---
title: Tensor PCA
url: https://www.ml-quant.com/papers/ssrn/4766865/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-09-26
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 4766865
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4766865
featured: 2024-03-27
citations: unknown
topic: Asset Pricing & Factors
---


# Tensor PCA

The article introduces a new estimation algorithm for high-dimensional panel datasets, including the asymptotic distribution theory and a test for the number of factors in a tensor factor model.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4766865
- Identifier: SSRN 4766865
- Released: 2023-01-04
- First featured: Quant Letter No. 42 (2024-03-27): https://www.ml-quant.com/issues/2024-03-27/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Asset Pricing & Factors

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