Skip to main content Accessibility help
×
Hostname: page-component-848d4c4894-r5zm4 Total loading time: 0 Render date: 2024-06-16T20:55:01.168Z Has data issue: false hasContentIssue false

10 - Sequential Investment

Published online by Cambridge University Press:  03 December 2009

Nicolo Cesa-Bianchi
Affiliation:
Università degli Studi di Milano
Gabor Lugosi
Affiliation:
Universitat Pompeu Fabra, Barcelona
Get access

Summary

Portfolio Selection

This chapter is devoted to the application of the ideas described in Chapter 9 to the problem of sequential investment. Imagine a market of m assets (stocks) in which, in each trading period (day), the price of a stock may vary in an arbitrary way. An investor operates on this market for n days with the goal of maximizing his final wealth. At the beginning of each day, on the basis of the past behavior of the market, the investor redistributes his current wealth among the m assets. Following the approach developed in the previous chapters, we avoid any statistical assumptions about the nature of the stock market, and evaluate the investor's wealth relative to the performance achieved by the best strategy in a class of reference investment strategie (the “experts”).

In the idealized stock market we assume that there are no transaction costs and the amount of each stock that can be bought at any trading period is only limited by the investor's wealth at that time. Similarly, the investor can sell any quantity of the stocks he possesses at any time at the actual market price.

The model may be formalized as follows. A market vectorx = (x1, …, xm) for m assets is a vector of nonnegative real numbers representing price relatives for a given trading period. In other words, the quantity xi ≥ 0 denotes the ratio of closing to opening price of the ith asset for that period.

Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2006

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

  • Sequential Investment
  • Nicolo Cesa-Bianchi, Università degli Studi di Milano, Gabor Lugosi, Universitat Pompeu Fabra, Barcelona
  • Book: Prediction, Learning, and Games
  • Online publication: 03 December 2009
  • Chapter DOI: https://doi.org/10.1017/CBO9780511546921.011
Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

  • Sequential Investment
  • Nicolo Cesa-Bianchi, Università degli Studi di Milano, Gabor Lugosi, Universitat Pompeu Fabra, Barcelona
  • Book: Prediction, Learning, and Games
  • Online publication: 03 December 2009
  • Chapter DOI: https://doi.org/10.1017/CBO9780511546921.011
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Sequential Investment
  • Nicolo Cesa-Bianchi, Università degli Studi di Milano, Gabor Lugosi, Universitat Pompeu Fabra, Barcelona
  • Book: Prediction, Learning, and Games
  • Online publication: 03 December 2009
  • Chapter DOI: https://doi.org/10.1017/CBO9780511546921.011
Available formats
×