# kaal:claim:3409548-007

**Claim.** Machine learning improves portfolio diversification by searching for instruments that are uncorrelated with each other and that still match the requirements of the target risk profile.

**Type.** mechanism  **Support.** asserted

**Holds when.**

- portfolio construction against a defined risk profile

**Source quote.**

> ML can help in accurate portfolio diversification by looking for uncorrelated instruments that match requirements of the risk profile.

**From.** Kaal, *Financial Technology and Hedge Funds* (2019), II. Financial Technology and Hedge Funds, page 8

**Cite as.** Kaal, Financial Technology and Hedge Funds (2019). SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3409548

**Verify.** sha256 of source PDF `74227ab2656b06bfe4a29c942fc2ba26df9f476917e0a9f85ec038b8c3402c40` at https://raw.githubusercontent.com/wulfkaal/Academic-Papers/main/papers/pdf/Kaal%20-%202019%20-%20Financial%20Technology%20and%20Hedge%20Funds.pdf

**Topics.** ai-and-agents, systemic-risk, risk-and-incentives

**Keywords.** machine-learning, diversification, portfolio-construction, risk-profile

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