smq/directoryAn evolving quant resource archive
Back to directoryResource
Paper / 2024SMQ / 177049526586534
Risk aggregation and stochastic dominance for a class of heavy-tailed distributions
Seva Shneer / Yuyu Chen
probabilityResource overview

Risk aggregation and stochastic dominance for a class of heavy-tailed distributions

Paper2024

by Seva Shneer, Yuyu Chen

Tags
probability

Access resource

Open original source Understand this paper

Continue on SelfMadeQuant

Understand this paper

Suggested foundations for probability and statistical reasoning and risk measurement and stress. Specialist prerequisites vary by paper.

Before you read

  1. Random Variables and Distributions

    Represent losses as a distribution rather than one forecast.

  2. Conditional Expectation

    Interpret expectations after information is observed.

  3. Expected Shortfall and Other Tail Risk Measures

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

Go further

  1. Confidence Intervals and Hypothesis Testing

    Assess uncertainty rather than treating an estimate as a fact.

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

    Compare risk estimators and their assumptions.

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

    Check forecasts against realised losses.

Explore a related reading path

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

Explore Probability, Statistics and Financial Data Explore Quantitative Risk Management

Keep exploring

Related resources

More ideas from similar topics.

6

From the same author

Seva Shneer, Yuyu Chen

6