Forecasting Realized Volatility Using a Nonnegative Semiparametric Time Series Model

Forecasting Realized Volatility Using a Nonnegative Semiparametric Time Series Model

This paper introduces a parsimonious and yet flexible nonnegative semiparametric model to forecast financial volatility. The new model extends the linear nonnegative autoregressive model of Barndorff-Nielsen & Shephard (2001) and Nielsen & Shephard (2003) by way of a power transformation. It...

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Bibliographic Details
Main Authors: Eriksson, A., Preve, D., YU, Jun
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2010
Subjects:
Autoregression
nonlinear/non-Gaussian time series
realized volatility
semiparametric model
volatility forecast.
Econometrics
Online Access:https://ink.library.smu.edu.sg/soe_research/1296
https://ink.library.smu.edu.sg/context/soe_research/article/2295/viewcontent/PEY.pdf
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Institution: Singapore Management University
Language: English

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https://ink.library.smu.edu.sg/soe_research/1296
https://ink.library.smu.edu.sg/context/soe_research/article/2295/viewcontent/PEY.pdf

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