The broad category of “artificial intelligence” comprises of multiple sub-categories with 2 standing out among the rest; Machine Learning and Deep Learning.
Example: A popular application of A.I. that is a good example of this is Netflix. When it creates viewing suggestions tailored to each subscriber’s preferences it’s using A.I. But it applies machine learning to update those recommendations after learning the subscriber’s interests and habits, what they watch, how long they watch it for, and what they don’t watch.
Automation VS AI
Fast forward to today, AI is the next-generation technology that is quickly changing industries and has now arrived in retail commodities trading.
A key feature
A key feature of automated AI trading, compared to merely automating something, is the ability to understand which are the best and worst decisions to be made, for a given task and data set. AI can be smart and intelligent, learning from success and past mistakes. In other words, AI can adapt itself in order to find the best trading strategies for specific scenarios in the commodities market.
Automation alone is no longer enough to build a commodities trading system, and the use of AI, such as machine learning and neural networks is the way forward.
Automation in commodities trading
Over the two last decades, the foreign exchange (commodities) markets were saturated with automated trading systems, from retail to institutional traders, thousands of commodities robots across the world were touted as the next-generation technology that everyone wanted to have.
Unfortunately, many trading systems of the past decade were short-lived and eventually could not adapt to changing market conditions. As a result, many commodities trading systems were overpriced and did not meet performance expectations.
Machine Learning constructs mathematical algorithms that are able to parse data, learn from that data and make data-related predictions based on what’s been learned to date.
Deep learning is a more sophisticated refinement, of machine learning. The key difference is that it can learn on its own, independently, through iterative learning or training process similar to how the human brain, processes information and arrive at intelligent decisions.
Artificial Neural Networks
Artificial neural networks (ANNs) are modeled after human brains to best mimic this process. A major reason why deep learning with artificial neural networks has become so popular recently is that they are powered by huge amounts of data which increases their ability to learn from that data and…
What is the Infratrader Infinity?
Infratrader Infinity uses a proprietary neural network that analyses market’s depth and looks for patterns of pre‐ set mathematical models (such as fractals, chaos and waves) that allows it to understand and forecast market’s trends on a real‐time basis (in fact it is a trending program).
By employing human knowledge, discretionary trading, artificial intelligence and oversight, our system helps members cut risk, increase profits and simplify investment decisions.
It’s intelligent and self-learning, with the ability to analyse and recognise patterns of accumulated historic data over a multitude of data points to better predict and react to future outcomes. The neural network is supervised, multi-layered and composed by variable nodes. Meaning:
- By feeding the network with pre-set data, the system creates its own real time strategies to achieve the established objectives.
- In only milliseconds, our system can choose the most appropriate strategy among more than 30,000 options in every single market condition.
Pattern recognition, Process optimization, Signal validation and information processing.Usage of analysed market intelligence and troubleshooting are the network’s main task.
If the system identifies a trend which is not followed by the market, our / software applies a counter strategy to solve the situation on a real‐time basis, adapting to the new scenario. During this non‐stop analysis, research and optimization process, all new movements and patterns are stored to be used in up‐coming scenarios, helping solve future market situations.
The A.I implements trades at a high frequency, low volume (HFLV) approach. This means that although there are potentially thousands of trades over the terms of the investment, only a tiny percentage of the account is utilized per trade. The A.I system is constantly monitored, updated and overseen by a team of experienced traders and coders. This ensures that human intuition and foresight is not removed from the product offering, rather only the inherent emotional risk with discretionary trading. In order to assure the quality of the AI trading system, our multi-layer platform is integrated with AWS, IBM Watson and Google AI.