Response surface Methodology for Simulating Hedging and Trading Strategies

R. Evren Baysal, Barry L. Nelson, Jeremy Staum

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations


Suppose that one wishes to evaluate the distribution of profit and loss (P&L) resulting from a dynamic trading strategy. A straightforward method is to simulate thousands of paths (i.e.-time series) of relevant financial variables and to track the resulting P&L at every time at which the trading strategy rebalances its portfolio. In many cases-this requires numerical computation of portfolio weights at every rebalancing time on every path-for example-by a nested simulation performed conditional on market conditions at that time on that path. Such a two-level simulation could involve many millions of simulations to compute portfolio weights-and thus be too computationally expensive to attain high accuracy. We show that response surface methodology enables a more efficient simulation procedure: in particular-it is possible to do far fewer simulations by using kriging to model portfolio weights as a function of underlying financial variables.

Original languageEnglish (US)
Title of host publicationProceedings of the 2008 Winter Simulation Conference, WSC 2008
Number of pages9
StatePublished - 2008
Event2008 Winter Simulation Conference, WSC 2008 - Miami, FL, United States
Duration: Dec 7 2008Dec 10 2008

Publication series

NameProceedings - Winter Simulation Conference
ISSN (Print)0891-7736


Other2008 Winter Simulation Conference, WSC 2008
Country/TerritoryUnited States
CityMiami, FL

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications


Dive into the research topics of 'Response surface Methodology for Simulating Hedging and Trading Strategies'. Together they form a unique fingerprint.

Cite this