arXiv · arXiv q-fin · 2020
This paper aims to examine whether the global economic policy uncertainty (GEPU) and uncertainty changes have different impacts on crude oil futures volatility. We establish single-factor and two-factor models under the GARCH-MIDAS framework to investigate the predictive power of GEPU and GEPU changes excluding and including realized volatility. The findings show that the models with rolling-window specification perf…
Peng-Fei Dai, Xiong Xiong, Wei-Xing Zhou
arXiv · arXiv q-fin · 2019
This non-linear relationship in the joint time-frequency domain has been studied for the Indian National Stock Exchange (NSE) with the international Gold price and WTI Crude Price being converted from Dollar to Indian National Rupee based on that week's closing exchange rate. Though a good correlation was obtained during some period, but as a whole no such cointegration relation can be found out. Using the \textit{Di…
Abhibasu Sen, Karabi Dutta Chaudhury
arXiv · arXiv q-fin · 2018
Energy markets are strategic to governments and economic development. Several commodities compete as substitutable energy sources and energy diversifiers. Such competition reduces the energy vulnerability of countries as well as portfolios' risk exposure. Vulnerability results mainly from price trends and fluctuations, following supply and demand shocks. Such energy price uncertainty attracts many market participants…
Hayette Gatfaoui
arXiv · arXiv q-fin · 2018
The dissertation investigates the application of Probabilistic Graphical Models (PGMs) in forecasting the price of Crude Oil. This research is important because crude oil plays a very pivotal role in the global economy hence is a very critical macroeconomic indicator of the industrial growth. Given the vast amount of macroeconomic factors affecting the price of crude oil such as supply of oil from OPEC countries, dem…
Danish A. Alvi
arXiv · arXiv q-fin · 2012
We perform detrending moving average analysis (DMA) and detrended fluctuation analysis (DFA) of the WTI crude oil futures prices (1983-2012) to investigate its efficiency. We further put forward a strict statistical test in the spirit of bootstrapping to verify the weak-form market efficiency hypothesis by employing the DMA (or DFA) exponent as the statistic. We verify the weak-form efficiency of the crude oil future…
Zhi-Qiang Jiang, Wen-Jie Xie, Wei-Xing Zhou
arXiv · arXiv · 2020
We propose the Hawkes flocking model that assesses systemic risk in high-frequency processes at the two perspectives -- endogeneity and interactivity. We examine the futures markets of WTI crude oil and gasoline for the past decade, and perform a comparative analysis with conditional value-at-risk as a benchmark measure. In terms of high-frequency structure, we derive the empirical findings. The endogenous systemic r…
Hyun Jin Jang, Kiseop Lee, Kyungsub Lee
arXiv · arXiv · 2026
Forecasting crude oil prices remains challenging because market-relevant information is embedded in large volumes of unstructured news and is not fully captured by traditional polarity-based sentiment measures. This paper examines whether multi-dimensional sentiment signals extracted by large language models improve the prediction of weekly WTI crude oil futures returns. Using energy-sector news articles from 2020 to…
Dehao Dai, Ding Ma, Dou Liu, Kerui Geng, Yiqing Wang
arXiv · arXiv · 2023
In this work, we study statistical arbitrage strategies in international crude oil futures markets. We analyse strategies that extend classical pairs trading strategies, considering the two benchmark crude oil futures (Brent and WTI) together with the newly introduced Shanghai crude oil futures. We document that the time series of these three futures prices are cointegrated and we model the resulting cointegration sp…
Viviana Fanelli, Claudio Fontana, Francesco Rotondi
arXiv · arXiv · 2022
This paper examines the relationship between the price of the Dubai crude oil and the price of the US natural gas using an updated monthly dataset from 1992 to 2018, incorporating the latter events in the energy markets. After employing a variety of unit root and cointegration tests, the long-run relationship is examined via the autoregressive distributed lag (ARDL) cointegration technique, along with the Toda-Yamamo…
Stavros Stavroyiannis
arXiv · arXiv · 2022
