---
title: Coherent Risk Measure on L0: NA Condition, Pricing and Dual Representation
url: https://www.ml-quant.com/papers/doi/10-1142-s0219024921500370/
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: doi:10.1142/s0219024921500370
source_url: http://dx.doi.org/10.1142/s0219024921500370
featured: 2024-05-15
citations: 0
topic: Derivatives & Volatility
---


# Coherent Risk Measure on L0: NA Condition, Pricing and Dual Representation

The article presents a revised version of the fundamental theorem of asset pricing in financial market models, demonstrating that all risk-hedging prices are consistent under the NA condition.

- Source: http://dx.doi.org/10.1142/s0219024921500370
- Identifier: doi:10.1142/s0219024921500370
- Released: 2024-05-10
- First featured: Quant Letter No. 49 (2024-05-15): https://www.ml-quant.com/issues/2024-05-15/
- Citations (Semantic Scholar): 0
- Published in: International Journal of Theoretical and Applied Finance
- Topic: Derivatives & Volatility

## Related

- [Risk Revisited](https://www.ml-quant.com/papers/ssrn/4825844/): The study identifies recency, cluster, and sign as three factors shaping investors' risk perceptions of a stock, influencing trading volume and future volatility.
- [Rough Volatility: Fact or Artefact?](https://www.ml-quant.com/papers/arxiv/2203.13820/): Fact or Artifact: The study proposes a new method to estimate the roughness of financial asset volatility, attributing observed roughness to microstructure noise.
- [Decentralized and Centralized Options Trading: A Risk Premia Perspective](https://www.ml-quant.com/papers/ssrn/4822783/): The research looks at OnChain options traded on a decentralized Ethereum blockchain exchange, underlining the differences in implied volatilities compared to OffChain options traded on centralized exchanges.
- [Hedging American Put Options with Deep Reinforcement Learning](https://www.ml-quant.com/papers/arxiv/2405.06774/): The article discusses a study that shows deep reinforcement learning (DRL) is more effective than traditional methods for hedging American put options, especially in real-world situations.
- [Fourier-Laplace Transforms in Polynomial Ornstein-Uhlenbeck Volatility Models](https://www.ml-quant.com/papers/ssrn/4816314/): The article investigates the Fourier-Laplace transforms of various polynomial Ornstein-Uhlenbeck volatility models, linking it with the solution of an infinite dimensional Riccati equation.
- [Fourier-Laplace Transforms in Polynomial Ornstein-Uhlenbeck Volatility Models](https://www.ml-quant.com/papers/arxiv/2405.02170/): The research investigates the Fourier-Laplace transforms of different volatility models, links them to the solution of a specific equation, and creates a numerical method for solving these equations for pricing options and volatility swaps.
