International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 141 | Views: 206 | Weekly Hits: ⮙1 | Monthly Hits: ⮙1

Research Paper | Computer Science & Engineering | India | Volume 7 Issue 10, October 2018


Forecasting Volatility with LSTM Techniques

Hemanth Kumar P | S. Basavaraj Patil


Abstract: Volatility forecasting is most searched topic in recent times, from past fears there has been tremendous research in this field of finance. This paper aims at forecasting volatility of stock index with high accuracy. The historical volatility was calculated from daily prices using Yang-Zhang method. Deep learning techniques have evolved over the years and have been successfully applied in time series forecasting problems. In this paper LSTM techniques are applied to forecasting volatility 10 days ahead. The performance of the techniques were measured with mean square error and mean absolute error. The performance of LSTM techniques has outperformed Arima, Arfima and Neural network based techniques.


Keywords: Volatility, Forecasting, LSTM, Time series


Edition: Volume 7 Issue 10, October 2018,


Pages: 840 - 844


How to Download this Article?

Type Your Valid Email Address below to Receive the Article PDF Link


Verification Code will appear in 2 Seconds ... Wait

Top