ESTABLISHING AN INDEX ARBITRAGE MODEL BY APPLYING NEURAL NETWORKS METHOD — A CASE STUDY OF NIKKEI 225 INDEX

2001 ◽  
Vol 11 (05) ◽  
pp. 489-496
Author(s):  
AN-PIN CHEN ◽  
CHIEH-YOW CHIANGLIN ◽  
HISU-PEI CHUNG
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Stock Index ◽  
The Neural Network ◽  
Time Period ◽  
Network Method ◽  
Index Arbitrage ◽  
Impact Risk ◽  
Cost Of Carry

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.

scholarly journals Does Index Arbitrage Distort the Market Reaction to Shocks?

2020 ◽  
Author(s):  
Stanislav Anatolyev ◽  
Sergei Seleznev ◽  
Veronika Selezneva
Keyword(s):  
Market Reaction ◽  
Index Arbitrage

The intraday ex post and ex ante profitability of index arbitrage

1991 ◽  
Vol 11 (3) ◽  
pp. 291-311 ◽  
Author(s):  
Robert C. Klemkosky ◽  
Jae Ha Lee
Keyword(s):  
Ex Post ◽  
Ex Ante ◽  
Index Arbitrage
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