Oil prices surged 25% in Q3 2023, due to robust global demand and OPEC+ supply cuts. JP Morgan expects Brent oil to hit $100 by the year-end and $150 per barrel by 2026. As oil prices spiked above $90 in September 2023, the highest since November 2022, gas prices also experienced upward pressure due to steady global demand.
Head of EMEA Energy Equity Research at JPMorgan, Christyan Malek, mentioned that an extremely volatile “supercycle” is on the horizon in the energy market. He added that the Brent spike, due to supply-demand disruptions, is accompanying intensifying global clean-energy efforts.
While the Russia-Ukraine conflict shows no sign of armistice, the Israel-Palestine dispute has added to the global geopolitical turmoil. The oil market was possibly the quickest to react to the latest conflict, spiking within hours. While Iran, a major supporter of Hamas, had not entered the war at the time of writing, any involvement of the country could severely hurt oil supply, which would drive prices up.
Conversely, major oil suppliers, including Saudi Arabia and Egypt, are not supporters of either side and have “an understanding” with the US to ensure that oil price upticks remain within the 10% to 15% range. The EIA has also assured that Israel has “virtually no crude oil and condensate production,” but the conflict has immense potential to widen into regional hostilities that may eventually affect oil movement and hence global supply.
Pierre Andurand, a French businessman and hedge fund manager, has also predicted that global oil demand may push oil prices to a high of $110 per barrel, given that international inventories are declining rapidly.
Yet, the risk that the conflict in the Middle East will offset a chain reaction, remains factored into analyst projections and investor sentiment due to the location of the conflict zone. The situation puts traders who cannot assess investor sentiment in a difficult position. They have no way to adequately measure the impact of a massive geopolitical event, one of the key influencers of market volatility.
Sentiment analysis informs traders of how the markets are “feeling” regarding an asset. When investor sentiment is positive, asset prices tend to rise, while the prices drop due to negative sentiment. So, sentiment analysis provides insights into whether the markets are bullish or bearish, whether traders are acting on fear or greed, and much more. As discussed above, oil prices spiked immediately after the news of the surprise Israeli attack. This is because traders realised that the regionality of the war may affect oil supply and acted in greed to capitalise on ensuing price fluctuations. Those who predicted the move, made significant profits.
But, gauging the mood of the market can be challenging. It requires the gathering of media updates, analyst forecasts, social media chatter, and much more. Next, the data needs to be collated and the market state assessed to gain actionable insights. Traders, especially scalpers, require real-time analysis, while high frequency trading algorithms also need instant reports for EAs to execute trades. Therefore, brokerages need to equip their customers with efficient AI-powered tools to enable them to capitalise on a maximum number of opportunities.
AI-powered algorithms have transformed trading by making advanced analysis accessible for retail traders. By doing so, it highlights trading opportunities creating an irresistible FOMO (fear of missing out) effect. It has augmented their ability to discover and maximise market opportunities like the oil spike referenced above.
The combination of ML and NLP creates powerful analysis and predictors. When fed with quality data, these technologies can adequately predict sentiment and market movement in response to it. Powerful algorithms generate actionable insights. High-frequency trading, driven by intelligent algorithms and analytics, helps traders explore more opportunities than they can with manual analysis.
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