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Is intraday data useful for forecasting VaR? : the evidence from EUR/PLN exchange rate

Będowska-Sójka, Barbara - In: Risk management : a journal of risk, crisis and disaster 20 (2018) 4, pp. 326-346

Persistent link: https://www.econbiz.de/10011962183

Empirical evidence on the importance of aggregation, asymmetry, and jumps for volatility prediction

Duong, Diep; Swanson, Norman R. - 2013

Many recent modelling advances in finance topics ranging from the pricing of volatility-based derivative products to asset management are predicated on the importance of jumps, or discontinuous movements in asset returns. In light of this, a number of recent papers have addressed volatility...

Persistent link: https://www.econbiz.de/10009771770

Forecasting co-volatilities via factor models with asymmetry and long memory in realized covariance

Asai, Manabu; McAleer, Michael - 2014

Modelling covariance structures is known to suffer from the curse of dimensionality. In order to avoid this problem for forecasting, the authors propose a new factor multivariate stochastic volatility (fMSV) model for realized covariance measures that accommodates asymmetry and long memory....

Persistent link: https://www.econbiz.de/10010259630

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

Forecasting realized volatility in turbulent times using temporal fusion transformers

Frank, Johannes - 2023

This paper analyzes the performance of temporal fusion transformers in forecasting realized volatilities of stocks listed in the S&P 500 in volatile periods by comparing the predictions with those of state-of-the-art machine learning methods as well as GARCH models. The models are trained on...

Persistent link: https://www.econbiz.de/10013552533

Modeling and forecasting realized range volatility

Caporin, Massimiliano; Velo, Gabriel G. - Dipartimento di Scienze Economiche "Marco Fanno", … - 2011

In this paper, we estimate, model and forecast Realized Range Volatility, a new realized measure and estimator of the quadratic variation of financial prices. This estimator was early introduced in the literature and it is based on the high-low range observed at high frequency during the day. We...

Persistent link: https://www.econbiz.de/10009021695

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

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

Lilla, Francesca - 2017

these two family forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the …-data models at 5% and 1% VaR level. Specifically, independently from the data frequency, allowing for jumps in price (or providing … fat-tails) and leverage effects translates in more accurate VaR measure. …

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

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

Lilla, Francesca - 2016

forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the assumptions of jumping … prices and leverage effects for volatility. Findings suggest that GARJI model provides more accurate VaR measures for the S … accurate risk measures even if jump contribution is provided. More sophisticated models might address this issue, improving VaR …

Persistent link: https://www.econbiz.de/10011730304

Modeling and forecasting multifractal volatility established upon the heterogeneous market hypothesis

Tao, Qizhi; Wei, Yu; Liu, Jiapeng; Zhang, Ting - In: International review of economics & finance : IREF 54 (2018), pp. 143-153

Persistent link: https://www.econbiz.de/10012033354

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