smq/directoryAn evolving quant resource archive
Back to directoryResource
Paper / 2026SMQ / 265541890533023
Optimal Loss Allocation in a Mean-Field Model of Systemic Risk
Qinxin Yan / Yucheng Guo
brownian motion / stochastic processesResource overview

Optimal Loss Allocation in a Mean-Field Model of Systemic Risk

Paper2026

by Qinxin Yan, Yucheng Guo

Tags
brownian motionstochastic processessystemic risk

Access resource

Open original source Understand this paper

Continue on SelfMadeQuant

Understand this paper

Suggested foundations for risk measurement and stress and stochastic processes and pricing. Specialist prerequisites vary by paper.

Before you read

  1. Random Variables and Distributions

    Represent losses as a distribution rather than one forecast.

  2. Expected Shortfall and Other Tail Risk Measures

    Distinguish a loss quantile from the average loss in the tail.

  3. Conditional Expectation

    Understand what it means to condition on current information.

  4. Stochastic Processes, Brownian Motion and Itô's Lemma

    Follow Brownian dynamics and the second-order term in Itô calculus.

Go further

  1. VaR Estimation in Practice: Variance-Covariance, Historical Simulation, Monte Carlo

    Compare risk estimators and their assumptions.

  2. Backtesting VaR and ES: Coverage Tests and Model Validation

    Check forecasts against realised losses.

  3. Market Model and Risk-Neutral Valuation

    Connect stochastic dynamics to no-arbitrage prices.

Explore a related reading path

Lesson links open public previews. Access to full lessons depends on the topic and your membership.

Explore Quantitative Risk Management Explore Derivatives Pricing and Computational Finance

Keep exploring

Related resources

More ideas from similar topics.

6

From the same author

Qinxin Yan, Yucheng Guo

1