Clear Specifications!
Our overriding goal is to generate a return of 3% per month. In a volatile market, a clear strategy and goals are required.
It starts with a goal!
Long-term success in trading digital assets is based on sustainable strategies and their effective implementation.
Our strategy is not focused on short-term gains with high risk, but on delivering sustainable and achievable returns. This is why we rely on fully automated trading.
Our intelligent trading robots are designed to detect significant market sell-offs early. In such cases, they act proactively by closing all open positions safely and efficiently. They then closely monitor the market, patiently waiting for the optimal moment to re-enter once the selling pressure has subsided.
This approach ensures that our trading robots are always positioned for sustainable profits—24/7, as long as they remain active. With this sophisticated strategy, we provide the stability and long-term growth you seek for your digital asset portfolio.
Depending on market conditions, we adjust the configuration of our trading robots to navigate both upward and downward trends effectively. In a bull market, we optimize strategies to maximize profit potential, employing wider stop-loss orders to allow the uptrend more room to develop. Conversely, in a bear market, we adopt a more conservative approach, setting lower profit targets and tightening stop-loss orders to minimize potential losses. With a diverse portfolio of trading robots, we can respond efficiently to a wide range of market conditions.
Our experience has shown us the importance of pursuing a transparent and well-thought-out strategy, always centered on a balanced risk/reward ratio. This approach allows us to seize attractive return opportunities while implementing appropriate measures to limit and manage risk effectively. Our strategy draws not only on our extensive experience and knowledge but also on our ability to continuously monitor and analyze markets, enabling us to respond swiftly and decisively to changes.
We primarily focus on macroeconomic indicators, particularly central banks' monetary policies. Our analysis covers the interplay between factors such as money supply, inflation rates, and financing conditions.
An integral part of our evaluations is the analysis of social media sentiment. Using custom filters powered by machine learning, we generate a comprehensive view of current sentiment. This allows us to detect public opinion and emerging trends early, integrating them seamlessly into our analyses.
To validate and enrich our findings, we incorporate additional analyses, including key elements such as on-chain data and quantitative assessments. By merging these diverse data sources, we aim to produce a thorough and precise market evaluation, guiding the development of our trading strategies.
Regression techniques enable us to conduct in-depth, multidimensional analyses of assets, providing valuable indicators that can be applied across various market conditions. Moving averages serve as reliable benchmarks for determining trade entry and exit points, which are continuously refined and optimized through machine learning methodologies.
The quality of an asset is fundamental to our approach. We focus on assets that not only have a large community but, more importantly, offer technological solutions to real-world challenges. Trends like 'meme coins' or NFTs (non-fungible tokens) do not align with our trading strategy and are therefore excluded from our portfolio.
Market Analyses
In our market analyses, we try to convey an overall impression.
Ahead of the market!
Our market analyses are in-depth and are based on well-founded sector-specific tools and exclusive fundamental analysis techniques.
They cover a wide range of areas. In addition to the application of classic chart techniques, we also turn to regressive in-depth analyses. We use machine learning to generate precise price forecasts and use time series modelling to capture seasonal fluctuations in the market.
Market analysis encompasses various elements, including technical indicators, regression-based moving averages, and data reflecting an asset's liquidity, such as open interest. When gathering data, we not only rely on information directly from the assets but also consider external sources. These include reputable analysis platforms such as CryptoQuant and Glassnode, whose data is integrated into our comprehensive market analysis.
To ensure transparency and traceability of our exclusive trading strategies, we regularly publish and archive them in their original form. Our in-depth market analyses, including those specific to Bitcoin, are freely accessible to the public. However, detailed reports on other topics and markets are exclusively available to registered members and clients.
We are committed to continuously and systematically enhancing the structure and content of our fundamental analyses. This involves regularly integrating innovative techniques and methodologies. Our goal is to present the market’s intricate complexity in a clear and comprehensive manner, achieved by expanding our perspectives and continuously adapting our approach to evolving market conditions.
Technical Indicators
Technical indicators show the current sentiment, which plays a strong role in trading!
Follow The Signals!
We rely on regression-based models and comprehensive statistical analyses for our technical indicators.
By employing these methods, we generate a three-dimensional logarithmic price curve that illustrates the predictable market dynamics within a predefined valuation period. This approach provides us with detailed insights into the market conditions of the respective trading cycle. To enhance and support our data visualizations, we incorporate moving averages. These moving averages are based on the principles of supervised learning, allowing them to be continuously refined and adapted to current market trends.
Our regression models leverage colors to represent market sentiment, with color intensity correlating strongly with trend confirmation: more intense colors indicate a more pronounced trend. Additionally, colors can signal potential trend reversal points, which often serve as valuable indicators for buy or sell opportunities. This approach has been highly successful in our trading robots.
Instead of traditional candlestick charts, we utilize dot or scatter charts to represent closing prices. This form of visualization excels in depicting so-called price clusters—areas with high trading activity over extended periods. In technical chart analysis, these price clusters are particularly significant, providing crucial entry and exit points for trading decisions.
Our technical indicators include moving averages, which are generated through the application of machine learning. Artificial intelligence plays a crucial role, especially in identifying recurring patterns.
In our analyses, we start with the classic 200-day moving average as a fundamental indicator. This is complemented by our proprietary moving average, which is based on AI-driven algorithms. Both indicators have distinct characteristics: they not only represent significant price support and resistance levels but also mark bull and bear cycles.
Another important feature is that an intersection of these two lines can signal a potential medium-term trend reversal. This offers a valuable indication of possible market changes and can serve as a foundation for strategic decisions. By combining traditional indicators with AI-based ones in our analysis, we enable a comprehensive and precise market assessment, which supports optimal trading decisions.
Example
Time Series
The models give us an insight into possible developments in the future!
Ahead of the times!
The use of time series models is a central aspect of our analysis methodology. They enable us to narrow down the probable range of future price developments and visualise them within a trend channel.
Using machine learning methods, we are able to create moving averages that represent a mean value as well as upper and lower limits.
When calculating these averages, we take into account overriding influencing factors, such as current monetary policy measures by central banks. We also integrate the seasonal averages into our models in order to take into account any seasonal influences on price trends. By combining these different methods and data sets, we aim to achieve a precise and comprehensive forecast of price trends.
Our time series analysis models are created daily and updated at regular intervals. They take into account the entire available time period of an asset since the beginning of its stock market recording in order to ensure a comprehensive and accurate picture of the price development.
For better clarity and handling, however, we always visualise the last two years of price development. This keeps the focus on relevant, current trends and patterns that are particularly important for short to medium-term investment decisions.
We place great importance on recognizing and incorporating distinctive features in price trends. This includes, for instance, significant price spikes, unusual volatility, or other anomalous price movements. To the extent that the data allows, these characteristics are integrated into our models to create the most realistic and meaningful representation of price trends.
The seasonality analysis we apply helps us gain a deeper understanding of how the market typically behaves at specific times. Our time horizon encompasses weekly, monthly, and annual cycles. In analyzing seasonality, we consider the entire available history of the asset in question. This approach provides valuable insights into recurring patterns and trends, aiding us in making well-informed forecasts and decisions.
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