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Investors' perspective on forecasting crude oil return volatility : where do we stand today?

Liu, Li; Geng, Qianjie; Zhang, Yaojie; Wang, Yudong - In: Journal of management science and engineering 7 (2022) 3, pp. 423-438

In this paper, we review studies of oil volatility prediction from a new perspective: that of investors who require economic evaluations of forecasting performance. Our results indicate that no single volatility model outperforms all of the competing models, of which GARCH and realized...

Persistent link: https://www.econbiz.de/10014310613

A hybrid of Box-Jenkins ARIMA model and Neural Networks for forecasting South African crude oil prices

Tsoku, Johannes Tshepiso; Metsileng, Daniel; Botlhoko, … - In: International Journal of Financial Studies : open … 12 (2024) 4, pp. 1-13

The current study aims to model the South African crude oil prices using the hybrid of Box-Jenkins autoregressive integrated moving average (ARIMA) and Neural Networks (NNs). This study introduces a hybrid approach to forecasting methods aimed at resolving the issues of lack of precision in...

Persistent link: https://www.econbiz.de/10015337777

Quantifying time-varying forecast uncertainty and risk for the real price of oil

Aastveit, Knut Are; Cross, Jamie; Dijk, Herman K. van - 2021

We propose a novel and numerically efficient quantification approach to forecast uncertainty of the real price of oil …, estimation of time-varying forecast biases and facets of miscalibration of individual forecast densities and time-varying inter …-varying forecast uncertainty and risk for the real price of oil over the period 1974-2018. We show that the combination approach …

Persistent link: https://www.econbiz.de/10012544443

Multi-source model of heterogeneous data analysis for oil price forecasting

Baboshkin, Pavel; Uandykova, Mafura - In: International Journal of Energy Economics and Policy : IJEEP 11 (2021) 2, pp. 384-391

Persistent link: https://www.econbiz.de/10012616117

The impact of China's economic growth on crude oil price : evidence from structural VAR

Hamendi, Ahmed; Law, Siong Hook - In: Review of Economic Analysis : REA 15 (2023) 3/4, pp. 237-252

This paper examines the impact of Chinese economic growth on the real price of crude oil based on monthly time series data from 1992:01 to 2017:06 using structural vector auto-regression (SVAR). The variables of the SVAR model are global crude oil production, index of global economic activity,...

Persistent link: https://www.econbiz.de/10014481185

The second RP-PCA factor and crude oil price predictability

Shi, Qi - In: Prague economic papers : a bimonthly journal of … 33 (2024) 6, pp. 662-690

Although it is notoriously difficult to utilize financial ratios to forecast the crude oil market prices, our study … ability to forecast oil market sentiment. Our study presents a novel and indicatable financial instrument for policymakers to …

Persistent link: https://www.econbiz.de/10015413385

Modelling and forecasting crude oil prices during COVID-19 Pandemic

Hendrawaty, Ernie; Azhar, Rialdi; Kesumah, Fajrin Satria Dwi - In: International Journal of Energy Economics and Policy : IJEEP 11 (2021) 2, pp. 149-154

Persistent link: https://www.econbiz.de/10012608864

To jump or not to jump : momentum of jumps in crude oil price volatility prediction

Zhang, Yaojie; Wang, Yudong; Ma, Feng; Wei, Yu - In: Financial innovation : FIN 8 (2022), pp. 1-31

competing strategies such as forecast combinations and shrinkage methods. A mean-variance investor who targets a constant Sharpe …

Persistent link: https://www.econbiz.de/10013272635

A hybrid autoregressive integrated moving average-phGMDH model to forecast crude oil price

Sarpong-Streetor, Richard Manu Nana Yaw; Rajalingam A/L … - In: International Journal of Energy Economics and Policy : IJEEP 9 (2019) 5, pp. 135-141

Persistent link: https://www.econbiz.de/10012425150

Oil market factors as a source of commonality in liquidity in international equity markets

Alhassan, Abdulrahman; Naka, Atsuyuki; Noman, Abdullah - In: Journal of risk and financial management : JRFM 14 (2021) 8, pp. 1-33

When stock markets are less liquid or illiquid, investors are expected to require compensation for taking the risk of not being able to sell quickly. Many studies have documented the existence of the co-movements (commonality) of market liquidity in equity markets as a priced factor. The primary...

Persistent link: https://www.econbiz.de/10012626765