A comparison of global, recurrent and smoothed-piecewise neural models for Istanbul stock exchange (ISE) prediction

Serdar Yümlü، نويسنده , , Fikret S. Gürgen، نويسنده , , Nesrin Okay، نويسنده ,

روزنامه با شماره پیاپی سال 2005

11

2093

2103

Financial time series (FTS) prediction , Global , Feedback , Smoothed-piecewise neural models , Exponential generalizedautoregressive conditional heteroskedasticity (EGARCH) model , Risk estimation , Volatility

PATTERN RECOGNITION LETTERS

2005

PATTERN RECOGNITION LETTERS

251180