the difficulty of determining intrinsic value of stock prices have led many people to use technical analysis in order to forecast stock prices in the future. to predict the stock price we need to determine the generating process of stock prices. in recent years many time - series methods have been used for forecasting purposes. one of these methods is the rescaled range analysis (ris). in the a...

Since the increasing trend of Guangzhou housing price stopped after Covid-19 epidemic in early 2020, investors and citizens are hesitant about purchasing, keeping, or selling their real estate Guangzhou. This paper intends to utilize ARIMA model forecast market from September 2022 August 2023 based on data last 10 years, compare yearly profits purchasing houses storing money Bank China for a ye...

In section 2, a definition of “trend” is given. In section 3, it is shown how to detect a trend using an auto-associative neural network. Experimental methods and results are reported in sections 4 and 5, and concluding remarks are given in section 6. Abstract — This paper reports the results of a new neural network based trend detector. An auto-associative neural network was trained with the “...

in this article, real exchange rate behavior and its effects on macroeconomic variables are studied by explaining two models; impulse function and forecasting predicted error decomposition. studies show that high artificial currency value has caused domestic and foreign accounts equilibrium disturbance and foreign income decrease due to the slackening of commercial and agricultural activities, ...

In many practical situations, one needs to construct a model for an input/output process. For example, one is interested in the price of a stock five years from now. The rating industry description for the stock typically lists such indicators as the increase in the price over the last year, the last 5 years, 10 years, life of the stock, P/E ratio, and alpha and beta risk factors. The buyer is ...