A probabilistic analysis of the trading the line strategy

V. Abramov, M. K. Khan and R. A. Khan

Quantitative Finance, 2008, vol. 8, issue 5, 499-512

Abstract: We provide analytic models for which the appropriate statistics of the trading the line strategy, Nh, can be derived in closed form. In particular, we provide closed-form expressions concerning the average duration of the open position, E(Nh), the variance of the open duration, Var(Nh), the average of the stopped log price, E(SNh), the variance of the stopped log price, Var(SNh), the correlation, Corr(Nh, SNh), and the Laplace transform, E(e-sNh). These results are obtained, in discrete time settings, for binomial and other price scenarios. Furthermore, when analytic results are not possible, such as the case of a normal distribution for log returns, we show by simulation that our general conclusions still hold. Using these statistics we point out some of the subtle features of the trailing stops strategy.

Keywords: Binomial model; Cumulative sum procedure; Financial securities; Geometric random walk; Long position; Short position; SPRT; Trailing stops strategy; Trinomial model (search for similar items in EconPapers)
Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/14697680701489427 (text/html)
Access to full text is restricted to subscribers.

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:taf:quantf:v:8:y:2008:i:5:p:499-512

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RQUF20

DOI: 10.1080/14697680701489427

Access Statistics for this article

Quantitative Finance is currently edited by Michael Dempster and Jim Gatheral

More articles in Quantitative Finance from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().