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344 – Methods in Financial Econometrics
Realized Measures and Statistical Inference for Stochastic Volatility Models
Md. Nazmul Ahsan
McGill University
Since realized measures of volatility are affected by measurement errors, the study considers a new class of discrete time stochastic volatility (SV) models, which can relate many realized volatility measures to the latent conditional variance. We propose a hybrid estimator for this class of models that combines a generalized least square (GLS) type transformation and instrumental variable (IV) approach. A simulation study reveals that the hybrid estimation method has excellent finite sample properties. We illustrate the proposed method’s empirical relevance using mixed frequency IBM stock returns and options prices.