Stock Forecast Algorithms: An Overview

dr roitmanCo-Founder & CTO of I Know First Ltd. With over 35 years of research in AI and machine learning. Dr. Roitman earned a Ph.D  from the Weizmann Institute of Science
A stock forecast relies on a series of accumulative events which determine the rise and fall of a stock. While stock forecast is not always entirely accurate, there seems to be a great deal of accuracy among many of the most popular stock market forecast reviews. By incorporating popular types of convergence averages and moving averages which have been used for stock forecast for years with more updated technology and genetic algorithms, professionals are now able to build a complex and intelligent algorithm to predict stocks more accurately and efficiently.

Learning systems
Learning systems is a term which is becoming more widely accepted as an effective and efficient means of replacing human error. With the availability of learning systems on the rise, stock forecast services are able to use this technology to program software capable of rapid and accurate stock forecast. The fundamentals of an algorithm lie in the principles of an artificial neural network (ANN). It is based on a series of consistent commands with conditional circumstances for each movement based, on a variety of internal and external factors. But the series of movement and reaction is somewhat limited. This technology must also be combined with a more sophisticated algorithm: The genetic algorithm for stock forecast.

Genetic algorithm
Genetic algorithm is an optimization method that mimics the natural selection process of biological systems. It combines two or more good algorithms resulting in a new algorithm that could be better than each of the previous ones. It also uses random variations, or “mutations”. At each cycle the best combination is selected for further refinement. Repeating these processes may result in a new, better fitting algorithm. All this requires large computing power and careful programming to avoid some common traps, such as local minima and overfitting.

Machine Learning
A genetic algorithm is very much centered on the technology of machine learning. A learning system can gather information from external databases to make decisions which go beyond its original capability with an ANN. By reviewing stock performance and taking into consideration hundreds of thousands of publicly shared corporate data, these clever algorithms are able to predict the future direction of a stock rather accurately. Each stock forecast presents an opportunity for a trader to make both modest and generous profits.

We are quickly becoming a society in which machines do much of our work. By applying both simple and highly complex mathematical equations, we are more quickly and easily able to determine the most logical outcome of events. This is an exciting age for traders and brokers, because there is now online access to stock market forecast algorithms which can help make more profitable trades and spend less time wondering why you didn’t place the most intelligent trade you could. Traders everywhere are able to reap the rewards of higher intelligence, with more up to date and accurate stock forecast at the fingertips of every person investing in the stock market.









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