MCQ IN COMPUTER SCIENCE & ENGINEERING

Detailed explanation-1: -ARIMA is one such model that is used for predicting futuristic time-related predictions. LSTM is also one such technique that has been used for stock price predictions.

Detailed explanation-2: -Long short-term memory (LSTM): Many experts currently consider LSTM as the most promising algorithm for stock prediction.

Detailed explanation-3: -Which machine learning algorithm is best for stock price prediction? Based on experiments conducted in this article, LSTMs seem to be the best initial approach in solving the stock price prediction problem. Other methods can combine features extracted from LSTM or Bi-LSTM models and fed into a classical ANN regressor.

Detailed explanation-4: -Stock market algorithms are computer programs that can perform market filtering, analytics, and trade executions in the stock market. They can be as simple as bracket orders or extrapolated a thousand times over with a million lines of code.

Detailed explanation-5: -Purchasing power parity looks at the prices of goods in different countries and is one of the more widely used methods for forecasting exchange rates due to its indoctrination in textbooks. The relative economic strength approach compares levels of economic growth across countries to forecast exchange rates.