---
title: Inflation's Impact on Fund Liquidity
url: https://www.ml-quant.com/papers/ssrn/4922867/
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: SSRN 4922867
source_url: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4922867
featured: 2024-08-15
citations: unknown
topic: Trading, Microstructure & Execution
---


# Inflation's Impact on Fund Liquidity

Inflation impacts the liquidity of closed-end funds differently in the short and long term, with a confirmed rate showing a reverse relationship between the prime rate and liquidity, and between liquidity and CEFs discounts.

- Source: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4922867
- Identifier: SSRN 4922867
- Released: 2024-08-12
- First featured: Quant Letter No. 61 (2024-08-15): https://www.ml-quant.com/issues/2024-08-15/
- Citations (Semantic Scholar): not tracked
- Published in: not yet
- Topic: Trading, Microstructure & Execution

## Related

- [Inflation and Trading](https://www.ml-quant.com/papers/ssrn/4822700/): Research indicates that investors often hold unrealistic expectations about stock returns during high inflation, and lack knowledge about inflation-hedging strategies, affecting their trading decisions.
- [US. Treasuries: Liquidity Premiums and Results](https://www.ml-quant.com/papers/ssrn/4619340/): Liquidity Premiums and Results: A new model of U.S. Treasuries suggests that liquidity factors are more significant than others, Federal Reserve asset purchases impact expected rates and term premiums, and inflation expectations are less stable than previously thought.
- [FAST: Efficient Action Tokenization for Vision-Language-Action Models](https://www.ml-quant.com/papers/arxiv/2501.09747/): A new tokenization scheme, Frequency-space Action Sequence Tokenization (FAST), has been proposed for robot actions, facilitating the training of vision-language action policies for complex and high-frequency tasks.
- [Deep Reinforcement Learning for Active High Frequency Trading](https://www.ml-quant.com/papers/arxiv/2101.07107/): A new Deep Reinforcement Learning framework has been developed for high frequency stock trading, showing potential for profitable long-term strategies.
- [The Economic Analysis of the Common Pool Method through the HARA Utility Functions](https://www.ml-quant.com/papers/arxiv/2408.05194/): The study uses a mathematical model to compare two water trading systems, demonstrating that the 'common pool' system is significantly more efficient than the improved pair-wise trading system.
- [Periodic Trading Activities in Financial Markets: Mean-field Liquidation Game with Major-Minor Players](https://www.ml-quant.com/papers/arxiv/2408.09505/): The article investigates the causes and effects of periodic trading activities in equity markets, establishing a unique open-loop Nash equilibrium and providing new insights into market dynamics.
