---
title: Teflon Capitalism: Geopolitical Risk and Investment Funds
url: https://www.ml-quant.com/papers/repec/een-camaaa-2026-88/
site: ML-Quant (https://www.ml-quant.com)
updated: 2026-11-14
license: Summaries CC BY 4.0; links go to the original sources
index: https://www.ml-quant.com/llms.txt
identifier: RePEc:een:camaaa:2026-88
source_url: https://econpapers.repec.org/RePEc:een:camaaa:2026-88
featured: 2026-11-13
citations: unknown
topic: Portfolio & Allocation
---


# Teflon Capitalism: Geopolitical Risk and Investment Funds

Investment funds buy depressed stocks of geopolitically exposed firms seeking yield, stabilizing valuations during shocks while raising portfolio concentration.

- Source: https://econpapers.repec.org/RePEc:een:camaaa:2026-88
- Identifier: RePEc:een:camaaa:2026-88
- Released: 2026-11-02
- First featured: Quant Letter No. 139 (2026-11-13): https://www.ml-quant.com/issues/2026-11-13/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Portfolio & Allocation
- Authors: Daniel Marcel te Kaat, Jiancong Liu, Alexander Raabe

## Related

- [Impact of Geopolitical Risk on Mutual Funds](https://www.ml-quant.com/papers/ssrn/5087499/): The research shows that active funds in the U.S. lessen the impact of geopolitical shocks by selling stocks of firms exporting to China and buying lottery stocks.
- [Strengthening Investment Portfolios through Resilience – A Primer](https://www.ml-quant.com/papers/ssrn/4667697/): The article promotes an adaptive investment strategy that focuses on resilience thinking, active ownership, and moving away from narrow financial models due to fast-paced technological, geopolitical, and environmental changes.
- [Market Regime-Based Multi-Asset Portfolio Optimization Using Nested Clustered Optimization for Tactical Asset Allocation](https://www.ml-quant.com/papers/arxiv/2610.27751/): The study integrates market regime detection with Nested Clustered Optimization to build multi-asset portfolios, showing improved risk-adjusted returns and reduced downside risk versus regime-agnostic approaches.
- [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.
- [Optimal Investment and Consumption in Financial Markets with Integrated Variance Clocks](https://www.ml-quant.com/papers/arxiv/2609.26349/): Characterizes optimal consumption and investment strategies in markets with stochastic volatility clocks using infinite-horizon backward SDEs, extending to rough and hyper-rough regimes.