{
  "annotation_id": "952f5670-aae2-481c-8b47-33f565b7078b",
  "date_created": "2026-02-17T05:53:23.350000Z",
  "date_modified": "2026-02-17T05:53:23.350000Z",
  "file_hash": "4708c842b13afccba310564d10999cec8b2383b841c2704b0944fe6749f750f0",
  "private": false,
  "record": {
    "abstract": "The asset pricing literature emphasizes factor models that minimize pricing errors but overlooks unselected candidate factors that could enhance the performance of test assets. This paper proposes a framework for factor model selection and testing by (i) selecting the optimal model that spans the joint efficient frontier of test assets and all candidate factors, and (ii) testing pricing performance on both test assets and unselected candidate factors. Our framework updates a baseline model (e.g., CAPM) sequentially by adding or removing factors based on asset pricing tests. Ensuring model selection consistency, our framework utilizes the asset pricing duality: minimizing cross-sectionally unexplained pricing errors aligns with maximizing the Sharpe ratio of the selected factor model. Empirical evidence shows that workhorse factor models fail asset pricing tests, whereas our proposed 8-factor model is not rejected and exhibits robust out-of-sample performance.",
    "arxiv_id": "2601.10279",
    "authors": [
      "Guanhao Feng",
      "Wei Lan",
      "Hansheng Wang",
      "Jun Zhang"
    ],
    "categories": [
      "econ.EM",
      "stat.AP"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "title": "Selecting and Testing Asset Pricing Models: A Stepwise Approach",
    "url": "https://arxiv.org/abs/2601.10279",
    "version": "v1"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "0d92f132-b8d7-474e-9b08-88c9bb1403a1",
    "id": "arXiv Dataset",
    "type": "Model",
    "variant": "snapshot-2026-01-17",
    "version": "0.1.0"
  },
  "user_id": 1000002
}