Nonparametric kernel-based sequential investment strategies

L. Györfi, Gábor Lugosi, Frederic Udina

Research output: Contribution to journalArticle

47 Citations (Scopus)

Abstract

The purpose of this paper is to introduce sequential investment strategies that guarantee an optimal rate of growth of the capital, under minimal assumptions on the behavior of the market. The new strategies are analyzed both theoretically and empirically. The theoretical results show that the asymptotic rate of growth matches the optimal one that one could achieve with a full knowledge of the statistical properties of the underlying process generating the market, under the only assumption that the market is stationary and ergodic. The empirical results show that the performance of the proposed investment strategies measured on past NYSE and currency exchange data is solid, and sometimes even spectacular.

Original languageEnglish
Pages (from-to)337-357
Number of pages21
JournalMathematical Finance
Volume16
Issue number2
DOIs
Publication statusPublished - Apr 2006

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kernel
market
Electronic data interchange
Optimal Rates
data exchange
Currency
Data Exchange
currency
Statistical property
guarantee
performance
Market
Strategy
Kernel
Investment strategy
Sequential investment
Knowledge
Guarantee
New York Stock Exchange
Empirical results

Keywords

  • Kernel estimation
  • Sequential investment
  • Universal portfolios

ASJC Scopus subject areas

  • Applied Mathematics
  • Finance
  • Accounting
  • Economics and Econometrics
  • Social Sciences (miscellaneous)

Cite this

Nonparametric kernel-based sequential investment strategies. / Györfi, L.; Lugosi, Gábor; Udina, Frederic.

In: Mathematical Finance, Vol. 16, No. 2, 04.2006, p. 337-357.

Research output: Contribution to journalArticle

Györfi, L. ; Lugosi, Gábor ; Udina, Frederic. / Nonparametric kernel-based sequential investment strategies. In: Mathematical Finance. 2006 ; Vol. 16, No. 2. pp. 337-357.
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