â â â â â â â  this paper proposes a new forecasting model for investigating relationship between the price of crude oil, as an important energy source and gdp of the us, as the largest oil consumer, and the uk, as the oil producer. gmdh neural network and mlff neural network approaches, which are both non-linear models, are employed to forecast gdp responses to the oil price changes. the resul...

A combined wavelet transform (WT) and multiple linear regression (MLR) based technique to forecast price profile in a single settlement real time electricity market has been presented. The historical price and load data has been decomposed into better-behaved wavelet domain constitutive subseries using WT and then combined with other time domain variables to form the set of input variables for ...

Introduction In posted-offer markets the competitive outcome for a market, defined by the intersection of market supply and market demand curves, is frequently not a Nash equilibrium for the market viewed as a stage game. Rather, one or more sellers often have incentives to deviate unilaterally from the competitive outcome. A simple example illustrates. Consider a market with two sellers, S1 an...

Energy price forecast is the key information for generating companies to prepare their bids in the electricity markets. However, this forecasting problem is complex due to nonlinear, non-stationary, and time variant behavior of electricity price time series. Accordingly, in this paper a new strategy is proposed for electricity price forecast. The forecast strategy includes Wavelet Transform (WT...

forecasting stock price had been paying attention to many analysts and stockholders. today, this issue more recent years has been do by new methods but new methods, good enough, not have analysis of description and changes effective variables on stock price whereas all this method rely on regression bases. ardl (autoregression distributed lag ) of one equation cumulative regression method obtai...

Cement companies in Indonesia support the government’s role development of property sector. However, Covid-19 pandemic has caused problems making a profit. Therefore, main problem this study is to find out and analyze how profitability affects leverage market value with variables price earnings ratio (PER) book (PBV) as proxies. Second, knowing analyzing an intervening variable that relates eff...

The day-ahead electricity market is closely related to other commodity markets such as the fuel and emission markets and is increasingly playing a significant role in human life. Thus, in the electricity markets, accurate electricity price forecasting plays significant role for power producers and consumers. Although many studies developing and proposing highly accurate forecasting models exist...

We retrieve news stories and earnings announcements of the S&P 100 constituents from two professional news providers, along with ten macroeconomic indicators. We also gather data from Google Trends about these firms’ assets as an index of retail investors’ attention. Thus, we create an extensive and innovative database that contains precise information with which to analyze the link between new...