Controlling the Effect of Microstructure Noise and Removing Jumps Effect in Estimating of Systematic Risk by High Frequency Data

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 companie's 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.