be predicted in a matter of seconds. Earlier, experts used to employ various methods to try to predict the stock market; however, with the advent of deep learning and data science, these predictions are quicker and more accurate than ever before. This significantly increases the profits of businesses and investors alike.
What are Stock Prediction Systems?
Stock prediction systems are programs that use algorithms to predict future trends in the stock market. The algorithms used in stock prediction systems were originally used for scientific research in fields such as genetics, astronomy and quantum physics.
However, scientists soon discovered that these algorithms can be applied to stock markets as the field produces huge amounts of data and follows some sort of pattern.
The most commonly used techniques in stock market prediction include genetic algorithms (GA) and artificial neural networks (ANNs).
The use of ANN methods for stock prediction has been found to be widely successful. The ANNs predict future lows by analyzing low price and time lags, while the future highs are predicted using lagged highs. These predictions are then used to determine stop prices for buying and selling.
Benefits of using a Stock Prediction System
Predicting stock market performance is challenging and risky. There are many factors to be considered – physical factors, psychological and behavioral factors. These aspects make share prices unstable and difficult to predict accurately. However, with the use of algorithms and data science, there has been improvement in the predictions. The following are some of the benefits of using stock prediction systems:
- Using ANN systems, which utilize a classification approach as opposed to a traditional quantitative output approach, produces a better predictive reliability.
- Certain kinds of data which could earlier not be collected or processed, like unstructured text data, can be used for making predictions which the help of algorithms. This unstructured text data refers to news reports or public sentiment. Use of Big Data techniques makes it possible to keep track of values, opinions and behavioral patterns of people while making predictions; this means that the predictions are not based solely on technical or numerical data.
- Algorithms help in speedily processing huge amounts of data that is perishable. In the stock market, conditions are constantly and rapidly changing. This means that in order to predict future events in the market, a reliable and quick system is needed. Algorithms provide this benefit. Algorithms may use pre-processed data, reducing data storage space and speeding up the calculations.