A Dynamic Level Technical Indicator Model for Oil Price Forecasting

Forecasting Crude Oil Price Volatility

We use high-frequency intra-day realized volatility to evaluate the relative forecasting performance of several models for the volatility of crude oil daily spot returns. Our objective is to evaluate the predictive ability of time-invariant and Markov switching GARCH models over different horizons. Using Carasco, Hu and Ploberger (2014) test for regime switching in the mean and variance of the ...

Dynamic Hybrid Model for Short-Term Electricity Price Forecasting

Accurate forecasting tools are essential in the operation of electric power systems, especially in deregulated electricity markets. Electricity price forecasting is necessary for all market participants to optimize their portfolios. In this paper we propose a hybrid method approach for short-term hourly electricity price forecasting. The paper combines statistical techniques for pre-processing ...

Crude Oil Price Forecasting with Anfis

Crude oil pricing is commonly expressed as a formula referenced to Brent or WTI crude oil. The final price of these two qualities and the spread between WTI and Brent can drive the decision when the purchase of a crude oil cargo is evaluated. A crude oil price-forecasting model is presented. It is based on past data, inventory level and volatility index and it is derived with a neuro fuzzy infe...

Forecasting Crude Oil Price and Stock Price by Jump Stochastic Time Effective Neural Network Model

The interacting impact between the crude oil prices and the stock market indices in China is investigated in the present paper, and the corresponding statistical behaviors are also analyzed. The database is based on the crude oil prices of Daqing and Shengli in the 7-year period from January 2003 to December 2009 and also on the indices of SHCI, SZCI, SZPI, and SINOPEC with the same time period...

A Hybrid Intelligent System For Forecasting Gasoline Price