---
title: Investment Mandates and the Value of Distribution Timing in Currency Portfolios Choice
url: https://www.ml-quant.com/papers/ssrn/7660982/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-10-30
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: SSRN 7660982
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7660982
featured: 2026-10-30
citations: unknown
topic: Portfolio & Allocation
---


# Investment Mandates and the Value of Distribution Timing in Currency Portfolios Choice

Adding skewness and kurtosis to mean-variance allocations in currency markets produces economically meaningful gains that depend critically on the investment mandate and ability to adjust gross exposure.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=7660982
- Identifier: SSRN 7660982
- Released: 2026-10-24
- First featured: Quant Letter No. 137 (2026-10-30): https://www.ml-quant.com/issues/2026-10-30/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Portfolio & Allocation
- Authors: Mattia Alfero, Stefano Grassi, Francesco Violante

## Related

- [Sparse International Portfolio Optimization](https://www.ml-quant.com/papers/ssrn/4575065/): A study shows that a regularized joint optimization approach for multicurrency asset allocation surpasses traditional strategies, enhancing portfolio performance and currency risk management.
- [Forex Market Jumps and Semivariances](https://www.ml-quant.com/papers/repec/cai-finpug-fina-pr-018/): A reliability-based design optimization framework is developed for portfolio optimization problems.
- [Conditional value-at-risk under reward-penalty mechanism with applications to robust portfolio management](https://www.ml-quant.com/papers/arxiv/2610.09246/): Derives a closed-form expression for worst-case conditional value-at-risk under reward-penalty mechanisms and distribution uncertainty, enabling optimal portfolio allocations that balance losses with downside risk.
- [The Critical Line Algorithm and the Constrained LASSO: One Curve, Two Literatures](https://www.ml-quant.com/papers/arxiv/2609.25704/): Shows that mean-variance portfolio selection and the constrained LASSO trace identical piecewise-linear solution paths, mapping their parametrizations exactly.
- [Signed network models for portfolio optimization](https://www.ml-quant.com/papers/arxiv/2510.05377/): The study shows that using negative edges in weighted signed network representations of financial markets can help reduce portfolio risk, performing on par with traditional models.
- [Bayesian Portfolio Optimization by Predictive Synthesis](https://www.ml-quant.com/papers/arxiv/2510.07180/): The article discusses a portfolio optimization technique using Bayesian predictive synthesis, which merges various asset return prediction models to handle financial market uncertainty.