The significant jump in world crude oil price over the past year has raised great concern over the economic impact that such a price shock may bring about on Taiwan’s economy, which has been characterized by extremely high import-oil dependence. Previous analyses have been tackling similar issue from several different angles, but it has rarely been discussed from a complete view of interactions...

Crude oil prices do play significant role in the global economy and are a key input into option pricing formulas, portfolio allocation, and risk measurement. In this paper, a hybrid model integrating wavelet and multiple linear regressions (MLR) is proposed for crude oil price forecasting. In this model, Mallat wavelet transform is first selected to decompose an original time series into severa...

Futures contract is one of the most important derivatives that is used in financial markets in all over the world to buy or sell an asset or commodity in the future. Pricing of this tool depends on expected price of asset or commodity at the maturity date. According to this, theoretical futures pricing models try to find this expected price in order to use in the futures contract. So in this ar...

Recent empirical studies reveal evidence of the co-existence of heterogeneous data characteristics distinguishable by time scale in the movement crude oil prices. In this paper we propose a new multivariate Empirical Mode Decomposition (EMD)-based model to take advantage of these heterogeneous characteristics of the price movement and model them in the crude oil markets. Empirical studies in be...

In this paper, a hybrid model integrating wavelet and least squares support machines (LSSVM) is proposed for crude oil price forecasting. In this model, Haar à trous wavelet transform is first selected to decompose an original time series into several sub-series with different scales. Then the LSSVM is used to predict each sub-series. And the final oil price forecasting is obtained by reconstru...

This paper implements the real-valued negative selection with variable-sized detectors (V-Detectors) for projecting the right decision with respect to crude oil price. The Brent crude oil data is retrieved from US department of energy. Using varying radius values of the V-Detector, comparison in terms of detection rate and false alarm rate, with support vector machine, naïve bayes, multi-layer ...

This paper reexamines the oil price-macroeconomy relationship with rolling Granger causality and structural stability tests. It finds that the relationship broke down amidst the falling oil prices and market collapse of the 1980s, suggesting misspecification of the oil price rather than a weakened relationship. Some proposed respecifications of the oil price yield considerable improvements, alt...

A model with costly adjustment of production and costly inventories implies that wholesale gasoline prices will respond with a lag to crude oil cost shocks. Unlike explanations that rely upon menu costs, imperfect information, or long-term buyer/seller relationships, this model also predicts that futures prices for gasoline will adjust incompletely to crude oil price shocks that occur close to ...

Generally, high oil prices slow economic growth, cause inflationary pressures and creates global imbalances. In addition, oil price volatility increase uncertainty and restrain the much-needed investment in the capital market. Thus, this paper applies the Augmented Dickey Fuller and Johansen Co-integration Tests in which the effect of oil price volatility, crude oil price and stock price is ana...

This paper applies a macroeconomic-based model for estimating default probabilities on Dutch data. The …rst part of the paper focuses on the relation between macroeconomic variables and the default behaviour of Dutch …rms. A convincing relationship with GDP growth and oil price, and to a lesser extent, the interest and exchange rate exists. The second part assesses the default behaviour based o...