Global energy prices have spiked alarmingly again, driven largely in recent days by the escalating conflict between Yemen's Houthis and Saudi Arabia causing chaos for the oil industry. Petrol and diesel costs have risen rapidly in most countries while the wholesale price of natural gas - used for heating homes and generating electricity - has almost doubled in the UK and Europe since July. There are growing concerns of another inflationary shock on the world economy, which could cause interest rates to rise, increase mortgage costs and raise the price of almost everything in the shops including food. So what is behind this latest surge - and what are the implications for the world economy? The global oil price is currently above $108 (£80) per barrel, up from $70 (£52) in June 2026 - a roughly 50% increase.

Brent crude has risen above $100 a barrel as war in Iran disrupts shipping through the Strait of Hormuz, while the Houthis' capture of Mayun Island raises concerns over another major oil route through the Bab al-Mandeb. JD Vance insists US is'on top of' Houthi advance in Red Sea China rejects AI'threat narratives', urges global cooperation US may be'forced to intervene' in the Red Sea

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What is Iran's Pickaxe Mountain? Crude oil and natural gas supplies have been disrupted worldwide by the United States-Israel war on Iran, but one energy sector appears to be cashing in - coal. This week, South Africa's thermal coal producer Thungela Resources said it had doubled its half-year profits as the war has forced more countries to buy the fuel. Mining it causes water pollution, and burning it releases enormous amounts of carbon into the atmosphere, which contributes to global warming. In recent months, several countries, especially in Asia, have reversed or delayed promises to scale back on coal production.

Long-term borrowing costs across some of the word's biggest economies hit fresh highs because of concerns over inflation, government debt levels and spending on Artificial Intelligence (AI). The interest rate on US borrowing over 30 years hit 5.33% on Tuesday, the highest since June 2007, meanwhile UK long-term debt reached 5.85%. There were similar moves in Germany and Japan. Interest rates on bonds - which are a type of debt - are known as yields and can directly affect the borrowing costs consumers pay on mortgages, car loans and credit cards. Rising oil prices are the main driver behind this recent surge in bond yields, as investors fear inflation could spike again. If that happens, central banks may choose to raise interest rates to cool inflation.

Chevron and Williams are big winners in the race to power artificial intelligence as they build out gas-fired power plants and pipelines. It's been a banner year for oil and gas companies. Some of the world's biggest oil giants have announced billions of dollars in quarterly profits over the past two weeks, boosted largely by the soaring price of oil thanks to the conflict in the Middle East. But the artificial intelligence boom is also giving fossil fuel companies a new industry to sell their gas, pipelines, and power plants to: data centers . Two American oil and gas companies, Williams and Chevron, are presenting that demand to investors as a huge win.

A screen displays stock market index data as traders work on the floor at the New York Stock Exchange in New York City on Tuesday. A screen displays stock market index data as traders work on the floor at the New York Stock Exchange in New York City on Tuesday. S&P 500 shot up 1.8% and the main measure of Wall Street's health topped its prior all-time high set a few months ago Tue 4 Aug 2026 16.56 EDTLast modified on Tue 4 Aug 2026 18.03 EDT The US stock market rallied to records on Tuesday as profits kept piling up for companies and as oil prices eased. The S&P 500 shot up 1.8%, and the main measure of Wall Street's health topped its prior all-time high set a couple months ago. The Dow Jones industrial average added 907 points, or 1.7%, to its own record set the day before, while the Nasdaq composite jumped 2.6%.

Oil prices have dropped following a report the US and Iran have reached a deal, subject to President Donald Trump's approval. Axios reported officials had made an agreement over an extended ceasefire on Thursday. It drove the price of a barrel of Brent crude down to a low of $93.36 from a earlier high of $98, before rebounding to about $94. Prices had jumped earlier after the US carried out new attacks on Iran, targeting a military site in Bandar Abbas, a strategic port city. The strikes occurred despite an ongoing ceasefire between Tehran and Washington to allow for talks to end the three-month-long war that has effectively closed the Strait of Hormuz waterway, pushing up global energy costs.

The energy market has faced a significant structural change in the past decade. The global strife for decarbonization is encouraging the use of renewable energy sources, thus affecting the traditional supply-demand pattern, which were historically dominated by fossil fuels like coal, oil, and natural gas [18]. The growing integration of renewable energy sources into the power supply increases uncertainties in the electricity market due to intermittent nature of the sources such as wind or sunshine [57]. The volatility of the generation sources causes high price shocks and regime changes that is compromising to financial stability as well as investment strategies in the power market [58]. Particularly for countries such as Germany, where the larger percentage of electricity is produced by renewable energy sources [37], levels of sunlight and wind impact electricity generation and thus prices. This introduces, in addition to the physical problem of balancing the grid, non-stationarity to most price models, which further adds unreliability to the predictions. Accurate electricity price forecasting is crucial for efficient resource planning, financial risk management, and stabilization of the market, especially with increasing renewable energy penetration, which enables utilities, businesses, and governments to optimize planning and policy maximization while matching demand and supply. The building of an adequate prediction model, which is relatively straightforward and understandable but at the same time can reflect the market complexity and all influence factors engaged in it is not straightforward, and authors have utilized quite broadly three types of model for prediction: statistical/(probability-based) models [12], machine learning/deep learning models [42], and mixed models [30]. Precise forecasting allows the players in the market to make sound monetary policy.