Narges Habibi’s Blog

An artificial neural network (ANN), often just called a “neural network” (NN), is a mathematical model or computational model based on Biological neural networks. It consists of an interconnected group of artificial neurons. In a neural network model, simple nodes are connected together to form a network of nodes — hence the term “neural network”.

In most cases an ANN is an adaptive system that changes the strength (weights) of the connections in the network, based on information that flows through the network during the learning phase.

The utility of artificial neural network models lies in the fact that they can be used to infer a function from observations. This is particularly useful in applications where the complexity of the data or task makes the design of such a function by hand impractical.

(Source: Wikipedia)

ANN has application in many areas, like Stock Market Prediction. We’ve investigated the efficiency of ANN for predicting the low and high monthly stock price, by using some technical indicators, and prices of previous months, as ANN input.

The ANN is a feedforward one with Backpropagation learning algorithm. We have predicted low and high monthly price for some companies in S&P500. Prices are gotten from Yahoo! Finance. Several technical indicators are applied and results are analyzed. Implementation is done with NeuroSolutions software. You can find our paper here.

More information:
- M. Hagan et al., “Neural Network Design”
- In depth description of Technical Indicators
- S&P500 list