Controlling the Effect of Microstructure Noise and Removing Jumps Effect in Estimating of Systematic Risk by High Frequency Data
Subject Areas : Financial engineering
Keywords: high frequency data, Microstructure noise, Pre_averaging, Jump, Systematic Risk, Realized Volatility,
Abstract :
Today, another important significant time series exist in markets. These time series include a lot of information such as the price of bid-ask, trading volume, trading time and etc. in one day, these time series are known as high frequency data which have issues such as: Non-synchronous trading, microstructure noise and jumps; they have different analyzing compared to conventional time series and the researcher is able to use them in a short period of time. This article will discuss about estimating of national Iranian copper industries companies' systematic risk by "pre-averaging" approach and removing jumps in Khordad until Aban 1393(June-November). The outcome of this research indicates that jumps and microstructure noises have impression over estimating of realized volatility and consequently on the systematic risk; and it is crucial to control them then estimating of systematic risk would be more reliable and as a result, risk management of portfolio will be more functional.