What constraints can I apply to Modern Portfolio Theory (MPT) in Fincanva?

Modern Portfolio Theory (MPT), or Markowitz portfolio, in Fincanva allows users to optimize portfolios for maximum return at a given level of risk or minimum risk for a desired return. To make the results practical and aligned with your investment preferences or regulatory requirements, you can apply several constraints. These constraints tailor the allocation outcome and control how capital is distributed across assets or models.

• Positive Weights Only: This constraint ensures that all weights in the portfolio are positive. In other words, the optimizer won’t allocate negative values, which would represent short positions. This is essential if you want a long-only portfolio or are restricted from short-selling by regulation or strategy.

Please note:
When using MPT at portfolio level, "Positive weights" is applied by default and cannot be removed.

• Constrained Weights: You can set minimum and/or maximum limits for each asset or model’s allocation. This allows for greater control and prevents over-concentration. For example, you can restrict any single asset from exceeding 20% of the portfolio or enforce a minimum exposure of 5% to ensure relevance.

• Diversified: This constraint enforces broad capital distribution to avoid concentration in a few assets. It may be implemented by requiring a minimum number of assets with non-zero weights or setting a cap on the Herfindahl Index (a measure of portfolio concentration). It ensures a more balanced, diversified portfolio and aligns with risk-mitigation goals.

Considerations:
- If “Constrained Weights” is enabled, certain constraints might result in an unsolvable optimization problem.
- If “Diversified” is enabled, the outcome might be equivalent to Equal Weights, since this is conceptually the most diversified solution.