Stock-Market Related Price Determination in Consideration of Time Dynamic Cost Factors

Abstract

Providing their customers with the most accurate pricing has become one of the key competitive factors ensuring commercial success for tool and mould manufacturers. However, time dynamic costs influence the pricing calculations significantly, indeed, they are rarely taken into consideration adequately. This paper presents an approach which allows to improve conventional tool performances by developing a novel forecasting method which combines mechanisms related to the stock market with techniques of stochastic prediction methods.

Prediction of Stock Market Price using Neural Network

“…Result of technical analysis is much better than fundamental analysis. [8] Indicators for stock prediction In statistics, a moving average is a calculation to analyze data points by creating a series of averages of different type of subsets of the full data set. It is also called a moving mean and is a type of finite impulse response filter.…”