KAJIAN MODEL HIDDEN MARKOV UNTUK MENDUGA VOLATILITAS INDEKS HARGA SAHAM

Abstrak Volatility is a measure of uncertainty. Volatility can either be measured by using the standard deviation or variance between returns. The problem is volatility is unobservable, and estimating volatility is not a trivial task. Therefore, it needs daily volatility proxy as a benchmark in calculating error. This research used daily volatility proxy proposed by Alizadeh, Brandt, dan Diebolt (2002). Hidden Markov model is used for estimating volatility proposed by Rossi and Gallo (2006). Forecasting volatility for LQ45 index using the model performs well. This is indicated by SMAPE (Symmetric Mean Absolute Percentage Error) about 13.62%. K ata kunci : volatility, hidden Markov model, forecasting