Can Data Science Help in The Stock Market?
Nowadays, data science has grown to become a popular subject with many utilizing it across many businesses and industries. Some of the most prevalently stored data include information about consumers, sales, inventory, and even cash.
With new innovative technologies, data science concepts may now also be applied towards the Stock Market. In fact, data science is used to make analyses on the market, where organizations may determine which stocks are worth the investment and when.
Applications of Data Science in the Stock Market
Algorithms → In data science, an algorithm is a set of rules used to perform a certain task. With algorithmic trading in the stock market, trading algorithms analyze data to check if they satisfy specific rules in order to make safer more intelligent decisions on stock purchases. (Ex: Buying a stock only after it has gone down exactly 6% that day)
Training → Combining both the uses of data science and machine learning, training allows for a machine learning model to analyze selected data in order to discover new patterns for intelligent predictions on things like future stock prices.
Testing → On the same token as training, machine learning models may utilize data science in order to test their accuracies on their predictions. For instance, in order to validate the model’s performance, we would compare their predictions to that of pre-existing stock price data.
Classification → With data science and machine learning, a type of model called a ‘Classification Model’ can be used to analyze stock data like P/E Ratio, Daily Volume, or Total Debt in order to determine certain classifications for stocks such as whether we should buy, hold, or sell.
How Effective is Data Science in the Stock Market?
Currently, many companies and firms such as Google or Microsoft utilize data science and machine algorithms to predict stock prices. However, they have had the same amount of success almost as they did failures. In other words, although data science may provide assistance to traders within the stock market, it is still capped to a certain extent. Nevertheless, data science will continue to advance towards providing ever more accurate predictions and analyses in the stock market in the future.
Conclusion:
Although the patterns within the stock market may seem extremely abstract and unpredictable, with the help of data science, traders are able to better predict stock trends and trade more wisely. However, as data science and machine learning are still developing fields, one must still take precautions and invest at their own risk.
