Derivatives Performance Attribution

Mark Rubinstein.

No RPF-274-Rev, Research Program in Finance Working Papers from University of California at Berkeley

Abstract: This paper shows how to decompose the dollar profit earned from an option into two basic components: 1) mispricing of the option relative to the asset at the time of purchase, and 2) profit from subsequent fortuitous changes or mispricing of the underlying asset. This separation hinges on measuring the "true relative value" of the option from its realized payoff. The payoff from any one option has a huge standard error about this value which can be reduced by averaging the payoff from several independent option positions. It appears from simulations that 95% reductions in standard errors can be further achieved by using the payoff of a dynamic replicating portfolio as a Monte Carlo control variate. In addition, it is shown that these low standard errors are robust to discrete rather than continuous dynamic replication and to the likely degree of misspecification of the benchmark formula used to implement the replication.

Date: 1997-11-01
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://haas.berkeley.edu/finance/WP/rpf274.pdf main text (application/pdf)
Our link check indicates that this URL is bad, the error code is: 404 Not Found

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ucb:calbrf:rpf-274-rev

Ordering information: This working paper can be ordered from
IBER, F502 Haas Building, University of California at Berkeley, Berkeley CA 94720-1922

Access Statistics for this paper

More papers in Research Program in Finance Working Papers from University of California at Berkeley University of California at Berkeley, Berkeley, CA USA. Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F. Baum ().