The project analyzes how the inclusion or exclusion of specific securities from an index is becoming a decisive factor in modern investment strategies, driven by the evolution of digital finance and artificial intelligence (AI).

Traditionally, investors replicated indices through ETFs. With Direct Indexing, however, they can build personalized indices by directly purchasing fractional shares of individual stocks — excluding or including securities based on ethical, strategic, or risk-based criteria.

This AI-enhanced approach enables the creation of actively managed thematic indices, which are immediately investable and adaptable to market trends.

The entire model is based on three classes of AI applications, coordinated by a Supervisor:

A.I. is employed to estimate, for each financial instrument analyzed, the probability of upward or downward movement for each of the 20 market days following the most recent trading value.

Risk is classified into three categories:

The investable universe includes only instruments with acceptable risk profiles, explicitly excluding illiquid assets.

Through the analysis of over 50,000 instruments, the system identified 12 statistically significant zones within each market cycle, represented as a clock:

Zones between 6 and 3 (via 12) are statistically favorable.

Each day, the system calculates for every instrument:

It also generates an automated English commentary for each instrument, ensuring consistent, unbiased insights.

Index Entry & Exit:

• Instruments enter the index with equal weighting (e.g., 10 stocks = 10% each)
• Exclusion rules triggered by:
  • Lack of liquidity
  • Excessive correlation
  • Reaching maximum number of constituents

Cash Allocation (Golden Ratio):

The cash allocation is dynamically calculated based on the proportion of "Long" signals within the investable universe, following a ratio inspired by the Golden Ratio (1.6 ≈ φ).