---
title: Factor Timing China
url: https://www.ml-quant.com/papers/repec/bla-acctfi-v-63-y-2023-i-1-p-485-505/
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: RePEc:bla:acctfi:v:63:y:2023:i:1:p:485-505
source_url: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fdoi.org%2F10.1111%2Facfi.13033%3Bh%3Drepec%3Abla%3Aacctfi%3Av%3A63%3Ay%3A2023%3Ai%3A1%3Ap%3A485-505
featured: 2024-07-10
citations: unknown
topic: Asset Pricing & Factors
---


# Factor Timing China

The paper proposes a factor timing strategy using deep learning and 146 characteristic-based factors, which performs better than other portfolios, especially in the Chinese stock market.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fdoi.org%2F10.1111%2Facfi.13033%3Bh%3Drepec%3Abla%3Aacctfi%3Av%3A63%3Ay%3A2023%3Ai%3A1%3Ap%3A485-505
- Identifier: RePEc:bla:acctfi:v:63:y:2023:i:1:p:485-505
- Released: 2023-05-20
- First featured: Quant Letter No. 56 (2024-07-10): https://www.ml-quant.com/issues/2024-07-10/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Asset Pricing & Factors

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