Axyon AI | Advanced AI for Hedge Funds

THE FUTURE OF FUND MANAGEMENT IS AI-DRIVEN

A recent study* revealed that 81% of fund management businesses are leveraging AI to enhance efficiency.

As the industry evolves, integrating AI-driven insights is becoming essential to staying competitive.

*Source: XPS Group, December 2024. Study conducted with 76 investment managers overseeing a combined £34 trillion in assets globally, covering a diverse range of asset classes, including listed equities, fixed income, private assets, and hedgefunds.

WHY AXYON AI - KEY BENEFITS

SMOOTH
IMPLEMENTATION

Don't let AI technical complexity hold you back.
We have different ways to deliver or integrate our AI-based solutions into our clients' investment processes: web app, SFTP, API, e-mail or Excel.

TIME
EFFICIENCY Our expertise and AI-based solutions are designed to integrate seamlessly with your existing systems, enabling a smooth and swift transition.
You can bypass a lengthy and costly process and be live with a cutting-edge solution in just 1 week.

AI
RELIABILITY Reliability is the bedrock of successful AI integration. Our AI/DL algorithms are subject to regular audits, ensuring they remain unbiased and technically supervised.

FOR TRADITIONAL & QUANTITATIVE FUND MANAGERS

TRADITIONAL HEDGE FUNDS

Traditional Hedge Fund teams willing to include Axyon AI’s signals in their daily research to add AI-powered insights into their investment process, such as:

Evaluate AI-based performance stock rankings as an additional alpha component in portfolio assessment
Utilise Axyon AI stock ranking outside the core list for “completion” purposes SHAP values available to confirm value drivers at a single-name level

QUANTITATIVE HEDGE FUNDS

Quant Teams looking to ingest additional signals & dataset to enhance stock selection and optimise portfolio construction:

Equity Quant hedge funds using AI–Ready Factors to identify patterns and signals for trading equities
Raw forecast and Long + “point in time”-like history / back tests available
Stock rankings available for assessing correlations with clients’ internal generated alpha signals SHAP values available for comparison with internal performance analysis / attribution tools

Understanding AI Explainability in our Predictions

Our AI platform natively supports SHAP (Shapley Additive Explanations) state-of-the-art technique to decompose each prediction into the contributions of each individual input variable. Therefore, for each input variable we can compute a (positive or negative) contribution, and if we sum all these contribution we obtain the models’ prediction.

As the typical number of input variables per model is in the range of 200~500 features, to simplify the interpretation of these contributions we can group together all features belonging to the same semantic “category” (e.g. all features related to the fundamentals of a certain stock) and compute their aggregated contribution. By doing this, we can explain a prediction in terms of a small number (5-6) of “feature categories”, e.g. corresponding to classical financial factors, thanks to the fact that SHAP values are additive.

AI-Ready Factors

High-quality, normalised & ready-to-quant factors leveraging AI insights

AI-Ready Factors can be used as input variables to train AI models and enhance traditional investment strategies by uncovering hidden patterns, trends, and correlations that are not easily detectable through conventional analysis methods.

Axyon AI’s Machine Learning algorithms develop custom, data-driven factors that offer deeper insights into financial markets, facilitating the integration of AI solutions into the investment strategy process.

40+ engineered AI-Ready Factors which are correlated amongst them and highly informative of asset performance.

Accuracy: integration into quantitative models to add breadth to sources of data to improve forecasting accuracy

Precision: Used as inputs to help generate more precise buy/sell signals or optimise portfolio allocations

AI integration: High-quality, normalised & ready-to-quant factors to leverage AI technology

Customisation: Insights into what drives asset performance enable managers to tailor investment strategies to meet specific client needs and preferences, enhancing client satisfaction and retention.

AI-Based Signals

AI-based asset signals that predict over and underperformers within an investment universe & time horizon

Daily rankings of constituents of the selected investment universe (such as a benchmark index) and with Signal information that includes rank, change in ranking, relative performance score, and the top forecast drives (descriptors).

Axyon AI’s models learn to rank assets according to their expected relative outperformance or underperformance over a specified time horizon of one week, one month, or three months.

These AI-Based Signals, tailored for a specified investment universe and timeframe, can help Hedge Funds transform complex, high-dimensional data into actionable insights, enhancing decision-making and strategy development.

Enhanced stock selection: provide a data-driven, objective assessment of assets, aiding managers in selecting stocks or other assets that are predicted to out or underperform

Deep insights: To identify and analyse the underlying factors driving asset performance, providing deeper insights into market behaviour and asset dynamics.

Strategic Allocation: Understanding the drivers behind performance aids in constructing portfolios aligned with prevailing market trends and economic conditions, enhancing strategic asset allocation

Efficiency: Automating the ranking and weighting process with AI reduces time and effort for analysis, allowing managers to focus on strategic decision-making rather than data crunching.

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AI-POWERED SOLUTIONS FOR HEDGE FUNDS