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 ...

We solve a Pareto risk-sharing problem with heterogeneous agents with recursive utility over multiple goods. We use this optimal consumption allocation to derive a pricing kernel and the price of oil and related futures contracts. This gives us insight into the dynamics of risk premia in commodity markets for oil. As an example, in a calibrated version of our model we show how rising oil prices...

this research studies the application of hybrid algorithms for predicting the prices of crude oil. brent crude oil price data and hybrid intelligent algorithm (time delay neural network, probabilistic neural network, and fuzzy logic) were used to build intelligent decision support systems for predicting crude oil prices. the proposed model was able to predict future crude oil prices from august...

The macroeconomic implications of oil price fluctuations vary according to their sources. Our estimated two-country DSGE model distinguishes between country-specific oil supply shocks, various domestic and foreign activity shocks, and oil efficiency shocks. Changes in foreign oil efficiency, modeled as factor-augmenting technology, were the key driver of fluctuations in oil prices between 1984 ...

We attempt to determine the impact of production decisions on the price of heating oil. A model for the production of distillate fuel oil is proposed. Its solution, obtained using stochastic dynamic programming, closely matches history. By perturbing the problem in a deliberate manner, we can determine the value of additional units of inventory by examining diierences in costs. Using these diie...

This paper uses STR (Smooth Transition Regression) model to study the nonlinear relation between CPI in China and international oil price. The results show that the change of CPI in current period has a positive effect to the next period, and the non-linear effect of international oil price almost completely reveals the changing characteristics of CPI.

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...

This study examines how crude oil price volatility affected the stock returns of major global and gas corporations during three oil-price wars that took place between October 1991 June 2020. Episodes considered include 1998 Saudi Arabia – Venezuela war, 2014–2016 conflict 2020 Russia war in a time unprecedented crisis caused by COVID-19 pandemic. The persistence prices times specific is capture...

in this paper we investigate the effect of oil price shocks on stock market index in iran, by using of a structural var (svar) approach. we used four variables in the model namely kilian index, global oil supply, real oil price and real stock market index. the data are monthly and spanning the period 1997m10-2014m12. we identify the effect of four different shocks on stock market including oil ...