Establishing an index arbitrage model by applying neural networks method--a case study of Nikkei 225 index.

An-Pin Chen*, C. Y. Chianglin, H. P. Chung

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

This paper applies the neural network method to establish an index arbitrage model and compares the arbitrage performances to that from traditional cost of carry arbitrage model. From the empirical results of the Nikkei 225 stock index market, following conclusions can be stated: (1) The basis will get enlarged for a time period, more profitability may be obtained from the trend. (2) If the neural network is applied within the index arbitrage model, twofold of return would be obtained than traditional arbitrage model can do. (3) If the T_basis has volatile trend, the neural network arbitrage model will ignore the peak. Although arbitrageur would lose the chance to get profit, they may reduce the market impact risk.

Original languageEnglish
Pages (from-to)489-496
Number of pages8
JournalInternational journal of neural systems
Volume11
Issue number5
DOIs
StatePublished - Oct 2001

Fingerprint

Dive into the research topics of 'Establishing an index arbitrage model by applying neural networks method--a case study of Nikkei 225 index.'. Together they form a unique fingerprint.

Cite this