Forecasting Realized Volatility Using a Nonnegative Semiparametric Model

Forecasting Realized Volatility Using a Nonnegative Semiparametric Model

This paper introduces a parsimonious and yet flexible semiparametric model to forecast financial volatility. The new model extends a related linear nonnegative autoregressive model previously used in the volatility literature by way of a power transformation. It is semiparametric in the sense that t...

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Bibliographic Details
Main Authors: Anders Eriksson, Daniel P. A. Preve, Jun Yu
Format: Article
Language:English
Published: MDPI AG 2019-08-01
Series:Journal of Risk and Financial Management
Subjects:
volatility forecasting
realized volatility
linear programming estimator
Tukey’s power transformation
nonlinear nonnegative autoregression
forecast comparisons
Online Access:https://www.mdpi.com/1911-8074/12/3/139

Internet

https://www.mdpi.com/1911-8074/12/3/139

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