# kaal:claim:3409548-010

**Claim.** Requiring data scientists to stake a cryptocurrency on their own predictions is a workable remedy for overfitting, because the stake expresses confidence in live performance and lets the fund select the optimal model.

**Type.** design  **Support.** argued

**Holds when.**

- crowdsourced modeling competition with a stakeable token

**Source quote.**

> The staking process, in turn, enables Numerai to choose the optimal model and in the process improve the performance of its hedge fund.

**From.** Kaal, *Financial Technology and Hedge Funds* (2019), II.2 Artificial Intelligence and Big Data, page 12

**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.** risk-and-incentives

**Keywords.** staking, numeraire, incentive-design, overfitting, model-selection

**Related claims.**

- extends: https://wulfkaal.github.io/claims/2998033-022

**Canonical form.** This markdown file is the canonical hashed representation of the claim. Its sha256 is the content hash used for attestation.