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Forecasting financial crashes : a dynamic risk management approach
Gerlach, Jan-Christian; Zhao, Dongshuai; Sornette, Didier - 2020
Since 2009, stock markets have resided in a long bull market regime. Passive investment strategies have succeeded during this low-volatility growth period. From 2018 on, however, there was a transition into a more volatile market environment interspersed by corrections increasing in amplitude...
Persistent link: https://www.econbiz.de/10012419688
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Comparison of Block Maxima and Peaks Over Threshold Value-at-Risk models for market risk in various economic conditions
Szubzda, Filip; Chlebus, Marcin - In: Central European economic journal 6 (2019) 53, pp. 70-85
The aim of the presented study was to assess the quality of VaR forecasts in various states of the economic situation … movements. While in the pre-crisis period the results were satisfactory, in the period of crisis VaR forecasts were too often …
Persistent link: https://www.econbiz.de/10012302139
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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
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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
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Copula-based vMEM specifications versus alternatives : the case of trading activity
Cipollini, Fabrizio; Engle, Robert F.; Gallo, Giampiero M. - In: Econometrics : open access journal 5 (2017) 2, pp. 1-24
We discuss several multivariate extensions of the Multiplicative Error Model to take into account dynamic interdependence and contemporaneously correlated innovations (vector MEM or vMEM). We suggest copula functions to link Gamma marginals of the innovations, in a specification where past...
Persistent link: https://www.econbiz.de/10011654447
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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
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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
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Aggregating credit and market risk : the impact of model specification
Lucas, André; Verhoef, Bastiaan - 2012
Persistent link: https://www.econbiz.de/10010191011
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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
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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