Artificial intelligence factors into uncertainty of commodities future

Analyst Mike Zuzolo believes AI is why producers perceive a growing disconnect in how commodity prices are determined.

Artificial Intelligence Can Make Markets More Efficient—and More ...

Market participants we surveyed concur that high-frequency, AI-driven trading is expected to become more prevalent, particularly in liquid asset ...

The critical role of commodity trading in times of uncertainty - McKinsey

The rapid growth of commodities markets has drawn a wave of new entrants—such as tech-focused trading players, hedge funds, and banks, as well ...

Commodity Futures Price Prediction, an Artificial Intelligence ...

The effects of various factors on a particular commodity's price are unique to ... according to the behavior of the error function in order to overcome ...

On the Commoditization of Artificial Intelligence - PMC

In fact, the commoditization of AI has already begun. This paper presents the arguments to demonstrate that AI is moving rapidly in this ...

2024.06.11-Hedge-Fund-Use-of-AI-Report.pdf

risks of future impacts resulting from AI use in investment decisions go beyond potential harm to ... in commodities, futures, or swaps, they must ...

The influence of uncertainty on commodity futures returns and ...

We find that uncertainty has a significant influence on returns, but the direction of the response is due to whether uncertainty emanates from demand shocks ( ...

AI in commodity trading: is it the future of the industry? - Agiboo

The complexities associated with Commodity Trade and Risk Management software as mentioned in arguments 1 and 2 are of course hardly new. AI can ...

The Future of Commodity Futures in the AI Era | by Samir H Bhatt

By carefully selecting and implementing the right AI tools, traders in the commodity futures market can optimize their strategies for better ...

Artificial Intelligence and Machine Learning in Financial Services

technology is not new, and there are elements to its adoption of AI ... Commodity and Futures Trading Commission (CFTC), stipulated in a primer ...

Predictability of commodity futures returns with machine learning ...

We use prevailing machine learning models to investigate the predictability of futures returns in 22 commodities with commodity‐specific and ...

Improving the explainability of autoencoder factors for commodities ...

Autoencoders are dimension reduction models in the field of machine learning which can be thought of as a neural network counterpart of ...

AI-driven commodity price optimization | Roland Berger

In this article, we take a closer look at how commodity purchasing firms can optimize prices in uncertain, volatile markets.

Forecasting crude oil futures price using machine learning methods

To cope with this challenge, this paper introduces artificial intelligence methods to evaluate the optimal forecasting strategy for China's crude oil futures ...

Predictability of commodity futures returns with machine learning ...

We use prevailing machine learning models to investigate the predictability of futures returns in 22 commodities with commodity-specific and macroeconomic ...

How AI is Changing Commodity Trading: Core Benefits - PriceVision

Improving Commodity Price Forecasting with Artificial Intelligence · Real-time Insights into the Commodity Market · Minimizing Human Error in ...

A Primer on Artificial Intelligence in Financial Markets

It is not intended to state the official policy or position of the Commodity Futures Trading Commission (CFTC), or to limit the. CFTC's current or future ...

AI under great uncertainty: implications and decision strategies for ...

Decisions on public policy on AI are uncertain due to three features specific to the current landscape of AI, namely (i) the vagueness of the ...

AI use in and risk to derivatives markets | IATP

AI adds to the upfront cost structure of trading and likely would make it harder for commodity trading specialists to compete with AI-enabled ...

Pair People and AI for Better Product Demand Forecasting

AI models excel in this volatile environment because they assimilate information from a vast array of internal and external data sources to ...