Journal of Statistical and Econometric Methods
Forecasting Volatility in Indian Stock Market using State Space Models
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The paper examines and compares forecasting ability of
Autoregressive Moving Average (ARMA) and Stochastic Volatility models
represented in the state space form and Kalman Filter is used as an estimator for
the models.The models are applied in the context of Indian stock market. For
estimation purpose, daily values of Sensex from Bombay Stock Exchange (BSE) are
used as the inputs. The results of the study confirm the volatility forecasting
capabilities of both the models. Finally, we interpreted that which model
performs better in the out-of-sample forecast for h-step ahead forecast.
Forecast errors of the volatility were found in favour of SV model for a 30-day
ahead forecast. This also shows that Kalman filter can be used for better
estimates and forecasts of the volatility using state space models.
ISSN: 2241-0376 (Online)