A parsimonious parametric model for generating margin requirements for futures

Carol Alexander, Andreas Kaeck and Anannit Sumawong

European Journal of Operational Research, 2019, vol. 273, issue 1, 31-43

Abstract: Major exchanges employ the Standard Portfolio Analysis of Risk (SPAN) software to measure maintenance margins. However, its methodology has become cumbersome and opaque, having evolved over several decades and by now it requires that several hundred parameter values are re-set every day. We present a new, parsimonious parametric model for calculating margin requirements for futures which has a rigorous econometric foundation, being derived entirely from the median tail loss (MTL) of the returns distribution. This facilitates maximum likelihood volatility model calibration and state-of-the-art backtests. Then the parameters of the margin scheme which overlays the MTL may be calibrated using a variety of objectives. We examine three such objectives, including two which are designed to generate margins which mimic SPAN.

Keywords: Finance; Backtesting; Margin rules; Median tail loss; WTI crude oil (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377221718306830
Full text for ScienceDirect subscribers only

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:eee:ejores:v:273:y:2019:i:1:p:31-43

DOI: 10.1016/j.ejor.2018.08.006

Access Statistics for this article

European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().