The ongoing COVID-19 shocked financial markets globally, including China's crude oil future market, which is the third most traded crude oil futures after WTI and Brent. As China's first crude oil futures accessible to foreign investors, the Shanghai crude oil futures (SC) have attracted significant interest since launch at the Shanghai International Energy Exchange. The impact of COVID-19 on the new crude oil future…
Shao Ying-Hui, Liu Ying-Lin, Yang Yan-Hong
arXiv · arXiv · 2015
In order to obtain a reasonable and reliable forecast method for crude oil price volatility, this paper evaluates the forecast performance of single-regime GARCH models (including the standard linear GARCH model and the nonlinear GJR-GARCH and EGARCH models) and the two-regime Markov Regime Switching GARCH (MRS-GARCH) model for crude oil price volatility at different data frequencies and time horizons. The results in…
Yue-Jun Zhang, Ting Yao, Ling-Yun He
arXiv · arXiv · 2015
This paper analyzes the direction of the causality between crude oil, gold and stock markets for the largest economy in the world with respect to such markets, the US. To do so, we apply non-linear Granger causality tests. We find a nonlinear causal relationship among the three markets considered, with the causality going in all directions, when the full sample and different subsamples are considered. However, we fin…
Semei Coronado, Rebeca Jiménez-Rodríguez, Omar Rojas
arXiv · arXiv · 2014
This article investigates the correlation structure of the global crude oil market using the daily returns of 71 oil price time series across the world from 1992 to 2012. We identify from the correlation matrix six clusters of time series exhibiting evident geographical traits, which supports Weiner's (1991) regionalization hypothesis of the global oil market. We find that intra-cluster pairs of time series are highl…
Yue-Hua Dai, Wen-Jie Xie, Zhi-Qiang Jiang, George J. Jiang, Wei-Xing Zhou
arXiv · arXiv q-fin · 2024
In this paper, we study large losses arising from defaults of a credit portfolio. We assume that the portfolio dependence structure is modelled by the Archimedean copula family as opposed to the widely used Gaussian copula. The resulting model is new, and it has the capability of capturing extremal dependence among obligors. We first derive sharp asymptotics for the tail probability of portfolio losses and the expect…
Hengxin Cui, Ken Seng Tan, Fan Yang
arXiv · arXiv q-fin · 2022
In this bachelor thesis, we show how four different machine learning methods (Long Short-Term Memory, Random Forest, Support Vector Machine Regression, and k-Nearest Neighbor) perform compared to already successfully applied trading strategies such as Cross Signal Trading and a conventional statistical time series model ARMA-GARCH. The aim is to show that machine learning methods perform better than conventional meth…
Danijel Jevtic, Romain Deleze, Joerg Osterrieder
arXiv · arXiv q-fin · 2017
This paper considers the problem of measuring the credit risk in portfolios of loans, bonds, and other instruments subject to possible default under multi-factor models. Due to the amount of the portfolio, the heterogeneous effect of obligors, and the phenomena that default events are rare and mutually dependent, it is difficult to calculate portfolio credit risk either by means of direct analysis or crude Monte Carl…
Cheng-Der Fuh, Chuan-Ju Wang
arXiv · arXiv · 2014
We introduce a multi-factor stochastic volatility model based on the CIR/Heston stochastic volatility process. In order to capture the Samuelson effect displayed by commodity futures contracts, we add expiry-dependent exponential damping factors to their volatility coefficients. The pricing of single underlying European options on futures contracts is straightforward and can incorporate the volatility smile or skew o…
Lorenz Schneider, Bertrand Tavin
arXiv · arXiv · 2024
In the analysis of commodity futures, it is commonly assumed that futures prices are driven by two latent factors: short-term fluctuations and long-term equilibrium price levels. In this study, we extend this framework by introducing a novel state-space functional regression model that incorporates yield curve dynamics. Our model offers a distinct advantage in capturing the interdependencies between commodity futures…
Peilun He, Gareth W. Peters, Nino Kordzakhia, Pavel V. Shevchenko