# Forecasting

`kaal:entity:forecasting`

**Status.** derived

This node is assembled mechanically from the 4 claims that carry the concept tag `forecasting`. It is a roster of what the corpus says under this term. It is **not** an adjudicated definition: no single statement here has been ruled canonical, and no first-appearance call has been made. Read the claims and judge for yourself.

## Every claim under this term

4 claims across 4 works, 2016 to 2025.

**2016**

- [2732915-036](https://wulfkaal.github.io/claims/2732915-036) [predictive/evidenced] -- Half of the respondents indicated that the Dodd-Frank registration and disclosure rules create higher costs that will affect their funds over the next five years, while 17.4 percent expected no effect and 6.5 percent expected lower returns.
  > while 17.4% believed there was no effect and 6.5% suggest the effect is lower returns, 50% indicated that the Dodd- Frank registration and disclosure rules create higher costs that affect their funds.
  Wulf A. Kaal, The Private Fund Industry Five Years after the Dodd-Frank Act – A Survey Study (2016). SSRN: https://ssrn.com/abstract=2732915

**2021**

- [3808852-005](https://wulfkaal.github.io/claims/3808852-005) [empirical/evidenced] *(failure mode)* -- The centralization of scientific methods and output has produced suboptimal outcomes for society, as evidenced by widespread irreproducibility, by non-expert forecasters often outperforming experts, and by random stock selection outperforming expert selection.
  > Non-expert forecasters are often better than expert forecasters.2 Random selection of stocks can produce superior results in comparison with expert selection.3
  Wulf A. Kaal, Decentralization and Feedback Effects (2021). SSRN: https://ssrn.com/abstract=3808852

**2024**

- [4900878-023](https://wulfkaal.github.io/claims/4900878-023) [failure/asserted] *(failure mode)* -- Traditional economic models fail to predict cryptocurrency price movements accurately, because token values swing rapidly on market sentiment, regulatory news, technological change, and macroeconomic trends, which are inherently unpredictable.
  > Traditional economic models often struggle to accurately predict these fluctuations due to their inherent unpredictability.
  Wulf A. Kaal, Quantum Economy and Tokenomics (2024). SSRN: https://ssrn.com/abstract=4900878

**2025**

- [5095633-001](https://wulfkaal.github.io/claims/5095633-001) [predictive/evidenced] -- The accessible reserves of publicly available human-created text usable for training large language models could be exhausted by 2028 at current usage trajectories.
  > the accessible reserves of publicly available human-created text could be exhausted by 2028, given current usage trajectories.
  Wulf A. Kaal, Artificial Intelligence The Final Frontier (2025). SSRN: https://ssrn.com/abstract=5095633

## Verify

Every claim above resolves to a record carrying a verbatim source quote, the sha256 of the source PDF, and a preformatted citation. Nothing here asks to be taken on trust.

    curl -s https://wulfkaal.github.io/entities/forecasting.md | sha256sum

**Canonical form.** This markdown file is the canonical hashed representation of this entity node. Its sha256 is the content hash.