Long Cast Advisers Q1 2026 Letter
Long Cast Advisers reported flat returns for the first quarter of 2026, aligning with small-cap benchmarks amid macroeconomic volatility. The firm made strategic adjustments to its portfolio, adding to positions in National Research Corporation and Cross Country Healthcare while exiting others. Additionally, Matrix Service Company and Pro-Dex provided updates on their financial performance and strategic moves.
- ▪Cumulative net returns for Long Cast Advisers in Q1 2026 were flat, matching small-cap market indexes.
- ▪The firm added to positions in National Research Corporation and Cross Country Healthcare during the quarter.
- ▪Matrix Service Company reported a profitable quarter with revenue guidance suggesting potential EBITDA growth.
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| Original publisher | Seeking Alpha |
| Canonical URL | https://seekingalpha.com/article/4908427-long-cast-advisers-q1-2026-letter?source=feed_all_articles |
| Publication time | Sun, 24 May 2026 23:50:00 -0400 |
| Retrieval time | 2026-05-25T03:52:35.227Z |
| Last seen | 2026-05-25T03:52:35.227Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | QaPBJgNUx57T |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
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