Transparency is very important to us! That's why we publish parts of our source code to create trust. Find out more here!

The use of AI in our analyses!

In our quest to advance analytical precision, we harness sophisticated machine learning techniques to meticulously analyze historical financial data, from which we generate predictive insights. Our methodology encompasses the creation and perpetual enhancement of various regression models, decision tree algorithms, and ensemble strategies like random forests, along with intricate neural network architectures.

We ensure that each model is dynamically infused with the latest data, thereby augmenting their predictive precision and maintaining the models' evolutionary adaptability. Through continuous iterative refinement, we progressively sharpen the efficacy of our analytical instruments.


It must be underscored that, despite advancements in artificial intelligence and the deployment of complex algorithms, an absolute guarantee of predictive accuracy cannot be provided. AI is incapable of forecasting future events with unwavering certainty. Nevertheless, it does offer invaluable perspectives on potential trends and the formulation of moving averages, which can be crucial indicators for support and resistance levels in technical analysis.

In conclusion, our analytical approach is rooted in the application of cutting-edge machine learning techniques, with a continuous drive to enhance their efficacy and to yield pertinent market insights. This is done with a conscientious acknowledgment of the intrinsic constraints inherent to these technological tools. As is evident, the trend channel for Ethereum, as depicted in the accompanying image, has been established.

How is AI traded?

The use of artificial intelligence (AI) in real-time trading is currently still limited, which is mainly due to the challenging dynamics and extreme speed of the financial markets. In certain complex scenarios, the current performance of AI systems could still reach its limits. Despite these challenges, AI technology is already being used successfully to analyse and evaluate stock market indicators and plays a key role in forecasting daily market trends.

The AI systems serve as supporting tools that provide evidence-based recommendations to the Quantum Data Analytics analysis team. Whilst the AI does not currently perform any autonomous actions, it is an integral part of the source code of our trading algorithms. The systems are programmed to continuously learn from transaction data in order to gradually achieve greater autonomy. The aim is for AI to be able to make trading decisions independently in the future. It is expected that AI-based systems will be able to comprehensively control and optimise the trading process in the foreseeable future.


For the development and operation of our AI-powered trading robots, we utilize the Python programming language, incorporating specialized libraries such as TA-LIB, TensorFlow, XGBoost, Pandas, NumPy, and Scikit-Learn. These tools were meticulously chosen for their robust performance and versatility, and they have consistently proven their efficacy in real-world applications. Our AI solutions extend beyond generating market predictions; they are integral to enhancing our trading algorithms and formulating actionable recommendations.

Our empirical evidence demonstrates that the strategic implementation of AI technologies significantly refines the precision of our analyses, thereby generating substantial value for our trading approaches. We are committed to harnessing the full capabilities of AI to secure a lasting competitive edge in the market.

Artificial intelligence is the mirror that humanity has created to look not only into its own soul, but also beyond into the immeasurable potential of the universe.

Erik Wimmer

How does AI protect Quantum?

Our digital platforms employ cutting-edge, AI-powered security systems to ensure robust protection. These systems are engineered to proactively identify and counteract a broad spectrum of cyber threats. The AI is meticulously trained to detect malware and automated botnets, promptly triggering defensive actions upon recognition. It is also proficient in recognizing and thwarting brute force attacks effectively.

An additional safeguard is provided by our integrated Web Application Firewall (WAF), which offers another layer of defense against targeted attacks at the application layer. Furthermore, our Intrusion Detection System (IDS) is adept at monitoring and analyzing unusual activities and anomalies in network traffic, facilitating the early detection of potential security infringements.

Client Portal

We also employ AI-based technologies for user authentication. These systems scrutinize the login credentials for any irregularities and affirm the legitimacy of the email addresses by validating their provenance. Upon successful verification of the login particulars, the AI system activates the customer account, granting the user access.

By perpetually refining our AI algorithms, we ensure that our security infrastructure adapts proactively to emerging threat landscapes, thus providing dependable security for our digital ecosystems.