Estimation methods for stochastic volatility models: a survey
综述了随机波动率模型的主要估计方法，比较了参数和波动率估计量的优缺点，并应用于标普500指数，帮助研究者选择合适方法。
Abstract. Although stochastic volatility (SV) models have an intuitive appeal, their empirical application has been limited mainly due to difficulties involved in their estimation. The main problem is that the likelihood function is hard to evaluate. However, recently, several new estimation methods have been introduced and the literature on SV models has grown substantially. In this article, we review this literature. We describe the main estimators of the parameters and the underlying volatilities focusing on their advantages and limitations both from the theoretical and empirical point of view. We complete the survey with an application of the most important procedures to the S&P 500 stock price index.