---
title: Portfolio Decision Analysis: Friction and Decision Rules
url: https://www.ml-quant.com/papers/repec/inm-ordeca-v-18-y-2021-i-2-p-101-120/
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:inm:ordeca:v:18:y:2021:i:2:p:101-120
source_url: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fdx.doi.org%2F10.1287%2Fdeca.2020.0421%3Bh%3Drepec%3Ainm%3Aordeca%3Av%3A18%3Ay%3A2021%3Ai%3A2%3Ap%3A101-120
featured: 2023-09-21
citations: unknown
topic: Portfolio & Allocation
---


# Portfolio Decision Analysis: Friction and Decision Rules

Friction and Decision Rules: The research suggests that the traditional method of maximizing expected utility in portfolio decision analysis may not always be the best approach, highlighting the need for further studies on friction.

- Source: https://econpapers.repec.org/scripts/redir.pf?u=http%3A%2F%2Fdx.doi.org%2F10.1287%2Fdeca.2020.0421%3Bh%3Drepec%3Ainm%3Aordeca%3Av%3A18%3Ay%3A2021%3Ai%3A2%3Ap%3A101-120
- Identifier: RePEc:inm:ordeca:v:18:y:2021:i:2:p:101-120
- Released: 2021-11-11
- First featured: Quant Letter No. 16 (2023-09-21): https://www.ml-quant.com/issues/2023-09-21/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Portfolio & Allocation

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