The last years, new “fundamentals” however have entered the market in full force. The impact of so-called sentiments in the oil markets is however still underestimated. A simple example is the unexpected and sometimes destructive tweets being sent by US president Trump, statements made by OPEC leaders or weekly reports of institutional investors and financing, such as GoldmanSachs or CITI. Without diminishing the relevance of all, the impact of ‘sentiments’, or possible unsubstantiated statements on oil and gas is enormous. Price volatility due to politically induced remarks, threats or outright policy changes has increased, as shown by Trump’s former tweets on oil and OPEC volumes. As Trump tweets have become infamous, some are forgetting that large scale organizations, such as GoldmanSachs, or NGO’s, as shown by Greta Thunberg, also have their own impact and can substantially change sentiments for oil and gas on the long-term.
The last years, new approaches have been tried to understand and interpret market sentiments via Artificial Intelligence (AI), neural networks and machine-learning. The growing amount and use of algorithms in commodity trading and oil price forecasts is clear, as an overwhelming majority of trading companies, hedge-funds and financial institutions are linking it to their own strategies. A full-scale AI-machine learning industry has seen the light. Even that most are partly successful, mainly mitigating some of the risks in the market, most of them are still lacking a total birdseye view of oil and gas markets. As has been stated before, oil and gas are politics, without these energy sources the world would be looking totally different and geopolitical powers would have been arranged in different ways. To integrate however the Beta-side of life, AI-neural networks, with the Alpha-side has still been a major issue. People, even CEO-CIO-COOs, are not always acting purely on rational facts but on their own unconscious biases and backgrounds. Geopolitics and power conflicts are just another side of the same coin but need to be integrated in a full-fledged approach of forecasting and foresighting.
One main example where markets and almost 99.9% of analysts were wrong, put on a wrong footing by traditional and AI based assessments, was the WTI-negative price situation. Hedge funds, investors and operators alike all were not looking outside of their own comfort zones, forgetting principle underlying factors while pretending to have a crystal ball. A need for the integration of Alpha and Beta systems and interpretations is clear, but still largely unavailable. The coming years new approaches will have to be introduced, especially when looking at the ongoing power play restructuring, the new role of geopolitics and renewables, or the impact of COVID-19 on oil and gas investments. At the same time, changing sentiments in societies and politics will have to be incorporated in the forecasts and foresights in oil and gas markets. Oil price predictions is just one major focus point, as mitigating risks in futures is a major instrument not only for commodity traders, oil storage owners but the whole line of economic sectors directly and indirectly influenced by oil price levels or the availability of these crucial natural resources. By combining alpha-based (human factors) analysis with rational, factional and applicable factors, figures and sentiments, produced by Beta-systems (AI, Neural), a more “predictable” future is reachable.
The coming months or years, oil and gas sectors are facing major watersheds or possible perfect storms. Some, such as COVID-19, will be real Black Swans, unpredictable and disastrous. Others are able to be predicted as the first signs of developments or shocks to the system will be visible way-before major changes happen. To understand the impact of a Biden-victory, a change in powers of the Washington Administration, or a restructuring of globalization due to COVID-19, is increasingly able to be predicted. Volatility at present is high and could be even much higher if sentiments hiding behind the headlines of media publications or twitter-storms, are not being assessed and taken into account.
Understanding Dynamics and Impact
Complexity, uncertainty and volatility can be partly mitigated by instigating and implementing neural network- machine learning approaches. The need to understand the direct and indirect interaction between rational and obvious factors, such as market fundamentals or geopolitical developments, is clear but has not been fully assessed at present. The total amalgamation of factors, even unconscious biases, out-of-the-box developments, need to be taken into account. Obvious examples are the surprise election victory of Trump in 2016, the Brexit decision in the UK, or the Saudi King decision to promote deputy-Crown Prince Mohammed bin Salman as the new Crown Prince, in a break with Kingdom traditions, have their impact on oil markets. The fact that MSM, political analysts and others, did not foresee the latter, is partly based on the use of mainstream conventional sources and thinking. New ways of assessing and introducing additional sources of information, data and human interaction is needed, to mitigate surprises in the market. The surface has been scratched, but more sentiments are needed to be taken into account. Future strategies and issues could already be discussed and decided under the surface, such as energy transition in Latin America, Abraham Agreements 2.0 or democracy in Turkey. Official media, fundamentals or think tanks are no longer the right basis or sufficient enough to look into the future.
Accurate Ai Enabled Foresighting
Verocy, in cooperation with Belgium based AI-neural network consultancy NERAI, has set up a unique approach. This approach has been developed based on an integration of conventional systemology, including geopolitics, economics, market fundamentals and trade, but now with a specific emphasis on prediction of social, economic and political events, dynamics and shifts, substantiated by neural networks and machine learning.
We focus on “what is likely to happen” and enable clients to quantify and assess political, social and financial risks and its implications with key indicators specific to the industries and markets by providing daily, monthly and yearly predictions with high accuracy.
Our prediction approach and analysis is also capable of creating latent factors as an early signal of changes in political, social and financial environment and demonstrates phase transitions.
Until now the outcome of the research has come up with surprising conclusions and new insights. The total approach and machine-learning exercise already has generated oil price predictions with more than 85% accuracy. Targets are being set to increase the latter to >95% accuracy, which sometimes have already been reached. The total is not targeting an oil price prediction systemology to be totally accurate and put hedge-funds out of business. For most sectors oil price indicators and future (3-6-12 months) price correlations and upward/downward price potentials are more of interest.
Visit https://verocy.com/predictions/oil-price-prediction/. Download our presentation and ask for a demo.
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Rob van der Stel | P: +31 6 5396 1864 | E: firstname.lastname@example.org | https://www.linkedin.com/in/rob-van-der-stel-25867215/