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How informative is high-frequency data for tail risk estimation and forecasting? : an intrinsic time perspectice
Dimitriadis, Timo; Halbleib, Roxana - 2019
This paper proposes a novel and simple approach to compute daily Value at Risk (VaR) and Expected Shortfall (ES) directly from high-frequency data. It assumes that financial logarithm prices are subordinated unifractal processes in the intrinsic time, which stochastically transforms the clock...
Persistent link: https://www.econbiz.de/10012317619
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Forecasting GDP at the regional level with many predictors
Lehmann, Robert; Wohlrabe, Klaus - 2013
In this paper, we assess the accuracy of macroeconomic forecasts at the regional level using a unique data set at quarterly frequency. We forecast gross domestic product (GDP) for two German states (Free State of Saxony and Baden-Württemberg) and Eastern Germany. We overcome the problem of a...
Persistent link: https://www.econbiz.de/10011685344
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Measuring persistence in volatility spillovers : conference paper
Conrad, Christian; Weber, Enzo - Wettbewerbspolitik und Regulierung in einer Globalen … - 2013
This paper analyzes volatility spillovers in multivariate GARCH-type models. We show that the cross-effects between the … conditional variances determine the persistence of the transmitted volatility innovations. In particular, the influence of a … foreign volatility innovation on a conditional variance is even more persistent than an own innovation unless this effect is …
Persistent link: https://www.econbiz.de/10010341118
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Directed graphs and variable selection in large vector autoregressive models
Bertsche, Dominik; Brüggemann, Ralf; Kascha, Christian - 2019 - First draft: July 17, 2017, this version: December 10, 2018
We represent the dynamic relation among variables in vector autoregressive (VAR) models as directed graphs. Based on these graphs, we identify so-called strongly connected components (SCCs). Using this graphical representation, we consider the problem of variable selection. We use the relations...
Persistent link: https://www.econbiz.de/10012317407
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Robust inference in time-varying structural VAR models : the DC-cholesky multivariate stochastic volatility model
Hartwig, Benny - 2020
Cholesky multivariate stochastic volatility model. It establishes that systematically different dynamic restrictions are … divergent when volatility clusters idiosyncratically. It is illustrated that this property is important for empirical … multivariate stochastic volatility model is proposed as a robust alternative. …
Persistent link: https://www.econbiz.de/10012424283
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Out-of-sample stock return prediction using higher-order moments
Faias, José Afonso; Castel-Branco, Tiago - In: International journal of theoretical and applied finance 21 (2018) 6, pp. 1-27
Persistent link: https://www.econbiz.de/10011926608
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Time scale and fractionality in financial time series
Sproul, Thomas W. - In: Agricultural finance review 76 (2016) 1, pp. 76-93
Persistent link: https://www.econbiz.de/10011695555
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On guidance and volatility
Billings, Mary Brooke; Jennings, Robert H.; Lev, Baruch - In: Journal of accounting & economics 60 (2015) 2/3, pp. 161-180
Persistent link: https://www.econbiz.de/10011437528
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On the predictability of realized volatility using feasible GLS
Bentes, Sonia R.; Menezes, Rui - In: Journal of Asian economics 28 (2013), pp. 58-66
Persistent link: https://www.econbiz.de/10010400866
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Correlated beliefs, returns, and stock market volatility
David, Joel M.; Simonovska, Ina - In: Journal of international economics 99 (2016), pp. 58-77
Persistent link: https://www.econbiz.de/10011655068