Date of Award
5-2016
Degree Type
Thesis
Degree Name
Master of Arts (MA)
Department
Economics and Finance
Committee Chair(s)
Tyler Brough
Committee
Tyler Brough
Committee
Devon Gorry
Committee
James Feigenbaum
Abstract
As a basic principle in statistics, a larger sample size is preferred whenever possible. Nonetheless, in the financial world, especially equities and currencies trading, including all available data poses great challenges due to the noise present in the volatility estimation. In his paper I examine the Two Time Scales Realized Volatility estimator by Zhang, Mykland, and Ait-Sahalia (2005b) and I find that it not only provides a more efficient estimator than a basic estimator of the integrated volatility of returns, but it also consistently estimates the microstructure noise present in the latent efficient return process. I find that by using this approach, it is possible to compare the efficiency of the prices of securities with lower transaction costs traded against those with higher transactions costs.
Recommended Citation
Romero, Aristides, "Microstructure Noise: The Use of Two Scales Realized Volatility for the Noisy High-Frequency Data and its Implications for Market Efficiency and Financial Forecasting" (2016). All Graduate Plan B and other Reports, Spring 1920 to Spring 2023. 826.
https://digitalcommons.usu.edu/gradreports/826
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