Microstructure Noise in the Continuous Case: The Pre-Averaging Approach ∗
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In this article, a generalized pre-averaging approach for estimating the integrated volatility is presented, which can generate rate optimal estimators with convergence rate n 1/4. But the convergence rate is not guaranteed.About:
This article is published in Stochastic Processes and their Applications.The article was published on 2009-07-01 and is currently open access. It has received 525 citations till now. The article focuses on the topics: Stochastic volatility & Estimator.read more
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Kernel Estimation of Spot Volatility with Microstructure Noise Using Pre-Averaging
TL;DR: In this article, a kernel estimation of spot volatility in a general continuous It\^o semimartingale model in the absence of microstructure noise was studied, and a new type of pre-averaging/kernel estimator was proposed for spot volatility under the presence of additive micro structure noise.
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Volatility estimation and forecasts based on price durations
TL;DR: In this article, price duration estimators are used for the estimation and forecasting of the integrated variance of an underlying semi-martingale price process and how they are affected by discrete and irregular spacing of observations, market microstructure noise, and finite price jumps.
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Nonparametric Estimation of the Volatility Under Microstructure Noise: Wavelet Adaptation
TL;DR: In this paper, the authors study nonparametric estimation of the volatility function of a diffusion process from discrete data, when the data are blurred by additional noise, and propose a new criterion to assess the quality of estimation.
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Local linear estimator for stochastic differential equations driven by α -stable Lévy motions
TL;DR: In this paper, the local linear estimator for the drift coefficient of stochastic differential equations driven by α-stable Levy motions observed at discrete instants was studied and the weak consistency and central limit theorem of the estimator was derived under regular conditions.
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Testing for Jump Spillovers Without Testing for Jumps
TL;DR: The authors developed statistical tools for testing conditional independence among the jump components of the daily quadratic variation, which they estimate using intraday data. But they did not consider the conditional independence of the jump component.
References
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Journal ArticleDOI
A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options
TL;DR: In this paper, a closed-form solution for the price of a European call option on an asset with stochastic volatility is derived based on characteristi c functions and can be applied to other problems.
Book
Limit Theorems for Stochastic Processes
Jean Jacod,Albert N. Shiryaev +1 more
TL;DR: In this article, the General Theory of Stochastic Processes, Semimartingales, and Stochastically Integrals is discussed and the convergence of Processes with Independent Increments is discussed.
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Answering the skeptics: yes, standard volatility models do provide accurate forecasts*
TL;DR: In this article, a voluminous literature has emerged for modeling the temporal dependencies in financial market volatility using ARCH and stochastic volatility models and it has been shown that volatility models produce strikingly accurate inter-daily forecasts for the latent volatility factor that would be of interest in most financial applications.
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Modeling and forecasting realized volatility
TL;DR: In this article, the authors provide a general framework for integration of high-frequency intraday data into the measurement, modeling, and forecasting of daily and lower frequency volatility and return distributions.
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A Simple Implicit Measure of the Effective Bid‐Ask Spread in an Efficient Market
TL;DR: In this article, the effective bid-ask spread is measured by Spread = 2−cov where cov is the first-order serial covariance of price changes, and is shown empirically to be closely related to firm size.