The analysis of financial markets is based on complex data patterns that consist of historical prices, macroeconomic factors, sentiment analyses and financial figures. Bavest uses specialized AI models that process millions of data points and make well-founded predictions. Asset managers in particular benefit from the analysis of small and medium-sized companies (small and mid-caps), which are traditionally less focused on by analysts.

Machine learning for more accurate forecasts

The Bavest AI Engine uses modern machine learning models to analyze financial metrics on a deep level. The following elements are included in the calculations:

• Historical data: Previous financial figures, price movements and dividend histories.
• Macroeconomic factors: inflation, interest rates, economic indicators.
• Sentiment analyses: Evaluation of news, social media and corporate communications.
• Company-specific key figures: Cash flow, EBITDA, profit margins and revenue forecasts.

Using this data, the AI creates reliable forecasts, from simple dividend forecasts to complex company valuations. While human analysts can often only consider a limited number of factors, AI uses a variety of input parameters simultaneously and recognizes relationships that remain hidden from humans.

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Why AI models are more accurate than humans

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Backtesting: Reliable strategy review

One of the biggest strengths of the Bavest AI Engine is the ability to backtest. Historical market data is used to test data assumptions and to evaluate their accuracy. This helps to identify data mismatches early on and optimize the quality of estimates before they reach the API and are available. Traditional analysts can often only perform this process manually, while AI models can process millions of data points and make adaptive optimizations in a fraction of a second.

AI as an analytics assistant

AI models not only serve as independent analysis tools, but also as valuable assistants for human analysts. They support experts by providing data-based and emotionless analyses that are free from cognitive distortions. While human analysts are often influenced by market sentiment or personal assessments, AI remains strictly fact-based and objective. This leads to more precise decisions and helps to avoid wrong decisions based on emotional reactions.

AI-based models have the advantage that they are trained on enormous amounts of data and are constantly adapting to new market conditions. The higher precision of AI models is based on several principles:

1. Data-based decisions: AI models analyze millions of historical and current data points. According to a McKinsey study, AI-based financial models can improve the forecast accuracy of earnings per share (EPS) by up to 20%.
2. Specialized models (“Divide and Conquer”): Instead of using a single model for all analyses, Bavest uses specialized ML algorithms that have been trained for specific tasks, such as dividend forecasts, revenue development or cash flow calculations.
3. Emotional neutrality: Unlike human analysts, AI is not susceptible to cognitive distortions or emotional decisions.
4. Automated adjustment to market changes: While human analysts need weeks to develop new models, the Bavest AI Engine can constantly update and improve their models.

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Importance of market data in the modern financial world

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Black Swan Events: Challenge for Short-Term Investors

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A “Black Swan Event” (in German “Black Swan Event”) describes extremely rare and unpredictable events that have profound effects on markets, societies or systems. Because of their rarity and enormous scope, they are barely or impossible to predict. The term was introduced by Nassim Nicholas Taleb's book The Black Swan known. Events such as the 2008 financial crisis or the COVID-19 pandemic pose enormous challenges for all asset managers and investors. AI models are also unable to predict such events. Short-term investors are particularly affected, as sudden and extreme volatility can have a strong negative impact on their returns. For long-term asset managers, on the other hand, a black swan event can even represent a strategic opportunity. It enables them to enter certain asset classes or expand existing positions at more favourable conditions. However, precise market timing remains almost impossible, as markets often behave irrationally and unpredictably during such phases. Dealing with black swan events therefore requires careful risk management, a solid diversification strategy and a disciplined investment horizon.

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High data quality & analytics mean better investment decisions

The better the data quality and the underlying estimates, the more precise and well-founded are the investment decisions — and therefore the results achieved. Data is the decisive factor for success on the capital market, as they form the basis of every analysis, forecast and strategy.

Financial markets are based on expectations about future developments. Analysts and investors make decisions by evaluating available data and estimating future profits, growth, or risks. The more accurate these data and estimates are, the better opportunities and risks can be assessed.

example:

• When profit estimates for a company are based on incorrect or outdated data, this can result in an incorrect valuation and poor investment decisions.
• Precise and up-to-date estimates, on the other hand, enable a more accurate assessment of overvaluations or undervaluations and help to place strategic investments in a targeted manner.

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How AI improves the quality of data estimates

Artificial intelligence can help Systematically clean, analyze, and convert data into actionable estimates. AI plays a key role in several areas:

1. Better forecasts through large amounts of data
   AI can historical market data, macroeconomic indicators and company reports Evaluate in real time and generate more precise estimates from them.
2. Data validation and correction
   Unclean or incomplete data can falsify forecasts. AI detects inconsistencies and fixes errors to improve the quality of estimates.
3. Combining structured and unstructured data
   In addition to classic financial figures, AI also uses alternative data sources (e.g. news analysis, satellite data, social media) to create more comprehensive and accurate estimates.
4. Dynamic adjustment to market changes
   AI-powered estimates are constantly adapting to new market conditions, allowing investors to react faster and more precisely to changes.

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Transforming financial industries: AI & data

The financial sector is undergoing profound change, driven by technological innovations. While traditional market analyses often rely on historical data and intuitive decisions, AI models enable predictive analysis across various asset classes. This opens up new opportunities for:

• Portfolio management: Automated risk analysis and dynamic asset allocation.
• Risk management: Faster identification of financial risks through AI-based simulations.
• Cross-asset class analysis: The Bavest AI Engine can evaluate stocks, bonds, commodities, and cryptocurrencies in parallel and uncover correlations between them.
• Future-oriented investment strategies: AI-based forecasts help investors react early to market developments and identify new opportunities.

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Bavest AI Engine: Specialized machine learning models

The Bavest AI Engine uses specially developed ML models that are specifically optimized for various financial metrics. As a result, more precise forecasts can be made than with general financial models. For example, the engine analyses:

• Simple metrics: Dividend forecasts, EBITDA growth, revenue trends.
• More complex topics: Cash flow analysis, sentiment data from company reports, risk forecasts.
• Dynamic market indicators: Interest rate developments, currency fluctuations and macroeconomic influences.

These tailored models ensure higher forecast accuracy than traditional financial analyses, as they are optimized for the specific characteristics of individual metrics.

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Scalability and reliability: The benefits of the Bavest API

A key advantage of the Bavest AI Engine is its scalability and continuous availability. The API is available around the clock and enables rapid integration into existing systems. While human analysts often need days or weeks to build financial models in Excel, the Bavest AI Engine delivers results in real time.

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Humans and AI: Working together for the future

Despite all progress in AI-powered financial analysis, human analysts are not being completely replaced. Rather, AI complements human decision-making by providing precise predictions and analyses, while continuing to make the final investment decision by humans.

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Use AI-based estimates & alternative data with the Bavest API now

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Whether you're an asset manager, a fintech company, or an innovative bank, the seamless integration of our comprehensive data solution opens the way for even greater success. Contact us today and arrange a demo: Let yourself be convinced of the possibilities of our platform and find out how we can optimally support your individual requirements.

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conclusion

The future of financial analysis belongs to hybrid models in which AI and human expertise work hand in hand. With its specialized AI engine, Bavest enables more accurate and faster financial forecasts and helps investors make better decisions. The combination of data-driven analysis, scalability and automation makes Bavest a leading provider in the modern financial world.

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