---
title: Factor Models in Bond Portfolios
url: https://www.ml-quant.com/papers/repec/wsi-wschap-9789811272578-0010/
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:wsi:wschap:9789811272578_0010
source_url: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.worldscientific.com%2Fdoi%2Fpdf%2F10.1142%2F9789811272578_0010%3Bh%3Drepec%3Awsi%3Awschap%3A9789811272578_0010
featured: 2023-11-29
citations: unknown
topic: Portfolio & Allocation
---


# Factor Models in Bond Portfolios

The chapter highlights the use of factor models in understanding bond portfolio risk and return, stressing the importance of model specification.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=https%3A%2F%2Fwww.worldscientific.com%2Fdoi%2Fpdf%2F10.1142%2F9789811272578_0010%3Bh%3Drepec%3Awsi%3Awschap%3A9789811272578_0010
- Identifier: RePEc:wsi:wschap:9789811272578_0010
- Released: 2023-11-29
- First featured: Quant Letter No. 27 (2023-11-29): https://www.ml-quant.com/issues/2023-11-29/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Portfolio & Allocation

## Related

- [On Unified Adaptive Black-Litterman Mean-Variance Portfolio Management](https://www.ml-quant.com/papers/arxiv/2307.03391/): The paper presents a new adaptive portfolio management framework that merges dynamic Black-Litterman optimization with the general factor model and Elastic Net regression, showing computational benefits and promising trading results.
- [Smart Beta ETFs & Increased Flow Sensitivity to Multi-Factor Alphas](https://www.ml-quant.com/papers/ssrn/4620486/): Smart beta ETFs trading activity significantly impacts mutual fund flow sensitivity, especially in funds with high nonmarket risk factor exposure.
- [Comparing Factor Models for Portfolios](https://www.ml-quant.com/papers/repec/eee-jimfin-v-140-y-2024-i-c-s0261560623001985/): The paper finds no significant difference in investment outcomes when using the Hou-Xue-Zhang four-factor model versus the Fama-French five-factor model.
- [HighDimensional Portfolio Optimization with Tree-Structured Factor Model](https://www.ml-quant.com/papers/repec/eee-pacfin-v-81-y-2023-i-c-s0927538x23001774/): The paper proposes a new portfolio optimization method that uses multiple characteristic information to predict stock returns and risk exposures, demonstrating its effectiveness in achieving higher Sharpe ratios, smaller standard deviations, and lower turnover.
- [Course 2023-2024 in Portfolio Allocation and Asset Management](https://www.ml-quant.com/papers/ssrn/4698165/): The University of Paris-Saclay offers an advanced asset management course covering portfolio optimization, smart beta factor investing, and the use of machine learning in asset management.
- [An End-to-End Direct Reinforcement Learning Approach for Multi-Factor Based Portfolio Management](https://www.ml-quant.com/papers/ssrn/4729683/): A new online portfolio decision model combines the multifactor model and mean-variance portfolio optimization in one step, enhancing overall performance.
