We examine the predictive value of gold-to-silver and gold-to-platinum price ratios, as proxies for global risks affecting realized variance (RV) oil-price movements, using monthly data over longest available periods 1915:01–2021:03 1968:01–2021:03, respectively. Using two we find statistically significant evidence in-sample predictability increases in RV both ratios. This finding also translat...

this paper investigates the forecasting gold coin futures contract price in iran mercantile exchange. this research has presented a hybrid model based on genetic fuzzy systems (gfs) and artificial neural network (ann) to forecast the gold futures contract, at first, we use stepwise regression analysis (sra) to determine factors which have most influence on stock prices. at the next stage we div...

Recent human population increase has been enabled by a massive expansion of global agricultural production. A key component of this "Green Revolution" has been application of inorganic fertilizers to produce and maintain high crop yields. However, the long-term sustainability of these practices is unclear given the eutrophying effects of fertilizer runoff as well as the reliance of fertilizer p...

This paper attempts to reconcile an apparent contradiction between short-run and long-run movements in the price of gold. A theoretical model is developed that suggests a set of the conditions that would have to be satisfied for the price of gold to rise over time at the general rate of inflation and hence be an effective long-run hedge against inflation. The model also demonstrates that short-...

The purpose of this article is to analyse the trend global gold price yields and volatility with aim making effective financial decisions about investments in precious metal, by applying comparing results ARCH GARCH competing models, using lowest values chosen information criteria. models are intended for time series' analysis, observed instability conditional variance. Gold usually has functio...

Improving return forecasting is very important for both investors and researchers in financial markets. In this study we try to aim this object by two new methods. First, instead of using traditional variable, gold prices have been used as predictor and compare the results with Goyal's variables. Second, unlike previous researches new machine learning algorithm called Deep learning (DP) has bee...

With the spread of market sentiment global economic recession, favors hedging varieties such as gold and agricultural products. This paper seeks to investigate explanations corn futures price movements from perspective investor attention. We employ a time series autoregressive model (VAR) analyze relationship between them. Empirical results indicate that attention is Granger cause changes in pr...