Proper models for prediction of time series data can be an advantage in making important decisions. In this study, we tried with the comparison between one of the most useful classic models of economic evaluation, auto-regressive integrated moving average model and one of the most useful artificial intelligence models, adaptive neuro-fuzzy inference system (ANFIS), investigate modeling procedur...

Gold price has significant nonlinearity and time-variance with many indeterminate influencing factors. In order to improve the forecast accuracy of gold price, this paper puts forward a gold price forecast model combing projection pursuit with neural network. At first, projection pursuit algorithm is used to screen the influencing factors, and then the influencing factors are used as the input ...

in this paper, we investigate variations of gold coin price and also probe to model the fluctuations and conditional variance of coin market returns. the data consist of daily market prices of gold coin over the 1380 – 1386 period. since volatility clustering is viewed in time series of returns, we employ arch (autoregressive conditional heteroskedasticity) methodology in order to model the var...

This paper studies the exposure of the stock prices of Australian gold-mining firms to changes in gold prices and the valuation effects of gold price exposure. Goldmining firms have significant gold price exposure; the price of the average goldmining stock moves 0.76% for each 1.00% change in Australian-dollar-denominated gold prices. Evidence from the behaviour of stock price sensitivities sug...

the successful key of trading in the forex market is the selection of correct exchange in proper time based on an exact prediction of future exchange rate. foreign exchange rates are affected by many correlated economic, political and even psychological factors. therefore, in order to achieve a profitable trade these factors should be considered. the application of intelligent techniques for fo...

In this paper, the effects of oil and gold prices on stock market index are investigated. We use a cointegrated vector autoregressive Markov-switching model to examine the nonlinear properties of these three variables during the period of January 2003 - December 2014. The Markov-switching vector-equilibrium-correction model with three regimes representing "deep recession", "mild recession" and ...

Statistical and spatial analyses of both historical time series and remotely sensed data show a link between the spatial distribution and growth of gold production across the Guiana Shield in northeast Amazonia. Results indicate that an exponential rise in production across an expanding area is primarily a delayed response to the 1971-1978 market flotation of international gold prices. The subs...

The current gold market shows a high degree of nonlinearity and uncertainty. In order to predict the gold price, Empirical Mode Decomposition (EMD) was introduced into Support vector machine (SVM). Firstly, we used the EMD method to decompose the original gold price series into a finite number of independent intrinsic mode functions (IMFs), and then grouped the IMFs according to different frequ...