Monte Carlo VaR modeling on options portfolio

CLIENT

A European Investment Bank.

OPPORTUNITY

The client wanted to develop a Value at Risk (VaR) model for their large options book. The option book contained financial instruments with path dependent payment structures.

SOLUTION

SG Analytics deployed a team of offshore quant analysts to support the client’s onshore team in conducting daily VaR calculations based on a Monte Carlo approach.
  1. The team assessed the client’s option portfolio and broke down its components by underlying asset classes, e.g. stocks, futures, commodities, currency, and indices to build a replicating portfolio.
  2. Under consideration of the client’s models for possible movements of the underlying asset prices, the team simulated a large number of scenarios consisting of potential price paths.
  3. Using the scenarios, the team calculated the portfolio’s overall VaR as a percentile of the option book’s Monte Carlo risk distribution.
SG Analytics would monitor the model and report real-time, end of day VaR on 95% and 99% fallouts to the client’s risk managers.

VALUE DELIVERED

  1. The management could gather a complete risk profile of their options book spread across currencies and index options.
  2. They could know the VaR, Gamma, Theta, Vega of the book in real time and hence control the risk exposures.
  3. The reports became one of the most insightful tools for the client’s risk management to control their option book.

CLIENT

A European Investment Bank.

OPPORTUNITY

The client wanted to develop a Value at Risk (VaR) model for their large options book. The option book contained financial instruments with path dependent payment structures.

SOLUTION

SG Analytics deployed a team of offshore quant analysts to support the client’s onshore team in conducting daily VaR calculations based on a Monte Carlo approach.
  1. The team assessed the client’s option portfolio and broke down its components by underlying asset classes, e.g. stocks, futures, commodities, currency, and indices to build a replicating portfolio.
  2. Under consideration of the client’s models for possible movements of the underlying asset prices, the team simulated a large number of scenarios consisting of potential price paths.
  3. Using the scenarios, the team calculated the portfolio’s overall VaR as a percentile of the option book’s Monte Carlo risk distribution.

SG Analytics would monitor the model and report real-time, end of day VaR on 95% and 99% fallouts to the client’s risk managers.

VALUE DELIVERED

►
1
The client's management could gather a complete risk profile of their options book spread across currencies and index options.
►
2
SG Analytics model also allowed real-time insights into the VaR, Gamma, Theta, and Vega of the option book and hence control the risk exposures.
►
3
The reports became one of the most insightful tools for the client's risk management to control their option book.