Economic factors and the stock market: a new perspective

✍ Scribed by Min Qi; G. S. Maddala

• Publisher: John Wiley and Sons
• Year: 1999
• Tongue: English
• Weight: 201 KB
• Volume: 18
• Category: Article
• ISSN: 0277-6693
• DOI: 10.1002/(sici)1099-131x(199905)18:3<151::aid-for716>3.0.co;2-v

✦ Synopsis

It has been widely accepted that many ®nancial and economic variables are non-linear, and neural networks can model ¯exible linear or non-linear relationships among variables. The present paper deals with an important issue: Can the many studies in the ®nance literature evidencing predictability of stock returns by means of linear regression be improved by a neural network? We show that the predictive accuracy can be improved by a neural network, and the results largely hold out-of-sample. Both the neural network and linear forecasts show signi®cant market timing ability. While the switching portfolio based on the linear forecasts outperforms the buy-and-hold market portfolio under all three transaction cost scenarios, the switching portfolio based on the neural network forecasts beats the market only if there is no transaction cost.