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Full-Text Articles in Finance and Financial Management
Forecasting Realized Volatility Using A Nonnegative Semiparametric Model, Anders Eriksson, Daniel P. A. Preve, Jun Yu
Forecasting Realized Volatility Using A Nonnegative Semiparametric Model, Anders Eriksson, Daniel P. A. Preve, Jun Yu
Research Collection School Of Economics
This paper introduces a parsimonious and yet flexible semiparametric model to forecastfinancial volatility. The new model extends a related linear nonnegative autoregressive modelpreviously used in the volatility literature by way of a power transformation. It is semiparametric inthe sense that the distributional and functional form of its error component is partially unspecified.The statistical properties of the model are discussed and a novel estimation method is proposed.Simulation studies validate the new method and suggest that it works reasonably well in finitesamples. The out-of-sample forecasting performance of the proposed model is evaluated against anumber of standard models, using data on S&P 500 …
A Two-Stage Realized Volatility Approach To The Estimation For Diffusion Processes From Discrete Observations, Peter C. B. Phillips, Jun Yu
A Two-Stage Realized Volatility Approach To The Estimation For Diffusion Processes From Discrete Observations, Peter C. B. Phillips, Jun Yu
Research Collection School Of Economics
This paper motivates and introduces a two-stage method for estimating diffusion processes based on discretely sampled observations. In the first stage we make use of the feasible central limit theory for realized volatility, as recently developed in Barndorff-Nielsen and Shephard (2002), to provide a regression model for estimating the parameters in the diffusion function. In the second stage the in-fill likelihood function is derived by means of the Girsanov theorem and then used to estimate the parameters in the drift function. Consistency and asymptotic distribution theory for these estimates are established in various contexts. The finite sample performance of the …