Statistical Process Control in Asset Management

Vasyl Golosnoy and Wolfgang Schmid
Additional contact information
Vasyl Golosnoy: Christian-Albrechts-Universität Kiel, Institut für Statistik und Ökonometrie
Wolfgang Schmid: European University, Department of Statistics

Chapter 20 in Applied Quantitative Finance, 2009, pp 399-416 from Springer

Abstract: Statistical process control (SPC) suggests tools for the on-line detection of changes in the parameters of the process of interest. For the purpose of the data analysis the observations are divided into two parts, historical and online observations. The historical observations are used to make statements about the distributional properties of the process. Such results are necessary for the calculation of the design of control charts, which are the most important monitoring instruments in SPC. Every newly incoming information is immediately exploited. The new observations are analyzed on-line. It is examined at each time point whether the process parameters identified from the historical observations remain unchanged. The control chart gives a signal if the process parameters have changed in a statistically significant way. A decision maker should carefully analyze possible causes and consequences of any signal. The rest of the chapter is organized as follows. Section 20.2 provides a brief review of the terminology, instruments, and procedures of SPC. Section 20.3 discusses the application of SPC in asset management for passive as well as for active portfolio investors. In particular, Section 20.3.1 deals with monitoring a fund manager’s performance, while in Section 20.3.2 the monitoring the GMVP weights is discussed. Section 20.4 concludes.

Keywords: Control Chart; Optimal Portfolio; Risky Asset; Fund Manager; Exponentially Weighted Move Average (search for similar items in EconPapers)
Date: 2009
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:spr:sprchp:978-3-540-69179-2_20

Ordering information: This item can be ordered from
http://www.springer.com/9783540691792

DOI: 10.1007/978-3-540-69179-2_20

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().