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Estimating the volatility of asset pricing factors

Becker, Janis; Leschinski, Christian - 2018 - This version: May 20, 2018

Models based on factors such as size, value, or momentum are ubiquitous in asset pricing. Therefore, portfolio allocation and risk management require estimates of the volatility of these factors. While realized volatility has become a standard tool for liquid individual assets, this measure is...

Persistent link: https://www.econbiz.de/10011860248

GARCH Family Models vs EWMA : which is the best model to forecast volatility of the Moroccan stock exchange market?

Jebari, Ouael El; Hakmaoui, Abdelati - In: Revista de métodos cuantitativos para la economía y … 26 (2018), pp. 237-249

article is to compare the GARCH (Generalised Auto Regressive Conditional Heteroskedasticity) family models -GARCH (1.1), GJR-GARCH …

Persistent link: https://www.econbiz.de/10012023967

A multivariate Kernel approach to forecasting the variance covariance of stock market returns

Becker, Ralf; Clements, Adam; O'Neill, Rob - In: Econometrics : open access journal 6 (2018) 1, pp. 1-27

This paper introduces a multivariate kernel based forecasting tool for the prediction of variance-covariance matrices of stock returns. The method introduced allows for the incorporation of macroeconomic variables into the forecasting process of the matrix without resorting to a decomposition of...

Persistent link: https://www.econbiz.de/10011823257

A latent dynamic factor approach to forecasting multivariate stock market volatility : conference paper

Gribisch, Bastian - 2013

This paper proposes a latent dynamic factor model for low- as well as high-dimensional realized covariance matrices of stock returns. The approach is based on the matrix logarithm and allows for flexible dynamic dependence patterns by combining common latent factors driven by HAR dynamics and...

Persistent link: https://www.econbiz.de/10010341025

Jump variation estimation with noisy high frequency financial data via wavelets

Zhang, Xin; Kim, Donggyu; Wang, Yazhen - In: Econometrics : open access journal 4 (2016) 3, pp. 1-26

This paper develops a method to improve the estimation of jump variation using high frequency data with the existence of market microstructure noises. Accurate estimation of jump variation is in high demand, as it is an important component of volatility in finance for portfolio allocation,...

Persistent link: https://www.econbiz.de/10011568279

Forecasting the realized variance in the presence of intraday periodicity

Dumitru, Ana-Maria H.; Hizmeri, Rodrigo; Izzeldin, Marwan - 2019

This paper examines the impact of intraday periodicity on forecasting realized volatility using a heterogeneous autoregressive model (HAR) framework. We show that periodicity inflates the variance of the realized volatility and biases jump estimators. This combined effect adversely affects...

Persistent link: https://www.econbiz.de/10012063222

The contribution of jump signs and activity to forecasting stock price volatility

Hizmeri, Rodrigo; Izzeldin, Marwan; Murphy, Anthony; … - 2019

We document the forecasting gains achieved by incorporating measures of signed, finite and infinite jumps in forecasting the volatility of equity prices, using high-frequency data from 2000 to 2016. We consider the SPY and 20 stocks that vary by sector, volume and degree of jump activity. We use...

Persistent link: https://www.econbiz.de/10012030057

GARCH models, tail indexes and error distributions : an empirical investigation

Šopov, Boril; Horváth, Roman - 2015

heteroskedasticity (GARCH) models capture extreme events in stock market returns. We estimate Hill's tail indexes for individual S&P 500 … stock market returns ranging from 1995-2014 and compare these to the tail indexes produced by simulating GARCH models. Our … results suggest that actual and simulated values differ greatly for GARCH models with normal conditional distributions, which …

Persistent link: https://www.econbiz.de/10010529886

GARCH models for daily stock returns : impact of estimation frequency on value-at-risk and expected shortfall forecasts

Ardia, David; Hoogerheide, Lennart - 2013

Persistent link: https://www.econbiz.de/10010191413

High frequency vs. daily resolution : the economic value of forecasting volatility models 2nd ed

Lilla, Francesca - 2017

Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer from many limitations. HF data feature microstructure problem,...

Persistent link: https://www.econbiz.de/10011674479

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