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 "text": "Research on the Application of Artificial Intelligence in Quantitative Investment: Implementation Scenarios, Practical Challenges, and Future Trends should be assessed against Kaal's source-bound claim that Artificial intelligence and machine learning are used far more heavily for idea generation and portfolio optimization than for execution: two thirds of surveyed funds use them to generate trading ideas and optimize portfolios, while only just over a quarter use automation to execute trades. The current metadata indicates a plausible connection through regulatory lag, but the defensible response is a qualification until the source text confirms agreement, scope, methods, and limitations.",
 "author": {
  "@type": "Person",
  "name": "Wulf A. Kaal",
  "identifier": "https://orcid.org/0009-0008-7840-1847"
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 "datePublished": "2026-07-31",
 "dateModified": "2026-07-31",
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  "External evidence level: abstract indexed.",
  "Mapping review tier: mapping review before claim review.",
  "The literature-to-claim mapping remains explicitly ambiguous and should not be treated as a settled equivalence."
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 "currentDebate": {
  "name": "Research on the Application of Artificial Intelligence in Quantitative Investment: Implementation Scenarios, Practical Challenges, and Future Trends",
  "url": "https://www.semanticscholar.org/paper/e2846b6fb9841398891517b329d43016f780a068"
 },
 "extends": {
  "identifier": "kaal:claim:3409548-026",
  "url": "https://wulfkaal.github.io/claims/3409548-026",
  "citation": "Kaal, Financial Technology and Hedge Funds (2019). SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3409548",
  "paper": "Financial Technology and Hedge Funds",
  "authors": [
   "Wulf A. Kaal"
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  "year": "2019",
  "ssrn": "",
  "source_pdf_sha256": "74227ab2656b06bfe4a29c942fc2ba26df9f476917e0a9f85ec038b8c3402c40"
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 "canonical_url": "https://wulfkaal.github.io/positions/2026-07-31-2016",
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 "candidateId": "kaal:response-candidate:2026-07-31:34f9a71ec5a85c71",
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 "mappingAmbiguous": true,
 "mappingMethod": "idf-weighted multi-field mapping v1",
 "mappingWhyRelevant": "Shared high-information concepts: artificial, intelligence, technology, learning, while, financial, optimization, trading. Scope: 2018 BarclayHedge survey respondents.",
 "sourceProvenance": {
  "source": "Semantic Scholar",
  "api": "https://api.semanticscholar.org/graph/v1/paper/search/bulk",
  "query": "regulatory lag",
  "queryId": "concept:b18d258a2388",
  "page": 1,
  "sourceRank": 181,
  "retrievedAt": "2026-07-31T13:58:29.364Z",
  "citationCount": 1,
  "venue": "SHS Web of Conferences",
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