Realized Volatility Based on Tick Time Sampling

Central limit theorem for the realized volatility based on tick time sampling

Volatility Forecasting with High Frequency Data

The daily volatility is typically unobserved but can be estimated using high frequent tick-by-tick data. In this paper, we study the problem of forecasting the unobserved volatility using past values of measured volatility. Specifically, we use daily estimates of volatility based on high frequency data, called realized variance, and construct the optimal linear forecast of future volatility. Ut...

Analysis of Realized Volatility in Tehran Stock Exchange using Heterogeneous Autoregressive Models Approach

Objective: The present study aims atinvestigating the behavior of realized volatility for high-frequency data of Tehran Stock Index from April28th, 2012 to August 8th, 2018. Methods: Three different types of HAR models including of HAR-RV-CJ, HAR-RV and HAR-RVJ were used to analyze the Realized Volatility. Results: The obtained results of three diverse models revealed that the estimated Reali...

Consistent High-Precision Volatility from High-Frequency Data

Estimates of daily volatility are investigated. Realized volatility can be computed from returns observed over time intervals of different sizes. For simple statistical reasons, volatility estimators based on high-frequency returns have been proposed, but such estimators are found to be strongly biased as compared to volatilities of daily returns. This bias originates from microstructure effect...

Realized Volatility When Sampling Times can be Endogenous ∗

When estimating integrated volatilities based on high-frequency data, simplifying assumptions are usually imposed on the relationship between the observation times and the price process. In this paper, we establish a central limit theorem for the Realized Volatility in a general endogenous time setting. We also document that this endogeneity can be present in financial data.